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@opencode-ai/cli-linux-arm64 - npm Package Compare versions
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/get.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect, Option } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.get,\n Effect.fn(\"cli.service.get\")(function* (input) {\n process.stdout.write((yield* ServiceConfig.get(Option.getOrUndefined(input.key))) + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "2B0B3A459E6BA6D664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/auth.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport {\n OpenCode,\n type IntegrationAttemptStatus,\n type IntegrationOAuthMethod,\n type OpenCodeClient,\n} from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { resolveIntegration } from \"./resolve\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.auth,\n Effect.fn(\"cli.mcp.auth\")(function* (input) {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n\n const integration = yield* resolveIntegration(client, input.name, location)\n if (!integration)\n return yield* Effect.fail(new Error(`MCP server \"${input.name}\" is not an OAuth-capable remote server`))\n const method = integration.methods.find(\n (candidate): candidate is IntegrationOAuthMethod => candidate.type === \"oauth\",\n )\n if (!method)\n return yield* Effect.fail(new Error(`MCP server \"${input.name}\" is not an OAuth-capable remote server`))\n\n const started = yield* Effect.promise(() =>\n client.integration.oauth.connect({ integrationID: integration.id, methodID: method.id, inputs: {}, location }),\n )\n const attempt = started.data\n if (attempt.mode === \"code\")\n return yield* Effect.fail(new Error(\"This server requires manual code entry, which the CLI does not support\"))\n\n process.stdout.write(attempt.instructions + EOL + attempt.url + EOL)\n\n const result = yield* poll(client, integration.id, attempt.attemptID)\n if (result.status === \"complete\") {\n process.stdout.write(`Authenticated with ${input.name}` + EOL)\n return\n }\n const reason = result.status === \"failed\" ? `: ${result.message}` : \"\"\n return yield* Effect.fail(new Error(`Authentication ${result.status}${reason}`))\n }),\n)\n\nconst poll = (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n): Effect.Effect<Exclude<IntegrationAttemptStatus, { status: \"pending\" }>> =>\n Effect.gen(function* () {\n const status = yield* Effect.promise(() =>\n client.integration.oauth.status({ integrationID, attemptID, location }),\n ).pipe(Effect.map((result) => result.data))\n if (status.status === \"pending\") {\n yield* Effect.sleep(\"1 second\")\n return yield* poll(client, integrationID, attemptID)\n }\n return status\n })\n" | ||
| ], | ||
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| "debugId": "DF90C063B3CED6DA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/tool-stream.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { LLMError, LLMEvent, type ProviderMetadata, type ToolCall, type ToolInputError } from \"../../schema\"\nimport { eventError, parseToolInput, type ToolAccumulator } from \"../shared\"\n\ntype StreamKey = string | number\n\n/**\n * One pending streamed tool call. Providers emit the tool identity and JSON\n * argument text across separate chunks; `input` is the raw JSON string collected\n * so far, not the parsed object.\n */\nexport interface PendingTool extends ToolAccumulator {\n readonly providerExecuted?: boolean\n readonly providerMetadata?: ProviderMetadata\n}\n\n/**\n * Sparse parser state keyed by the provider's stream-local tool identifier.\n *\n * This key is not the final tool-call id (`call_...`). It is the id/index the\n * provider uses while streaming a partial call: OpenAI Chat / Anthropic /\n * Bedrock use numeric content indexes, while OpenAI Responses uses string\n * `item_id`s. The generic keeps each protocol internally consistent.\n */\nexport type State<K extends StreamKey> = Partial<Record<K, PendingTool>>\n\n/**\n * Result of adding argument text to one pending tool call. It returns both the\n * next `tools` state and the updated `tool` because parsers often need the\n * current id/name immediately. `events` contains lifecycle and delta events\n * produced by the append; metadata-only deltas update identity without output.\n */\nexport interface AppendOutcome<K extends StreamKey> {\n readonly tools: State<K>\n readonly tool: PendingTool\n readonly events: ReadonlyArray<LLMEvent>\n}\n\n/** Create empty accumulator state for one provider stream. */\nexport const empty = <K extends StreamKey>(): State<K> => ({})\n\nconst withTool = <K extends StreamKey>(tools: State<K>, key: K, tool: PendingTool): State<K> => {\n return { ...tools, [key]: tool }\n}\n\nconst withoutTool = <K extends StreamKey>(tools: State<K>, key: K): State<K> => {\n const next = { ...tools }\n delete next[key]\n return next\n}\n\nconst inputStart = (tool: PendingTool) =>\n LLMEvent.toolInputStart({\n id: tool.id,\n name: tool.name,\n providerExecuted: tool.providerExecuted ? true : undefined,\n providerMetadata: tool.providerMetadata,\n })\n\nconst inputDelta = (tool: PendingTool, text: string) =>\n LLMEvent.toolInputDelta({\n id: tool.id,\n name: tool.name,\n text,\n })\n\nconst toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {\n const raw = inputOverride ?? tool.input\n return parseToolInput(route, tool.name, raw).pipe(\n Effect.map((input): ToolCall | ToolInputError =>\n LLMEvent.toolCall({\n id: tool.id,\n name: tool.name,\n input,\n providerExecuted: tool.providerExecuted ? true : undefined,\n providerMetadata: tool.providerMetadata,\n }),\n ),\n Effect.catch((error) =>\n tool.providerExecuted\n ? Effect.fail(error)\n : Effect.succeed(\n LLMEvent.toolInputError({\n id: tool.id,\n name: tool.name,\n raw,\n }),\n ),\n ),\n )\n}\n\nconst finishEvents = (tool: PendingTool, event: ToolCall | ToolInputError): ReadonlyArray<LLMEvent> =>\n event.type === \"tool-input-error\"\n ? [event]\n : [LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }), event]\n\n/** Store the updated tool and produce the optional public delta event. */\nconst appendTool = <K extends StreamKey>(\n tools: State<K>,\n key: K,\n tool: PendingTool,\n text: string,\n): AppendOutcome<K> => {\n const events: LLMEvent[] = []\n if (!tools[key]) events.push(inputStart(tool))\n if (text.length > 0) events.push(inputDelta(tool, text))\n return {\n tools: withTool(tools, key, tool),\n tool,\n events,\n }\n}\n\nexport const isError = <K extends StreamKey>(result: AppendOutcome<K> | LLMError): result is LLMError =>\n result instanceof LLMError\n\n/**\n * Register a tool call whose start event arrived before any argument deltas.\n * Used by Anthropic `content_block_start`, Bedrock `contentBlockStart`, and\n * OpenAI Responses `response.output_item.added`.\n */\nexport const start = <K extends StreamKey>(\n tools: State<K>,\n key: K,\n tool: Omit<PendingTool, \"input\"> & { readonly input?: string },\n) => withTool(tools, key, { ...tool, input: tool.input ?? \"\" })\n\n/**\n * Append a streamed argument delta, starting the tool if this provider encodes\n * identity on the first delta instead of a separate start event. OpenAI Chat has\n * this shape: `tool_calls[].index` is the stream key, and `id` / `name` may only\n * appear on the first delta for that index.\n */\nexport const appendOrStart = <K extends StreamKey>(\n route: string,\n tools: State<K>,\n key: K,\n delta: { readonly id?: string; readonly name?: string; readonly text: string },\n missingToolMessage: string,\n): AppendOutcome<K> | LLMError => {\n const current = tools[key]\n const id = current?.id ?? delta.id\n const name = current?.name ?? delta.name\n if (!id || !name) return eventError(route, missingToolMessage)\n\n const tool = {\n id,\n name,\n input: `${current?.input ?? \"\"}${delta.text}`,\n providerExecuted: current?.providerExecuted,\n providerMetadata: current?.providerMetadata,\n }\n if (current && delta.text.length === 0 && current.id === id && current.name === name)\n return { tools, tool: current, events: [] }\n return appendTool(tools, key, tool, delta.text)\n}\n\n/**\n * Append argument text to a tool that must already have been started. This keeps\n * protocols honest when their stream grammar promises a start event before any\n * argument delta.\n */\nexport const appendExisting = <K extends StreamKey>(\n route: string,\n tools: State<K>,\n key: K,\n text: string,\n missingToolMessage: string,\n): AppendOutcome<K> | LLMError => {\n const current = tools[key]\n if (!current) return eventError(route, missingToolMessage)\n if (text.length === 0) return { tools, tool: current, events: [] }\n return appendTool(tools, key, { ...current, input: `${current.input}${text}` }, text)\n}\n\n/**\n * Finalize one pending tool call: parse the accumulated raw JSON, remove it\n * from state, and return either a call or a non-executable local input error.\n * Missing keys are a no-op because some providers emit stop events for\n * non-tool content blocks.\n */\nexport const finish = <K extends StreamKey>(route: string, tools: State<K>, key: K) =>\n Effect.gen(function* () {\n const tool = tools[key]\n if (!tool) return { tools }\n return {\n tools: withoutTool(tools, key),\n events: finishEvents(tool, yield* toolCall(route, tool)),\n }\n })\n\n/**\n * Finalize one pending tool call with an authoritative final input string.\n * OpenAI Responses can send accumulated deltas and then repeat the completed\n * arguments on `response.output_item.done`; the final value wins.\n */\nexport const finishWithInput = <K extends StreamKey>(route: string, tools: State<K>, key: K, input: string) =>\n Effect.gen(function* () {\n const tool = tools[key]\n if (!tool) return { tools }\n return {\n tools: withoutTool(tools, key),\n events: finishEvents(tool, yield* toolCall(route, tool, input)),\n }\n })\n\n/**\n * Finalize every pending tool call at once. OpenAI Chat has this shape: it does\n * not emit per-tool stop events, so all accumulated calls finish independently\n * when the choice receives a terminal `finish_reason`.\n */\nexport const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =>\n Effect.gen(function* () {\n const pending = Object.values<PendingTool | undefined>(tools).filter(\n (tool): tool is PendingTool => tool !== undefined,\n )\n return {\n tools: empty<K>(),\n events: yield* Effect.forEach(pending, (tool) =>\n toolCall(route, tool).pipe(Effect.map((event) => finishEvents(tool, event))),\n ).pipe(Effect.map((events) => events.flat())),\n }\n })\n\nexport * as ToolStream from \"./tool-stream\"\n" | ||
| ], | ||
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| "debugId": "D8E09DABB81C90FA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openrouter.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route, type RouteDefaultsInput } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport { ProviderID, type ModelID, type ProviderOptions } from \"../schema\"\nimport * as OpenAICompatibleProfiles from \"./openai-compatible-profile\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport { isRecord } from \"../protocols/shared\"\n\nexport const profile = OpenAICompatibleProfiles.profiles.openrouter\nexport const id = ProviderID.make(profile.provider)\nconst ADAPTER = \"openrouter\"\n\nexport interface OpenRouterOptions {\n readonly [key: string]: unknown\n readonly usage?: boolean | Record<string, unknown>\n readonly reasoning?: Record<string, unknown>\n readonly promptCacheKey?: string\n}\n\nexport type OpenRouterProviderOptionsInput = ProviderOptions & {\n readonly openrouter?: OpenRouterOptions\n}\n\nexport type ModelOptions = Omit<RouteDefaultsInput, \"providerOptions\"> &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n readonly providerOptions?: OpenRouterProviderOptionsInput\n }\n\nconst OpenRouterBody = Schema.StructWithRest(Schema.Struct(OpenAIChat.bodyFields), [\n Schema.Record(Schema.String, Schema.Any),\n])\nexport type OpenRouterBody = Schema.Schema.Type<typeof OpenRouterBody>\n\nexport const protocol = Protocol.make({\n id: \"openrouter-chat\",\n body: {\n schema: OpenRouterBody,\n from: (request) =>\n OpenAIChat.protocol.body.from(request).pipe(\n Effect.map(\n (body) =>\n ({\n ...body,\n ...bodyOptions(request.providerOptions?.openrouter),\n }) as OpenRouterBody,\n ),\n ),\n },\n stream: OpenAIChat.protocol.stream,\n})\n\nconst bodyOptions = (input: unknown) => {\n const openrouter = isRecord(input) ? input : {}\n return {\n ...(openrouter.usage === true\n ? { usage: { include: true } }\n : isRecord(openrouter.usage)\n ? { usage: openrouter.usage }\n : {}),\n ...(isRecord(openrouter.reasoning) ? { reasoning: openrouter.reasoning } : {}),\n ...(typeof openrouter.promptCacheKey === \"string\" ? { prompt_cache_key: openrouter.promptCacheKey } : {}),\n }\n}\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: profile.provider,\n protocol,\n endpoint: Endpoint.path(\"/chat/completions\", { baseURL: profile.baseURL }),\n framing: Framing.sse,\n})\n\nexport const routes = [route]\n\nconst configuredRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return route.with({\n ...rest,\n endpoint: { baseURL: baseURL ?? profile.baseURL },\n auth: AuthOptions.bearer(input, \"OPENROUTER_API_KEY\"),\n })\n}\n\nexport const configure = (input: ModelOptions = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model = provider.model\n" | ||
| ], | ||
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| "debugId": "14EF1035E3D3620264756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/frontend/actions.ts", "../simulation/src/recording.ts", "../simulation/src/frontend/renderer.ts", "../simulation/src/frontend/semantics.ts", "../simulation/src/frontend/server.ts", "../simulation/src/frontend/simulation.ts"], | ||
| "sourcesContent": [ | ||
| "import { tmpdir } from \"node:os\"\nimport { extname, join, resolve } from \"node:path\"\nimport type { CliRenderer, Renderable } from \"@opentui/core\"\nimport {\n createMockKeys,\n createMockMouse,\n KeyCodes,\n type KeyInput,\n type MockInput,\n type MockMouse,\n} from \"@opentui/core/testing\"\nimport { Config, Effect, FileSystem, Schema } from \"effect\"\nimport { SimulationProtocol } from \"../protocol\"\nimport { SimulationRenderer } from \"./renderer\"\nimport { SimulationSemantics } from \"./semantics\"\n\nexport type Action = SimulationProtocol.Frontend.Action\nexport type Element = SimulationProtocol.Frontend.Element\n\nexport interface Harness {\n readonly renderer: CliRenderer\n readonly mockInput: MockInput\n readonly mockMouse: MockMouse\n readonly resize: (cols: number, rows: number) => void\n readonly renderOnce: () => Promise<void>\n readonly screen: () => string\n}\n\ntype RenderBuffer = {\n readonly width: number\n readonly height: number\n getRealCharBytes(includeAnsi?: boolean): Uint8Array\n}\n\nconst decoder = new TextDecoder()\n\nfunction isKeyCode(key: string): key is keyof typeof KeyCodes {\n return Object.hasOwn(KeyCodes, key)\n}\n\nfunction keyInput(key: string): KeyInput {\n const named = key.toUpperCase()\n return isKeyCode(named) ? named : key\n}\n\nfunction children(renderable: Renderable) {\n return renderable.getChildren().filter((child): child is Renderable => \"num\" in child)\n}\n\nfunction all(renderable: Renderable): Renderable[] {\n return [renderable, ...children(renderable).flatMap(all)]\n}\n\nfunction mouseListeners(renderable: Renderable) {\n const general = Reflect.get(renderable, \"_mouseListener\")\n const specific = Reflect.get(renderable, \"_mouseListeners\")\n return Boolean(general) || (specific && typeof specific === \"object\" && Object.keys(specific).length > 0)\n}\n\nfunction hit(renderer: CliRenderer, renderable: Renderable) {\n if (renderable.width <= 0 || renderable.height <= 0) return false\n const x = Math.floor(renderable.screenX + renderable.width / 2)\n const y = Math.floor(renderable.screenY + renderable.height / 2)\n const target = renderer.hitTest(x, y)\n return all(renderable).some((item) => item.num === target)\n}\n\n/**\n * Builds the harness the simulation server drives.\n *\n * When the renderer is the headless simulation renderer, its TestRendererSetup\n * provides the supported testing APIs. For the visible terminal renderer the\n * harness falls back to `requestRender` + `idle` and reading the private\n * `currentRenderBuffer`.\n */\nexport function createHarness(renderer: CliRenderer): Harness {\n const setup = SimulationRenderer.setupFor(renderer)\n return {\n renderer,\n mockInput: setup?.mockInput ?? createMockKeys(renderer),\n mockMouse: setup?.mockMouse ?? createMockMouse(renderer),\n resize: setup?.resize ?? ((cols, rows) => renderer.resize(cols, rows)),\n renderOnce:\n setup?.renderOnce ??\n (async () => {\n renderer.requestRender()\n await renderer.idle()\n }),\n // captureCharFrame follows the test renderer's output sink. Recording\n // redirects that sink to the timeline, so read the live render buffer\n // instead; it is also the source used by screenshots.\n screen: () => decoder.decode((Reflect.get(renderer, \"currentRenderBuffer\") as RenderBuffer).getRealCharBytes()),\n }\n}\n\nexport function elements(renderer: CliRenderer): Element[] {\n return all(renderer.root)\n .filter((renderable) => renderable.visible && !renderable.isDestroyed)\n .map((renderable) => {\n const clickable = mouseListeners(renderable) && hit(renderer, renderable)\n return {\n id: renderable.id,\n num: renderable.num,\n x: renderable.screenX,\n y: renderable.screenY,\n width: renderable.width,\n height: renderable.height,\n focusable: renderable.focusable,\n focused: renderable.focused,\n clickable,\n editor: renderer.currentFocusedEditor === renderable,\n } satisfies Element\n })\n .filter((element) => element.focusable || element.clickable || element.editor)\n}\n\nexport function state(harness: Harness) {\n return {\n focused: {\n renderable: harness.renderer.currentFocusedRenderable?.num,\n editor: Boolean(harness.renderer.currentFocusedEditor),\n },\n elements: elements(harness.renderer),\n }\n}\n\nexport function snapshot(harness: Harness): SimulationProtocol.Frontend.SemanticSnapshot {\n const ids = new Set<string>()\n const visit = (renderable: Renderable, parent?: string): SimulationProtocol.Frontend.SemanticNode[] => {\n if (!renderable.visible || renderable.isDestroyed) return []\n const definition = SimulationSemantics.read(renderable)?.()\n if (definition && ids.has(renderable.id)) throw new Error(`duplicate semantic UI id: ${renderable.id}`)\n if (definition) ids.add(renderable.id)\n const node = definition\n ? [{ id: renderable.id, ...definition, ...(parent === undefined ? {} : { parent }), element: renderable.num }]\n : []\n const ancestor = definition ? renderable.id : parent\n return [...node, ...children(renderable).flatMap((child) => visit(child, ancestor))]\n }\n return Schema.decodeUnknownSync(SimulationProtocol.Frontend.SemanticSnapshot)({\n format: \"opencode-ui-snapshot-v1\",\n nodes: visit(harness.renderer.root),\n })\n}\n\nexport function matches(harness: Pick<Harness, \"screen\">, text: string) {\n return harness.screen().includes(text)\n}\n\nexport const capture = Effect.fn(\"SimulationActions.capture\")(function* (harness: Harness) {\n yield* Effect.tryPromise(() => harness.renderOnce())\n const buffer = harness.renderer.currentRenderBuffer\n return {\n cols: buffer.width,\n rows: buffer.height,\n cursor: [0, 0] as const,\n lines: buffer.getSpanLines().map((line) => ({\n spans: line.spans.map((span) => ({\n text: span.text,\n fg: span.fg.toInts(),\n bg: span.bg.toInts(),\n attributes: span.attributes,\n width: span.width,\n })),\n })),\n } satisfies SimulationProtocol.Frontend.CapturedFrame\n})\n\nexport const screenshot = Effect.fn(\"SimulationActions.screenshot\")(function* (harness: Harness, name?: string) {\n const filename = name ?? `screenshot-${crypto.randomUUID()}`\n if (!filename || filename.includes(\"/\") || filename.includes(\"\\\\\") || extname(filename))\n return yield* Effect.fail(new Error(\"screenshot name must not contain a path or extension\"))\n yield* Effect.tryPromise(() => harness.renderOnce())\n const { SimulationPng } = yield* Effect.promise(() => import(\"./png\"))\n const image = SimulationPng.screenshot(harness.renderer)\n const directory = resolve(\n yield* Config.string(\"OPENCODE_DRIVE_MEDIA_DIR\").pipe(\n Config.withDefault(join(tmpdir(), \"opencode-drive\", \"output\")),\n ),\n )\n const fs = yield* FileSystem.FileSystem\n yield* fs.makeDirectory(directory, { recursive: true })\n const path = join(directory, `${filename}.png`)\n yield* fs.writeFile(path, image.data)\n return path\n})\n\nexport const execute = Effect.fn(\"SimulationActions.execute\")(function* (harness: Harness, action: Action) {\n switch (action.type) {\n case \"ui.type\":\n yield* Effect.tryPromise(() => harness.mockInput.typeText(action.text))\n break\n case \"ui.press\":\n harness.mockInput.pressKey(keyInput(action.key), action.modifiers)\n break\n case \"ui.enter\":\n harness.mockInput.pressEnter()\n break\n case \"ui.arrow\":\n harness.mockInput.pressArrow(action.direction)\n break\n case \"ui.focus\":\n all(harness.renderer.root)\n .find((item) => item.num === action.target)\n ?.focus()\n break\n case \"ui.click\": {\n const target = all(harness.renderer.root).find((item) => item.num === action.target)\n if (!target || !target.visible || target.isDestroyed)\n return yield* Effect.fail(new Error(`click target is stale or unavailable: ${action.target}`))\n if (action.semantic) {\n const current = snapshot(harness).nodes.find((node) => node.element === action.target)\n if (\n current?.id !== action.semantic.id ||\n current.instance !== action.semantic.instance ||\n current.element !== action.semantic.element\n )\n return yield* Effect.fail(new Error(`semantic click target is stale or unavailable: ${action.semantic.id}`))\n }\n if (\n !Number.isFinite(action.x) ||\n action.x < 0 ||\n action.x >= target.width ||\n !Number.isFinite(action.y) ||\n action.y < 0 ||\n action.y >= target.height\n )\n return yield* Effect.fail(new Error(\"click position must be within the target element\"))\n yield* Effect.tryPromise(() => harness.mockMouse.click(target.screenX + action.x, target.screenY + action.y))\n break\n }\n case \"ui.resize\":\n if (\n !Number.isSafeInteger(action.cols) ||\n action.cols <= 0 ||\n !Number.isSafeInteger(action.rows) ||\n action.rows <= 0\n ) {\n return yield* Effect.fail(new Error(\"resize cols and rows must be positive integers\"))\n }\n harness.resize(action.cols, action.rows)\n SimulationRenderer.recordResize(harness.renderer, action.cols, action.rows)\n break\n }\n yield* Effect.tryPromise(() => harness.renderOnce())\n return state(harness)\n})\n\nexport * as SimulationActions from \"./actions\"\n", | ||
| "import { createWriteStream, type WriteStream } from \"node:fs\"\nimport { mkdir } from \"node:fs/promises\"\nimport { dirname } from \"node:path\"\nimport { Writable } from \"node:stream\"\nimport { finished } from \"node:stream/promises\"\nimport { Schema } from \"effect\"\n\nexport const Header = Schema.Struct({\n type: Schema.Literal(\"header\"),\n version: Schema.Literal(1),\n cols: Schema.Number,\n rows: Schema.Number,\n encoding: Schema.Literal(\"base64\"),\n})\nexport interface Header extends Schema.Schema.Type<typeof Header> {}\n\nexport const Output = Schema.Struct({\n type: Schema.Literal(\"output\"),\n at_ms: Schema.Number,\n data: Schema.String,\n})\nexport interface Output extends Schema.Schema.Type<typeof Output> {}\n\nexport const Resize = Schema.Struct({\n type: Schema.Literal(\"resize\"),\n at_ms: Schema.Number,\n cols: Schema.Number,\n rows: Schema.Number,\n})\nexport interface Resize extends Schema.Schema.Type<typeof Resize> {}\n\nexport const Event = Schema.Union([Header, Output, Resize])\nexport type Event = Schema.Schema.Type<typeof Event>\n\nexport class Timeline extends Writable {\n readonly isTTY = true\n readonly path: string\n readonly columns: number\n readonly rows: number\n private readonly output: WriteStream\n private readonly started = performance.now()\n private readonly timestamps: number[] = []\n private done?: Promise<string>\n\n private constructor(path: string, cols: number, rows: number, output: WriteStream) {\n super()\n this.path = path\n this.columns = cols\n this.rows = rows\n this.output = output\n // finish() reports stream failures; keep Writable from also throwing them process-wide.\n this.on(\"error\", () => {})\n output.on(\"error\", (error) => this.destroy(error))\n }\n\n static async create(path: string, cols: number, rows: number) {\n await mkdir(dirname(path), { recursive: true })\n const output = createWriteStream(path)\n const timeline = new Timeline(path, cols, rows, output)\n await new Promise<void>((resolve, reject) => {\n output.write(\n `${JSON.stringify({ type: \"header\", version: 1, cols, rows, encoding: \"base64\" } satisfies Header)}\\n`,\n (error) => (error ? reject(error) : resolve()),\n )\n })\n return timeline\n }\n\n getColorDepth() {\n return 24\n }\n\n override write(chunk: unknown, callback?: (error?: Error | null) => void): boolean\n override write(chunk: unknown, encoding: BufferEncoding, callback?: (error?: Error | null) => void): boolean\n override write(\n chunk: unknown,\n encoding?: BufferEncoding | ((error?: Error | null) => void),\n callback?: (error?: Error | null) => void,\n ) {\n if (!this.writableEnded) {\n this.timestamps.push(this.elapsed())\n if (typeof encoding === \"function\") return super.write(chunk, encoding)\n if (encoding === undefined) return super.write(chunk, callback)\n return super.write(chunk, encoding, callback)\n }\n const done = typeof encoding === \"function\" ? encoding : callback\n queueMicrotask(() => done?.(null))\n return true\n }\n\n override _write(chunk: Buffer, _encoding: BufferEncoding, callback: (error?: Error | null) => void) {\n this.writeOutput(chunk, this.timestamps.shift() ?? this.elapsed(), callback)\n }\n\n override _final(callback: (error?: Error | null) => void) {\n this.writeOutput(Buffer.alloc(0), this.elapsed(), (error) => {\n if (error) return callback(error)\n this.output.end(callback)\n })\n }\n\n finish() {\n if (this.done) return this.done\n this.end()\n this.done = finished(this).then(() => this.path)\n return this.done\n }\n\n resize(cols: number, rows: number) {\n if (this.writableEnded) return\n const event = { type: \"resize\", at_ms: this.elapsed(), cols, rows } satisfies Resize\n this.output.write(`${JSON.stringify(event)}\\n`)\n }\n\n private elapsed() {\n return Math.max(0, Math.round(performance.now() - this.started))\n }\n\n private writeOutput(data: Buffer, at_ms: number, callback: (error?: Error | null) => void) {\n const event = {\n type: \"output\",\n at_ms,\n data: data.toString(\"base64\"),\n } satisfies Output\n this.output.write(`${JSON.stringify(event)}\\n`, callback)\n }\n}\n\nexport * as SimulationRecording from \"./recording\"\n", | ||
| "import type { CliRenderer, CliRendererConfig } from \"@opentui/core\"\nimport { createTestRenderer, type TestRendererSetup } from \"@opentui/core/testing\"\nimport { Effect } from \"effect\"\nimport { Timeline } from \"../recording\"\n\nconst setups = new WeakMap<CliRenderer, TestRendererSetup>()\nconst recordings = new WeakMap<CliRenderer, Timeline>()\n\n/**\n * Creates a headless renderer with optional recording: a real CliRenderer\n * backed by an in-memory screen buffer. The TestRendererSetup is kept\n * module-side so the harness can use supported testing APIs without app\n * code carrying it around.\n */\nexport interface Viewport {\n readonly cols: number\n readonly rows: number\n}\n\nexport const create = Effect.fn(\"SimulationRenderer.create\")(function* (\n options: CliRendererConfig,\n path?: string,\n viewport?: Viewport,\n) {\n const cols = viewport?.cols ?? 100\n const rows = viewport?.rows ?? 40\n const recording = path\n ? yield* Effect.acquireRelease(\n Effect.tryPromise(() => Timeline.create(path, cols, rows)),\n (recording) =>\n Effect.tryPromise(() => recording.finish()).pipe(\n Effect.catch((error) =>\n Effect.sync(() => process.stderr.write(`Failed to finish UI recording: ${error}\\n`)),\n ),\n ),\n )\n : undefined\n const setup = yield* Effect.acquireRelease(\n Effect.tryPromise(() =>\n createTestRenderer({\n ...options,\n width: cols,\n height: rows,\n ...(recording\n ? {\n stdout: recording as unknown as NodeJS.WriteStream,\n bufferedOutput: \"stdout\" as const,\n }\n : {}),\n }),\n ),\n (setup) =>\n Effect.sync(() => {\n if (!setup.renderer.isDestroyed) setup.renderer.destroy()\n }),\n )\n setups.set(setup.renderer, setup)\n if (recording) recordings.set(setup.renderer, recording)\n return setup.renderer\n})\n\nexport function recordResize(renderer: CliRenderer, cols: number, rows: number) {\n recordings.get(renderer)?.resize(cols, rows)\n}\n\nexport function setupFor(renderer: CliRenderer): TestRendererSetup | undefined {\n return setups.get(renderer)\n}\n\nexport function finish(renderer: CliRenderer) {\n const recording = recordings.get(renderer)\n if (!recording) return Effect.fail(new Error(\"UI recording is not available\"))\n return Effect.tryPromise(() => recording.finish())\n}\n\nexport * as SimulationRenderer from \"./renderer\"\n", | ||
| "import type { Renderable } from \"@opentui/core\"\nimport type { SimulationProtocol } from \"../protocol\"\n\n// Semantic renderables set an explicit stable OpenTUI id so ui.state and\n// ui.snapshot expose the same identity. Hierarchy and element handles come\n// from the live render tree.\nexport type Definition = Omit<SimulationProtocol.Frontend.SemanticNode, \"id\" | \"element\" | \"parent\">\n\nconst key = Symbol.for(\"opencode.simulation.semantics\")\n\nconst bind = (definition: () => Definition) => (renderable: Renderable) => {\n Object.defineProperty(renderable, key, { value: definition, configurable: true })\n}\n\nexport const read = (renderable: Renderable) => {\n const definition: unknown = Reflect.get(renderable, key)\n return typeof definition === \"function\" ? (definition as () => Definition) : undefined\n}\n\nexport const SimulationSemantics = { bind, read }\n", | ||
| "import { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Effect } from \"effect\"\nimport { SimulationControlServer } from \"../control-server\"\nimport { SimulationProtocol } from \"../protocol\"\nimport { SimulationActions, type Harness } from \"./actions\"\nimport { SimulationRenderer } from \"./renderer\"\n\nfunction handle(harness: Harness, request: SimulationProtocol.Frontend.Request) {\n switch (request.method) {\n case \"simulation.handshake\":\n return SimulationProtocol.Handshake.dispatch(\n {\n role: \"ui\",\n server: { name: \"opencode\", version: InstallationVersion },\n capabilities: SimulationProtocol.Frontend.Capabilities,\n },\n request.params,\n )\n case \"ui.capture\":\n return SimulationActions.capture(harness)\n case \"ui.screenshot\":\n return SimulationActions.screenshot(harness, request.params?.name)\n case \"ui.state\":\n return Effect.sync(() => SimulationActions.state(harness))\n case \"ui.snapshot\":\n return Effect.sync(() => SimulationActions.snapshot(harness))\n case \"ui.matches\":\n return Effect.sync(() => SimulationActions.matches(harness, request.params.text))\n case \"ui.recording.finish\":\n return SimulationRenderer.finish(harness.renderer)\n case \"ui.type\":\n return SimulationActions.execute(harness, { type: \"ui.type\", text: request.params.text })\n case \"ui.enter\":\n return SimulationActions.execute(harness, { type: \"ui.enter\" })\n case \"ui.press\":\n return SimulationActions.execute(harness, {\n type: \"ui.press\",\n key: request.params.key,\n modifiers: request.params.modifiers,\n })\n case \"ui.arrow\":\n return SimulationActions.execute(harness, { type: \"ui.arrow\", direction: request.params.direction })\n case \"ui.focus\":\n return SimulationActions.execute(harness, { type: \"ui.focus\", target: request.params.target })\n case \"ui.click\":\n return SimulationActions.execute(harness, {\n type: \"ui.click\",\n target: request.params.target,\n x: request.params.x,\n y: request.params.y,\n semantic: request.params.semantic,\n })\n case \"ui.resize\":\n return SimulationActions.execute(harness, {\n type: \"ui.resize\",\n cols: request.params.cols,\n rows: request.params.rows,\n })\n }\n}\n\nexport const start = Effect.fn(\"SimulationServer.start\")(function* (harness: Harness, endpoint: string) {\n return yield* SimulationControlServer.start({\n endpoint,\n label: \"opencode drive ui websocket\",\n data: () => ({ drive: true as const }),\n decode: SimulationProtocol.Frontend.decodeRequestEffect,\n handle: (_socket, request) => handle(harness, request),\n })\n})\n\nexport * as SimulationServer from \"./server\"\n", | ||
| "import { createCliRenderer, type CliRendererConfig } from \"@opentui/core\"\nimport { Config, Effect } from \"effect\"\nimport { DriveManifest } from \"../manifest\"\nimport { SimulationActions } from \"./actions\"\nimport { SimulationRenderer } from \"./renderer\"\nimport { SimulationServer } from \"./server\"\n\n/** Drive-mode renderer and control-server acquisition. */\nexport const create = Effect.fn(\"Drive.create\")(function* (options: CliRendererConfig) {\n const headless = (yield* Config.string(\"OPENCODE_DRIVE_RENDERER\").pipe(Config.withDefault(\"visible\"))) === \"headless\"\n const manifest = yield* DriveManifest.resolve()\n const renderer = headless\n ? yield* SimulationRenderer.create(options, manifest.recording?.timeline, manifest.viewport)\n : yield* Effect.acquireRelease(\n Effect.tryPromise(() => createCliRenderer(options)),\n (renderer) =>\n Effect.sync(() => {\n if (!renderer.isDestroyed) renderer.destroy()\n }),\n )\n if (!headless && manifest.viewport) renderer.resize(manifest.viewport.cols, manifest.viewport.rows)\n const server = yield* SimulationServer.start(SimulationActions.createHarness(renderer), manifest.endpoints.ui)\n yield* Effect.sync(() => process.stderr.write(`opencode drive ui websocket: ${server.url}\\n`))\n return renderer\n})\n\nexport * as Drive from \"./simulation\"\n" | ||
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| ||
| "debugId": "CC64734843CBF5CE64756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/plugin/list.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.plugin.commands.list,\n Effect.fn(\"cli.plugin.list\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.plugin.list({ location: { directory: process.cwd() } }))\n const plugins = response.data.toSorted((a, b) => a.id.localeCompare(b.id))\n if (plugins.length === 0) {\n process.stdout.write(\"No plugins loaded\" + EOL)\n return\n }\n process.stdout.write(plugins.map((plugin) => plugin.id).join(EOL) + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "9FA00D09A102DFA664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/lifecycle.ts", "../ai/src/protocols/utils/gemini-tool-schema.ts", "../ai/src/protocols/utils/tool-schema.ts"], | ||
| "sourcesContent": [ | ||
| "import { LLMEvent, type FinishReason, type ProviderMetadata, type Usage } from \"../../schema\"\n\nexport interface State {\n readonly stepStarted: boolean\n readonly text: ReadonlySet<string>\n readonly reasoning: ReadonlySet<string>\n}\n\nexport const initial = (): State => ({ stepStarted: false, text: new Set(), reasoning: new Set() })\n\nexport const stepStart = (state: State, events: LLMEvent[]): State => {\n if (state.stepStarted) return state\n events.push(LLMEvent.stepStart({ index: 0 }))\n return { ...state, stepStarted: true }\n}\n\nexport const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {\n const stepped = stepStart(state, events)\n if (stepped.text.has(id)) {\n events.push(LLMEvent.textDelta({ id, text }))\n return stepped\n }\n events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))\n return { ...stepped, text: new Set([...stepped.text, id]) }\n}\n\nexport const reasoningStart = (\n state: State,\n events: LLMEvent[],\n id: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n if (state.reasoning.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.reasoningStart({ id, providerMetadata }))\n return { ...stepped, reasoning: new Set([...stepped.reasoning, id]) }\n}\n\nexport const reasoningDelta = (\n state: State,\n events: LLMEvent[],\n id: string,\n text: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n const started = reasoningStart(state, events, id, providerMetadata)\n events.push(LLMEvent.reasoningDelta({ id, text }))\n return started\n}\n\nexport const reasoningEnd = (\n state: State,\n events: LLMEvent[],\n id: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n if (!state.reasoning.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.reasoningEnd({ id, providerMetadata }))\n const reasoning = new Set(stepped.reasoning)\n reasoning.delete(id)\n return { ...stepped, reasoning }\n}\n\nexport const textEnd = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {\n if (!state.text.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.textEnd({ id, providerMetadata }))\n const text = new Set(stepped.text)\n text.delete(id)\n return { ...stepped, text }\n}\n\nconst closeOpenBlocks = (state: State, events: LLMEvent[]): State => {\n for (const id of state.reasoning) events.push(LLMEvent.reasoningEnd({ id }))\n for (const id of state.text) events.push(LLMEvent.textEnd({ id }))\n return { ...state, text: new Set(), reasoning: new Set() }\n}\n\nexport const finish = (\n state: State,\n events: LLMEvent[],\n input: {\n readonly reason: FinishReason\n readonly usage?: Usage\n readonly providerMetadata?: ProviderMetadata\n },\n): State => {\n const stepped = closeOpenBlocks(stepStart(state, events), events)\n events.push(\n LLMEvent.stepFinish({\n index: 0,\n reason: input.reason,\n usage: input.usage,\n providerMetadata: input.providerMetadata,\n }),\n LLMEvent.finish(input),\n )\n return { ...stepped, stepStarted: false }\n}\n\nexport * as Lifecycle from \"./lifecycle\"\n", | ||
| "import { isRecord } from \"../../utils/record\"\n\n// Gemini accepts a JSON Schema-like dialect for tool parameters, but rejects a\n// handful of common JSON Schema shapes. Keep this projection isolated so the\n// Gemini protocol file still reads like the other protocol modules.\nconst SCHEMA_INTENT_KEYS = [\n \"type\",\n \"properties\",\n \"items\",\n \"prefixItems\",\n \"enum\",\n \"const\",\n \"$ref\",\n \"additionalProperties\",\n \"patternProperties\",\n \"required\",\n \"not\",\n \"if\",\n \"then\",\n \"else\",\n]\n\nconst hasCombiner = (schema: unknown) =>\n isRecord(schema) && (Array.isArray(schema.anyOf) || Array.isArray(schema.oneOf) || Array.isArray(schema.allOf))\n\nconst hasSchemaIntent = (schema: unknown) =>\n isRecord(schema) && (hasCombiner(schema) || SCHEMA_INTENT_KEYS.some((key) => key in schema))\n\nconst sanitizeNode = (schema: unknown): unknown => {\n if (!isRecord(schema)) return Array.isArray(schema) ? schema.map(sanitizeNode) : schema\n\n const result: Record<string, unknown> = Object.fromEntries(\n Object.entries(schema).map(([key, value]) => [\n key,\n key === \"enum\" && Array.isArray(value) ? value.map(String) : sanitizeNode(value),\n ]),\n )\n\n if (Array.isArray(result.enum) && (result.type === \"integer\" || result.type === \"number\")) result.type = \"string\"\n\n const properties = result.properties\n if (result.type === \"object\" && isRecord(properties) && Array.isArray(result.required)) {\n result.required = result.required.filter((field) => typeof field === \"string\" && field in properties)\n }\n\n if (result.type === \"array\" && !hasCombiner(result)) {\n result.items = result.items ?? {}\n if (isRecord(result.items) && !hasSchemaIntent(result.items)) result.items = { ...result.items, type: \"string\" }\n }\n\n if (typeof result.type === \"string\" && result.type !== \"object\" && !hasCombiner(result)) {\n delete result.properties\n delete result.required\n }\n\n return result\n}\n\nconst emptyObjectSchema = (schema: Record<string, unknown>) =>\n schema.type === \"object\" &&\n (!isRecord(schema.properties) || Object.keys(schema.properties).length === 0) &&\n !schema.additionalProperties\n\nconst projectNode = (schema: unknown): Record<string, unknown> | undefined => {\n if (!isRecord(schema)) return undefined\n if (emptyObjectSchema(schema)) return undefined\n return Object.fromEntries(\n [\n [\"description\", schema.description],\n [\"required\", schema.required],\n [\"format\", schema.format],\n [\"type\", Array.isArray(schema.type) ? schema.type.filter((type) => type !== \"null\")[0] : schema.type],\n [\"nullable\", Array.isArray(schema.type) && schema.type.includes(\"null\") ? true : undefined],\n [\"enum\", schema.const !== undefined ? [schema.const] : schema.enum],\n [\n \"properties\",\n isRecord(schema.properties)\n ? Object.fromEntries(Object.entries(schema.properties).map(([key, value]) => [key, projectNode(value)]))\n : undefined,\n ],\n [\n \"items\",\n Array.isArray(schema.items)\n ? schema.items.map(projectNode)\n : schema.items === undefined\n ? undefined\n : projectNode(schema.items),\n ],\n [\"allOf\", Array.isArray(schema.allOf) ? schema.allOf.map(projectNode) : undefined],\n [\"anyOf\", Array.isArray(schema.anyOf) ? schema.anyOf.map(projectNode) : undefined],\n [\"oneOf\", Array.isArray(schema.oneOf) ? schema.oneOf.map(projectNode) : undefined],\n [\"minLength\", schema.minLength],\n ].filter((entry) => entry[1] !== undefined),\n )\n}\n\nexport const convert = (schema: unknown) => projectNode(sanitizeNode(schema))\n\nexport * as GeminiToolSchema from \"./gemini-tool-schema\"\n", | ||
| "import type { JsonSchema, ModelToolSchemaCompatibility } from \"../../schema\"\nimport { isRecord } from \"../../utils/record\"\nimport { GeminiToolSchema } from \"./gemini-tool-schema\"\n\nconst removeNullSchemas = (value: unknown): unknown => {\n if (Array.isArray(value)) return value.map(removeNullSchemas)\n if (!isRecord(value)) return value\n const fields = Object.fromEntries(\n Object.entries(value)\n .filter(([key]) => key !== \"anyOf\")\n .map(([key, field]) => [key, removeNullSchemas(field)]),\n )\n if (!Array.isArray(value.anyOf)) return fields\n const variants = value.anyOf.filter((variant) => !isRecord(variant) || variant.type !== \"null\").map(removeNullSchemas)\n if (variants.length === 1 && isRecord(variants[0])) return { ...fields, ...variants[0] }\n return { ...fields, anyOf: variants }\n}\n\nconst tupleItemsSchema = (items: ReadonlyArray<unknown>) => {\n const projected = items.map(moonshotNode)\n if (projected.length === 0) return {}\n if (projected.length === 1) return projected[0]\n return { anyOf: projected }\n}\n\nconst moonshotNode = (schema: unknown): unknown => {\n if (Array.isArray(schema)) return schema.map(moonshotNode)\n if (!isRecord(schema)) return schema\n if (typeof schema.$ref === \"string\") return { $ref: schema.$ref }\n return Object.fromEntries(\n Object.entries(schema).flatMap(([key, value]) => {\n if (key === \"items\" && Array.isArray(value)) return [[key, tupleItemsSchema(value)]]\n if (key === \"prefixItems\") {\n if (\"items\" in schema) return []\n return [[\"items\", tupleItemsSchema(Array.isArray(value) ? value : [])]]\n }\n if (key === \"unevaluatedItems\") return []\n return [[key, moonshotNode(value)]]\n }),\n )\n}\n\nconst moonshot = (schema: JsonSchema): JsonSchema => {\n const projected = moonshotNode(schema)\n return isRecord(projected) ? projected : {}\n}\n\nconst openAI = (schema: JsonSchema): JsonSchema => {\n const variants = Array.isArray(schema.anyOf) ? schema.anyOf.filter(isRecord) : []\n const flattened =\n variants.length === 0\n ? { ...schema, type: \"object\" }\n : {\n ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== \"anyOf\")),\n type: \"object\",\n properties: variants.reduce(\n (properties, variant) => ({ ...(isRecord(variant.properties) ? variant.properties : {}), ...properties }),\n {},\n ),\n additionalProperties: false,\n }\n const normalized = removeNullSchemas(flattened)\n return isRecord(normalized) ? normalized : { type: \"object\" }\n}\n\nconst gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}\n\nconst modelCompatibility = (\n schema: JsonSchema,\n compatibility: ModelToolSchemaCompatibility | undefined,\n): JsonSchema => {\n if (compatibility === undefined) return schema\n switch (compatibility) {\n case \"gemini\":\n return gemini(schema)\n case \"moonshot\":\n return moonshot(schema)\n }\n}\n\nexport const ToolSchemaProjection = {\n gemini,\n modelCompatibility,\n moonshot,\n openAI,\n} as const\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/bedrock-event-stream.ts", "../ai/src/protocols/utils/bedrock-auth.ts", "../ai/src/protocols/utils/bedrock-cache.ts", "../ai/src/protocols/utils/bedrock-media.ts", "../ai/src/protocols/bedrock-converse.ts", "../ai/src/providers/amazon-bedrock.ts"], | ||
| "sourcesContent": [ | ||
| "import { EventStreamCodec } from \"@smithy/eventstream-codec\"\nimport { fromUtf8, toUtf8 } from \"@smithy/util-utf8\"\nimport { Effect, Stream } from \"effect\"\nimport { Framing } from \"../route/framing\"\nimport { ProviderShared } from \"./shared\"\n\n// Bedrock streams responses using the AWS event stream binary protocol — each\n// frame is `[length:4][headers-length:4][prelude-crc:4][headers][payload][crc:4]`.\n// We use `@smithy/eventstream-codec` to validate framing and CRCs, then\n// reconstruct the JSON wrapping by `:event-type` so the chunk schema can match.\nconst eventCodec = new EventStreamCodec(toUtf8, fromUtf8)\nconst utf8 = new TextDecoder()\n\n// Cursor-tracking buffer state. Bytes accumulate in `buffer`; `offset` is the\n// read position. Reading by `subarray` is zero-copy. We only allocate a fresh\n// buffer when a new network chunk arrives and we need to append.\ninterface FrameBufferState {\n readonly buffer: Uint8Array\n readonly offset: number\n}\n\nconst initialFrameBuffer: FrameBufferState = { buffer: new Uint8Array(0), offset: 0 }\n\nconst appendChunk = (state: FrameBufferState, chunk: Uint8Array): FrameBufferState => {\n const remaining = state.buffer.length - state.offset\n // Compact: drop the consumed prefix and append the new chunk in one alloc.\n // This bounds buffer growth to at most one network chunk past the live\n // window, regardless of stream length.\n const next = new Uint8Array(remaining + chunk.length)\n next.set(state.buffer.subarray(state.offset), 0)\n next.set(chunk, remaining)\n return { buffer: next, offset: 0 }\n}\n\nconst consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8Array) =>\n Effect.gen(function* () {\n let cursor = appendChunk(state, chunk)\n const out: object[] = []\n while (cursor.buffer.length - cursor.offset >= 4) {\n const view = cursor.buffer.subarray(cursor.offset)\n const totalLength = new DataView(view.buffer, view.byteOffset, view.byteLength).getUint32(0, false)\n if (view.length < totalLength) break\n\n const decoded = yield* Effect.try({\n try: () => eventCodec.decode(view.subarray(0, totalLength)),\n catch: (error) =>\n ProviderShared.eventError(\n route,\n `Failed to decode Bedrock Converse event-stream frame: ${\n error instanceof Error ? error.message : String(error)\n }`,\n ),\n })\n cursor = { buffer: cursor.buffer, offset: cursor.offset + totalLength }\n\n if (decoded.headers[\":message-type\"]?.value !== \"event\") continue\n const eventType = decoded.headers[\":event-type\"]?.value\n if (typeof eventType !== \"string\") continue\n const payload = utf8.decode(decoded.body)\n if (!payload) continue\n // The AWS event stream pads short payloads with a `p` field. Drop it\n // before handing the object to the chunk schema. JSON decode goes\n // through the shared Schema-driven codec to satisfy the package rule\n // against ad-hoc `JSON.parse` calls.\n const parsed = (yield* ProviderShared.parseJson(\n route,\n payload,\n \"Failed to parse Bedrock Converse event-stream payload\",\n )) as Record<string, unknown>\n delete parsed.p\n out.push({ [eventType]: parsed })\n }\n return [cursor, out] as const\n })\n\n/**\n * AWS event-stream framing for Bedrock Converse. Each frame is decoded by\n * `@smithy/eventstream-codec` (length + header + payload + CRC) and rewrapped\n * under its `:event-type` header so the chunk schema can match the JSON\n * payload directly.\n */\nexport const framing = (route: string): Framing.Definition<object> => ({\n id: \"aws-event-stream\",\n frame: (bytes) => bytes.pipe(Stream.mapAccumEffect(() => initialFrameBuffer, consumeFrames(route))),\n})\n\nexport * as BedrockEventStream from \"./bedrock-event-stream\"\n", | ||
| "import { AwsV4Signer } from \"aws4fetch\"\nimport { Effect } from \"effect\"\nimport { Headers } from \"effect/unstable/http\"\nimport { Auth, type AuthInput } from \"../../route/auth\"\nimport { ProviderShared } from \"../shared\"\n\n/**\n * AWS credentials for SigV4 signing. Bedrock also supports Bearer API key auth,\n * which provider facades configure as route auth instead of SigV4. STS-vended\n * credentials should be refreshed by the consumer (rebuild the model) before\n * they expire; the route does not refresh.\n */\nexport interface Credentials {\n readonly region: string\n readonly accessKeyId: string\n readonly secretAccessKey: string\n readonly sessionToken?: string\n}\n\nconst signRequest = (input: {\n readonly url: string\n readonly body: string\n readonly headers: Headers.Headers\n readonly credentials: Credentials\n}) =>\n Effect.tryPromise({\n try: async () => {\n const signed = await new AwsV4Signer({\n url: input.url,\n method: \"POST\",\n headers: Object.entries(input.headers),\n body: input.body,\n region: input.credentials.region,\n accessKeyId: input.credentials.accessKeyId,\n secretAccessKey: input.credentials.secretAccessKey,\n sessionToken: input.credentials.sessionToken,\n service: \"bedrock\",\n }).sign()\n return Object.fromEntries(signed.headers.entries())\n },\n catch: (error) =>\n ProviderShared.invalidRequest(\n `Bedrock Converse SigV4 signing failed: ${error instanceof Error ? error.message : String(error)}`,\n ),\n })\n\n/** Sign the exact JSON bytes with SigV4 using credentials configured on the route. */\nexport const sigV4 = (credentials: Credentials | undefined) =>\n Auth.custom((input: AuthInput) => {\n return Effect.gen(function* () {\n if (!credentials) {\n return yield* ProviderShared.invalidRequest(\n \"Bedrock Converse requires either route bearer auth or AWS credentials configured on the route\",\n )\n }\n const headersForSigning = Headers.set(input.headers, \"content-type\", \"application/json\")\n const signed = yield* signRequest({\n url: input.url,\n body: input.body,\n headers: headersForSigning,\n credentials,\n })\n return Headers.setAll(headersForSigning, signed)\n })\n })\n\n/** Bedrock route auth defaults to SigV4 and expects credentials from route configuration. */\nexport const auth = sigV4(undefined)\n\nexport * as BedrockAuth from \"./bedrock-auth\"\n", | ||
| "import { Schema } from \"effect\"\nimport type { CacheHint } from \"../../schema\"\nimport { newBreakpoints, ttlBucket, type Breakpoints } from \"./cache\"\n\n// Bedrock cache markers are positional: emit a `cachePoint` block immediately\n// after the content the caller wants treated as a cacheable prefix. Bedrock\n// accepts optional `ttl: \"5m\" | \"1h\"` on cachePoint, mirroring Anthropic.\nexport const CachePointBlock = Schema.Struct({\n cachePoint: Schema.Struct({\n type: Schema.tag(\"default\"),\n ttl: Schema.optional(Schema.Literals([\"5m\", \"1h\"])),\n }),\n})\nexport type CachePointBlock = Schema.Schema.Type<typeof CachePointBlock>\n\n// Bedrock-Claude enforces the same 4-breakpoint cap as the Anthropic Messages\n// API. Callers pass a shared counter through every `block()` call site so the\n// budget is respected across `system`, `messages`, and `tools`.\nexport const BEDROCK_BREAKPOINT_CAP = 4\n\nexport type { Breakpoints } from \"./cache\"\nexport const breakpoints = () => newBreakpoints(BEDROCK_BREAKPOINT_CAP)\n\nconst DEFAULT_5M: CachePointBlock = { cachePoint: { type: \"default\" } }\nconst DEFAULT_1H: CachePointBlock = { cachePoint: { type: \"default\", ttl: \"1h\" } }\n\nexport const block = (breakpoints: Breakpoints, cache: CacheHint | undefined): CachePointBlock | undefined => {\n if (cache?.type !== \"ephemeral\" && cache?.type !== \"persistent\") return undefined\n if (breakpoints.remaining <= 0) {\n breakpoints.dropped += 1\n return undefined\n }\n breakpoints.remaining -= 1\n return ttlBucket(cache.ttlSeconds) === \"1h\" ? DEFAULT_1H : DEFAULT_5M\n}\n\nexport * as BedrockCache from \"./bedrock-cache\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport type { MediaPart } from \"../../schema\"\nimport { ProviderShared } from \"../shared\"\n\n// Bedrock Converse accepts image `format` as the file extension and\n// `source.bytes` as base64 in the JSON wire format.\nexport const ImageFormat = Schema.Literals([\"png\", \"jpeg\", \"gif\", \"webp\"])\nexport type ImageFormat = Schema.Schema.Type<typeof ImageFormat>\n\nexport const ImageBlock = Schema.Struct({\n image: Schema.Struct({\n format: ImageFormat,\n source: Schema.Struct({ bytes: Schema.String }),\n }),\n})\nexport type ImageBlock = Schema.Schema.Type<typeof ImageBlock>\n\n// Bedrock document blocks require a user-facing name so the model can refer to\n// the uploaded document.\nexport const DocumentFormat = Schema.Literals([\"pdf\", \"csv\", \"doc\", \"docx\", \"xls\", \"xlsx\", \"html\", \"txt\", \"md\"])\nexport type DocumentFormat = Schema.Schema.Type<typeof DocumentFormat>\n\nexport const DocumentBlock = Schema.Struct({\n document: Schema.Struct({\n format: DocumentFormat,\n name: Schema.String,\n source: Schema.Struct({ bytes: Schema.String }),\n }),\n})\nexport type DocumentBlock = Schema.Schema.Type<typeof DocumentBlock>\n\nconst IMAGE_FORMATS = {\n \"image/png\": \"png\",\n \"image/jpeg\": \"jpeg\",\n \"image/jpg\": \"jpeg\",\n \"image/gif\": \"gif\",\n \"image/webp\": \"webp\",\n} as const satisfies Record<string, ImageFormat>\n\nconst DOCUMENT_FORMATS = {\n \"application/pdf\": \"pdf\",\n \"text/csv\": \"csv\",\n \"application/msword\": \"doc\",\n \"application/vnd.openxmlformats-officedocument.wordprocessingml.document\": \"docx\",\n \"application/vnd.ms-excel\": \"xls\",\n \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\": \"xlsx\",\n \"text/html\": \"html\",\n \"text/plain\": \"txt\",\n \"text/markdown\": \"md\",\n} as const satisfies Record<string, DocumentFormat>\n\nconst documentBlock = (part: MediaPart, format: DocumentFormat, bytes: string): DocumentBlock => ({\n document: {\n format,\n name: part.filename ?? `document.${format}`,\n source: { bytes },\n },\n})\n\n// Route by MIME. Known image/document formats lower into a typed block; anything\n// else fails with a clear error instead of silently degrading to a malformed\n// document block. Image MIME types not in `IMAGE_FORMATS` (e.g. `image/svg+xml`)\n// get an image-specific error so the caller knows it's a format-support issue,\n// not a kind-detection issue.\nexport const lower = Effect.fn(\"BedrockMedia.lower\")(function* (part: MediaPart) {\n const mime = part.mediaType.toLowerCase()\n const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]\n if (imageFormat) {\n const media = yield* ProviderShared.validateMedia(\n \"Bedrock Converse\",\n part,\n new Set<string>(Object.keys(IMAGE_FORMATS)),\n )\n return { image: { format: imageFormat, source: { bytes: media.base64 } } } satisfies ImageBlock\n }\n if (mime.startsWith(\"image/\"))\n return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)\n const documentFormat = DOCUMENT_FORMATS[mime as keyof typeof DOCUMENT_FORMATS]\n if (documentFormat) {\n const media = yield* ProviderShared.validateMedia(\n \"Bedrock Converse\",\n part,\n new Set<string>(Object.keys(DOCUMENT_FORMATS)),\n )\n return documentBlock(part, documentFormat, media.base64)\n }\n return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)\n})\n\nexport * as BedrockMedia from \"./bedrock-media\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type CacheHint,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type ModelToolSchemaCompatibility,\n type ProviderMetadata,\n type ReasoningPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolResultPart,\n} from \"../schema\"\nimport { BedrockEventStream } from \"./bedrock-event-stream\"\nimport { classifyProviderFailure } from \"../provider-error\"\nimport { JsonObject, optionalArray, ProviderShared } from \"./shared\"\nimport { BedrockAuth } from \"./utils/bedrock-auth\"\nimport { BedrockCache } from \"./utils/bedrock-cache\"\nimport { BedrockMedia } from \"./utils/bedrock-media\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"bedrock-converse\"\n\nexport type { Credentials as BedrockCredentials } from \"./utils/bedrock-auth\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst BedrockTextBlock = Schema.Struct({\n text: Schema.String,\n})\ntype BedrockTextBlock = Schema.Schema.Type<typeof BedrockTextBlock>\n\nconst BedrockToolUseBlock = Schema.Struct({\n toolUse: Schema.Struct({\n toolUseId: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n }),\n})\ntype BedrockToolUseBlock = Schema.Schema.Type<typeof BedrockToolUseBlock>\n\nconst BedrockToolResultContentItem = Schema.Union([\n Schema.Struct({ text: Schema.String }),\n Schema.Struct({ json: Schema.Unknown }),\n BedrockMedia.ImageBlock,\n])\n\nconst BedrockToolResultBlock = Schema.Struct({\n toolResult: Schema.Struct({\n toolUseId: Schema.String,\n content: Schema.Array(BedrockToolResultContentItem),\n status: Schema.optional(Schema.Literals([\"success\", \"error\"])),\n }),\n})\ntype BedrockToolResultBlock = Schema.Schema.Type<typeof BedrockToolResultBlock>\n\nconst BedrockReasoningBlock = Schema.Struct({\n reasoningContent: Schema.Struct({\n reasoningText: Schema.optional(\n Schema.Struct({\n text: Schema.String,\n signature: Schema.optional(Schema.String),\n }),\n ),\n }),\n})\n\nconst BedrockUserBlock = Schema.Union([\n BedrockTextBlock,\n BedrockMedia.ImageBlock,\n BedrockMedia.DocumentBlock,\n BedrockToolResultBlock,\n BedrockCache.CachePointBlock,\n])\ntype BedrockUserBlock = Schema.Schema.Type<typeof BedrockUserBlock>\n\nconst BedrockAssistantBlock = Schema.Union([\n BedrockTextBlock,\n BedrockReasoningBlock,\n BedrockToolUseBlock,\n BedrockCache.CachePointBlock,\n])\ntype BedrockAssistantBlock = Schema.Schema.Type<typeof BedrockAssistantBlock>\n\nconst BedrockMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"user\"), content: Schema.Array(BedrockUserBlock) }),\n Schema.Struct({ role: Schema.Literal(\"assistant\"), content: Schema.Array(BedrockAssistantBlock) }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype BedrockMessage = Schema.Schema.Type<typeof BedrockMessage>\n\nconst BedrockSystemBlock = Schema.Union([BedrockTextBlock, BedrockCache.CachePointBlock])\ntype BedrockSystemBlock = Schema.Schema.Type<typeof BedrockSystemBlock>\n\nconst BedrockToolSpec = Schema.Struct({\n toolSpec: Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n inputSchema: Schema.Struct({\n json: JsonObject,\n }),\n }),\n})\ntype BedrockToolSpec = Schema.Schema.Type<typeof BedrockToolSpec>\n\nconst BedrockTool = Schema.Union([BedrockToolSpec, BedrockCache.CachePointBlock])\ntype BedrockTool = Schema.Schema.Type<typeof BedrockTool>\n\nconst BedrockToolChoice = Schema.Union([\n Schema.Struct({ auto: Schema.Struct({}) }),\n Schema.Struct({ any: Schema.Struct({}) }),\n Schema.Struct({ tool: Schema.Struct({ name: Schema.String }) }),\n])\n\nconst BedrockBodyFields = {\n modelId: Schema.String,\n messages: Schema.Array(BedrockMessage),\n system: optionalArray(BedrockSystemBlock),\n inferenceConfig: Schema.optional(\n Schema.Struct({\n maxTokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n topP: Schema.optional(Schema.Number),\n stopSequences: optionalArray(Schema.String),\n }),\n ),\n toolConfig: Schema.optional(\n Schema.Struct({\n tools: Schema.Array(BedrockTool),\n toolChoice: Schema.optional(BedrockToolChoice),\n }),\n ),\n additionalModelRequestFields: Schema.optional(JsonObject),\n}\nconst BedrockConverseBody = Schema.Struct(BedrockBodyFields)\nexport type BedrockConverseBody = Schema.Schema.Type<typeof BedrockConverseBody>\n\nconst BedrockUsageSchema = Schema.Struct({\n inputTokens: Schema.optional(Schema.Number),\n outputTokens: Schema.optional(Schema.Number),\n totalTokens: Schema.optional(Schema.Number),\n cacheReadInputTokens: Schema.optional(Schema.Number),\n cacheWriteInputTokens: Schema.optional(Schema.Number),\n})\ntype BedrockUsageSchema = Schema.Schema.Type<typeof BedrockUsageSchema>\n\n// Streaming event shape — the AWS event stream wraps each JSON payload by its\n// `:event-type` header (e.g. `messageStart`, `contentBlockDelta`). We\n// reconstruct that wrapping in `decodeFrames` below so the event schema can\n// stay a plain discriminated record.\nconst BedrockEvent = Schema.Struct({\n messageStart: Schema.optional(Schema.Struct({ role: Schema.String })),\n contentBlockStart: Schema.optional(\n Schema.Struct({\n contentBlockIndex: Schema.Number,\n start: Schema.optional(\n Schema.Struct({\n toolUse: Schema.optional(Schema.Struct({ toolUseId: Schema.String, name: Schema.String })),\n }),\n ),\n }),\n ),\n contentBlockDelta: Schema.optional(\n Schema.Struct({\n contentBlockIndex: Schema.Number,\n delta: Schema.optional(\n Schema.Struct({\n text: Schema.optional(Schema.String),\n toolUse: Schema.optional(Schema.Struct({ input: Schema.String })),\n reasoningContent: Schema.optional(\n Schema.Struct({\n text: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n }),\n ),\n }),\n ),\n }),\n ),\n contentBlockStop: Schema.optional(Schema.Struct({ contentBlockIndex: Schema.Number })),\n messageStop: Schema.optional(\n Schema.Struct({\n stopReason: Schema.String,\n additionalModelResponseFields: Schema.optional(Schema.Unknown),\n }),\n ),\n metadata: Schema.optional(\n Schema.Struct({\n usage: Schema.optional(BedrockUsageSchema),\n metrics: Schema.optional(Schema.Unknown),\n }),\n ),\n internalServerException: Schema.optional(Schema.Struct({ message: Schema.String })),\n modelStreamErrorException: Schema.optional(Schema.Struct({ message: Schema.String })),\n validationException: Schema.optional(Schema.Struct({ message: Schema.String })),\n throttlingException: Schema.optional(Schema.Struct({ message: Schema.String })),\n serviceUnavailableException: Schema.optional(Schema.Struct({ message: Schema.String })),\n})\ntype BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({\n toolSpec: {\n name: tool.name,\n description: tool.description,\n inputSchema: { json: inputSchema },\n },\n})\n\nconst lowerTools = (\n compatibility: ModelToolSchemaCompatibility | undefined,\n breakpoints: BedrockCache.Breakpoints,\n tools: ReadonlyArray<ToolDefinition>,\n): BedrockTool[] => {\n const result: BedrockTool[] = []\n for (const tool of tools) {\n result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, compatibility)))\n const cachePoint = BedrockCache.block(breakpoints, tool.cache)\n if (cachePoint) result.push(cachePoint)\n }\n return result\n}\n\nconst textWithCache = (\n breakpoints: BedrockCache.Breakpoints,\n text: string,\n cache: CacheHint | undefined,\n): Array<BedrockTextBlock | BedrockCache.CachePointBlock> => {\n const cachePoint = BedrockCache.block(breakpoints, cache)\n return cachePoint ? [{ text }, cachePoint] : [{ text }]\n}\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Bedrock Converse\", toolChoice, {\n auto: () => ({ auto: {} }) as const,\n none: () => undefined,\n required: () => ({ any: {} }) as const,\n tool: (name) => ({ tool: { name } }) as const,\n })\n\nconst bedrockMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ bedrock: metadata })\n\nconst reasoningSignature = (part: ReasoningPart) => {\n const bedrock = part.providerMetadata?.bedrock\n return (\n part.encrypted ??\n (ProviderShared.isRecord(bedrock) && typeof bedrock.signature === \"string\" ? bedrock.signature : undefined)\n )\n}\n\nconst lowerToolCall = (part: ToolCallPart): BedrockToolUseBlock => ({\n toolUse: {\n toolUseId: part.id,\n name: part.name,\n input: part.input,\n },\n})\n\nconst lowerToolResultContent = Effect.fn(\"BedrockConverse.lowerToolResultContent\")(function* (part: ToolResultPart) {\n if (part.result.type === \"text\" || part.result.type === \"error\")\n return [{ text: ProviderShared.toolResultText(part) }]\n if (part.result.type === \"json\") return [{ json: part.result.value }]\n\n const content: Array<Schema.Schema.Type<typeof BedrockToolResultContentItem>> = []\n for (const item of part.result.value) {\n if (item.type === \"text\") {\n content.push({ text: item.text })\n continue\n }\n const media = yield* BedrockMedia.lower({\n type: \"media\",\n mediaType: item.mime,\n data: item.uri,\n filename: item.name,\n })\n if (!(\"image\" in media))\n return yield* ProviderShared.invalidRequest(\"Bedrock Converse only supports image media in tool results\")\n content.push(media)\n }\n return content\n})\n\nconst lowerToolResult = Effect.fn(\"BedrockConverse.lowerToolResult\")(function* (part: ToolResultPart) {\n return {\n toolResult: {\n toolUseId: part.id,\n content: yield* lowerToolResultContent(part),\n status: part.result.type === \"error\" ? \"error\" : \"success\",\n },\n } satisfies BedrockToolResultBlock\n})\n\nconst lowerMessages = Effect.fn(\"BedrockConverse.lowerMessages\")(function* (\n request: LLMRequest,\n breakpoints: BedrockCache.Breakpoints,\n) {\n const messages: BedrockMessage[] = []\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Bedrock Converse\", message)\n const content = textWithCache(breakpoints, part.text, part.cache)\n const previous = messages.at(-1)\n if (previous?.role === \"user\")\n messages[messages.length - 1] = { role: \"user\", content: [...previous.content, ...content] }\n else messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"user\") {\n const content: BedrockUserBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"media\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"user\", [\"text\", \"media\"])\n if (part.type === \"text\") {\n content.push(...textWithCache(breakpoints, part.text, part.cache))\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* BedrockMedia.lower(part))\n continue\n }\n }\n messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: BedrockAssistantBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"assistant\", [\n \"text\",\n \"reasoning\",\n \"tool-call\",\n ])\n if (part.type === \"text\") {\n content.push(...textWithCache(breakpoints, part.text, part.cache))\n continue\n }\n if (part.type === \"reasoning\") {\n content.push({\n reasoningContent: {\n reasoningText: { text: part.text, signature: reasoningSignature(part) },\n },\n })\n continue\n }\n if (part.type === \"tool-call\") {\n content.push(lowerToolCall(part))\n continue\n }\n }\n messages.push({ role: \"assistant\", content })\n continue\n }\n\n const content: BedrockUserBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"tool\", [\"tool-result\"])\n content.push(yield* lowerToolResult(part))\n const cachePoint = BedrockCache.block(breakpoints, part.cache)\n if (cachePoint) content.push(cachePoint)\n }\n messages.push({ role: \"user\", content })\n }\n\n return messages\n})\n\n// System prompts share the cache-point convention: emit the text block, then\n// optionally a positional `cachePoint` marker.\nconst lowerSystem = (\n breakpoints: BedrockCache.Breakpoints,\n system: ReadonlyArray<LLMRequest[\"system\"][number]>,\n): BedrockSystemBlock[] => system.flatMap((part) => textWithCache(breakpoints, part.text, part.cache))\n\nconst fromRequest = Effect.fn(\"BedrockConverse.fromRequest\")(function* (request: LLMRequest) {\n const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined\n const generation = request.generation\n // Bedrock-Claude shares Anthropic's 4-breakpoint cap. Spend the budget in\n // tools → system → messages order to favour the highest-impact prefixes.\n const breakpoints = BedrockCache.breakpoints()\n const toolConfig =\n request.tools.length > 0 && request.toolChoice?.type !== \"none\"\n ? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }\n : undefined\n const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)\n const messages = yield* lowerMessages(request, breakpoints)\n if (breakpoints.dropped > 0) {\n yield* Effect.logWarning(\n `Bedrock Converse: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${BedrockCache.BEDROCK_BREAKPOINT_CAP} per request.`,\n )\n }\n return {\n modelId: request.model.id,\n messages,\n system,\n inferenceConfig:\n generation?.maxTokens === undefined &&\n generation?.temperature === undefined &&\n generation?.topP === undefined &&\n (generation?.stop === undefined || generation.stop.length === 0)\n ? undefined\n : {\n maxTokens: generation?.maxTokens,\n temperature: generation?.temperature,\n topP: generation?.topP,\n stopSequences: generation?.stop,\n },\n toolConfig,\n // Converse's base inferenceConfig has no topK; Anthropic/Nova accept it\n // as a model-specific field, so it goes through additionalModelRequestFields.\n additionalModelRequestFields: generation?.topK === undefined ? undefined : { top_k: generation.topK },\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\nconst mapFinishReason = (reason: string): FinishReason => {\n if (reason === \"end_turn\" || reason === \"stop_sequence\") return \"stop\"\n if (reason === \"max_tokens\") return \"length\"\n if (reason === \"tool_use\") return \"tool-calls\"\n if (reason === \"content_filtered\" || reason === \"guardrail_intervened\") return \"content-filter\"\n return \"unknown\"\n}\n\n// AWS Bedrock Converse reports `inputTokens` (inclusive total) with\n// `cacheReadInputTokens` and `cacheWriteInputTokens` as subsets. Pass\n// the total through and derive the non-cached breakdown. Bedrock does\n// not break reasoning out of `outputTokens` for any current model.\nconst mapUsage = (usage: BedrockUsageSchema | undefined): Usage | undefined => {\n if (!usage) return undefined\n const cacheTotal = (usage.cacheReadInputTokens ?? 0) + (usage.cacheWriteInputTokens ?? 0)\n const nonCached = ProviderShared.subtractTokens(usage.inputTokens, cacheTotal)\n return new Usage({\n inputTokens: usage.inputTokens,\n outputTokens: usage.outputTokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: usage.cacheReadInputTokens,\n cacheWriteInputTokens: usage.cacheWriteInputTokens,\n totalTokens: ProviderShared.totalTokens(usage.inputTokens, usage.outputTokens, usage.totalTokens),\n providerMetadata: { bedrock: usage },\n })\n}\n\ninterface ParserState {\n readonly tools: ToolStream.State<number>\n // Bedrock splits the finish into `messageStop` (carries `stopReason`) and\n // `metadata` (carries usage). Hold the terminal event in state so `onHalt`\n // can emit exactly one finish after both chunks have had a chance to arrive.\n readonly pendingFinish: { readonly reason: FinishReason; readonly usage?: Usage } | undefined\n readonly hasToolCalls: boolean\n readonly lifecycle: Lifecycle.State\n readonly reasoningSignatures: Readonly<Record<number, string>>\n}\n\nconst step = (state: ParserState, event: BedrockEvent) =>\n Effect.gen(function* () {\n if (event.contentBlockStart?.start?.toolUse) {\n const index = event.contentBlockStart.contentBlockIndex\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n tools: ToolStream.start(state.tools, index, {\n id: event.contentBlockStart.start.toolUse.toolUseId,\n name: event.contentBlockStart.start.toolUse.name,\n }),\n },\n [\n ...events,\n LLMEvent.toolInputStart({\n id: event.contentBlockStart.start.toolUse.toolUseId,\n name: event.contentBlockStart.start.toolUse.name,\n }),\n ],\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.text) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.textDelta(\n state.lifecycle,\n events,\n `text-${event.contentBlockDelta.contentBlockIndex}`,\n event.contentBlockDelta.delta.text,\n ),\n },\n events,\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.reasoningContent) {\n const index = event.contentBlockDelta.contentBlockIndex\n const reasoning = event.contentBlockDelta.delta.reasoningContent\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: reasoning.text\n ? Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text)\n : state.lifecycle,\n reasoningSignatures: reasoning.signature\n ? { ...state.reasoningSignatures, [index]: reasoning.signature }\n : state.reasoningSignatures,\n },\n events,\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.toolUse) {\n const index = event.contentBlockDelta.contentBlockIndex\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n index,\n event.contentBlockDelta.delta.toolUse.input,\n \"Bedrock Converse tool delta is missing its tool call\",\n )\n if (ToolStream.isError(result)) return yield* result\n const events: LLMEvent[] = []\n const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...result.events)\n return [{ ...state, lifecycle, tools: result.tools }, events] as const\n }\n\n if (event.contentBlockStop) {\n const index = event.contentBlockStop.contentBlockIndex\n const result = yield* ToolStream.finish(ADAPTER, state.tools, index)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length\n ? Lifecycle.stepStart(state.lifecycle, events)\n : Lifecycle.reasoningEnd(\n Lifecycle.textEnd(state.lifecycle, events, `text-${index}`),\n events,\n `reasoning-${index}`,\n state.reasoningSignatures[index]\n ? bedrockMetadata({ signature: state.reasoningSignatures[index] })\n : undefined,\n )\n events.push(...resultEvents)\n return [\n {\n ...state,\n hasToolCalls:\n resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||\n state.hasToolCalls,\n lifecycle,\n tools: result.tools,\n reasoningSignatures: Object.fromEntries(\n Object.entries(state.reasoningSignatures).filter(([key]) => key !== String(index)),\n ),\n },\n events,\n ] as const\n }\n\n if (event.messageStop) {\n return [\n {\n ...state,\n pendingFinish: { reason: mapFinishReason(event.messageStop.stopReason), usage: state.pendingFinish?.usage },\n },\n [],\n ] as const\n }\n\n if (event.metadata) {\n const usage = mapUsage(event.metadata.usage)\n return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? \"stop\", usage } }, []] as const\n }\n\n const exception = (\n [\n [\"internalServerException\", event.internalServerException],\n [\"modelStreamErrorException\", event.modelStreamErrorException],\n [\"serviceUnavailableException\", event.serviceUnavailableException],\n [\"throttlingException\", event.throttlingException],\n [\"validationException\", event.validationException],\n ] as const\n ).find((entry) => entry[1] !== undefined)\n if (exception) {\n return yield* new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({\n message: exception[1]?.message ?? \"Bedrock Converse stream error\",\n code: exception[0],\n }),\n })\n }\n\n return [state, []] as const\n })\n\nconst framing = BedrockEventStream.framing(ADAPTER)\n\nconst onHalt = (state: ParserState): ReadonlyArray<LLMEvent> =>\n state.pendingFinish\n ? (() => {\n const events: LLMEvent[] = []\n Lifecycle.finish(state.lifecycle, events, {\n reason:\n state.pendingFinish.reason === \"stop\" && state.hasToolCalls ? \"tool-calls\" : state.pendingFinish.reason,\n usage: state.pendingFinish.usage,\n })\n return events\n })()\n : []\n\n// =============================================================================\n// Protocol And Bedrock Route\n// =============================================================================\n/**\n * The Bedrock Converse protocol — request body construction, body schema, and\n * the streaming-event state machine.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: BedrockConverseBody,\n from: fromRequest,\n },\n stream: {\n event: BedrockEvent,\n initial: () => ({\n tools: ToolStream.empty<number>(),\n pendingFinish: undefined,\n hasToolCalls: false,\n lifecycle: Lifecycle.initial(),\n reasoningSignatures: {},\n }),\n step,\n onHalt,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"bedrock\",\n providerMetadataKey: \"bedrock\",\n protocol,\n // Bedrock's URL embeds the region in the route endpoint host and the\n // validated modelId in the path. We read the validated body so the URL\n // matches the body that gets signed.\n endpoint: Endpoint.path<BedrockConverseBody>(\n ({ body }) => `/model/${encodeURIComponent(body.modelId)}/converse-stream`,\n ),\n auth: BedrockAuth.auth,\n framing,\n})\n\nexport const sigV4Auth = BedrockAuth.sigV4\n\nexport * as BedrockConverse from \"./bedrock-converse\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as BedrockConverse from \"../protocols/bedrock-converse\"\nimport type { BedrockCredentials } from \"../protocols/bedrock-converse\"\n\nexport const id = ProviderID.make(\"amazon-bedrock\")\n\nexport type Config = RouteDefaultsInput & {\n readonly apiKey?: string\n readonly headers?: Record<string, string>\n readonly credentials?: BedrockCredentials\n /** AWS region. Defaults to `us-east-1` when neither this nor `credentials.region` is set. */\n readonly region?: string\n /** Override the computed `https://bedrock-runtime.<region>.amazonaws.com` URL. */\n readonly baseURL?: string\n}\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly auth?: \"bearer\" | \"sigv4\"\n readonly baseURL?: string\n readonly credentials?: BedrockCredentials\n readonly region?: string\n readonly topP?: number\n}\nexport const routes = [BedrockConverse.route]\n\nconst bedrockBaseURL = (region: string) => `https://bedrock-runtime.${region}.amazonaws.com`\n\nconst configuredRoute = (input: Config) => {\n const { apiKey, credentials, region, baseURL, ...rest } = input\n const resolvedRegion = region ?? credentials?.region ?? \"us-east-1\"\n return BedrockConverse.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? bedrockBaseURL(resolvedRegion) },\n auth: apiKey === undefined ? BedrockConverse.sigV4Auth(credentials) : Auth.bearer(apiKey),\n })\n}\n\nexport const configure = (input: Config = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.auth === \"bearer\" && settings.apiKey === undefined)\n throw new Error(\"Amazon Bedrock bearer auth requires apiKey\")\n if (settings.auth === \"sigv4\" && settings.apiKey !== undefined)\n throw new Error(\"Amazon Bedrock SigV4 auth does not accept apiKey\")\n return configure({\n apiKey: settings.auth === \"sigv4\" ? undefined : settings.apiKey,\n baseURL: settings.baseURL,\n credentials: settings.credentials,\n generation: settings.topP === undefined ? undefined : { topP: settings.topP },\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n region: settings.region,\n }).model(modelID)\n}\n" | ||
| ], | ||
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| ||
| "debugId": "E48145E7836170B164756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/unset.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.unset,\n Effect.fn(\"cli.service.unset\")(function* (input) {\n yield* ServiceConfig.unset(input.key)\n }),\n)\n" | ||
| ], | ||
| "mappings": ";o2BAKA,SAAe,SAAQ,aACrB,OAAS,cAAS,aAAQ,cAAS,WACnC,OAAO,QAAG,wBAAmB,OAAE,cAAU,MAAC,OAAO,MAC/C,WAAO,OAAc,WAAM,OAAM,QAAG,OACrC,MACH", | ||
| "debugId": "551B74A27E285C3964756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-images.ts", "../ai/src/providers/openai.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Encoding, Schema } from \"effect\"\nimport { Headers, HttpClientRequest } from \"effect/unstable/http\"\nimport {\n ImageModel,\n GeneratedImage,\n ImageResponse,\n type ImageRequest,\n type ImageModelDefaults,\n type ImageRoute,\n} from \"../image\"\nimport { Auth, type Definition as AuthDefinition } from \"../route/auth\"\nimport { InvalidProviderOutputReason, LLMError, Usage, mergeHttpOptions, mergeJsonRecords } from \"../schema\"\nimport { ProviderShared } from \"./shared\"\nimport { OpenAIImage } from \"./utils/openai-image\"\n\nconst ADAPTER = \"openai-images\"\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/images/generations\"\n\nexport interface OpenAIImageOptions {\n readonly quality?: \"auto\" | \"low\" | \"medium\" | \"high\"\n readonly background?: \"auto\" | \"opaque\" | \"transparent\"\n readonly moderation?: \"auto\" | \"low\"\n readonly outputFormat?: \"png\" | \"jpeg\" | \"webp\"\n readonly outputCompression?: number\n}\n\nconst OpenAIImageBody = Schema.Struct({\n model: Schema.String,\n prompt: Schema.String,\n n: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),\n size: Schema.optional(Schema.String),\n quality: Schema.optional(Schema.Literals([\"auto\", \"low\", \"medium\", \"high\"])),\n background: Schema.optional(Schema.Literals([\"auto\", \"opaque\", \"transparent\"])),\n moderation: Schema.optional(Schema.Literals([\"auto\", \"low\"])),\n output_format: Schema.optional(Schema.Literals([\"png\", \"jpeg\", \"webp\"])),\n output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),\n})\nexport type OpenAIImageBody = Schema.Schema.Type<typeof OpenAIImageBody>\n\nconst OpenAIImageResponse = Schema.Struct({\n data: Schema.Array(\n Schema.Struct({\n b64_json: Schema.optional(Schema.String),\n url: Schema.optional(Schema.String),\n revised_prompt: Schema.optional(Schema.String),\n }),\n ),\n output_format: Schema.optional(Schema.String),\n usage: Schema.optional(\n Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n output_tokens: Schema.optional(Schema.Number),\n total_tokens: Schema.optional(Schema.Number),\n input_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n }),\n ),\n})\n\nexport interface ModelInput {\n readonly id: string\n readonly auth: AuthDefinition\n readonly baseURL?: string\n readonly headers?: Record<string, string>\n readonly defaults?: ImageModelDefaults\n}\n\nconst providerOptions = (request: ImageRequest): OpenAIImageOptions => ({\n ...request.model.defaults?.providerOptions?.openai,\n ...request.providerOptions?.openai,\n})\n\nconst body = (request: ImageRequest): OpenAIImageBody => {\n const options = providerOptions(request)\n return {\n model: request.model.id,\n prompt: request.prompt,\n n: request.count,\n size: request.size === undefined ? undefined : `${request.size.width}x${request.size.height}`,\n quality: options.quality,\n background: options.background,\n moderation: options.moderation,\n output_format: options.outputFormat,\n output_compression: options.outputCompression,\n }\n}\n\nconst invalidOutput = (message: string) =>\n new LLMError({\n module: ADAPTER,\n method: \"generate\",\n reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),\n })\n\nconst applyQuery = (url: string, query: Record<string, string> | undefined) => {\n if (!query) return url\n const next = new URL(url)\n Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))\n return next.toString()\n}\n\nconst PROTOCOL_BODY_FIELDS = new Set([\n \"model\",\n \"prompt\",\n \"n\",\n \"size\",\n \"quality\",\n \"background\",\n \"moderation\",\n \"output_format\",\n \"output_compression\",\n])\n\nconst bodyWithOverlay = Effect.fn(\"OpenAIImages.bodyWithOverlay\")(function* (\n imageBody: OpenAIImageBody,\n overlay: Record<string, unknown> | undefined,\n) {\n if (!overlay) return imageBody\n const reserved = Object.keys(overlay).filter((key) => PROTOCOL_BODY_FIELDS.has(key))\n if (reserved.length > 0)\n return yield* ProviderShared.invalidRequest(\n `http.body cannot overlay protocol-owned field(s): ${reserved.join(\", \")}`,\n )\n return mergeJsonRecords(imageBody, overlay) ?? imageBody\n})\n\nexport const model = (input: ModelInput) => {\n const route: ImageRoute = {\n id: ADAPTER,\n generate: Effect.fn(\"OpenAIImages.generate\")(function* (request: ImageRequest, execute) {\n if (request.aspectRatio !== undefined)\n return yield* ProviderShared.invalidRequest(\"OpenAI Images does not support the common aspectRatio option\")\n if (request.seed !== undefined)\n return yield* ProviderShared.invalidRequest(\"OpenAI Images does not support the common seed option\")\n\n const requestBody = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIImageBody))(body(request))\n const http = mergeHttpOptions(request.model.defaults?.http, request.http)\n const overlaidBody = yield* bodyWithOverlay(requestBody, http?.body)\n const text = ProviderShared.encodeJson(overlaidBody)\n const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\\/$/, \"\")}${PATH}`, http?.query)\n const headers = yield* Auth.toEffect(input.auth)({\n request,\n method: \"POST\",\n url,\n body: text,\n headers: Headers.fromInput({ ...input.headers, ...http?.headers }),\n })\n const response = yield* execute(\n HttpClientRequest.post(url).pipe(\n HttpClientRequest.setHeaders(headers),\n HttpClientRequest.bodyText(text, \"application/json\"),\n ),\n )\n const payload = yield* response.json.pipe(\n Effect.mapError(() => invalidOutput(\"Failed to read the OpenAI Images response\")),\n )\n const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(\n Effect.mapError(() => invalidOutput(\"OpenAI Images returned an invalid response\")),\n )\n const format = decoded.output_format ?? providerOptions(request).outputFormat ?? \"png\"\n const images = yield* Effect.forEach(decoded.data, (item, index) => {\n if (item.b64_json)\n return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(\n Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),\n Effect.map(\n (data) =>\n new GeneratedImage({\n mediaType: `image/${format}`,\n data,\n providerMetadata:\n item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },\n }),\n ),\n )\n if (item.url)\n return Effect.succeed(\n new GeneratedImage({\n mediaType: `image/${format}`,\n data: item.url,\n providerMetadata:\n item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },\n }),\n )\n return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))\n })\n if (images.length === 0) return yield* invalidOutput(\"OpenAI Images returned no images\")\n return new ImageResponse({\n images,\n usage:\n decoded.usage === undefined\n ? undefined\n : new Usage({\n inputTokens: decoded.usage.input_tokens,\n outputTokens: decoded.usage.output_tokens,\n totalTokens: decoded.usage.total_tokens,\n providerMetadata: { openai: decoded.usage },\n }),\n providerMetadata: { openai: { outputFormat: format } },\n })\n }),\n }\n return ImageModel.make({ id: input.id, provider: \"openai\", route, defaults: input.defaults })\n}\n\nexport const OpenAIImages = {\n model,\n} as const\n", | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route, RouteDefaultsInput } from \"../route/client\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { HttpOptions, ProviderID, ToolDefinition, mergeHttpOptions, type ModelID } from \"../schema\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\nimport { withOpenAIOptions, type OpenAIProviderOptionsInput } from \"./openai-options\"\nimport { OpenAIImages, type OpenAIImageOptions } from \"../protocols/openai-images\"\n\nexport type { OpenAIOptionsInput, OpenAIResponseIncludable } from \"./openai-options\"\nexport type { OpenAIImageOptions } from \"../protocols/openai-images\"\n\nexport const id = ProviderID.make(\"openai\")\n\nexport const routes = [OpenAIResponses.route, OpenAIResponses.webSocketRoute, OpenAIChat.route]\n\n// This provider facade wraps the lower-level Responses and Chat model factories\n// with OpenAI-specific conveniences: typed options, API-key sugar, env fallback,\n// and default option normalization.\nexport type Config = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n readonly queryParams?: Record<string, string>\n readonly providerOptions?: OpenAIProviderOptionsInput\n readonly image?: ImageConfig\n }\n\nexport interface ImageConfig {\n readonly providerOptions?: OpenAIImageOptions\n}\n\nexport interface ImageGenerationOptions {\n readonly action?: \"auto\" | \"generate\" | \"edit\"\n readonly background?: \"auto\" | \"opaque\" | \"transparent\"\n readonly inputFidelity?: \"low\" | \"high\"\n readonly outputCompression?: number\n readonly outputFormat?: \"png\" | \"jpeg\" | \"webp\"\n readonly partialImages?: number\n readonly quality?: \"auto\" | \"low\" | \"medium\" | \"high\"\n readonly size?: string\n}\n\nexport const imageGeneration = (options: ImageGenerationOptions = {}) =>\n ToolDefinition.make({\n name: \"image_generation\",\n description: \"Generate or edit an image using OpenAI's hosted image generation tool.\",\n inputSchema: { type: \"object\", properties: {}, additionalProperties: false },\n native: {\n openai: {\n type: \"image_generation\",\n action: options.action,\n background: options.background,\n input_fidelity: options.inputFidelity,\n output_compression: options.outputCompression,\n output_format: options.outputFormat,\n partial_images: options.partialImages,\n quality: options.quality,\n size: options.size,\n },\n },\n })\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL?: string\n readonly organization?: string\n readonly project?: string\n readonly queryParams?: Readonly<Record<string, string>>\n readonly transport?: \"http\" | \"websocket\"\n readonly providerOptions?: OpenAIProviderOptionsInput\n}\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => AuthOptions.bearer(options, \"OPENAI_API_KEY\")\n\nconst defaults = (input: Config) => {\n const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, image: _image, ...rest } = input\n return rest\n}\n\nconst configuredRoute = <Body, Prepared>(route: Route<Body, Prepared>, input: Config) =>\n route.with({\n auth: auth(input),\n endpoint: { baseURL: input.baseURL, query: input.queryParams },\n })\n\nexport const configure = (input: Config = {}) => {\n const responsesRoute = configuredRoute(OpenAIResponses.route, input)\n const responsesWebSocketRoute = configuredRoute(OpenAIResponses.webSocketRoute, input)\n const chatRoute = configuredRoute(OpenAIChat.route, input)\n const modelDefaults = defaults(input)\n const responses = (id: string | ModelID) =>\n responsesRoute.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true })).model({ id })\n const responsesWebSocket = (id: string | ModelID) =>\n responsesWebSocketRoute.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true })).model({ id })\n const chat = (id: string | ModelID) => chatRoute.with(withOpenAIOptions(id, modelDefaults)).model({ id })\n const image = (modelID: string | ModelID) =>\n OpenAIImages.model({\n id: modelID,\n auth: auth(input),\n baseURL: input.baseURL,\n headers: input.headers,\n defaults: {\n providerOptions:\n input.image?.providerOptions === undefined ? undefined : { openai: { ...input.image.providerOptions } },\n http: mergeHttpOptions(\n input.http === undefined ? undefined : HttpOptions.make(input.http),\n input.queryParams === undefined ? undefined : new HttpOptions({ query: input.queryParams }),\n ),\n },\n })\n\n return {\n id,\n model: responses,\n responses,\n responsesWebSocket,\n chat,\n image,\n configure,\n }\n}\n\nexport const provider = configure()\n\nconst config = (settings: Settings): Config => {\n const headers = {\n ...(settings.organization === undefined ? {} : { \"OpenAI-Organization\": settings.organization }),\n ...(settings.project === undefined ? {} : { \"OpenAI-Project\": settings.project }),\n ...settings.headers,\n }\n return {\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: Object.keys(headers).length === 0 ? undefined : headers,\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n queryParams: settings.queryParams === undefined ? undefined : { ...settings.queryParams },\n }\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n const configured = configure(config(settings))\n if (settings.transport === undefined || settings.transport === \"http\") return configured.responses(modelID)\n if (settings.transport === \"websocket\") return configured.responsesWebSocket(modelID)\n throw new Error(`Unsupported OpenAI Responses transport: ${String(settings.transport)}`)\n}\n\nexport const chatModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).chat(modelID)\nexport const responses = provider.responses\nexport const responsesWebSocket = provider.responsesWebSocket\nexport const chat = provider.chat\nexport const image = provider.image\n" | ||
| ], | ||
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| "debugId": "CA36003241B49D1D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/restart.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.restart,\n Effect.fn(\"cli.service.restart\")(function* () {\n const options = yield* ServiceConfig.options()\n yield* Service.stop(options)\n const transport = yield* Service.ensure(options)\n process.stdout.write(transport.url + EOL)\n }),\n)\n" | ||
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| } |
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/add.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport path from \"node:path\"\nimport { readFile, stat, writeFile } from \"node:fs/promises\"\nimport { Effect, Option } from \"effect\"\nimport { applyEdits, modify } from \"jsonc-parser\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.add,\n Effect.fn(\"cli.mcp.add\")(function* (input) {\n const url = Option.getOrUndefined(input.url)\n const headers = Option.getOrUndefined(input.header)\n const environment = Option.getOrUndefined(input.env)\n // The CLI framework strands `--` operands on the root command, so read the local server command\n // straight from argv after `--`. This also lets the command carry its own flags (e.g. `npx -y`).\n const dash = process.argv.indexOf(\"--\")\n const command = dash === -1 ? [...input.command] : process.argv.slice(dash + 1)\n\n const hasCommand = command.length > 0\n if (url && hasCommand)\n return yield* Effect.fail(new Error(\"Provide either --url <url> or a command after --, not both\"))\n if (!url && !hasCommand) return yield* Effect.fail(new Error(\"Provide either --url <url> or a command after --\"))\n if (url && !URL.canParse(url)) return yield* Effect.fail(new Error(`Invalid URL: ${url}`))\n if (url && environment) return yield* Effect.fail(new Error(\"--env is only valid for local MCP servers\"))\n if (hasCommand && headers) return yield* Effect.fail(new Error(\"--header is only valid for remote MCP servers\"))\n\n const server = url\n ? { type: \"remote\" as const, url, ...(headers ? { headers } : {}) }\n : { type: \"local\" as const, command, ...(environment ? { environment } : {}) }\n\n const configPath = yield* Effect.promise(() => resolveConfigPath(input.global ? Global.Path.config : process.cwd()))\n yield* Effect.promise(() => write(configPath, input.name, server))\n process.stdout.write(`MCP server \"${input.name}\" added to ${configPath}` + EOL)\n }),\n)\n\nexport async function resolveConfigPath(directory: string) {\n const candidates = [\n path.join(directory, \"opencode.json\"),\n path.join(directory, \"opencode.jsonc\"),\n path.join(directory, \".opencode\", \"opencode.json\"),\n path.join(directory, \".opencode\", \"opencode.jsonc\"),\n ]\n for (const candidate of candidates) {\n if (\n await stat(candidate).then(\n (info) => info.isFile(),\n () => false,\n )\n )\n return candidate\n }\n return candidates[0]\n}\n\nasync function write(configPath: string, name: string, server: unknown) {\n const text = await readFile(configPath, \"utf8\").catch((error) => {\n if (typeof error === \"object\" && error !== null && \"code\" in error && error.code === \"ENOENT\") return \"{}\"\n throw error\n })\n const edits = modify(text, [\"mcp\", \"servers\", name], server, {\n formattingOptions: { tabSize: 2, insertSpaces: true },\n })\n await writeFile(configPath, applyEdits(text, edits))\n}\n" | ||
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| "debugId": "FA6D85F8E5CAAD8D64756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openai-options.ts"], | ||
| "sourcesContent": [ | ||
| "import type { ProviderOptions, ReasoningEffort, TextVerbosity } from \"../schema\"\nimport { mergeProviderOptions } from \"../schema\"\nimport type { OpenAIResponseIncludable, OpenAIServiceTier } from \"../protocols/utils/openai-options\"\n\nexport type { OpenAIResponseIncludable, OpenAIServiceTier } from \"../protocols/utils/openai-options\"\n\nexport interface OpenAIOptionsInput {\n readonly [key: string]: unknown\n readonly store?: boolean\n readonly promptCacheKey?: string\n readonly reasoningEffort?: ReasoningEffort\n readonly reasoningSummary?: \"auto\"\n // OpenAI Responses `include` wire field. Mirrors the official SDK's\n // `ResponseIncludable[]` union exactly so AI SDK callers and direct\n // native-SDK callers share one shape and no translation is required.\n readonly include?: ReadonlyArray<OpenAIResponseIncludable>\n readonly textVerbosity?: TextVerbosity\n readonly serviceTier?: OpenAIServiceTier\n}\n\nexport type OpenAIProviderOptionsInput = ProviderOptions & {\n readonly openai?: OpenAIOptionsInput\n}\n\nconst definedEntries = (input: Record<string, unknown>) =>\n Object.entries(input).filter((entry) => entry[1] !== undefined)\n\nconst openAIProviderOptions = (options: OpenAIOptionsInput | undefined): ProviderOptions | undefined => {\n const openai = Object.fromEntries(\n definedEntries({\n store: options?.store,\n promptCacheKey: options?.promptCacheKey,\n reasoningEffort: options?.reasoningEffort,\n reasoningSummary: options?.reasoningSummary,\n include: options?.include,\n textVerbosity: options?.textVerbosity,\n serviceTier: options?.serviceTier,\n }),\n )\n if (Object.keys(openai).length === 0) return undefined\n return { openai }\n}\n\nexport const gpt5DefaultOptions = (\n modelID: string,\n options: { readonly textVerbosity?: boolean } = {},\n): ProviderOptions | undefined => {\n const id = modelID.toLowerCase()\n if (!id.includes(\"gpt-5\") || id.includes(\"gpt-5-chat\") || id.includes(\"gpt-5-pro\")) return undefined\n return openAIProviderOptions({\n reasoningEffort: \"medium\",\n reasoningSummary: \"auto\",\n // GPT-5 reasoning models are configured stateless (`store: false`) by\n // `openAIDefaultOptions` below, so the only way a follow-up turn can\n // carry reasoning state is via the encrypted reasoning include. Without\n // this, callers using the default model facade get reasoning summaries\n // they cannot replay statelessly.\n include: [\"reasoning.encrypted_content\"],\n textVerbosity:\n options.textVerbosity === true && id.includes(\"gpt-5.\") && !id.includes(\"codex\") && !id.includes(\"-chat\")\n ? \"low\"\n : undefined,\n })\n}\n\nexport const openAIDefaultOptions = (\n modelID: string,\n options: { readonly textVerbosity?: boolean } = {},\n): ProviderOptions | undefined =>\n mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID, options))\n\nexport const withOpenAIOptions = <Options extends { readonly providerOptions?: OpenAIProviderOptionsInput }>(\n modelID: string,\n options: Options,\n defaults: { readonly textVerbosity?: boolean } = {},\n): Omit<Options, \"providerOptions\"> & { readonly providerOptions?: ProviderOptions } => {\n return {\n ...options,\n providerOptions: mergeProviderOptions(openAIDefaultOptions(modelID, defaults), options.providerOptions),\n }\n}\n\nexport * as OpenAIProviderOptions from \"./openai-options\"\n" | ||
| ], | ||
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| "debugId": "819BEB8FA62A55A664756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/plugin/sdk.ts", "../plugin/src/v2/effect/tool.ts", "../plugin/src/v2/effect/plugin.ts", "../schema/src/session.ts", "../schema/src/command.ts", "../schema/src/reference.ts"], | ||
| "sourcesContent": [ | ||
| "export * as SdkPlugins from \"./sdk\"\n\nimport type { Plugin } from \"@opencode-ai/plugin/v2/effect/plugin\"\nimport { Context, Effect, Layer } from \"effect\"\nimport { makeGlobalNode } from \"../effect/app-node\"\nimport { EventV2 } from \"../event\"\nimport type { PluginV2 } from \"../plugin\"\n\nexport const Updated = EventV2.ephemeral({ type: \"sdk.plugin.updated\", schema: {} })\n\n/**\n * Holds the plugins an embedder (the `@opencode-ai/sdk-next` host) contributes,\n * so `PluginSupervisor` can add them on every Location boot through the ordinary\n * generation path that `PluginSupervisor` uses for plugins discovered from\n * config. Registration publishes an unlocated update so every booted Location\n * reloads its plugin generation from the shared store.\n *\n * Each host-global layer owns one private store. Location graphs reuse that\n * layer through Effect's memoization, so separate hosts remain isolated while\n * every Location in one host sees the same registrations.\n */\nexport interface Interface {\n readonly register: (plugin: Plugin) => Effect.Effect<void>\n readonly all: () => readonly PluginV2.Versioned[]\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/SdkPlugins\") {}\n\nexport const layer = Layer.effect(\n Service,\n Effect.gen(function* () {\n const events = yield* EventV2.Service\n const plugins = new Map<string, PluginV2.Versioned>()\n let revision = 0\n return Service.of({\n register: (plugin) =>\n Effect.sync(() => {\n plugins.set(plugin.id, { ...plugin, version: String(++revision) })\n }).pipe(Effect.andThen(events.publish(Updated, {})), Effect.asVoid),\n all: () => [...plugins.values()],\n })\n }),\n)\n\nexport const node = makeGlobalNode({ service: Service, layer, deps: [EventV2.node] })\n", | ||
| "export * as Tool from \"./tool.js\"\n\nimport { Agent } from \"@opencode-ai/schema/agent\"\nimport type { LLM } from \"@opencode-ai/schema/llm\"\nimport { Session } from \"@opencode-ai/schema/session\"\nimport { SessionMessage } from \"@opencode-ai/schema/session-message\"\nimport type { StandardJSONSchemaV1, StandardSchemaV1 } from \"@standard-schema/spec\"\nimport { Effect, JsonSchema, Schema } from \"effect\"\nimport type { Hooks, Transform } from \"./registration.js\"\n\nexport interface Context {\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n readonly progress: (update: Progress) => Effect.Effect<void>\n}\n\nexport interface Progress {\n readonly structured: Readonly<Record<string, unknown>>\n readonly content?: ReadonlyArray<Content>\n}\n\nexport type StandardSchemaType<Input = unknown, Output = Input> = StandardSchemaV1<Input, Output> &\n StandardJSONSchemaV1<Input, Output>\nexport type SchemaType<A> = Schema.Codec<A, any> | StandardSchemaType<any, A>\ntype IsAny<A> = 0 extends 1 & A ? true : false\nexport type InputValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<infer A, any>\n ? A\n : S extends StandardSchemaV1<any, infer A>\n ? A\n : never\nexport type OutputValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<infer A, any>\n ? A\n : S extends StandardSchemaV1<infer A, any>\n ? A\n : never\nexport type EncodedValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<any, infer A>\n ? A\n : S extends StandardSchemaV1<any, infer A>\n ? A\n : never\n\ntype ToolDefinition = {\n readonly name: string\n readonly description: string\n readonly inputSchema: JsonSchema.JsonSchema\n readonly outputSchema?: JsonSchema.JsonSchema\n}\n\ntype ToolCall = {\n readonly input: unknown\n readonly [key: string]: unknown\n}\n\ntype ToolResultValue =\n | { readonly type: \"json\"; readonly value: unknown }\n | { readonly type: \"text\"; readonly value: unknown }\n | { readonly type: \"error\"; readonly value: unknown }\n | { readonly type: \"content\"; readonly value: ReadonlyArray<LLM.ToolContent> }\n\ntype ToolOutput = {\n readonly structured: unknown\n readonly content: ReadonlyArray<LLM.ToolContent>\n}\n\nexport class Failure extends Schema.TaggedErrorClass<Failure>()(\"LLM.ToolFailure\", {\n message: Schema.String,\n error: Schema.optional(Schema.Defect()),\n metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n}) {}\n\nexport class RegistrationError extends Schema.TaggedErrorClass<RegistrationError>()(\"Tool.RegistrationError\", {\n name: Schema.String,\n message: Schema.String,\n}) {}\n\nexport type Content =\n | { readonly type: \"text\"; readonly text: string }\n | { readonly type: \"file\"; readonly data: string; readonly mime: string; readonly name?: string }\n\nexport type Definition<\n Input extends SchemaType<any>,\n Structured extends SchemaType<any>,\n Output extends SchemaType<any> = any,\n> = {\n readonly description: string\n readonly input: Input\n readonly output: Output\n readonly structured?: Structured\n readonly permission?: string\n readonly toStructuredOutput?: (input: {\n readonly input: InputValue<Input>\n readonly output: EncodedValue<Output>\n }) => OutputValue<Structured>\n readonly execute: (input: InputValue<Input>, context: Context) => Effect.Effect<OutputValue<Output>, Failure>\n readonly toModelOutput?: (input: {\n readonly input: InputValue<Input>\n readonly output: EncodedValue<Output>\n }) => ReadonlyArray<Content>\n}\n\nexport type DynamicOutput = {\n readonly structured: unknown\n readonly content: ReadonlyArray<Content>\n}\n\n/**\n * Config for a tool whose input shape is a raw JSON Schema not known at compile\n * time (MCP servers, plugin manifests). Input is passed through as `unknown`;\n * `execute` returns the already-projected structured value and model content.\n */\nexport type DynamicDefinition = {\n readonly description: string\n readonly jsonSchema: JsonSchema.JsonSchema\n readonly outputSchema?: JsonSchema.JsonSchema\n readonly permission?: string\n readonly execute: (input: unknown, context: Context) => Effect.Effect<DynamicOutput, Failure>\n}\n\nexport type AnyTool = Definition<any, any> | DynamicDefinition\n\nexport function make<\n Input extends SchemaType<any>,\n Output extends SchemaType<any>,\n Structured extends SchemaType<any> = Output,\n>(config: Definition<Input, Structured, Output>): Definition<Input, Structured, Output>\nexport function make(config: DynamicDefinition): DynamicDefinition\nexport function make(config: AnyTool): AnyTool\nexport function make(config: AnyTool): AnyTool {\n return config\n}\n\nfunction toModelContent(part: Content) {\n if (part.type === \"text\") return { type: \"text\" as const, text: part.text }\n return { type: \"file\" as const, uri: `data:${part.mime};base64,${part.data}`, mime: part.mime, name: part.name }\n}\n\nexport const validateName = (name: string) =>\n /^[A-Za-z][A-Za-z0-9_-]{0,63}$/.test(name)\n ? Effect.void\n : Effect.fail(new RegistrationError({ name, message: `Invalid tool name: ${name}` }))\n\nexport const registrationEntries = (tools: Readonly<Record<string, AnyTool>>, namespace?: string) =>\n Object.entries(tools).map(([name, tool]) => {\n const normalized = name.replace(/[^a-zA-Z0-9_-]/g, \"_\")\n return {\n key: namespace === undefined ? normalized : `${namespace.replaceAll(\".\", \"_\")}_${normalized}`,\n name: normalized,\n namespace,\n tool,\n }\n })\n\nexport const validateNamespace = (namespace: string) =>\n namespace.split(\".\").every((segment) => /^[A-Za-z][A-Za-z0-9_-]{0,63}$/.test(segment))\n ? Effect.void\n : Effect.fail(\n new RegistrationError({ name: namespace, message: `Invalid tool namespace: ${JSON.stringify(namespace)}` }),\n )\n\nexport const withPermission = <T extends AnyTool>(\n tool: T,\n permission: string,\n): Omit<T, \"permission\"> & {\n readonly permission: string\n} => ({ ...tool, permission })\n\nexport const permission = (tool: AnyTool, name: string) => tool.permission ?? name\n\nexport const definition = (name: string, tool: AnyTool): ToolDefinition =>\n \"jsonSchema\" in tool\n ? {\n name,\n description: tool.description,\n inputSchema: tool.jsonSchema,\n outputSchema: tool.outputSchema,\n }\n : {\n name,\n description: tool.description,\n inputSchema: inputJsonSchema(tool.input),\n outputSchema: outputJsonSchema(tool.structured ?? tool.output),\n }\n\nexport const settle = (tool: AnyTool, call: ToolCall, context: Context): Effect.Effect<ToolOutput, Failure> =>\n Effect.gen(function* () {\n if (\"jsonSchema\" in tool) {\n const output = yield* tool.execute(call.input, context)\n return { structured: output.structured, content: output.content.map(toModelContent) }\n }\n\n const input = yield* decodeInput(tool.input, call.input)\n const value = yield* tool.execute(input, context)\n const output = yield* encodeOutput(tool.output, value)\n const structured =\n tool.structured && tool.toStructuredOutput\n ? yield* encodeOutput(tool.structured, tool.toStructuredOutput({ input, output }))\n : output\n return {\n structured,\n content:\n tool.toModelOutput?.({ input, output }).map(toModelContent) ??\n (typeof output === \"string\" ? [{ type: \"text\" as const, text: output }] : []),\n }\n })\n\nfunction decodeInput(schema: SchemaType<any>, value: unknown): Effect.Effect<any, Failure> {\n if (Schema.isSchema(schema))\n return Schema.decodeUnknownEffect(schema)(value).pipe(\n Effect.mapError((error) => new Failure({ message: `Invalid tool input: ${error.message}` })),\n )\n return validateStandard(schema, value, \"Invalid tool input\")\n}\n\nfunction encodeOutput(schema: SchemaType<any>, value: unknown): Effect.Effect<any, Failure> {\n if (Schema.isSchema(schema))\n return Schema.encodeEffect(schema)(value).pipe(\n Effect.mapError(\n (error) => new Failure({ message: `Tool returned an invalid value for its output schema: ${error.message}` }),\n ),\n )\n return validateStandard(schema, value, \"Tool returned an invalid value for its output schema\")\n}\n\nfunction validateStandard(schema: StandardSchemaType, value: unknown, prefix: string): Effect.Effect<unknown, Failure> {\n return Effect.gen(function* () {\n const pending = yield* Effect.try({\n try: () => schema[\"~standard\"].validate(value),\n catch: (error) => standardFailure(prefix, error),\n })\n const result =\n pending instanceof Promise\n ? yield* Effect.tryPromise({ try: () => pending, catch: (error) => standardFailure(prefix, error) })\n : pending\n if (result.issues)\n return yield* Effect.fail(\n new Failure({ message: `${prefix}: ${result.issues.map((issue) => issue.message).join(\", \")}` }),\n )\n return result.value\n })\n}\n\nfunction standardFailure(prefix: string, error: unknown) {\n return new Failure({ message: `${prefix}: ${error instanceof Error ? error.message : String(error)}` })\n}\n\nfunction inputJsonSchema(schema: SchemaType<any>): JsonSchema.JsonSchema {\n if (!Schema.isSchema(schema))\n return schema[\"~standard\"].jsonSchema.input({ target: \"draft-2020-12\" }) as JsonSchema.JsonSchema\n return toJsonSchema(schema)\n}\n\nfunction outputJsonSchema(schema: SchemaType<any>): JsonSchema.JsonSchema {\n if (!Schema.isSchema(schema))\n return schema[\"~standard\"].jsonSchema.output({ target: \"draft-2020-12\" }) as JsonSchema.JsonSchema\n return toJsonSchema(schema)\n}\n\nfunction toJsonSchema(schema: Schema.Top): JsonSchema.JsonSchema {\n const document = Schema.toJsonSchemaDocument(schema)\n if (Object.keys(document.definitions).length === 0) return document.schema\n return { ...document.schema, $defs: document.definitions }\n}\n\nexport interface ToolExecuteBeforeEvent {\n readonly tool: string\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n input: unknown\n}\n\nexport interface ToolExecuteAfterEvent {\n readonly tool: string\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n readonly input: unknown\n result: ToolResultValue\n output?: ToolOutput\n outputPaths?: ReadonlyArray<string>\n}\n\nexport interface RegisterOptions {\n readonly namespace?: string\n /** Defaults to true. False exposes the tool directly to the provider. */\n readonly codemode?: boolean\n}\n\nexport interface ToolDraft {\n add(name: string, tool: AnyTool, options?: RegisterOptions): void\n}\n\nexport interface ToolHooks {\n readonly \"execute.before\": ToolExecuteBeforeEvent\n readonly \"execute.after\": ToolExecuteAfterEvent\n}\n\nexport interface ToolDomain {\n readonly transform: Transform<ToolDraft>\n readonly hook: Hooks<ToolHooks>\n}\n", | ||
| "import type { PluginApi } from \"@opencode-ai/client/effect/api\"\nimport type { Effect, Scope } from \"effect\"\nimport type { PluginOptions } from \"../options.js\"\nimport type { AgentDomain } from \"./agent.js\"\nimport type { AISDKDomain } from \"./aisdk.js\"\nimport type { CatalogDomain } from \"./catalog.js\"\nimport type { CommandDomain } from \"./command.js\"\nimport type { EventDomain } from \"./event.js\"\nimport type { IntegrationDomain } from \"./integration.js\"\nimport type { ReferenceDomain } from \"./reference.js\"\nimport type { SessionDomain } from \"./session.js\"\nimport type { SkillDomain } from \"./skill.js\"\nimport type { ToolDomain } from \"./tool.js\"\n\nexport interface Context {\n readonly options: PluginOptions\n readonly agent: AgentDomain\n readonly aisdk: AISDKDomain\n readonly catalog: CatalogDomain\n readonly command: CommandDomain\n readonly event: EventDomain\n readonly integration: IntegrationDomain\n readonly plugin: PluginApi<unknown>\n readonly reference: ReferenceDomain\n readonly session: SessionDomain\n readonly skill: SkillDomain\n readonly tool: ToolDomain\n}\n\nexport interface Plugin<R = Scope.Scope> {\n readonly id: string\n readonly effect: (context: Context) => Effect.Effect<void, never, R>\n}\n\nexport function define<R = Scope.Scope>(plugin: Plugin<R>) {\n return plugin\n}\n", | ||
| "export * as Session from \"./session.js\"\n\nimport { Schema } from \"effect\"\nimport { Agent } from \"./agent.js\"\nimport { Location } from \"./location.js\"\nimport { Model } from \"./model.js\"\nimport { Project } from \"./project.js\"\nimport { DateTimeUtcFromMillis, optional, RelativePath } from \"./schema.js\"\nimport { SessionEvent } from \"./session-event.js\"\nimport { SessionID } from \"./session-id.js\"\nimport { SessionMessage } from \"./session-message.js\"\nimport { Money } from \"./money.js\"\nimport { TokenUsage } from \"./token-usage.js\"\nimport { Revert } from \"./session-revert.js\"\n\nexport const ID = SessionID\nexport type ID = SessionID\n\nexport const Event = SessionEvent\n\nexport { Revert }\n\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\nexport const Info = Schema.Struct({\n id: ID,\n parentID: ID.pipe(optional),\n fork: Schema.Struct({\n sessionID: ID,\n /** Messages before this exclusive boundary are copied into the fork. */\n messageID: SessionMessage.ID.pipe(optional),\n }).pipe(optional),\n projectID: Project.ID,\n agent: Agent.ID.pipe(optional),\n model: Model.Ref.pipe(optional),\n cost: Money.USD,\n tokens: TokenUsage.Info,\n time: Schema.Struct({\n created: DateTimeUtcFromMillis,\n updated: DateTimeUtcFromMillis,\n archived: DateTimeUtcFromMillis.pipe(optional),\n }),\n title: Schema.String,\n location: Location.Ref,\n subpath: RelativePath.pipe(optional),\n revert: Revert.pipe(optional),\n}).annotate({ identifier: \"Session.Info\" })\n\nexport const ListAnchor = Schema.Struct({\n id: ID,\n time: Schema.Finite,\n direction: Schema.Literals([\"previous\", \"next\"]),\n}).annotate({ identifier: \"Session.ListAnchor\" })\nexport interface ListAnchor extends Schema.Schema.Type<typeof ListAnchor> {}\n", | ||
| "export * as Command from \"./command.js\"\n\nimport { Schema } from \"effect\"\nimport { ephemeral, inventory } from \"./event.js\"\nimport { optional } from \"./schema.js\"\nimport { Model } from \"./model.js\"\nimport { Agent } from \"./agent.js\"\n\nconst Updated = ephemeral({ type: \"command.updated\", schema: {} })\n\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\nexport const Info = Schema.Struct({\n name: Schema.String,\n template: Schema.String,\n description: Schema.String.pipe(optional),\n agent: Agent.ID.pipe(optional),\n model: Model.Ref.pipe(optional),\n subtask: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Command.Info\" })\n\nexport const Event = {\n Updated,\n Definitions: inventory(Updated),\n}\n", | ||
| "export * as Reference from \"./reference.js\"\n\nimport { Schema } from \"effect\"\nimport { optional } from \"./schema.js\"\nimport { ephemeral, inventory } from \"./event.js\"\nimport { AbsolutePath } from \"./schema.js\"\n\nconst Updated = ephemeral({ type: \"reference.updated\", schema: {} })\nexport const Event = { Updated, Definitions: inventory(Updated) }\n\nexport interface LocalSource extends Schema.Schema.Type<typeof LocalSource> {}\nexport const LocalSource = Schema.Struct({\n type: Schema.Literal(\"local\"),\n path: AbsolutePath,\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Reference.LocalSource\" })\n\nexport interface GitSource extends Schema.Schema.Type<typeof GitSource> {}\nexport const GitSource = Schema.Struct({\n type: Schema.Literal(\"git\"),\n repository: Schema.String,\n branch: Schema.String.pipe(optional),\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Reference.GitSource\" })\n\nexport const Source = Schema.Union([LocalSource, GitSource])\n .pipe(Schema.toTaggedUnion(\"type\"))\n .annotate({ identifier: \"Reference.Source\" })\nexport type Source = typeof Source.Type\n\nexport const Info = Schema.Struct({\n name: Schema.String,\n path: AbsolutePath,\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n source: Source,\n}).annotate({ identifier: \"Reference.Info\" })\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\n" | ||
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| ||
| "debugId": "A56DEA607909CE8A64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Duration, Effect, Fiber, Layer, Schema, Stream } from \"effect\"\nimport type { PlatformError } from \"effect/PlatformError\"\nimport { ChildProcess } from \"effect/unstable/process\"\nimport { ChildProcessSpawner } from \"effect/unstable/process/ChildProcessSpawner\"\nimport { CrossSpawnSpawner } from \"./cross-spawn-spawner\"\nimport { makeGlobalNode } from \"./effect/app-node\"\n\nexport class AppProcessError extends Schema.TaggedErrorClass<AppProcessError>()(\"AppProcessError\", {\n command: Schema.String,\n exitCode: Schema.optional(Schema.Number),\n stderr: Schema.optional(Schema.String),\n cause: Schema.optional(Schema.Defect()),\n}) {\n override get message() {\n const detail =\n this.stderr?.trim() || (this.cause instanceof Error ? this.cause.message : this.cause && String(this.cause))\n const status = this.exitCode === undefined ? \"\" : ` (exit ${this.exitCode})`\n return `Command failed${status}: ${this.command}${detail ? `: ${detail}` : \"\"}`\n }\n}\n\nexport interface RunOptions {\n readonly combineOutput?: boolean\n readonly maxOutputBytes?: number\n readonly maxErrorBytes?: number\n readonly signal?: AbortSignal\n readonly timeout?: Duration.Input\n readonly stdin?: string | Uint8Array | Stream.Stream<Uint8Array, PlatformError>\n}\n\nexport interface RunStreamOptions {\n readonly signal?: AbortSignal\n readonly includeStderr?: boolean\n readonly okExitCodes?: ReadonlyArray<number>\n readonly maxErrorBytes?: number\n}\n\nexport interface RunResult {\n readonly command: string\n readonly exitCode: number\n readonly output?: Buffer\n readonly stdout: Buffer\n readonly stderr: Buffer\n readonly outputTruncated?: boolean\n readonly stdoutTruncated: boolean\n readonly stderrTruncated: boolean\n}\n\nexport type Interface = ChildProcessSpawner[\"Service\"] & {\n readonly run: (command: ChildProcess.Command, options?: RunOptions) => Effect.Effect<RunResult, AppProcessError>\n readonly runStream: (\n command: ChildProcess.Command,\n options?: RunStreamOptions,\n ) => Stream.Stream<string, AppProcessError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/AppProcess\") {}\n\nexport const requireSuccess = (result: RunResult): Effect.Effect<RunResult, AppProcessError> =>\n result.exitCode === 0\n ? Effect.succeed(result)\n : Effect.fail(\n new AppProcessError({\n command: result.command,\n exitCode: result.exitCode,\n stderr: result.stderr.toString(\"utf8\"),\n }),\n )\n\nexport const requireExitIn =\n (codes: ReadonlyArray<number>) =>\n (result: RunResult): Effect.Effect<RunResult, AppProcessError> =>\n codes.includes(result.exitCode)\n ? Effect.succeed(result)\n : Effect.fail(\n new AppProcessError({\n command: result.command,\n exitCode: result.exitCode,\n stderr: result.stderr.toString(\"utf8\"),\n }),\n )\n\nconst describeCommand = (command: ChildProcess.Command): string => {\n if (command._tag === \"StandardCommand\") {\n return command.args.length ? `${command.command} ${command.args.join(\" \")}` : command.command\n }\n return `${describeCommand(command.left)} | ${describeCommand(command.right)}`\n}\n\nconst wrapError = (description: string, cause: unknown): AppProcessError =>\n cause instanceof AppProcessError ? cause : new AppProcessError({ command: description, cause })\n\nexport const abortError = (signal: AbortSignal): Error => {\n const reason = signal.reason\n if (reason instanceof Error) return reason\n const err = new Error(\"Aborted\")\n err.name = \"AbortError\"\n return err\n}\n\nexport const waitForAbort = (signal: AbortSignal) =>\n Effect.callback<never, Error>((resume) => {\n if (signal.aborted) {\n resume(Effect.fail(abortError(signal)))\n return\n }\n const onabort = () => resume(Effect.fail(abortError(signal)))\n signal.addEventListener(\"abort\", onabort, { once: true })\n return Effect.sync(() => signal.removeEventListener(\"abort\", onabort))\n })\n\nconst normalizeStdin = (\n input: string | Uint8Array | Stream.Stream<Uint8Array, PlatformError>,\n): Stream.Stream<Uint8Array, PlatformError> =>\n typeof input === \"string\"\n ? Stream.make(new TextEncoder().encode(input))\n : input instanceof Uint8Array\n ? Stream.make(input)\n : input\n\nexport const collectStream = (stream: Stream.Stream<Uint8Array, PlatformError>, maxOutputBytes: number | undefined) =>\n Stream.runFold(\n stream,\n () => ({ chunks: [] as Uint8Array[], bytes: 0, truncated: false }),\n (acc, chunk) => {\n if (maxOutputBytes === undefined) {\n acc.chunks.push(chunk)\n acc.bytes += chunk.length\n return acc\n }\n const remaining = maxOutputBytes - acc.bytes\n if (remaining > 0) acc.chunks.push(remaining >= chunk.length ? chunk : chunk.slice(0, remaining))\n acc.bytes += chunk.length\n acc.truncated = acc.truncated || acc.bytes > maxOutputBytes\n return acc\n },\n ).pipe(Effect.map((x) => ({ buffer: Buffer.concat(x.chunks), truncated: x.truncated })))\n\nconst layer = Layer.effect(\n Service,\n Effect.gen(function* () {\n const spawner = yield* ChildProcessSpawner\n\n const runCommand = (command: ChildProcess.Command, options?: RunOptions) => {\n const description = describeCommand(command)\n const collect = Effect.scoped(\n Effect.gen(function* () {\n const handle = yield* spawner.spawn(command)\n if (options?.combineOutput) {\n const [output, exitCode] = yield* Effect.all(\n [collectStream(handle.all, options.maxOutputBytes), handle.exitCode],\n { concurrency: \"unbounded\" },\n )\n return {\n command: description,\n exitCode,\n output: output.buffer,\n stdout: Buffer.alloc(0),\n stderr: Buffer.alloc(0),\n outputTruncated: output.truncated,\n stdoutTruncated: false,\n stderrTruncated: false,\n } satisfies RunResult\n }\n const [stdout, stderr, exitCode] = yield* Effect.all(\n [\n collectStream(handle.stdout, options?.maxOutputBytes),\n collectStream(handle.stderr, options?.maxErrorBytes),\n handle.exitCode,\n ],\n { concurrency: \"unbounded\" },\n )\n return {\n command: description,\n exitCode,\n stdout: stdout.buffer,\n stderr: stderr.buffer,\n stdoutTruncated: stdout.truncated,\n stderrTruncated: stderr.truncated,\n } satisfies RunResult\n }),\n )\n const timed = options?.timeout\n ? Effect.timeoutOrElse(collect, {\n duration: options.timeout,\n orElse: () => Effect.fail(new AppProcessError({ command: description, cause: new Error(\"Timed out\") })),\n })\n : collect\n const aborted = options?.signal\n ? timed.pipe(\n Effect.raceFirst(\n waitForAbort(options.signal).pipe(Effect.mapError((cause) => wrapError(description, cause))),\n ),\n )\n : timed\n return aborted.pipe(Effect.catch((cause) => Effect.fail(wrapError(description, cause))))\n }\n\n const run = Effect.fn(\"AppProcess.run\")(function* (command: ChildProcess.Command, options?: RunOptions) {\n if (options?.stdin === undefined) return yield* runCommand(command, options)\n if (command._tag !== \"StandardCommand\") {\n return yield* new AppProcessError({\n command: describeCommand(command),\n cause: new Error(\"stdin option only supports StandardCommand; received PipedCommand\"),\n })\n }\n const next = ChildProcess.make(command.command, command.args, {\n ...command.options,\n stdin: normalizeStdin(options.stdin),\n })\n return yield* runCommand(next, options)\n })\n\n const runStream = (\n command: ChildProcess.Command,\n options?: RunStreamOptions,\n ): Stream.Stream<string, AppProcessError> => {\n const description = describeCommand(command)\n const okExitCodes = options?.okExitCodes\n const built: Stream.Stream<string, AppProcessError | PlatformError> = Stream.unwrap(\n Effect.gen(function* () {\n const handle = yield* spawner.spawn(command)\n const stderrFiber = yield* Effect.forkScoped(\n collectStream(handle.stderr, options?.maxErrorBytes).pipe(Effect.map((x) => x.buffer.toString(\"utf8\"))),\n )\n const source = options?.includeStderr === true ? handle.all : handle.stdout\n const lines = source.pipe(\n Stream.decodeText,\n Stream.splitLines,\n Stream.filter((line) => line.length > 0),\n )\n const tail = Stream.unwrap(\n Effect.gen(function* () {\n const code = yield* handle.exitCode\n if (okExitCodes && okExitCodes.length > 0 && !okExitCodes.includes(code)) {\n const stderr = yield* Fiber.join(stderrFiber)\n return Stream.fail(new AppProcessError({ command: description, exitCode: code, stderr }))\n }\n return Stream.empty\n }),\n )\n return Stream.concat(lines, tail) as Stream.Stream<string, AppProcessError | PlatformError>\n }),\n )\n const mapped = built.pipe(\n Stream.catch((cause): Stream.Stream<string, AppProcessError> => Stream.fail(wrapError(description, cause))),\n )\n if (!options?.signal) return mapped\n const signal = options.signal\n return mapped.pipe(\n Stream.interruptWhen(waitForAbort(signal).pipe(Effect.mapError((cause) => wrapError(description, cause)))),\n )\n }\n\n return Service.of({ ...spawner, run, runStream })\n }),\n)\n\nexport const node = makeGlobalNode({ service: Service, layer: layer, deps: [CrossSpawnSpawner.node] })\n\nexport * as AppProcess from \"./process\"\n" | ||
| ], | ||
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| "debugId": "626C5A390CEC905164756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/start.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.start,\n Effect.fn(\"cli.service.start\")(function* () {\n const transport = yield* Service.ensure(yield* ServiceConfig.options())\n process.stdout.write(transport.url + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "AD567623DCDCB62C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/image/photon-wasm.bun.ts", "../core/src/image/photon.ts"], | ||
| "sourcesContent": [ | ||
| "// @ts-ignore Bun embeds static file imports when compiling the CLI.\nimport photonWasm from \"@silvia-odwyer/photon-node/photon_rs_bg.wasm\" with { type: \"file\" }\n\nexport default photonWasm\n", | ||
| "import photonWasm from \"#photon-wasm\"\nimport { Effect } from \"effect\"\nimport path from \"node:path\"\nimport { fileURLToPath } from \"node:url\"\nimport { FileSystem } from \"../filesystem\"\nimport { DecodeError, ResizerUnavailableError, SizeError } from \"../image\"\n\nconst JPEG_QUALITIES = [80, 85, 70, 55, 40]\n\nexport const make = Effect.gen(function* () {\n ;(globalThis as typeof globalThis & { __OPENCODE_PHOTON_WASM_PATH?: string }).__OPENCODE_PHOTON_WASM_PATH =\n path.isAbsolute(photonWasm) ? photonWasm : fileURLToPath(new URL(photonWasm, import.meta.url))\n const loadPhoton = yield* Effect.cached(\n Effect.tryPromise({\n try: () => import(\"@silvia-odwyer/photon-node\"),\n catch: () => new ResizerUnavailableError(),\n }),\n )\n return Effect.fn(\"Image.Photon.normalize\")(function* (\n resource: string,\n content: FileSystem.Content & { readonly encoding: \"base64\" },\n limits: {\n readonly autoResize: boolean\n readonly maxWidth: number\n readonly maxHeight: number\n readonly maxBase64Bytes: number\n },\n ) {\n const photon = yield* loadPhoton\n const decoded = yield* Effect.try({\n try: () => photon.PhotonImage.new_from_byteslice(Buffer.from(content.content, \"base64\")),\n catch: () => new DecodeError({ resource }),\n })\n try {\n const width = decoded.get_width()\n const height = decoded.get_height()\n const bytes = Buffer.byteLength(content.content, \"utf-8\")\n if (width <= limits.maxWidth && height <= limits.maxHeight && bytes <= limits.maxBase64Bytes) return content\n if (!limits.autoResize)\n return yield* new SizeError({\n resource,\n width,\n height,\n bytes,\n maxWidth: limits.maxWidth,\n maxHeight: limits.maxHeight,\n maxBytes: limits.maxBase64Bytes,\n })\n const scale = Math.min(1, limits.maxWidth / width, limits.maxHeight / height)\n const sizes = Array.from({ length: 32 }).reduce<Array<{ width: number; height: number }>>((acc) => {\n const previous = acc.at(-1) ?? {\n width: Math.max(1, Math.round(width * scale)),\n height: Math.max(1, Math.round(height * scale)),\n }\n const next =\n acc.length === 0\n ? previous\n : {\n width: previous.width === 1 ? 1 : Math.max(1, Math.floor(previous.width * 0.75)),\n height: previous.height === 1 ? 1 : Math.max(1, Math.floor(previous.height * 0.75)),\n }\n return acc.some((item) => item.width === next.width && item.height === next.height) ? acc : [...acc, next]\n }, [])\n for (const size of sizes) {\n const resized = photon.resize(decoded, size.width, size.height, photon.SamplingFilter.Lanczos3)\n try {\n const encoders: Array<readonly [mime: string, encode: () => Uint8Array]> = [\n [\"image/png\", () => resized.get_bytes()],\n ...JPEG_QUALITIES.map((quality) => [\"image/jpeg\", () => resized.get_bytes_jpeg(quality)] as const),\n ]\n for (const [mime, encode] of encoders) {\n const candidate = Buffer.from(encode()).toString(\"base64\")\n if (Buffer.byteLength(candidate, \"utf-8\") <= limits.maxBase64Bytes)\n return { ...content, content: candidate, encoding: \"base64\" as const, mime }\n }\n } finally {\n resized.free()\n }\n }\n return yield* new SizeError({\n resource,\n width,\n height,\n bytes,\n maxWidth: limits.maxWidth,\n maxHeight: limits.maxHeight,\n maxBytes: limits.maxBase64Bytes,\n })\n } finally {\n decoded.free()\n }\n })\n})\n" | ||
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| "debugId": "92AEAA819F9D70A664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/debug/agents.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.debug.commands.agents,\n Effect.fn(\"cli.debug.agents\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.agent.list({ location: { directory: process.cwd() } }))\n process.stdout.write(\n JSON.stringify(\n response.data.toSorted((a, b) => a.id.localeCompare(b.id)),\n null,\n 2,\n ) + EOL,\n )\n }),\n)\n" | ||
| ], | ||
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| "debugId": "EE66DDA3E02833BF64756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/route/auth-options.ts"], | ||
| "sourcesContent": [ | ||
| "import type { Config, Redacted } from \"effect\"\nimport { Auth } from \"./auth\"\n\nexport type ApiKeyMode = \"optional\" | \"required\"\n\nexport type AuthOverride = {\n readonly auth: Auth.Definition\n readonly apiKey?: never\n}\n\nexport type OptionalApiKeyAuth = {\n readonly apiKey?: string | Redacted.Redacted<string> | Config.Config<string | Redacted.Redacted<string>>\n readonly auth?: never\n}\n\nexport type RequiredApiKeyAuth = {\n readonly apiKey: string | Redacted.Redacted<string> | Config.Config<string | Redacted.Redacted<string>>\n readonly auth?: never\n}\n\nexport type ProviderAuthOption<Mode extends ApiKeyMode> =\n | AuthOverride\n | (Mode extends \"optional\" ? OptionalApiKeyAuth : RequiredApiKeyAuth)\n\nexport type ModelOptions<Base, Mode extends ApiKeyMode> = Omit<Base, \"apiKey\" | \"auth\"> & ProviderAuthOption<Mode>\n\nexport type ModelArgs<Base, Mode extends ApiKeyMode> = Mode extends \"optional\"\n ? readonly [options?: ModelOptions<Base, Mode>]\n : readonly [options: ModelOptions<Base, Mode>]\n\nexport type ModelFactory<Base, Mode extends ApiKeyMode, Model> = (id: string, ...args: ModelArgs<Base, Mode>) => Model\n\n/**\n * Require at least one of the keys in `T`. Use for option shapes where any\n * subset of fields is acceptable but at least one must be present (e.g. Azure\n * accepts `resourceName` or `baseURL`).\n */\nexport type AtLeastOne<T> = {\n [K in keyof T]: Required<Pick<T, K>> & Partial<Omit<T, K>>\n}[keyof T]\n\n/**\n * Standard bearer-auth resolution for providers: honor an explicit `auth`\n * override, otherwise resolve `apiKey` (option > config var) and apply it as\n * a bearer token.\n */\nexport const bearer = (\n options: ProviderAuthOption<\"optional\">,\n envVar: string | ReadonlyArray<string>,\n): Auth.Definition => {\n if (\"auth\" in options && options.auth) return options.auth\n return (Array.isArray(envVar) ? envVar : [envVar])\n .reduce(\n (auth, name) => auth.orElse(Auth.config(name)),\n Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\"),\n )\n .bearer()\n}\n\nexport * as AuthOptions from \"./auth-options\"\n" | ||
| ], | ||
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| "debugId": "23399E331C5CFB9E64756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/stop.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.stop,\n Effect.fn(\"cli.service.stop\")(function* () {\n yield* Service.stop(yield* ServiceConfig.options())\n }),\n)\n" | ||
| ], | ||
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| } |
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/gemini.ts", "../ai/src/providers/google.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ProviderMetadata,\n type TextPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n} from \"../schema\"\nimport { JsonObject, optionalArray, ProviderShared } from \"./shared\"\nimport { GeminiToolSchema } from \"./utils/gemini-tool-schema\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\n\nconst ADAPTER = \"gemini\"\nconst MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)\nexport const DEFAULT_BASE_URL = \"https://generativelanguage.googleapis.com/v1beta\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst GeminiTextPart = Schema.Struct({\n text: Schema.String,\n thought: Schema.optional(Schema.Boolean),\n thoughtSignature: Schema.optional(Schema.String),\n})\n\nconst GeminiInlineDataPart = Schema.Struct({\n inlineData: Schema.Struct({\n mimeType: Schema.String,\n data: Schema.String,\n }),\n})\n\nconst GeminiFunctionCallPart = Schema.Struct({\n functionCall: Schema.Struct({\n name: Schema.String,\n args: Schema.Unknown,\n }),\n thoughtSignature: Schema.optional(Schema.String),\n})\n\nconst GeminiFunctionResponsePart = Schema.Struct({\n functionResponse: Schema.Struct({\n name: Schema.String,\n response: Schema.Unknown,\n }),\n})\n\nconst GeminiContentPart = Schema.Union([\n GeminiTextPart,\n GeminiInlineDataPart,\n GeminiFunctionCallPart,\n GeminiFunctionResponsePart,\n])\n\nconst GeminiContent = Schema.Struct({\n role: Schema.Literals([\"user\", \"model\"]),\n parts: Schema.Array(GeminiContentPart),\n})\ntype GeminiContent = Schema.Schema.Type<typeof GeminiContent>\n\nconst GeminiSystemInstruction = Schema.Struct({\n parts: Schema.Array(Schema.Struct({ text: Schema.String })),\n})\n\nconst GeminiFunctionDeclaration = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n parameters: Schema.optional(JsonObject),\n})\n\nconst GeminiTool = Schema.Struct({\n functionDeclarations: Schema.Array(GeminiFunctionDeclaration),\n})\n\nconst GeminiToolConfig = Schema.Struct({\n functionCallingConfig: Schema.Struct({\n mode: Schema.Literals([\"AUTO\", \"NONE\", \"ANY\"]),\n allowedFunctionNames: optionalArray(Schema.String),\n }),\n})\n\nconst GeminiThinkingConfig = Schema.Struct({\n thinkingBudget: Schema.optional(Schema.Number),\n includeThoughts: Schema.optional(Schema.Boolean),\n})\n\nconst GeminiGenerationConfig = Schema.Struct({\n maxOutputTokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n topP: Schema.optional(Schema.Number),\n topK: Schema.optional(Schema.Number),\n stopSequences: optionalArray(Schema.String),\n thinkingConfig: Schema.optional(GeminiThinkingConfig),\n})\n\nconst GeminiBodyFields = {\n contents: Schema.Array(GeminiContent),\n systemInstruction: Schema.optional(GeminiSystemInstruction),\n tools: optionalArray(GeminiTool),\n toolConfig: Schema.optional(GeminiToolConfig),\n generationConfig: Schema.optional(GeminiGenerationConfig),\n}\nconst GeminiBody = Schema.Struct(GeminiBodyFields)\nexport type GeminiBody = Schema.Schema.Type<typeof GeminiBody>\n\nconst GeminiUsage = Schema.Struct({\n cachedContentTokenCount: Schema.optional(Schema.Number),\n thoughtsTokenCount: Schema.optional(Schema.Number),\n promptTokenCount: Schema.optional(Schema.Number),\n candidatesTokenCount: Schema.optional(Schema.Number),\n totalTokenCount: Schema.optional(Schema.Number),\n})\ntype GeminiUsage = Schema.Schema.Type<typeof GeminiUsage>\n\nconst GeminiCandidate = Schema.Struct({\n content: Schema.optional(GeminiContent),\n finishReason: Schema.optional(Schema.String),\n})\n\nconst GeminiEvent = Schema.Struct({\n candidates: optionalArray(GeminiCandidate),\n usageMetadata: Schema.optional(GeminiUsage),\n})\ntype GeminiEvent = Schema.Schema.Type<typeof GeminiEvent>\n\ninterface ParserState {\n readonly finishReason?: string\n readonly hasToolCalls: boolean\n readonly nextToolCallId: number\n readonly usage?: Usage\n readonly lifecycle: Lifecycle.State\n readonly reasoningSignature?: string\n}\n\n// =============================================================================\n// Tool Schema Conversion\n// =============================================================================\n// Tool-schema conversion has two distinct concerns:\n//\n// 1. Sanitize — fix common authoring mistakes Gemini rejects: integer/number\n// enums (must be strings), `required` entries that don't match a property,\n// untyped arrays (`items` must be present), and `properties`/`required`\n// keys on non-object scalars. Mirrors OpenCode's historical Gemini rules.\n//\n// 2. Project — lossy mapping from JSON Schema to Gemini's schema dialect:\n// drop empty objects, derive `nullable: true` from `type: [..., \"null\"]`,\n// coerce `const` to `[const]` enum, recurse properties/items, propagate\n// only an allowlisted set of keys (description, required, format, type,\n// properties, items, allOf, anyOf, oneOf, minLength). Anything outside the\n// allowlist (e.g. `additionalProperties`, `$ref`) is silently dropped.\n//\n// Sanitize runs first, then project. The implementation lives in\n// `utils/gemini-tool-schema` so this protocol keeps the same shape as the other\n// provider protocols.\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema) => ({\n name: tool.name,\n description: tool.description,\n parameters: GeminiToolSchema.convert(inputSchema),\n})\n\nconst lowerToolConfig = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Gemini\", toolChoice, {\n auto: () => ({ functionCallingConfig: { mode: \"AUTO\" as const } }),\n none: () => ({ functionCallingConfig: { mode: \"NONE\" as const } }),\n required: () => ({ functionCallingConfig: { mode: \"ANY\" as const } }),\n tool: (name) => ({ functionCallingConfig: { mode: \"ANY\" as const, allowedFunctionNames: [name] } }),\n })\n\nconst lowerUserPart = Effect.fn(\"Gemini.lowerUserPart\")(function* (part: TextPart | MediaPart) {\n if (part.type === \"text\") return { text: part.text }\n const media = yield* ProviderShared.validateMedia(\"Gemini\", part, MEDIA_MIMES)\n return { inlineData: { mimeType: media.mime, data: media.base64 } }\n})\n\nconst googleMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ google: metadata })\n\nconst thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {\n const google = providerMetadata?.google\n return ProviderShared.isRecord(google) && typeof google.thoughtSignature === \"string\"\n ? google.thoughtSignature\n : undefined\n}\n\nconst lowerToolCall = (part: ToolCallPart) => ({\n functionCall: { name: part.name, args: part.input },\n thoughtSignature: thoughtSignature(part.providerMetadata),\n})\n\nconst lowerMessages = Effect.fn(\"Gemini.lowerMessages\")(function* (request: LLMRequest) {\n const contents: GeminiContent[] = []\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Gemini\", message)\n const previous = contents.at(-1)\n if (previous?.role === \"user\")\n contents[contents.length - 1] = { role: \"user\", parts: [...previous.parts, { text: part.text }] }\n else contents.push({ role: \"user\", parts: [{ text: part.text }] })\n continue\n }\n\n if (message.role === \"user\") {\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"media\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"user\", [\"text\", \"media\"])\n parts.push(yield* lowerUserPart(part))\n }\n contents.push({ role: \"user\", parts })\n continue\n }\n\n if (message.role === \"assistant\") {\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"assistant\", [\"text\", \"reasoning\", \"tool-call\"])\n if (part.type === \"text\") {\n parts.push({ text: part.text })\n continue\n }\n if (part.type === \"reasoning\") {\n parts.push({ text: part.text, thought: true, thoughtSignature: thoughtSignature(part.providerMetadata) })\n continue\n }\n if (part.type === \"tool-call\") {\n parts.push(lowerToolCall(part))\n continue\n }\n }\n contents.push({ role: \"model\", parts })\n continue\n }\n\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"tool\", [\"tool-result\"])\n if (part.result.type !== \"content\") {\n parts.push({\n functionResponse: {\n name: part.name,\n response: {\n name: part.name,\n content: ProviderShared.toolResultText(part),\n },\n },\n })\n continue\n }\n const content: ReadonlyArray<ToolContent> = part.result.value\n const text = content.filter((item) => item.type === \"text\").map((item) => item.text)\n parts.push({\n functionResponse: {\n name: part.name,\n response: {\n name: part.name,\n content: text.join(\"\\n\"),\n },\n },\n })\n for (const item of content) {\n if (item.type === \"text\") continue\n const media = yield* ProviderShared.validateToolFile(\"Gemini\", item, MEDIA_MIMES)\n parts.push({ inlineData: { mimeType: media.mime, data: media.base64 } })\n }\n }\n contents.push({ role: \"user\", parts })\n }\n\n return contents\n})\n\nconst geminiOptions = (request: LLMRequest) => request.providerOptions?.gemini\n\nconst thinkingConfig = (request: LLMRequest) => {\n const value = geminiOptions(request)?.thinkingConfig\n if (!ProviderShared.isRecord(value)) return undefined\n const result = {\n thinkingBudget: typeof value.thinkingBudget === \"number\" ? value.thinkingBudget : undefined,\n includeThoughts: typeof value.includeThoughts === \"boolean\" ? value.includeThoughts : undefined,\n }\n return Object.values(result).some((item) => item !== undefined) ? result : undefined\n}\n\nconst fromRequest = Effect.fn(\"Gemini.fromRequest\")(function* (request: LLMRequest) {\n const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== \"none\"\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n const generationConfig = {\n maxOutputTokens: generation?.maxTokens,\n temperature: generation?.temperature,\n topP: generation?.topP,\n topK: generation?.topK,\n stopSequences: generation?.stop,\n thinkingConfig: thinkingConfig(request),\n }\n\n return {\n contents: yield* lowerMessages(request),\n systemInstruction:\n request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },\n tools: toolsEnabled\n ? [\n {\n functionDeclarations: request.tools.map((tool) =>\n lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),\n ),\n },\n ]\n : undefined,\n toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,\n generationConfig: Object.values(generationConfig).some((value) => value !== undefined)\n ? generationConfig\n : undefined,\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// Gemini reports `promptTokenCount` (inclusive total) with a\n// `cachedContentTokenCount` subset. `candidatesTokenCount` is *exclusive*\n// of `thoughtsTokenCount` — visible-only, not a total — so we sum the two\n// to produce the inclusive `outputTokens` the rest of the contract expects.\nconst mapUsage = (usage: GeminiUsage | undefined) => {\n if (!usage) return undefined\n const cached = usage.cachedContentTokenCount\n const nonCached = ProviderShared.subtractTokens(usage.promptTokenCount, cached)\n // `candidatesTokenCount` is visible-only; sum with thoughts to produce the\n // inclusive `outputTokens` the contract expects. Only compute the total\n // when the visible component is reported — otherwise we'd fabricate an\n // inclusive number from a partial breakdown.\n const outputTokens =\n usage.candidatesTokenCount !== undefined ? usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0) : undefined\n return new Usage({\n inputTokens: usage.promptTokenCount,\n outputTokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: usage.thoughtsTokenCount,\n totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),\n providerMetadata: { google: usage },\n })\n}\n\nconst mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean): FinishReason => {\n if (finishReason === \"STOP\") return hasToolCalls ? \"tool-calls\" : \"stop\"\n if (finishReason === \"MAX_TOKENS\") return \"length\"\n if (\n finishReason === \"IMAGE_SAFETY\" ||\n finishReason === \"RECITATION\" ||\n finishReason === \"SAFETY\" ||\n finishReason === \"BLOCKLIST\" ||\n finishReason === \"PROHIBITED_CONTENT\" ||\n finishReason === \"SPII\"\n )\n return \"content-filter\"\n if (finishReason === \"MALFORMED_FUNCTION_CALL\") return \"error\"\n return \"unknown\"\n}\n\nconst finish = (state: ParserState): ReadonlyArray<LLMEvent> =>\n state.finishReason || state.usage\n ? (() => {\n const events: LLMEvent[] = []\n const lifecycle = state.reasoningSignature\n ? Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n \"reasoning-0\",\n googleMetadata({ thoughtSignature: state.reasoningSignature }),\n )\n : state.lifecycle\n Lifecycle.finish(lifecycle, events, {\n reason: mapFinishReason(state.finishReason, state.hasToolCalls),\n usage: state.usage,\n })\n return events\n })()\n : []\n\nconst step = (state: ParserState, event: GeminiEvent) => {\n const nextState = {\n ...state,\n usage: event.usageMetadata ? (mapUsage(event.usageMetadata) ?? state.usage) : state.usage,\n }\n const candidate = event.candidates?.[0]\n if (!candidate?.content)\n return Effect.succeed([\n { ...nextState, finishReason: candidate?.finishReason ?? nextState.finishReason },\n [],\n ] as const)\n\n const events: LLMEvent[] = []\n let hasToolCalls = nextState.hasToolCalls\n let lifecycle = nextState.lifecycle\n let nextToolCallId = nextState.nextToolCallId\n let reasoningSignature = nextState.reasoningSignature\n\n for (const part of candidate.content.parts) {\n if (\"thoughtSignature\" in part && part.thoughtSignature && \"thought\" in part && part.thought)\n reasoningSignature = part.thoughtSignature\n if (\"text\" in part && part.text.length > 0) {\n if (part.thought) {\n lifecycle = Lifecycle.reasoningDelta(\n lifecycle,\n events,\n \"reasoning-0\",\n part.text,\n part.thoughtSignature ? googleMetadata({ thoughtSignature: part.thoughtSignature }) : undefined,\n )\n continue\n }\n lifecycle = Lifecycle.reasoningEnd(\n lifecycle,\n events,\n \"reasoning-0\",\n reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,\n )\n lifecycle = Lifecycle.textDelta(lifecycle, events, \"text-0\", part.text)\n continue\n }\n\n if (\"functionCall\" in part) {\n const input = part.functionCall.args\n const id = `tool_${nextToolCallId++}`\n lifecycle = Lifecycle.reasoningEnd(\n lifecycle,\n events,\n \"reasoning-0\",\n reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,\n )\n lifecycle = Lifecycle.stepStart(lifecycle, events)\n events.push(\n LLMEvent.toolCall({\n id,\n name: part.functionCall.name,\n input,\n providerMetadata: part.thoughtSignature\n ? googleMetadata({ thoughtSignature: part.thoughtSignature })\n : undefined,\n }),\n )\n hasToolCalls = true\n }\n }\n\n return Effect.succeed([\n {\n ...nextState,\n hasToolCalls,\n lifecycle,\n nextToolCallId,\n reasoningSignature,\n finishReason: candidate.finishReason ?? nextState.finishReason,\n },\n events,\n ] as const)\n}\n\n// =============================================================================\n// Protocol And Gemini Route\n// =============================================================================\n/**\n * The Gemini protocol — request body construction, body schema, and the\n * streaming-event state machine. Used by Google AI Studio Gemini and (once\n * registered) Vertex Gemini.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: GeminiBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(GeminiEvent),\n initial: () => ({ hasToolCalls: false, nextToolCallId: 0, lifecycle: Lifecycle.initial() }),\n step,\n onHalt: finish,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"google\",\n providerMetadataKey: \"google\",\n protocol,\n // Gemini's path embeds the model id and pins SSE framing at the URL level.\n endpoint: Endpoint.path(({ request }) => `/models/${request.model.id}:streamGenerateContent?alt=sse`, {\n baseURL: DEFAULT_BASE_URL,\n }),\n auth: Auth.none,\n framing: Framing.sse,\n})\n\nexport * as Gemini from \"./gemini\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID, type ProviderOptions } from \"../schema\"\nimport * as Gemini from \"../protocols/gemini\"\n\nexport const id = ProviderID.make(\"google\")\n\nexport const routes = [Gemini.route]\n\nexport type Config = RouteDefaultsInput & ProviderAuthOption<\"optional\"> & { readonly baseURL?: string }\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL?: string\n readonly providerOptions?: ProviderOptions\n}\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in options && options.auth) return options.auth\n return Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"GOOGLE_GENERATIVE_AI_API_KEY\"))\n .pipe(Auth.header(\"x-goog-api-key\"))\n}\n\nconst configuredRoute = (input: Config) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return Gemini.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })\n}\n\nexport const configure = (input: Config = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure({\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n }).model(modelID)\n" | ||
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| ||
| "debugId": "C8E1B08CE6B6397664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/services/service-config.ts", "src/util/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Global } from \"@opencode-ai/core/global\"\nimport { InstallationChannel, InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Hash } from \"@opencode-ai/core/util/hash\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Effect, FileSystem, Option, Schema } from \"effect\"\nimport { randomBytes } from \"crypto\"\nimport path from \"path\"\nimport { selfCommand } from \"../util/process\"\n\n// The CLI's service configuration file, plus the Service.EnsureOptions binding that\n// points the client package's service operations at this CLI: which\n// registration file (by channel), which version, and how to spawn opencode.\n\nexport const Info = Schema.Struct({\n hostname: Schema.optional(Schema.String),\n port: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1), Schema.isLessThanOrEqualTo(65_535))),\n password: Schema.optional(Schema.String),\n})\nexport type Info = typeof Info.Type\n\nconst keys = [\"hostname\", \"port\", \"password\"] as const\ntype Key = (typeof keys)[number]\n\nconst decodeInfo = Schema.decodeUnknownEffect(Schema.fromJsonString(Info))\nconst decodeRegistration = Schema.decodeUnknownEffect(Schema.fromJsonString(Service.Info))\n\nexport function filename(channel = InstallationChannel) {\n if (channel === \"latest\") return \"service.json\"\n if (channel === \"local\") return \"service-local.json\"\n return `service-${Hash.fast(channel)}.json`\n}\n\nexport function defaultPort(channel = InstallationChannel) {\n if (channel === \"latest\") return 0xc0de\n if (channel === \"local\") return 0xc0df\n return 10_000 + (Number.parseInt(Hash.fast(channel).slice(0, 8), 16) % 50_000)\n}\n\nexport function versionBelongsToChannel(\n version: string | undefined,\n channel = InstallationChannel,\n installedVersion = InstallationVersion,\n) {\n if (version === undefined) return false\n if (version === installedVersion) return true\n const prefix = `0.0.0-${channel}-`\n if (!version.startsWith(prefix)) return false\n return /^\\d+(?:\\.\\d+)?$/.test(version.slice(prefix.length))\n}\n\nexport const migrateRegistration = Effect.fnUntraced(function* (\n legacy: string,\n file: string,\n channel = InstallationChannel,\n installedVersion = InstallationVersion,\n) {\n if (channel === \"latest\" || channel === \"local\") return\n const fs = yield* FileSystem.FileSystem\n const text = yield* fs.readFileString(legacy).pipe(Effect.option)\n if (Option.isNone(text)) return\n const registration = yield* decodeRegistration(text.value).pipe(Effect.option)\n if (Option.isNone(registration)) return\n if (!versionBelongsToChannel(registration.value.version, channel, installedVersion)) return\n yield* fs.writeFileString(file, text.value, { flag: \"wx\", mode: 0o600 }).pipe(Effect.ignore)\n})\n\nfunction configKey(key: string): Key {\n if (key === \"hostname\" || key === \"port\" || key === \"password\") return key\n throw new Error(`Unknown service config key: ${key}`)\n}\n\nconst paths = Effect.gen(function* () {\n const fs = yield* FileSystem.FileSystem\n const global = yield* Global.Service\n const name = filename()\n const file = path.join(global.state, name)\n return {\n fs,\n file,\n legacyFile: path.join(global.state, \"service.json\"),\n configFile: path.join(global.config, name),\n }\n})\n\nexport const options = Effect.fnUntraced(function* () {\n const { file, legacyFile } = yield* paths\n yield* migrateRegistration(legacyFile, file)\n return {\n file,\n version: InstallationVersion,\n command: [...selfCommand(), \"serve\", \"--service\"],\n }\n})\n\nexport const read = Effect.fn(\"cli.service-config.read\")(function* () {\n const { fs, configFile } = yield* paths\n return yield* fs.readFileString(configFile).pipe(\n Effect.flatMap(decodeInfo),\n Effect.catch(() => Effect.succeed({} as Info)),\n )\n})\n\nconst write = Effect.fn(\"cli.service-config.write\")(function* (value: Info) {\n const { fs, configFile } = yield* paths\n const temp = configFile + \".tmp\"\n yield* fs.makeDirectory(path.dirname(configFile), { recursive: true })\n yield* fs.writeFileString(temp, JSON.stringify(value, null, 2) + \"\\n\", { mode: 0o600 })\n yield* fs.rename(temp, configFile)\n})\n\nexport const password = Effect.fn(\"cli.service-config.password\")(function* (value?: string) {\n const existing = yield* read()\n if (value === undefined && existing.password) return existing.password\n const next = value ?? randomBytes(32).toString(\"base64url\")\n\n // Keep one private credential across server restarts so discovered clients\n // can reconnect without exposing a password flag or environment variable.\n yield* write({ ...existing, password: next })\n return next\n})\n\nexport const get = Effect.fn(\"cli.service-config.get\")(function* (key?: string) {\n if (key === undefined) {\n const { password: _password, ...safe } = yield* read()\n return JSON.stringify(safe, null, 2)\n }\n switch (configKey(key)) {\n case \"hostname\": {\n return (yield* read()).hostname ?? \"\"\n }\n case \"port\": {\n const port = (yield* read()).port\n return port === undefined ? \"\" : String(port)\n }\n case \"password\": {\n return yield* password()\n }\n }\n throw new Error(`Unknown service config key: ${key}`)\n})\n\nexport const set = Effect.fn(\"cli.service-config.set\")(function* (key: string, value: string) {\n switch (configKey(key)) {\n case \"hostname\": {\n yield* Service.stop(yield* options())\n yield* write({ ...(yield* read()), hostname: value })\n return\n }\n case \"port\": {\n const port = Number(value)\n if (!Number.isInteger(port) || port < 1 || port > 65_535) throw new Error(\"Port must be between 1 and 65535\")\n yield* Service.stop(yield* options())\n yield* write({ ...(yield* read()), port })\n return\n }\n case \"password\": {\n yield* Service.stop(yield* options())\n yield* password(value)\n return\n }\n }\n})\n\nexport const unset = Effect.fn(\"cli.service-config.unset\")(function* (key: string) {\n switch (configKey(key)) {\n case \"hostname\": {\n yield* Service.stop(yield* options())\n const { hostname: _hostname, ...next } = yield* read()\n yield* write(next)\n return\n }\n case \"port\": {\n yield* Service.stop(yield* options())\n const { port: _port, ...next } = yield* read()\n yield* write(next)\n return\n }\n case \"password\": {\n yield* Service.stop(yield* options())\n const { password: _password, ...next } = yield* read()\n yield* write(next)\n return\n }\n }\n})\n\nexport * as ServiceConfig from \"./service-config\"\n", | ||
| "import path from \"node:path\"\n\nexport function selfCommand() {\n const runtime = path.basename(process.execPath, path.extname(process.execPath)).toLowerCase()\n if (runtime !== \"bun\" && runtime !== \"node\" && runtime !== \"nodejs\") return [process.execPath]\n if (!process.argv[1]) throw new Error(\"Failed to resolve CLI entrypoint\")\n if (runtime === \"node\" || runtime === \"nodejs\") return [process.execPath, ...nodeFlags(), process.argv[1]]\n return [process.execPath, process.argv[1]]\n}\n\nfunction nodeFlags() {\n return process.execArgv.flatMap((arg, index, args) => {\n if (index > 0 && args[index - 1] === \"--conditions\") return []\n if (arg === \"--conditions\") return args[index + 1] ? [arg, args[index + 1]] : []\n if (arg.startsWith(\"--conditions=\")) return [arg]\n if (\n arg === \"--experimental-ffi\" ||\n arg === \"--use-system-ca\" ||\n arg === \"--enable-source-maps\" ||\n arg === \"--no-addons\"\n )\n return [arg]\n if (arg === \"--no-warnings\" || arg.startsWith(\"--disable-warning=\")) return [arg]\n return []\n })\n}\n" | ||
| ], | ||
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| "debugId": "E754D4C3DC5C8CD264756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/logout.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { resolveIntegration } from \"./resolve\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.logout,\n Effect.fn(\"cli.mcp.logout\")(function* (input) {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n\n const integration = yield* resolveIntegration(client, input.name, location)\n if (!integration) {\n process.stdout.write(`No stored credentials for ${input.name}` + EOL)\n return\n }\n\n const credentials = integration.connections.filter((connection) => connection.type === \"credential\")\n if (credentials.length === 0) {\n process.stdout.write(`No stored credentials for ${input.name}` + EOL)\n return\n }\n\n yield* Effect.forEach(\n credentials,\n (connection) => Effect.promise(() => client.credential.remove({ credentialID: connection.id, location })),\n { discard: true },\n )\n process.stdout.write(`Removed OAuth credentials for ${input.name}` + EOL)\n }),\n)\n" | ||
| ], | ||
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Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/openai-options.ts", "../ai/src/protocols/openai-chat.ts"], | ||
| "sourcesContent": [ | ||
| "import { Schema } from \"effect\"\nimport type { LLMRequest, TextVerbosity as TextVerbosityValue } from \"../../schema\"\nimport { ReasoningEfforts, TextVerbosity } from \"../../schema\"\n\nexport const OpenAIReasoningEfforts = ReasoningEfforts\nexport type OpenAIReasoningEffort = string\n\n// Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this\n// in lockstep with `openai-node/src/resources/responses/responses.ts`.\nexport const OpenAIResponseIncludables = [\n \"file_search_call.results\",\n \"web_search_call.results\",\n \"web_search_call.action.sources\",\n \"message.input_image.image_url\",\n \"computer_call_output.output.image_url\",\n \"code_interpreter_call.outputs\",\n \"reasoning.encrypted_content\",\n \"message.output_text.logprobs\",\n] as const\nexport type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number]\nexport const OpenAIServiceTiers = [\"auto\", \"default\", \"flex\", \"priority\"] as const\nexport type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]\n\nconst TEXT_VERBOSITY = new Set<string>([\"low\", \"medium\", \"high\"])\nconst INCLUDABLES = new Set<string>(OpenAIResponseIncludables)\nconst SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)\n\nexport const OpenAIReasoningEffort = Schema.String\nexport const OpenAITextVerbosity = TextVerbosity\nexport const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)\nexport const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)\n\nexport const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === \"string\"\n\nconst isTextVerbosity = (value: unknown): value is TextVerbosityValue =>\n typeof value === \"string\" && TEXT_VERBOSITY.has(value)\n\nconst options = (request: LLMRequest) => request.providerOptions?.openai\n\nexport const store = (request: LLMRequest): boolean | undefined => {\n const value = options(request)?.store\n return typeof value === \"boolean\" ? value : undefined\n}\n\nexport const reasoningEffort = (request: LLMRequest): string | undefined => {\n const value = options(request)?.reasoningEffort\n return typeof value === \"string\" ? value : undefined\n}\n\nexport const reasoningSummary = (request: LLMRequest): \"auto\" | undefined =>\n options(request)?.reasoningSummary === \"auto\" ? \"auto\" : undefined\n\n// Resolve the OpenAI Responses `include` field. Filters out unknown\n// includable values defensively so a typo in upstream config drops the\n// invalid entry instead of poisoning the wire body. An empty array (either\n// passed directly or produced by filtering) is treated as \"no include\" and\n// returns undefined so the request body omits the field entirely.\nexport const include = (request: LLMRequest): ReadonlyArray<OpenAIResponseIncludable> | undefined => {\n const value = options(request)?.include\n if (!Array.isArray(value)) return undefined\n const filtered = value.filter((entry): entry is OpenAIResponseIncludable => INCLUDABLES.has(entry))\n return filtered.length > 0 ? filtered : undefined\n}\n\nexport const promptCacheKey = (request: LLMRequest) => {\n const value = options(request)?.promptCacheKey\n return typeof value === \"string\" ? value : undefined\n}\n\nexport const textVerbosity = (request: LLMRequest) => {\n const value = options(request)?.textVerbosity\n return isTextVerbosity(value) ? value : undefined\n}\n\nexport const serviceTier = (request: LLMRequest) => {\n const value = options(request)?.serviceTier\n return typeof value === \"string\" && SERVICE_TIERS.has(value) ? (value as OpenAIServiceTier) : undefined\n}\n\nexport const instructions = (request: LLMRequest) => {\n const value = options(request)?.instructions\n return typeof value === \"string\" ? value : undefined\n}\n\nexport * as OpenAIOptions from \"./openai-options\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { HttpTransport } from \"../route/transport\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ReasoningPart,\n type TextPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n} from \"../schema\"\nimport { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from \"./shared\"\nimport { OpenAIOptions } from \"./utils/openai-options\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"openai-chat\"\nconst IMAGE_MIMES = new Set<string>(ProviderShared.IMAGE_MIMES)\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/chat/completions\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\n// The body schema is the provider-native JSON body. `fromRequest` below builds\n// this shape from the common `LLMRequest`, then `Route.make` validates and\n// JSON-encodes it before transport.\nconst OpenAIChatFunction = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n parameters: JsonObject,\n})\n\nconst OpenAIChatTool = Schema.Struct({\n type: Schema.tag(\"function\"),\n function: OpenAIChatFunction,\n})\ntype OpenAIChatTool = Schema.Schema.Type<typeof OpenAIChatTool>\n\nconst OpenAIChatAssistantToolCall = Schema.Struct({\n id: Schema.String,\n type: Schema.tag(\"function\"),\n function: Schema.Struct({\n name: Schema.String,\n arguments: Schema.String,\n }),\n})\ntype OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>\n\nconst OpenAIChatUserContent = Schema.Union([\n Schema.Struct({ type: Schema.Literal(\"text\"), text: Schema.String }),\n Schema.Struct({\n type: Schema.Literal(\"image_url\"),\n image_url: Schema.Struct({ url: Schema.String }),\n }),\n])\n\nconst OpenAIChatMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"system\"), content: Schema.String }),\n Schema.Struct({\n role: Schema.Literal(\"user\"),\n content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),\n }),\n Schema.Struct({\n role: Schema.Literal(\"assistant\"),\n content: Schema.NullOr(Schema.String),\n tool_calls: optionalArray(OpenAIChatAssistantToolCall),\n reasoning_content: Schema.optional(Schema.String),\n reasoning: Schema.optional(Schema.String),\n reasoning_text: Schema.optional(Schema.String),\n }),\n Schema.Struct({ role: Schema.Literal(\"tool\"), tool_call_id: Schema.String, content: Schema.String }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype OpenAIChatMessage = Schema.Schema.Type<typeof OpenAIChatMessage>\n\nconst OpenAIChatToolChoice = Schema.Union([\n Schema.Literals([\"auto\", \"none\", \"required\"]),\n Schema.Struct({\n type: Schema.tag(\"function\"),\n function: Schema.Struct({ name: Schema.String }),\n }),\n])\n\nexport const bodyFields = {\n model: Schema.String,\n messages: Schema.Array(OpenAIChatMessage),\n tools: optionalArray(OpenAIChatTool),\n tool_choice: Schema.optional(OpenAIChatToolChoice),\n stream: Schema.Literal(true),\n stream_options: Schema.optional(Schema.Struct({ include_usage: Schema.Boolean })),\n store: Schema.optional(Schema.Boolean),\n reasoning_effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),\n max_tokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n frequency_penalty: Schema.optional(Schema.Number),\n presence_penalty: Schema.optional(Schema.Number),\n seed: Schema.optional(Schema.Number),\n stop: optionalArray(Schema.String),\n}\nconst OpenAIChatBody = Schema.Struct(bodyFields)\nexport type OpenAIChatBody = Schema.Schema.Type<typeof OpenAIChatBody>\n\n// =============================================================================\n// Streaming Event Schema\n// =============================================================================\n// The event schema is one decoded SSE `data:` payload. `Framing.sse` splits the\n// byte stream into strings, then `Protocol.jsonEvent` decodes each string into\n// this provider-native event shape.\nconst OpenAIChatUsage = Schema.Struct({\n prompt_tokens: Schema.optional(Schema.Number),\n completion_tokens: Schema.optional(Schema.Number),\n total_tokens: Schema.optional(Schema.Number),\n prompt_tokens_details: optionalNull(\n Schema.Struct({\n cached_tokens: Schema.optional(Schema.Number),\n }),\n ),\n completion_tokens_details: optionalNull(\n Schema.Struct({\n reasoning_tokens: Schema.optional(Schema.Number),\n }),\n ),\n})\n\nconst OpenAIChatToolCallDeltaFunction = Schema.Struct({\n name: optionalNull(Schema.String),\n arguments: optionalNull(Schema.String),\n})\n\nconst OpenAIChatToolCallDelta = Schema.Struct({\n index: Schema.Number,\n id: optionalNull(Schema.String),\n function: optionalNull(OpenAIChatToolCallDeltaFunction),\n})\ntype OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta>\n\nconst OpenAIChatDelta = Schema.Struct({\n content: optionalNull(Schema.String),\n reasoning_content: optionalNull(Schema.String),\n reasoning: optionalNull(Schema.String),\n reasoning_text: optionalNull(Schema.String),\n tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),\n})\n\nconst OpenAIChatChoice = Schema.Struct({\n delta: optionalNull(OpenAIChatDelta),\n finish_reason: optionalNull(Schema.String),\n})\n\nexport const OpenAIChatEvent = Schema.Struct({\n choices: Schema.Array(OpenAIChatChoice),\n usage: optionalNull(OpenAIChatUsage),\n})\nexport type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>\ntype OpenAIChatRequestMessage = LLMRequest[\"messages\"][number]\n\ninterface PendingToolDelta {\n readonly id?: string\n readonly name?: string\n readonly input: string\n}\n\nexport interface ParserState {\n readonly tools: ToolStream.State<number>\n readonly pendingTools: Partial<Record<number, PendingToolDelta>>\n readonly toolCallEvents: ReadonlyArray<LLMEvent>\n readonly usage?: Usage\n readonly finishReason?: FinishReason\n readonly lifecycle: Lifecycle.State\n readonly reasoningField?: \"reasoning\" | \"reasoning_content\" | \"reasoning_text\"\n}\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\n// Lowering is the only place that knows how common LLM messages map onto the\n// OpenAI Chat wire format. Keep provider quirks here instead of leaking native\n// fields into `LLMRequest`.\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIChatTool => ({\n type: \"function\",\n function: {\n name: tool.name,\n description: tool.description,\n parameters: ToolSchemaProjection.openAI(inputSchema),\n },\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"OpenAI Chat\", toolChoice, {\n auto: () => \"auto\" as const,\n none: () => \"none\" as const,\n required: () => \"required\" as const,\n tool: (name) => ({ type: \"function\" as const, function: { name } }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): OpenAIChatAssistantToolCall => ({\n id: part.id,\n type: \"function\",\n function: {\n name: part.name,\n arguments: ProviderShared.encodeJson(part.input),\n },\n})\n\nconst lowerMedia = Effect.fn(\"OpenAIChat.lowerMedia\")(function* (part: MediaPart) {\n const media = yield* ProviderShared.validateMedia(\"OpenAI Chat\", part, IMAGE_MIMES)\n return { type: \"image_url\" as const, image_url: { url: media.dataUrl } }\n})\n\nconst openAICompatibleReasoningContent = (native: unknown) =>\n isRecord(native) && typeof native.reasoning_content === \"string\" ? native.reasoning_content : undefined\n\nconst reasoningField = (part: ReasoningPart) => {\n const field = part.providerMetadata?.openai?.reasoningField\n if (field === \"reasoning\" || field === \"reasoning_content\" || field === \"reasoning_text\") return field\n return \"reasoning_content\"\n}\n\nconst lowerUserMessage = Effect.fn(\"OpenAIChat.lowerUserMessage\")(function* (message: OpenAIChatRequestMessage) {\n const content: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text })\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* lowerMedia(part))\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"user\", [\"text\", \"media\"])\n }\n if (content.every((part) => part.type === \"text\"))\n return { role: \"user\" as const, content: content.map((part) => part.text).join(\"\") }\n return { role: \"user\" as const, content }\n})\n\nconst lowerAssistantMessage = Effect.fn(\"OpenAIChat.lowerAssistantMessage\")(function* (\n message: OpenAIChatRequestMessage,\n) {\n const content: TextPart[] = []\n const reasoning: ReasoningPart[] = []\n const toolCalls: OpenAIChatAssistantToolCall[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"assistant\", [\"text\", \"reasoning\", \"tool-call\"])\n if (part.type === \"text\") {\n content.push(part)\n continue\n }\n if (part.type === \"reasoning\") {\n reasoning.push(part)\n continue\n }\n if (part.type === \"tool-call\") {\n toolCalls.push(lowerToolCall(part))\n continue\n }\n }\n const text = reasoning.map((part) => part.text).join(\"\")\n const field = reasoning[0] ? reasoningField(reasoning[0]) : \"reasoning_content\"\n return {\n role: \"assistant\" as const,\n content: content.length === 0 ? null : ProviderShared.joinText(content),\n tool_calls: toolCalls.length === 0 ? undefined : toolCalls,\n reasoning_content:\n reasoning.length === 0\n ? openAICompatibleReasoningContent(message.native?.openaiCompatible)\n : field === \"reasoning_content\"\n ? text\n : undefined,\n reasoning: reasoning.length > 0 && field === \"reasoning\" ? text : undefined,\n reasoning_text: reasoning.length > 0 && field === \"reasoning_text\" ? text : undefined,\n }\n})\n\nconst lowerToolMessages = Effect.fn(\"OpenAIChat.lowerToolMessages\")(function* (message: OpenAIChatRequestMessage) {\n const messages: OpenAIChatMessage[] = []\n const images: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"tool\", [\"tool-result\"])\n if (part.result.type !== \"content\") {\n messages.push({ role: \"tool\", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })\n continue\n }\n const content: ReadonlyArray<ToolContent> = part.result.value\n const text = content.filter((item) => item.type === \"text\").map((item) => item.text)\n messages.push({ role: \"tool\", tool_call_id: part.id, content: text.join(\"\\n\") })\n const files = content.filter((item) => item.type === \"file\")\n images.push(\n ...(yield* Effect.forEach(files, (item) =>\n lowerMedia({ type: \"media\", mediaType: item.mime, data: item.uri, filename: item.name }),\n )),\n )\n }\n return { messages, images }\n})\n\nconst lowerMessage = Effect.fn(\"OpenAIChat.lowerMessage\")(function* (message: OpenAIChatRequestMessage) {\n if (message.role === \"user\") return [yield* lowerUserMessage(message)]\n if (message.role === \"assistant\") return [yield* lowerAssistantMessage(message)]\n return (yield* lowerToolMessages(message)).messages\n})\n\nconst lowerMessages = Effect.fn(\"OpenAIChat.lowerMessages\")(function* (request: LLMRequest) {\n const system: OpenAIChatMessage[] =\n request.system.length === 0 ? [] : [{ role: \"system\", content: ProviderShared.joinText(request.system) }]\n const messages = [...system]\n const pendingImages: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n const flushImages = () => {\n if (pendingImages.length === 0) return\n messages.push({ role: \"user\", content: pendingImages.splice(0) })\n }\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"OpenAI Chat\", message)\n if (pendingImages.length > 0) {\n messages.push({ role: \"user\", content: [...pendingImages.splice(0), { type: \"text\", text: part.text }] })\n continue\n }\n const previous = messages.at(-1)\n if (previous?.role === \"user\" && typeof previous.content === \"string\")\n messages[messages.length - 1] = { role: \"user\", content: `${previous.content}\\n${part.text}` }\n else if (previous?.role === \"user\" && Array.isArray(previous.content))\n messages[messages.length - 1] = {\n role: \"user\",\n content: [...previous.content, { type: \"text\", text: part.text }],\n }\n else messages.push({ role: \"user\", content: part.text })\n continue\n }\n if (message.role === \"tool\") {\n const lowered = yield* lowerToolMessages(message)\n messages.push(...lowered.messages)\n pendingImages.push(...lowered.images)\n continue\n }\n flushImages()\n messages.push(...(yield* lowerMessage(message)))\n }\n flushImages()\n return messages\n})\n\nconst lowerOptions = Effect.fn(\"OpenAIChat.lowerOptions\")(function* (request: LLMRequest) {\n const store = OpenAIOptions.store(request)\n const reasoningEffort = OpenAIOptions.reasoningEffort(request)\n return {\n ...(store !== undefined ? { store } : {}),\n ...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),\n }\n})\n\nconst fromRequest = Effect.fn(\"OpenAIChat.fromRequest\")(function* (request: LLMRequest) {\n // `fromRequest` returns the provider body only. Endpoint, auth, framing,\n // validation, and HTTP execution are composed by `Route.make`.\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n return {\n model: request.model.id,\n messages: yield* lowerMessages(request),\n tools:\n request.tools.length === 0\n ? undefined\n : request.tools.map((tool) =>\n lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),\n ),\n tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,\n stream: true as const,\n stream_options: { include_usage: true },\n max_tokens: generation?.maxTokens,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n frequency_penalty: generation?.frequencyPenalty,\n presence_penalty: generation?.presencePenalty,\n seed: generation?.seed,\n stop: generation?.stop,\n ...(yield* lowerOptions(request)),\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// Streaming parsers are small state machines: every event returns a new state\n// plus the common `LLMEvent`s produced by that event. Tool calls are accumulated\n// because OpenAI streams JSON arguments across multiple deltas.\nconst mapFinishReason = (reason: string | null | undefined): FinishReason => {\n if (reason === \"stop\") return \"stop\"\n if (reason === \"length\") return \"length\"\n if (reason === \"content_filter\") return \"content-filter\"\n if (reason === \"function_call\" || reason === \"tool_calls\") return \"tool-calls\"\n return \"unknown\"\n}\n\n// OpenAI Chat reports `prompt_tokens` (inclusive total) with a\n// `cached_tokens` subset, and `completion_tokens` (inclusive total) with\n// a `reasoning_tokens` subset. We pass the inclusive totals through and\n// derive the non-cached breakdown so the `LLM.Usage` contract is\n// satisfied on both sides.\nconst mapUsage = (usage: OpenAIChatEvent[\"usage\"]): Usage | undefined => {\n if (!usage) return undefined\n const cached = usage.prompt_tokens_details?.cached_tokens\n const reasoning = usage.completion_tokens_details?.reasoning_tokens\n const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, cached)\n return new Usage({\n inputTokens: usage.prompt_tokens,\n outputTokens: usage.completion_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: reasoning,\n totalTokens: ProviderShared.totalTokens(usage.prompt_tokens, usage.completion_tokens, usage.total_tokens),\n providerMetadata: { openai: usage },\n })\n}\n\nconst reasoningDelta = (delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null | undefined) => {\n if (delta?.reasoning_content) return { field: \"reasoning_content\", text: delta.reasoning_content } as const\n if (delta?.reasoning) return { field: \"reasoning\", text: delta.reasoning } as const\n if (delta?.reasoning_text) return { field: \"reasoning_text\", text: delta.reasoning_text } as const\n}\n\nconst step = (state: ParserState, event: OpenAIChatEvent) =>\n Effect.gen(function* () {\n const events: LLMEvent[] = []\n const usage = mapUsage(event.usage) ?? state.usage\n const choice = event.choices[0]\n const finishReason = choice?.finish_reason ? mapFinishReason(choice.finish_reason) : state.finishReason\n const delta = choice?.delta\n const toolDeltas = delta?.tool_calls ?? []\n let tools = state.tools\n let pendingTools = state.pendingTools\n\n let lifecycle = state.lifecycle\n\n const reasoning = reasoningDelta(delta)\n const reasoningField = state.reasoningField ?? reasoning?.field\n if (reasoning)\n lifecycle = Lifecycle.reasoningDelta(lifecycle, events, \"reasoning-0\", reasoning.text, {\n openai: { reasoningField: reasoningField ?? reasoning.field },\n })\n\n if (delta?.content) {\n lifecycle = Lifecycle.reasoningEnd(lifecycle, events, \"reasoning-0\")\n lifecycle = Lifecycle.textDelta(lifecycle, events, \"text-0\", delta.content)\n }\n\n if (toolDeltas.length) lifecycle = Lifecycle.reasoningEnd(lifecycle, events, \"reasoning-0\")\n\n for (const tool of toolDeltas) {\n const current = tools[tool.index]\n const pending = pendingTools[tool.index]\n const id = current?.id ?? pending?.id ?? (tool.id || undefined)\n const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)\n const text = `${pending?.input ?? \"\"}${tool.function?.arguments ?? \"\"}`\n if (!current && (!id || !name)) {\n pendingTools = { ...pendingTools, [tool.index]: { id: id || undefined, name: name || undefined, input: text } }\n continue\n }\n if (pending) {\n pendingTools = { ...pendingTools }\n delete pendingTools[tool.index]\n }\n const result = ToolStream.appendOrStart(\n ADAPTER,\n tools,\n tool.index,\n { id: id || undefined, name: name || undefined, text },\n \"OpenAI Chat tool call delta is missing id or name\",\n )\n if (ToolStream.isError(result)) return yield* result\n tools = result.tools\n if (result.events.length) lifecycle = Lifecycle.stepStart(lifecycle, events)\n events.push(...result.events)\n }\n\n if (finishReason !== undefined && state.finishReason === undefined && Object.keys(pendingTools).length > 0)\n return yield* ProviderShared.eventError(ADAPTER, \"OpenAI Chat tool call delta is missing id or name\")\n\n // Finalize accumulated tool inputs eagerly when finish_reason arrives so\n // valid calls and malformed local calls settle independently.\n const finished =\n finishReason !== undefined && state.finishReason === undefined && Object.keys(tools).length > 0\n ? yield* ToolStream.finishAll(ADAPTER, tools)\n : undefined\n\n return [\n {\n tools: finished?.tools ?? tools,\n pendingTools,\n toolCallEvents: finished?.events ?? state.toolCallEvents,\n usage,\n finishReason,\n lifecycle,\n reasoningField,\n },\n events,\n ] as const\n })\n\nconst finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {\n const events: LLMEvent[] = []\n const hasToolCalls = state.toolCallEvents.length > 0\n const reason = state.finishReason === \"stop\" && hasToolCalls ? \"tool-calls\" : state.finishReason\n const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...state.toolCallEvents)\n if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })\n return events\n}\n\n// =============================================================================\n// Protocol And OpenAI Route\n// =============================================================================\n/**\n * The OpenAI Chat protocol — request body construction, body schema, and the\n * streaming-event state machine. Reused by every route that speaks OpenAI Chat\n * over HTTP+SSE: native OpenAI, DeepSeek, TogetherAI, Cerebras, Baseten,\n * Fireworks, DeepInfra, and (once added) Azure OpenAI Chat.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: OpenAIChatBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(OpenAIChatEvent),\n initial: () => ({\n tools: ToolStream.empty<number>(),\n pendingTools: {},\n toolCallEvents: [],\n lifecycle: Lifecycle.initial(),\n reasoningField: undefined,\n }),\n step,\n onHalt: finishEvents,\n },\n})\n\nexport const httpTransport = HttpTransport.sseJson.with<OpenAIChatBody>()\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),\n auth: Auth.none,\n transport: httpTransport,\n})\n\nexport * as OpenAIChat from \"./openai-chat\"\n" | ||
| ], | ||
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| ||
| "debugId": "840B22F42CDF2E5C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/status.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.status,\n Effect.fn(\"cli.service.status\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover({ ...options, version: undefined })\n process.stdout.write((found?.url ?? \"stopped\") + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "C2DAED3B09D4DC8964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/set.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.set,\n Effect.fn(\"cli.service.set\")(function* (input) {\n yield* ServiceConfig.set(input.key, input.value)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "12347842F8C14FBB64756E2164756E21", | ||
| "names": [] | ||
| } |
Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/auth/connect.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type IntegrationCommandStatusOutput, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.auth.commands.connect,\n Effect.fn(\"cli.auth.connect\")(function* (input) {\n process.stdout.write(\"Connecting...\" + EOL + EOL)\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n yield* request(() => client.integration.wellknown.add({ url: input.url, location }))\n const integrationID = input.url.replace(/\\/+$/, \"\")\n const started = yield* request(() =>\n client.integration.command.connect({ integrationID, methodID: \"login\", location }),\n )\n yield* Effect.addFinalizer(() =>\n request(() =>\n client.integration.command.cancel({ integrationID, attemptID: started.data.attemptID, location }),\n ).pipe(Effect.ignore),\n )\n\n const status = yield* wait(client, integrationID, started.data.attemptID)\n if (status.status === \"failed\") return yield* Effect.fail(new Error(status.message))\n if (status.status === \"expired\") return yield* Effect.fail(new Error(\"Authentication expired\"))\n process.stdout.write(\"Connected\" + EOL)\n }),\n)\n\nconst wait = (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n shown = false,\n): Effect.Effect<Exclude<IntegrationCommandStatusOutput[\"data\"], { status: \"pending\" }>, unknown> =>\n Effect.gen(function* () {\n const response = yield* request(() => client.integration.command.status({ integrationID, attemptID, location }))\n if (response.data.status !== \"pending\") return response.data\n const output = response.data.message?.trim()\n if (!shown && output) process.stdout.write(output + EOL + EOL)\n yield* Effect.sleep(500)\n return yield* wait(client, integrationID, attemptID, shown || !!output)\n })\n\nfunction request<A>(task: () => Promise<A>) {\n return Effect.tryPromise({ try: task, catch: (cause) => cause })\n}\n" | ||
| ], | ||
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| "debugId": "589492F6965D34DC64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/image-client.ts", "../ai/src/image.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Effect, Layer } from \"effect\"\nimport { RequestExecutor } from \"./route/executor\"\nimport type { ImageRequest, ImageResponse } from \"./image\"\nimport type { LLMError } from \"./schema\"\n\nexport type Execute = RequestExecutor.Interface[\"execute\"]\n\nexport interface Interface {\n readonly generate: (request: ImageRequest) => Effect.Effect<ImageResponse, LLMError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/ImageClient\") {}\n\nexport const generate = (request: ImageRequest): Effect.Effect<ImageResponse, LLMError> =>\n Effect.gen(function* () {\n const client = yield* Service\n return yield* client.generate(request)\n }) as Effect.Effect<ImageResponse, LLMError>\n\nexport const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(\n Service,\n Effect.gen(function* () {\n const executor = yield* RequestExecutor.Service\n return Service.of({\n generate: (request) => request.model.route.generate(request, executor.execute),\n })\n }),\n)\n\nexport const ImageClient = {\n Service,\n layer,\n generate,\n} as const\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from \"./schema\"\nimport { ImageClient, type Execute as ImageExecute } from \"./image-client\"\n\nexport interface ImageRoute {\n readonly id: string\n readonly generate: (request: ImageRequest, execute: ImageExecute) => Effect.Effect<ImageResponse, LLMError>\n}\n\nexport class ImageModel {\n readonly id: ModelID\n readonly provider: ProviderID\n readonly route: ImageRoute\n readonly defaults?: ImageModelDefaults\n\n constructor(input: ImageModel.Input) {\n this.id = input.id\n this.provider = input.provider\n this.route = input.route\n this.defaults = input.defaults\n }\n\n static make(input: ImageModel.MakeInput) {\n return new ImageModel({\n id: ModelID.make(input.id),\n provider: ProviderID.make(input.provider),\n route: input.route,\n defaults: input.defaults,\n })\n }\n}\n\nexport namespace ImageModel {\n export interface Input {\n readonly id: ModelID\n readonly provider: ProviderID\n readonly route: ImageRoute\n readonly defaults?: ImageModelDefaults\n }\n\n export interface MakeInput extends Omit<Input, \"id\" | \"provider\"> {\n readonly id: string | ModelID\n readonly provider: string | ProviderID\n }\n}\n\nexport interface ImageModelDefaults {\n readonly providerOptions?: Record<string, Record<string, unknown>>\n readonly http?: HttpOptions\n}\n\nexport const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {\n expected: \"Image.Model\",\n})\n\nexport const ImageSize = Schema.Struct({\n width: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),\n height: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),\n}).annotate({ identifier: \"Image.Size\" })\nexport type ImageSize = Schema.Schema.Type<typeof ImageSize>\n\nexport class ImageRequest extends Schema.Class<ImageRequest>(\"Image.Request\")({\n model: ImageModelSchema,\n prompt: Schema.String,\n count: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),\n size: Schema.optional(ImageSize),\n aspectRatio: Schema.optional(Schema.String),\n seed: Schema.optional(Schema.Number),\n providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),\n http: Schema.optional(HttpOptions),\n metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n}) {}\n\nexport type ImageRequestInput = Omit<ConstructorParameters<typeof ImageRequest>[0], \"http\"> & {\n readonly http?: HttpOptions.Input\n}\n\nexport class GeneratedImage extends Schema.Class<GeneratedImage>(\"Image.Generated\")({\n mediaType: Schema.String,\n data: Schema.Union([Schema.String, Schema.Uint8Array]),\n providerMetadata: Schema.optional(ProviderMetadata),\n}) {}\n\nexport class ImageResponse extends Schema.Class<ImageResponse>(\"Image.Response\")({\n images: Schema.Array(GeneratedImage),\n usage: Schema.optional(Usage),\n providerMetadata: Schema.optional(ProviderMetadata),\n}) {\n get image() {\n return this.images[0]\n }\n}\n\nexport const request = (input: ImageRequest | ImageRequestInput) => {\n if (input instanceof ImageRequest) return input\n return new ImageRequest({\n ...input,\n http: input.http === undefined ? undefined : HttpOptions.make(input.http),\n })\n}\n\nexport const generate = (input: ImageRequest | ImageRequestInput) =>\n Effect.try({\n try: () => request(input),\n catch: (error) =>\n new LLMError({\n module: \"Image\",\n method: \"generate\",\n reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),\n }),\n }).pipe(Effect.flatMap(ImageClient.generate))\n\nexport const Image = {\n request,\n generate,\n} as const\n" | ||
| ], | ||
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| "debugId": "B5C9F17CF053109564756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/services/standalone.ts", "src/services/server-connection.ts"], | ||
| "sourcesContent": [ | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { CrossSpawnSpawner } from \"@opencode-ai/core/cross-spawn-spawner\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { Deferred, Effect, Schema, Stream } from \"effect\"\nimport { ChildProcess, ChildProcessSpawner } from \"effect/unstable/process\"\nimport { randomBytes } from \"node:crypto\"\nimport { selfCommand } from \"../util/process\"\n\nconst Ready = Schema.Struct({ url: Schema.String })\nconst decodeReady = Schema.decodeUnknownPromise(Schema.fromJsonString(Ready))\n\ntype Options = {\n readonly command?: ReadonlyArray<string>\n}\n\nfunction command(password: string, options: Options) {\n const [executable, ...args] = options.command ?? [...selfCommand(), \"serve\"]\n if (!executable) throw new Error(\"Failed to resolve standalone server command\")\n return ChildProcess.make(executable, [...args, \"--stdio\", \"--port\", \"0\"], {\n cwd: process.cwd(),\n // Explicit entry wins over anything inherited, so a user-exported\n // OPENCODE_PASSWORD cannot shadow the child's lease credential.\n env: { OPENCODE_PASSWORD: password },\n extendEnv: true,\n // The server treats EOF on this pipe as the end of its ownership lease.\n // The OS closes it even when the TUI is killed before Effect finalizers run.\n stdin: \"pipe\",\n stderr: \"ignore\",\n killSignal: \"SIGTERM\",\n forceKillAfter: \"3 seconds\",\n })\n}\n\nconst makeEndpoint = Effect.fn(\"cli.standalone.endpoint\")(\n function* (options: Options) {\n const password = randomBytes(32).toString(\"base64url\")\n const spawner = yield* ChildProcessSpawner.ChildProcessSpawner\n const proc = yield* spawner.spawn(command(password, options))\n const readyLine = yield* Deferred.make<string, Error>()\n // Keep draining stdout after readiness so later server writes cannot hit EPIPE.\n yield* proc.stdout.pipe(\n Stream.decodeText(),\n Stream.splitLines,\n Stream.runForEach((line) => Deferred.succeed(readyLine, line)),\n Effect.ensuring(Deferred.fail(readyLine, new Error(\"Standalone server exited before reporting readiness\"))),\n Effect.forkScoped,\n )\n const output = yield* Deferred.await(readyLine)\n const ready = yield* Effect.tryPromise(() => decodeReady(output))\n return {\n url: ready.url,\n auth: { type: \"basic\" as const, username: \"opencode\", password },\n pid: proc.pid,\n } satisfies Endpoint & { readonly pid: number }\n },\n Effect.provide(LayerNode.compile(CrossSpawnSpawner.node)),\n)\n\nexport function start(options: Options = {}) {\n return makeEndpoint(options)\n}\n\nexport * as Standalone from \"./standalone\"\n", | ||
| "import { Service, type Endpoint, type EnsureOptions } from \"@opencode-ai/client/effect/service\"\nimport { ClientError, isUnauthorizedError, OpenCode } from \"@opencode-ai/client/promise\"\nimport { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Effect, Redacted } from \"effect\"\nimport { Env } from \"../env\"\nimport { ServiceConfig } from \"./service-config\"\nimport { Standalone } from \"./standalone\"\n\nexport type Args = {\n readonly server?: string\n readonly standalone?: boolean\n readonly mismatch?: \"replace\" | \"ignore\" | \"error\"\n readonly onStart?: EnsureOptions[\"onStart\"]\n}\n\nexport type Resolved = {\n readonly endpoint: Endpoint\n readonly service?: ReturnType<typeof managedService>\n}\n\nexport const resolve = Effect.fn(\"cli.server-connection.resolve\")(function* (args: Args) {\n if (args.server !== undefined && args.standalone)\n return yield* Effect.fail(new Error(\"--server and --standalone cannot be combined\"))\n if (args.server !== undefined) {\n const password = yield* Env.password\n const endpoint = {\n url: args.server,\n auth: password ? { type: \"basic\" as const, username: \"opencode\", password: Redacted.value(password) } : undefined,\n } satisfies Endpoint\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const health = yield* Effect.tryPromise({\n try: () => client.health.get({ signal: AbortSignal.timeout(5_000) }),\n catch: (cause) => connectError(endpoint, cause),\n })\n if (health.version !== InstallationVersion)\n process.stderr.write(\n `Warning: Server at ${endpoint.url} has version ${health.version}; this client is ${InstallationVersion}. Continuing anyway.\\n`,\n )\n return { endpoint } satisfies Resolved\n }\n if (args.standalone) {\n return { endpoint: yield* Standalone.start() } satisfies Resolved\n }\n\n const options = yield* ServiceConfig.options()\n return {\n endpoint: yield* resolveManaged({ ...options, onStart: args.onStart }, args.mismatch ?? \"replace\"),\n service: managedService(options),\n } satisfies Resolved\n})\n\nfunction managedService(options: EnsureOptions) {\n const reconnectOptions = { ...options, version: undefined }\n return {\n reconnect: () => Service.ensure(reconnectOptions),\n restart: () =>\n Effect.gen(function* () {\n yield* Service.stop(options)\n yield* Service.ensure(reconnectOptions)\n }),\n }\n}\n\nconst resolveManaged = Effect.fnUntraced(function* (\n options: EnsureOptions,\n mismatch: NonNullable<Args[\"mismatch\"]>,\n) {\n if (mismatch === \"replace\") return yield* Service.ensure(options)\n if (mismatch === \"ignore\") return yield* Service.ensure({ ...options, version: undefined })\n\n const compatible = yield* Service.discover(options)\n if (compatible !== undefined) return compatible\n const existing = yield* Service.discover({ ...options, version: undefined })\n if (existing !== undefined)\n return yield* Effect.fail(new Error(\"Background server version does not match this client\"))\n return yield* Service.ensure(options)\n})\n\nfunction connectError(endpoint: Endpoint, cause: unknown) {\n if (isUnauthorizedError(cause)) {\n return new Error(\n endpoint.auth === undefined\n ? `Server at ${endpoint.url} requires a password; set OPENCODE_PASSWORD`\n : `Server at ${endpoint.url} rejected the password`,\n { cause },\n )\n }\n if (cause instanceof ClientError && cause.reason === \"Transport\")\n return new Error(`Could not reach server at ${endpoint.url}`, { cause })\n return new Error(`Server at ${endpoint.url} did not provide a compatible V2 health response`, { cause })\n}\n\nexport * as ServerConnection from \"./server-connection\"\n" | ||
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| "debugId": "F26947B2DAD7477C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/pair.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode } from \"@opencode-ai/client/promise\"\nimport { renderUnicodeCompact } from \"uqr\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServiceConfig } from \"../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.pair,\n Effect.fn(\"cli.pair\")(function* () {\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const password = yield* ServiceConfig.password()\n const server = yield* Effect.tryPromise(() =>\n OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) }).server.get(),\n )\n const info = { urls: server.urls, username: \"opencode\", password }\n process.stdout.write(\n [\n \"\",\n ` URLs ${info.urls[0] ?? \"(none)\"}`,\n ...info.urls.slice(1).map((url) => ` ${url}`),\n ` Username ${info.username}`,\n ` Password ${info.password}`,\n \"\",\n \" Scan to pair\",\n \"\",\n renderUnicodeCompact(JSON.stringify(info), { border: 2 })\n .split(EOL)\n .map((line) => \" \" + line)\n .join(EOL),\n \"\",\n ].join(EOL) + EOL,\n )\n\n const hostname = new URL(endpoint.url).hostname\n if (![\"localhost\", \"127.0.0.1\", \"[::1]\"].includes(hostname)) return\n process.stderr.write(\n ` Run \\`opencode service set hostname 0.0.0.0\\` to access the service remotely.${EOL}${EOL}`,\n )\n }),\n)\n" | ||
| ], | ||
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| "debugId": "2B88D24466C7AC9964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/server-process.ts", "src/commands/handlers/serve.ts"], | ||
| "sourcesContent": [ | ||
| "export * as ServerProcess from \"./server-process\"\n\nimport { NodeServices } from \"@effect/platform-node\"\nimport { Service, type DiscoverOptions, type Info } from \"@opencode-ai/client/effect/service\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { AppProcess } from \"@opencode-ai/core/process\"\nimport { randomBytes, randomUUID } from \"node:crypto\"\nimport path from \"node:path\"\nimport { Effect, FileSystem, Logger, Option, Redacted, Schedule, Schema } from \"effect\"\nimport { HttpServer } from \"effect/unstable/http\"\nimport { Env } from \"./env\"\nimport { ServiceConfig } from \"./services/service-config\"\nimport { Updater } from \"./services/updater\"\n\nexport type Mode = \"default\" | \"service\" | \"stdio\"\n\nexport type Options = {\n readonly mode: Mode\n readonly hostname?: string\n readonly port?: number\n}\n\n// The process effect lives until server shutdown; tracing it would parent every request to one process-lifetime trace.\nexport const run = Effect.fnUntraced(function* (options: Options) {\n return yield* processEffect(options).pipe(\n Effect.provide(Updater.layer),\n Effect.provide(LayerNode.compile(LayerNode.group([Global.node, AppProcess.node]))),\n Effect.provide(NodeServices.layer),\n )\n})\n\nconst processEffect = Effect.fnUntraced(function* (options: Options) {\n if (options.mode === \"service\") yield* Effect.sync(() => process.chdir(Global.Path.home))\n return yield* Effect.scoped(\n Effect.gen(function* () {\n const serviceOptions = options.mode === \"service\" ? yield* ServiceConfig.options() : undefined\n const config = options.mode === \"service\" ? yield* ServiceConfig.read() : {}\n const hostname = options.hostname ?? config.hostname ?? \"127.0.0.1\"\n const port = options.port ?? config.port ?? (options.mode === \"service\" ? ServiceConfig.defaultPort() : undefined)\n if (\n serviceOptions !== undefined &&\n port !== undefined &&\n (yield* Service.incumbent({ ...serviceOptions, url: serviceURL(hostname, port) })) !== undefined\n )\n return\n const { start } = yield* Effect.promise(() => import(\"@opencode-ai/server/process\"))\n const environmentPassword = yield* Env.password\n // Keep the lease credential out of the environment inherited by tools.\n if (options.mode === \"stdio\") {\n delete process.env.OPENCODE_PASSWORD\n delete process.env.OPENCODE_SERVER_PASSWORD\n }\n const password =\n options.mode === \"service\"\n ? config.password || randomBytes(32).toString(\"base64url\")\n : environmentPassword\n ? Redacted.value(environmentPassword)\n : randomBytes(32).toString(\"base64url\")\n if (!password) return yield* Effect.fail(new Error(\"Missing server password\"))\n const instanceID = randomUUID()\n const server = yield* start({\n hostname,\n port: Option.fromNullishOr(port),\n password,\n instanceID,\n service:\n serviceOptions === undefined\n ? undefined\n : {\n onListen: (address, shutdown) =>\n Effect.gen(function* () {\n if (!config.password) yield* ServiceConfig.password(password)\n return yield* register(address, password, instanceID, serviceOptions.file, shutdown)\n }),\n },\n }).pipe(\n Effect.provide(Logger.layer([], { mergeWithExisting: false })),\n Effect.catch((error) => {\n if (serviceOptions === undefined || port === undefined || !addressInUse(error)) return Effect.fail(error)\n return recognizeIncumbent(serviceOptions, hostname, port).pipe(\n Effect.flatMap((found) =>\n found\n ? Effect.void\n : Effect.fail(\n new Error(\n `Managed service port ${port} on ${hostname} is already in use by another process. ` +\n \"Configure another port with `opencode service set port <port>` and start the service again.\",\n { cause: error },\n ),\n ),\n ),\n )\n }),\n )\n if (server === undefined) return\n const url = HttpServer.formatAddress(server.address)\n console.log(options.mode === \"stdio\" ? JSON.stringify({ url }) : `server listening on ${url}`)\n if (options.mode === \"default\" && !environmentPassword) console.log(`server password ${password}`)\n const updater = yield* Updater.Service\n yield* updater.check().pipe(Effect.schedule(Schedule.spaced(\"10 minutes\")), Effect.forkScoped)\n return yield* options.mode === \"service\"\n ? server.shutdown\n : options.mode === \"stdio\"\n ? waitForStdinClose()\n : Effect.never\n }).pipe(Effect.annotateLogs({ role: \"server\" })),\n )\n})\n\nconst infoJson = Schema.fromJsonString(Service.Info)\nconst encodeInfo = Schema.encodeEffect(infoJson)\nconst decodeInfo = Schema.decodeUnknownEffect(infoJson)\n\nconst register = Effect.fnUntraced(function* (\n address: HttpServer.Address,\n password: string,\n id: string,\n file: string,\n shutdown: Effect.Effect<void>,\n) {\n const fs = yield* FileSystem.FileSystem\n const temp = file + \".\" + id + \".tmp\"\n yield* fs.makeDirectory(path.dirname(file), { recursive: true })\n const info = {\n id,\n version: InstallationVersion,\n url: HttpServer.formatAddress(address),\n pid: process.pid,\n password,\n }\n const encoded = yield* encodeInfo(info)\n const current = fs.readFileString(file).pipe(\n Effect.flatMap(decodeInfo),\n Effect.orElseSucceed(() => undefined),\n )\n const owns = (found: Info | undefined) =>\n found?.id === info.id &&\n found.version === info.version &&\n found.url === info.url &&\n found.pid === info.pid &&\n found.password === info.password\n yield* fs.writeFileString(temp, encoded, { mode: 0o600 }).pipe(Effect.andThen(fs.rename(temp, file)))\n yield* current.pipe(\n Effect.filterOrFail(owns),\n Effect.repeat(Schedule.spaced(\"5 seconds\")),\n Effect.ignore,\n Effect.andThen(shutdown),\n Effect.forkScoped,\n )\n return current.pipe(\n Effect.flatMap((found) => (owns(found) ? fs.remove(file) : Effect.void)),\n Effect.ignore,\n )\n})\n\nconst recognizeIncumbent = Effect.fnUntraced(function* (options: DiscoverOptions, hostname: string, port: number) {\n const found = yield* Service.incumbent({ ...options, url: serviceURL(hostname, port) }).pipe(\n Effect.filterOrFail((value) => value !== undefined),\n Effect.retry(Schedule.spaced(\"100 millis\")),\n Effect.timeoutOption(\"15 seconds\"),\n )\n return Option.isSome(found)\n})\n\nfunction serviceURL(hostname: string, port: number) {\n return `http://${hostname.includes(\":\") ? `[${hostname}]` : hostname}:${port}`\n}\n\nfunction addressInUse(error: unknown): boolean {\n if (typeof error !== \"object\" || error === null) return false\n if (\"code\" in error && error.code === \"EADDRINUSE\") return true\n return \"cause\" in error && addressInUse(error.cause)\n}\n\nfunction waitForStdinClose() {\n return Effect.callback<void>((resume) => {\n const close = () => resume(Effect.void)\n process.stdin.once(\"end\", close)\n process.stdin.once(\"close\", close)\n process.stdin.resume()\n if (process.stdin.readableEnded || process.stdin.destroyed) close()\n return Effect.sync(() => {\n process.stdin.off(\"end\", close)\n process.stdin.off(\"close\", close)\n process.stdin.pause()\n })\n })\n}\n", | ||
| "import { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerProcess } from \"../../server-process\"\n\nexport default Runtime.handler(\n Commands.commands.serve,\n Effect.fnUntraced(function* (input) {\n if (input.service && input.stdio) return yield* Effect.fail(new Error(\"--service and --stdio cannot be combined\"))\n return yield* ServerProcess.run({\n mode: input.service ? \"service\" : input.stdio ? \"stdio\" : \"default\",\n hostname: Option.getOrUndefined(input.hostname),\n port: Option.getOrUndefined(input.port),\n })\n }),\n)\n" | ||
| ], | ||
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| "debugId": "5B8384E95259DB6D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/api.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { ServerConnection } from \"../../services/server-connection\"\n\nconst methods = new Set([\"delete\", \"get\", \"head\", \"options\", \"patch\", \"post\", \"put\"])\n\ntype Operation = {\n operationId?: string\n}\n\ntype OpenApi = {\n paths?: Record<string, Record<string, Operation>>\n}\n\nexport default Runtime.handler(\n Commands.commands.api,\n Effect.fn(\"cli.api\")(function* (input) {\n const server = yield* ServerConnection.resolve({\n server: Option.getOrUndefined(input.server),\n standalone: input.standalone,\n mismatch: \"ignore\",\n })\n const endpoint = server.endpoint\n const params = Option.getOrElse(input.param, () => ({}))\n const request = yield* resolveRequest(endpoint, input.request, params)\n const headers = new Headers(Service.headers(endpoint))\n for (const header of input.header) {\n const index = header.indexOf(\":\")\n if (index < 1) return yield* Effect.fail(new Error(`Invalid header, expected name:value: ${header}`))\n headers.set(header.slice(0, index).trim(), header.slice(index + 1).trim())\n }\n const body = Option.getOrUndefined(input.data)\n if (body !== undefined && !headers.has(\"content-type\")) headers.set(\"content-type\", \"application/json\")\n\n const response = yield* Effect.tryPromise(() =>\n fetch(new URL(request.path, endpoint.url), {\n method: request.method,\n headers,\n body,\n }),\n )\n const output = yield* Effect.promise(() => response.text())\n if (output) process.stdout.write(output + (output.endsWith(EOL) ? \"\" : EOL))\n }),\n)\n\nexport function resolveOperation(spec: OpenApi, operationID: string, params: Record<string, string>) {\n for (const [path, operations] of Object.entries(spec.paths ?? {})) {\n for (const [method, operation] of Object.entries(operations)) {\n if (!methods.has(method) || operation.operationId !== operationID) continue\n return { method: method.toUpperCase(), path: interpolate(path, params) }\n }\n }\n throw new Error(`Operation not found: ${operationID}`)\n}\n\nexport function rawRequest(input: readonly string[]) {\n if (input.length !== 2 || !methods.has(input[0].toLowerCase()) || !input[1].startsWith(\"/\")) return\n return { method: input[0].toUpperCase(), path: input[1] }\n}\n\nfunction resolveRequest(endpoint: Endpoint, input: readonly string[], params: Record<string, string>) {\n const raw = rawRequest(input)\n if (raw) return Effect.succeed(raw)\n if (input.length !== 1) return Effect.fail(new Error(\"Expected an operation name or an HTTP method and path\"))\n return Effect.tryPromise(async () => {\n const response = await fetch(new URL(\"/openapi.json\", endpoint.url), { headers: Service.headers(endpoint) })\n if (!response.ok) throw new Error(`Failed to load OpenAPI document: HTTP ${response.status}`)\n return resolveOperation((await response.json()) as OpenApi, input[0], params)\n })\n}\n\nfunction interpolate(path: string, params: Record<string, string>) {\n const used = new Set<string>()\n const pathname = path.replaceAll(/\\{([^}]+)\\}/g, (_, name: string) => {\n const value = params[name]\n if (value === undefined) throw new Error(`Missing path parameter: ${name}`)\n used.add(name)\n return encodeURIComponent(value)\n })\n const query = new URLSearchParams(Object.entries(params).filter(([name]) => !used.has(name))).toString()\n return query ? `${pathname}?${query}` : pathname\n}\n" | ||
| ], | ||
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| "debugId": "31B96FF3E4B8ACB964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/azure.ts"], | ||
| "sourcesContent": [ | ||
| "import { Auth } from \"../route/auth\"\nimport { type AtLeastOne, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route as RouteDef, RouteDefaultsInput } from \"../route/client\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\nimport { withOpenAIOptions, type OpenAIProviderOptionsInput } from \"./openai-options\"\n\nexport const id = ProviderID.make(\"azure\")\nconst routeAuth = Auth.remove(\"authorization\")\n\n// Azure needs the customer's resource URL; supply either `resourceName`\n// (helper builds the URL) or `baseURL` directly.\ntype AzureURL = AtLeastOne<{ readonly resourceName: string; readonly baseURL: string }>\n\nexport type ModelOptions = AzureURL &\n RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly apiVersion?: string\n readonly queryParams?: Record<string, string>\n readonly useCompletionUrls?: boolean\n readonly providerOptions?: OpenAIProviderOptionsInput\n }\nexport type Config = ModelOptions\n\nexport type Settings = ProviderPackage.Settings &\n AzureURL & {\n readonly apiKey?: string\n readonly apiVersion?: string\n readonly queryParams?: Readonly<Record<string, string>>\n readonly providerOptions?: OpenAIProviderOptionsInput\n }\n\nconst resourceBaseURL = (resourceName: string) => `https://${resourceName.trim()}.openai.azure.com/openai/v1`\n\nconst responsesRoute = OpenAIResponses.route.with({\n id: \"azure-openai-responses\",\n provider: id,\n auth: routeAuth,\n endpoint: {\n query: { \"api-version\": \"v1\" },\n },\n})\n\nconst chatRoute = OpenAIChat.route.with({\n id: \"azure-openai-chat\",\n provider: id,\n auth: routeAuth,\n endpoint: {\n query: { \"api-version\": \"v1\" },\n },\n})\n\nexport const routes = [responsesRoute, chatRoute]\n\nconst defaults = (input: Config) => {\n const {\n apiKey: _,\n apiVersion: _apiVersion,\n resourceName: _resourceName,\n useCompletionUrls: _useCompletionUrls,\n baseURL: _baseURL,\n queryParams: _queryParams,\n ...rest\n } = input\n if (\"auth\" in rest) {\n const { auth: _, ...withoutAuth } = rest\n return withoutAuth\n }\n return rest\n}\n\nconst auth = (input: Config) => {\n if (\"auth\" in input && input.auth) return input.auth\n return Auth.remove(\"authorization\").andThen(\n Auth.optional(\"apiKey\" in input ? input.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"AZURE_OPENAI_API_KEY\"))\n .pipe(Auth.header(\"api-key\")),\n )\n}\n\nconst configuredRoute = <Body, Prepared>(route: RouteDef<Body, Prepared>, input: Config) =>\n route.with({\n auth: auth(input),\n endpoint: {\n // AtLeastOne guarantees at least one is set; baseURL wins if both are.\n baseURL: input.baseURL ?? resourceBaseURL(input.resourceName!),\n query: {\n ...(input.apiVersion ? { \"api-version\": input.apiVersion } : {}),\n ...input.queryParams,\n },\n },\n })\n\nexport const configure = (input: Config) => {\n const configuredResponsesRoute = configuredRoute(responsesRoute, input)\n const configuredChatRoute = configuredRoute(chatRoute, input)\n const modelDefaults = defaults(input)\n\n const responses = (modelID: string | ModelID) =>\n configuredResponsesRoute.with(withOpenAIOptions(modelID, modelDefaults)).model({ id: modelID })\n\n const chat = (modelID: string | ModelID) =>\n configuredChatRoute.with(withOpenAIOptions(modelID, modelDefaults)).model({ id: modelID })\n\n return {\n id,\n model: (modelID: string | ModelID) => (input.useCompletionUrls === true ? chat(modelID) : responses(modelID)),\n responses,\n chat,\n configure,\n }\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nconst config = (settings: Settings): Config => {\n const common = {\n apiKey: settings.apiKey,\n apiVersion: settings.apiVersion,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n queryParams: settings.queryParams === undefined ? undefined : { ...settings.queryParams },\n }\n if (settings.baseURL !== undefined) return { ...common, baseURL: settings.baseURL }\n if (settings.resourceName !== undefined) return { ...common, resourceName: settings.resourceName }\n throw new Error(\"Azure requires resourceName or baseURL\")\n}\n\nexport const responsesModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).responses(modelID)\nexport const chatModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).chat(modelID)\nexport const model = responsesModel\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/list.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode, type McpServer } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.list,\n Effect.fn(\"cli.mcp.list\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.mcp.list({ location: { directory: process.cwd() } }))\n const servers = response.data.toSorted((a, b) => a.name.localeCompare(b.name))\n if (servers.length === 0) {\n process.stdout.write(\"No MCP servers configured\" + EOL)\n return\n }\n const width = Math.max(...servers.map((server) => server.name.length))\n const lines = servers.map(\n (server) => `${icon(server.status)} ${server.name.padEnd(width)} ${describe(server.status)}`,\n )\n process.stdout.write(lines.join(EOL) + EOL)\n }),\n)\n\nfunction icon(status: McpServer[\"status\"]) {\n switch (status.status) {\n case \"connected\":\n return \"✓\"\n case \"needs_auth\":\n return \"⚠\"\n case \"failed\":\n case \"needs_client_registration\":\n return \"✗\"\n default:\n return \"○\"\n }\n}\n\nfunction describe(status: McpServer[\"status\"]) {\n switch (status.status) {\n case \"needs_auth\":\n return \"needs authentication\"\n case \"needs_client_registration\":\n return `needs client registration: ${status.error}`\n case \"failed\":\n return `failed: ${status.error}`\n default:\n return status.status\n }\n}\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/anthropic-compatible.ts", "../ai/src/providers/anthropic.ts"], | ||
| "sourcesContent": [ | ||
| "import type { ProviderPackage } from \"../provider-package\"\nimport { AnthropicMessages } from \"../protocols/anthropic-messages\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { ProviderID, type ModelID } from \"../schema\"\n\nexport const id = ProviderID.make(\"anthropic-compatible\")\n\nexport type Config = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly provider?: string\n readonly baseURL: string\n }\n\nexport type Settings = ProviderPackage.Settings &\n (\n | { readonly apiKey?: string; readonly authToken?: never }\n | { readonly apiKey?: never; readonly authToken?: string }\n ) & {\n readonly baseURL: string\n readonly provider?: string\n }\n\nexport const routes = [AnthropicMessages.route]\n\nconst auth = (input: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in input && input.auth) return input.auth\n return Auth.optional(\"apiKey\" in input ? input.apiKey : undefined, \"apiKey\").pipe(Auth.header(\"x-api-key\"))\n}\n\nexport const configure = (input: Config) => {\n if (!input.baseURL) throw new Error(\"Anthropic-compatible providers require a baseURL\")\n const provider = input.provider ?? \"anthropic-compatible\"\n const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input\n const route = AnthropicMessages.route.with({\n ...rest,\n provider,\n endpoint: { baseURL },\n auth: auth(input),\n })\n return {\n id: ProviderID.make(provider),\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.apiKey !== undefined && settings.authToken !== undefined)\n throw new Error(\"Anthropic-compatible apiKey cannot be combined with authToken\")\n return configure({\n ...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n provider: settings.provider,\n }).model(modelID)\n}\n\nexport * as AnthropicCompatible from \"./anthropic-compatible\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport { AnthropicMessages } from \"../protocols/anthropic-messages\"\nimport { AnthropicCompatible } from \"./anthropic-compatible\"\n\nexport const id = ProviderID.make(\"anthropic\")\n\nexport const routes = [AnthropicMessages.route]\n\nexport type Config = RouteDefaultsInput & ProviderAuthOption<\"optional\"> & { readonly baseURL?: string }\n\nexport type Settings = ProviderPackage.Settings &\n (\n | { readonly apiKey?: string; readonly authToken?: never }\n | { readonly apiKey?: never; readonly authToken?: string }\n ) & {\n readonly baseURL?: string\n }\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in options && options.auth) return options.auth\n return Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"ANTHROPIC_API_KEY\"))\n .pipe(Auth.header(\"x-api-key\"))\n}\n\nexport const configure = (input: Config = {}) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n const compatible = AnthropicCompatible.configure({\n ...rest,\n auth: auth(input),\n baseURL: baseURL ?? AnthropicMessages.DEFAULT_BASE_URL,\n provider: id,\n })\n return {\n id,\n model: (modelID: string | ModelID) => compatible.model(modelID),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.apiKey !== undefined && settings.authToken !== undefined)\n throw new Error(\"Anthropic apiKey cannot be combined with authToken\")\n return configure({\n ...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n }).model(modelID)\n}\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mini.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Effect, FileSystem, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerConnection } from \"../../services/server-connection\"\nimport { Config } from \"../../config\"\nimport { resolve } from \"@opencode-ai/tui/config\"\n\nexport default Runtime.handler(Commands.commands.mini, (input) =>\n Effect.gen(function* () {\n const { runMini, validateMiniTerminal } = yield* Effect.promise(() => import(\"../../mini\"))\n yield* Effect.promise(async () => validateMiniTerminal())\n const serverURL = Option.getOrUndefined(input.server)\n const server = yield* ServerConnection.resolve({ server: serverURL, standalone: input.standalone })\n const config = yield* Config.Service\n const resolved = resolve(yield* config.get(), { terminalSuspend: process.platform !== \"win32\" })\n const fileSystem = yield* FileSystem.FileSystem\n const runServicePromise = Effect.runPromiseWith(Context.make(FileSystem.FileSystem, fileSystem))\n const service = server.service\n yield* Effect.promise(() =>\n runMini({\n server: {\n endpoint: server.endpoint,\n reconnect: service ? (signal) => runServicePromise(service.reconnect(), { signal }) : undefined,\n },\n continue: input.continue,\n session: Option.getOrUndefined(input.session),\n fork: input.fork,\n model: Option.getOrUndefined(input.model),\n agent: Option.getOrUndefined(input.agent),\n prompt: Option.getOrUndefined(input.prompt),\n replay: input.replay,\n replayLimit: Option.getOrUndefined(input.replayLimit),\n demo: input.demo,\n tuiConfig: resolved,\n }),\n )\n }),\n)\n" | ||
| ], | ||
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| "debugId": "E7D7103A627E1D9364756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/run/run.ts", "src/run/noninteractive.ts", "src/run/ui.ts"], | ||
| "sourcesContent": [ | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient, type SessionMessageAssistantTool } from \"@opencode-ai/client/promise\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { open } from \"node:fs/promises\"\nimport path from \"node:path\"\nimport { readStdin } from \"../util/io\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { waitForCatalogReady } from \"../services/catalog\"\nimport { parseSessionTargetModel, resolveSessionTarget } from \"../session-target\"\nimport { toolInlineInfo } from \"@opencode-ai/tui/mini/tool\"\nimport { runNonInteractivePrompt } from \"./noninteractive\"\nimport { UI } from \"./ui\"\n\nexport type RunCommandInput = {\n server: ServerConnection.Resolved\n message: string[]\n continue?: boolean\n session?: string\n fork?: boolean\n model?: string\n agent?: string\n format: \"default\" | \"json\"\n file: string[]\n title?: string\n thinking?: boolean\n auto?: boolean\n}\n\ntype FilePart = {\n url: string\n filename: string\n mime: string\n}\n\ntype Prepared = {\n directory?: string\n message: string\n files: FilePart[]\n}\n\ntype ExecutionOptions = {\n root?: string\n directory?: string\n useServerDirectory?: boolean\n variant?: string\n attached?: boolean\n compatibility?: \"v1\"\n}\n\nclass RunTargetError extends Error {\n constructor(\n message: string,\n readonly sessionID?: string,\n ) {\n super(message)\n }\n}\n\nconst ATTACH_FILE_MAX_BYTES = 10 * 1024 * 1024\n\nexport function runNonInteractive(input: RunCommandInput) {\n return runNonInteractiveWithOptions(input, {})\n}\n\n/** @internal Used only by the V1 command boundary. */\nexport function runNonInteractiveWithOptions(input: RunCommandInput, options: ExecutionOptions) {\n return run(input, options).catch((error) => reportRunError(input, errorMessage(error)))\n}\n\nasync function run(input: RunCommandInput, options: ExecutionOptions) {\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n const root = options.root ?? process.env.PWD ?? process.cwd()\n const local = localDirectory(root)\n const directory = options.useServerDirectory ? undefined : (options.directory ?? local)\n const message = mergeInput(formatMessage(input.message), process.stdin.isTTY ? undefined : await readStdin())\n if (!message?.trim()) fail(\"You must provide a message\")\n const files = await Promise.all(input.file.map((file) => prepareFile(file, root, options)))\n const prepared = { directory, message, files }\n return execute(input, prepared, input.server.endpoint, options)\n}\n\nasync function execute(input: RunCommandInput, prepared: Prepared, endpoint: Endpoint, options: ExecutionOptions) {\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const explicit = parseRunModel(input.model)\n const target = await resolveSessionTarget({\n client,\n location: prepared.directory ? { directory: prepared.directory } : undefined,\n continue: input.continue,\n session: input.session,\n fork: input.fork,\n model: explicit\n ? { providerID: explicit.model.providerID, id: explicit.model.modelID, variant: explicit.variant }\n : undefined,\n agent: input.agent,\n prepare: async (next) => {\n const selected =\n next.model ??\n (await client.model\n .default({ location: { directory: next.location.directory, workspace: next.location.workspaceID } })\n .then((result) => result.data))\n const model = selected\n ? {\n providerID: selected.providerID,\n id: selected.id,\n variant: options.variant ?? (\"variant\" in selected ? selected.variant : undefined),\n }\n : undefined\n if ((options.variant ?? explicit?.variant) && !model)\n throw new RunTargetError(\"Cannot select a variant before selecting a model\", next.session?.id)\n if (model) {\n await waitForCatalogReady({\n sdk: client,\n directory: next.location.directory,\n workspace: next.location.workspaceID,\n model: { providerID: model.providerID, modelID: model.id },\n })\n const available = await client.model.list({\n location: { directory: next.location.directory, workspace: next.location.workspaceID },\n })\n if (!available.data.some((item) => item.providerID === model.providerID && item.id === model.id))\n throw new RunTargetError(`Model unavailable: ${model.providerID}/${model.id}`, next.session?.id)\n }\n return {\n model,\n agent: input.agent\n ? await validateAgent(client, next.location.directory, next.location.workspaceID, input.agent)\n : next.agent,\n }\n },\n }).catch((error) => {\n if (!(error instanceof RunTargetError)) throw error\n reportRunError(input, error.message, error.sessionID)\n return undefined\n })\n if (!target) return\n const model = target.model ? { providerID: target.model.providerID, modelID: target.model.id } : undefined\n const variant = target.model?.variant\n if (!target.resume && input.title !== undefined) {\n await client.session.rename({\n sessionID: target.session.id,\n title: input.title || prepared.message.slice(0, 50) + (prepared.message.length > 50 ? \"...\" : \"\"),\n })\n }\n\n await runNonInteractivePrompt({\n client,\n sessionID: target.session.id,\n location: target.location,\n message: prepared.message,\n files: prepared.files,\n agent: target.agent,\n model,\n variant,\n thinking: input.thinking ?? false,\n format: input.format,\n auto: input.auto ?? false,\n attached: options.attached ?? true,\n compatibility: options.compatibility,\n renderTool: (part) => renderTool(part, target.location.directory),\n renderToolError: (part) => renderToolError(part, target.location.directory),\n }).catch((error) => reportRunError(input, errorMessage(error), target.session.id))\n}\n\nexport function mergeInput(message: string | undefined, piped: string | undefined) {\n if (!message) return piped || undefined\n if (!piped) return message\n return message + \"\\n\" + piped\n}\n\nfunction formatMessage(message: string[]) {\n const value = message.map((part) => (part.includes(\" \") ? `\"${part.replace(/\"/g, '\\\\\"')}\"` : part)).join(\" \")\n return value || undefined\n}\n\nfunction localDirectory(root: string) {\n try {\n process.chdir(root)\n return process.cwd()\n } catch {\n fail(`Failed to change directory to ${root}`)\n }\n}\n\nexport function parseRunModel(value?: string) {\n const ref = parseSessionTargetModel(value)\n if (!ref) return\n return {\n model: { providerID: ref.providerID, modelID: ref.id },\n variant: ref.variant,\n }\n}\n\nasync function validateAgent(client: OpenCodeClient, directory: string, workspace: string | undefined, name?: string) {\n if (!name) return\n const agents = await client.agent\n .list({ location: { directory, workspace } })\n .then((result) => result.data)\n .catch(() => undefined)\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n const agent = agents.find((item) => item.id === name)\n if (!agent) {\n warning(`agent \"${name}\" not found. Falling back to default agent`)\n return\n }\n if (agent.mode === \"subagent\") {\n warning(`agent \"${name}\" is a subagent, not a primary agent. Falling back to default agent`)\n return\n }\n return name\n}\n\nasync function prepareFile(input: string, directory: string, options: ExecutionOptions): Promise<FilePart> {\n const file = path.resolve(directory, input)\n const handle = await open(file, \"r\").catch(() => fail(`File not found: ${input}`))\n try {\n const stat = await handle.stat()\n if (options.compatibility === \"v1\" && options.attached && stat.isDirectory())\n fail(`Cannot attach local directory without a shared filesystem: ${input}`)\n if (!stat.isFile() || stat.size > ATTACH_FILE_MAX_BYTES)\n fail(`Cannot attach a directory, special file, or file larger than 10 MiB: ${input}`)\n const content = Buffer.alloc(Number(stat.size))\n let offset = 0\n while (offset < content.length) {\n const read = await handle.read(content, offset, content.length - offset, offset)\n if (read.bytesRead === 0) break\n offset += read.bytesRead\n }\n const bytes = content.subarray(0, offset)\n const detected = FSUtil.mimeType(file)\n const text = bytes.toString(\"utf8\")\n const mime =\n detected.startsWith(\"image/\") || detected === \"application/pdf\"\n ? detected\n : !isBinaryContent(bytes) && Buffer.from(text, \"utf8\").equals(bytes)\n ? \"text/plain\"\n : detected\n return {\n url: `data:${mime};base64,${bytes.toString(\"base64\")}`,\n filename: path.basename(file),\n mime,\n }\n } finally {\n await handle.close()\n }\n}\n\nfunction isBinaryContent(bytes: Uint8Array) {\n if (bytes.length === 0) return false\n if (bytes.includes(0)) return true\n return bytes.reduce((count, byte) => count + Number(byte < 9 || (byte > 13 && byte < 32)), 0) / bytes.length > 0.3\n}\n\nasync function renderTool(part: SessionMessageAssistantTool, directory: string) {\n const info = toolInlineInfo(part, directory)\n if (info.mode === \"block\") {\n UI.empty()\n UI.println(UI.Style.TEXT_NORMAL + info.icon, UI.Style.TEXT_NORMAL + info.title)\n if (info.body?.trim()) UI.println(info.body)\n UI.empty()\n return\n }\n UI.println(\n UI.Style.TEXT_NORMAL + info.icon,\n UI.Style.TEXT_NORMAL + info.title,\n info.description ? UI.Style.TEXT_DIM + info.description + UI.Style.TEXT_NORMAL : \"\",\n )\n}\n\nasync function renderToolError(part: SessionMessageAssistantTool, directory: string) {\n const info = toolInlineInfo(part, directory)\n UI.println(UI.Style.TEXT_NORMAL + \"✗\", UI.Style.TEXT_NORMAL + `${info.title} failed`)\n}\n\nfunction warning(message: string) {\n UI.println(UI.Style.TEXT_WARNING_BOLD + \"!\", UI.Style.TEXT_NORMAL, message)\n}\n\nfunction errorMessage(error: unknown) {\n if (error instanceof Error) return error.message\n if (typeof error === \"object\" && error !== null && \"message\" in error && typeof error.message === \"string\")\n return error.message\n return String(error)\n}\n\n/** @internal Used by the V1 command boundary before a Session exists. */\nexport function reportRunError(input: Pick<RunCommandInput, \"format\">, message: string, sessionID?: string) {\n process.exitCode = 1\n if (input.format === \"json\") {\n process.stdout.write(\n JSON.stringify({\n type: \"error\",\n timestamp: Date.now(),\n sessionID: sessionID ?? \"\",\n error: { type: \"unknown\", message },\n }) + \"\\n\",\n )\n return\n }\n UI.error(message)\n}\n\nfunction fail(message: string): never {\n throw new Error(message)\n}\n", | ||
| "import type {\n EventSubscribeOutput,\n JsonValue,\n LLMToolContent,\n LocationRef,\n OpenCodeClient,\n SessionMessageAssistantTool,\n} from \"@opencode-ai/client/promise\"\nimport { SessionMessage } from \"@opencode-ai/schema/session-message\"\nimport { EOL } from \"node:os\"\nimport { readFile } from \"node:fs/promises\"\nimport { toolOutputText, type MiniToolPart } from \"@opencode-ai/tui/mini/tool\"\nimport { UI } from \"./ui\"\n\ntype Model = {\n providerID: string\n modelID: string\n}\n\ntype File = {\n url: string\n filename: string\n mime: string\n}\n\ntype Input = {\n client: OpenCodeClient\n sessionID: string\n location: LocationRef\n message: string\n files: File[]\n agent?: string\n model?: Model\n variant?: string\n thinking: boolean\n format: \"default\" | \"json\"\n auto: boolean\n /** True when the client is attached to a shared server rather than an exclusive in-process one. */\n attached: boolean\n compatibility?: \"v1\"\n renderTool: (part: SessionMessageAssistantTool) => Promise<void>\n renderToolError: (part: SessionMessageAssistantTool) => Promise<void>\n}\n\ntype StartedPart = {\n id: string\n timestamp: number\n}\n\ntype ToolState = StartedPart & {\n assistantMessageID: string\n tool: string\n input: Record<string, JsonValue>\n raw?: string\n provider?: unknown\n providerState?: SessionMessageAssistantTool[\"providerState\"]\n structured: Record<string, JsonValue>\n content: LLMToolContent[]\n}\n\ntype V2Event = EventSubscribeOutput\ntype FormRequest = Extract<V2Event, { type: \"form.created\" }>[\"data\"][\"form\"]\n\n// MCP elicitations are temporarily owned by the \"global\" sentinel instead of a real\n// session. An exclusive local process may treat them as this run's blockers; an\n// attached client must not cancel input that may belong to another session.\nconst GLOBAL_FORM_SESSION_ID = \"global\"\n\nexport async function runNonInteractivePrompt(input: Input) {\n const controller = new AbortController()\n const stream = input.client.event.subscribe({ signal: controller.signal })[Symbol.asyncIterator]()\n const connected = await stream.next()\n if (connected.done) throw new Error(\"Event stream disconnected before prompt admission\")\n\n const messageID = SessionMessage.ID.create()\n const starts = new Map<string, StartedPart>()\n const tools = new Map<string, ToolState>()\n let submitted = false\n let promoted = false\n let emittedError = false\n let permissionRejected = false\n let formCancelled = false\n let interrupted = false\n let v1InvalidOutput = false\n let admission: AbortController | undefined\n let pendingStep: { timestamp: number; part: Record<string, unknown>; label: string } | undefined\n\n const emit = (type: string, timestamp: number, data: Record<string, unknown>) => {\n if (input.format !== \"json\") return false\n process.stdout.write(JSON.stringify({ type, timestamp, sessionID: input.sessionID, ...data }) + EOL)\n return true\n }\n\n const writeText = (part: { text: string; [key: string]: unknown }, timestamp: number) => {\n if (emit(\"text\", timestamp, { part })) return\n const text = part.text.trim()\n if (!text) return\n if (!process.stdout.isTTY) {\n process.stdout.write(text + EOL)\n return\n }\n UI.empty()\n UI.println(text)\n UI.empty()\n }\n\n const flushStep = () => {\n if (!pendingStep) return\n const value = pendingStep\n pendingStep = undefined\n if (!emit(\"step_start\", value.timestamp, { part: value.part }) && input.format !== \"json\") {\n UI.empty()\n UI.println(value.label)\n UI.empty()\n }\n }\n\n const replyPermission = async (request: { id: string; action: string; resources: ReadonlyArray<string> }) => {\n if (!input.auto) {\n permissionRejected = true\n UI.println(\n UI.Style.TEXT_WARNING_BOLD + \"!\",\n UI.Style.TEXT_NORMAL +\n `permission requested: ${request.action} (${request.resources.join(\", \")}); auto-rejecting`,\n )\n }\n await input.client.permission\n .reply({\n sessionID: input.sessionID,\n requestID: request.id,\n reply: input.auto ? \"once\" : \"reject\",\n })\n .catch(() => {})\n if (!input.auto) {\n await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n }\n\n const cancelForm = async (request: Pick<FormRequest, \"id\" | \"sessionID\">) => {\n try {\n await input.client.form.cancel(\n { sessionID: request.sessionID, formID: request.id },\n ...formRequestOptions(request.sessionID === GLOBAL_FORM_SESSION_ID ? input.location : undefined),\n )\n } catch (error) {\n if (!formAlreadySettled(error)) throw error\n }\n formCancelled = true\n }\n\n const consume = async () => {\n while (!controller.signal.aborted) {\n const next = await stream.next().catch((error) => {\n if (!emittedError) throw error\n return { done: true as const, value: undefined }\n })\n if (next.done) {\n if (emittedError) return\n throw new Error(\"Event stream disconnected during prompt execution\")\n }\n const event = next.value\n\n if (event.type === \"permission.v2.asked\" && submitted && event.data.sessionID === input.sessionID) {\n await replyPermission(event.data)\n continue\n }\n if (\n event.type === \"form.created\" &&\n submitted &&\n (event.data.form.sessionID === input.sessionID ||\n (!input.attached &&\n event.data.form.sessionID === GLOBAL_FORM_SESSION_ID &&\n sameLocation(event.location, input.location)))\n ) {\n await cancelForm(event.data.form)\n continue\n }\n if (!(\"sessionID\" in event.data) || event.data.sessionID !== input.sessionID) continue\n const time = toMillis(\"created\" in event ? event.created : undefined)\n\n if (event.type === \"session.input.promoted\") {\n if (event.data.inputID === messageID) {\n promoted = true\n continue\n }\n }\n if (\n event.type === \"session.execution.interrupted\" &&\n event.data.reason === \"user\" &&\n (interrupted || permissionRejected || formCancelled)\n ) {\n return\n }\n if (!promoted) continue\n\n if (event.type === \"session.step.started\") {\n const part = {\n id: partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"step-start\",\n snapshot: event.data.snapshot,\n }\n if (input.compatibility === \"v1\") {\n pendingStep = {\n timestamp: time,\n part,\n label: `> ${event.data.agent} · ${event.data.model.id}`,\n }\n continue\n }\n if (!emit(\"step_start\", time, { part }) && input.format !== \"json\") {\n UI.empty()\n UI.println(`> ${event.data.agent} · ${event.data.model.id}`)\n UI.empty()\n }\n continue\n }\n\n if (event.type === \"session.text.started\") {\n flushStep()\n starts.set(\"text\", { id: partID(event.id), timestamp: time })\n continue\n }\n if (event.type === \"session.text.ended\") {\n const started = starts.get(\"text\")\n starts.delete(\"text\")\n const part = {\n id: started?.id ?? partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"text\",\n text: event.data.text,\n time: { start: started?.timestamp ?? time, end: time },\n }\n writeText(part, time)\n continue\n }\n\n if (event.type === \"session.reasoning.started\") {\n flushStep()\n starts.set(\"reasoning\", { id: partID(event.id), timestamp: time })\n continue\n }\n if (event.type === \"session.reasoning.ended\" && input.thinking) {\n const started = starts.get(\"reasoning\")\n starts.delete(\"reasoning\")\n const part = {\n id: started?.id ?? partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"reasoning\",\n text: event.data.text,\n metadata: event.data.state,\n time: { start: started?.timestamp ?? time, end: time },\n }\n if (emit(\"reasoning\", time, { part })) continue\n const text = part.text.trim()\n if (!text) continue\n const line = `Thinking: ${text}`\n if (!process.stdout.isTTY) {\n process.stdout.write(line + EOL)\n continue\n }\n UI.empty()\n UI.println(`${UI.Style.TEXT_DIM}\\u001b[3m${line}\\u001b[0m${UI.Style.TEXT_NORMAL}`)\n UI.empty()\n continue\n }\n\n if (event.type === \"session.tool.input.started\") {\n flushStep()\n tools.set(toolKey(event.data.assistantMessageID, event.data.callID), {\n id: partID(event.id),\n timestamp: time,\n assistantMessageID: event.data.assistantMessageID,\n tool: event.data.name,\n input: {},\n structured: {},\n content: [],\n })\n continue\n }\n if (event.type === \"session.tool.input.ended\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) current.raw = event.data.text\n continue\n }\n if (event.type === \"session.tool.input.delta\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) current.raw = (current.raw ?? \"\") + event.data.delta\n continue\n }\n if (event.type === \"session.tool.called\") {\n flushStep()\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key)\n tools.set(key, {\n id: current?.id ?? partID(event.id),\n timestamp: current?.timestamp ?? time,\n assistantMessageID: event.data.assistantMessageID,\n tool: current?.tool ?? \"tool\",\n input: event.data.input,\n raw: current?.raw,\n provider: { executed: event.data.executed, state: event.data.state },\n providerState: event.data.state,\n structured: {},\n content: [],\n })\n continue\n }\n if (event.type === \"session.tool.progress\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) {\n current.structured = event.data.structured\n current.content = event.data.content\n }\n continue\n }\n if (event.type === \"session.tool.success\") {\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key) ?? fallbackTool(event)\n const tool: SessionMessageAssistantTool = {\n type: \"tool\",\n id: event.data.callID,\n name: current.tool,\n executed: event.data.executed,\n providerState: current.providerState,\n providerResultState: event.data.resultState,\n state: {\n status: \"completed\",\n input: current.input,\n structured: event.data.structured,\n content: event.data.content,\n result: event.data.result,\n },\n time: { created: current.timestamp, ran: current.timestamp, completed: time },\n }\n const part: MiniToolPart = {\n id: current.id,\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"tool\",\n callID: event.data.callID,\n tool: current.tool,\n state: {\n status: \"completed\",\n input: current.input,\n output: toolOutputText(current.tool, event.data.content),\n title: current.tool,\n metadata: {\n structured: event.data.structured,\n content: event.data.content,\n result: event.data.result,\n providerCall: current.provider,\n providerResult: { executed: event.data.executed, state: event.data.resultState },\n rawInput: current.raw,\n },\n time: { start: current.timestamp, end: time },\n },\n }\n tools.delete(key)\n if (!emit(\"tool_use\", time, { part })) await input.renderTool(tool)\n continue\n }\n if (event.type === \"session.tool.failed\") {\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key) ?? fallbackTool(event)\n const error = event.data.error.message\n const tool: SessionMessageAssistantTool = {\n type: \"tool\",\n id: event.data.callID,\n name: current.tool,\n executed: event.data.executed,\n providerState: current.providerState,\n providerResultState: event.data.resultState,\n state: {\n status: \"error\",\n input: current.input,\n structured: current.structured,\n content: current.content,\n error: event.data.error,\n result: event.data.result,\n },\n time: { created: current.timestamp, ran: current.timestamp, completed: time },\n }\n const part: MiniToolPart = {\n id: current.id,\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"tool\",\n callID: event.data.callID,\n tool: current.tool,\n state: {\n status: \"error\",\n input: current.input,\n error,\n metadata: {\n result: event.data.result,\n providerCall: current.provider,\n providerResult: { executed: event.data.executed, state: event.data.resultState },\n rawInput: current.raw,\n },\n time: { start: current.timestamp, end: time },\n },\n }\n tools.delete(key)\n if (input.compatibility === \"v1\" && (permissionRejected || formCancelled)) continue\n if (!emit(\"tool_use\", time, { part })) {\n if (toolOutputText(current.tool, current.content).trim())\n await input.renderTool({\n ...tool,\n state: {\n status: \"completed\",\n input: current.input,\n structured: current.structured,\n content: current.content,\n result: event.data.result,\n },\n })\n await input.renderToolError(tool)\n UI.error(error)\n }\n continue\n }\n\n if (event.type === \"session.step.ended\") {\n flushStep()\n const part = {\n id: partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"step-finish\",\n reason: event.data.finish,\n snapshot: event.data.snapshot,\n cost: event.data.cost,\n tokens: event.data.tokens,\n }\n emit(\"step_finish\", time, { part })\n continue\n }\n if (event.type === \"session.step.failed\") {\n if (\n input.compatibility === \"v1\" &&\n event.data.error.message === \"Provider stream ended without a terminal finish event\"\n ) {\n pendingStep = undefined\n v1InvalidOutput = true\n continue\n }\n if (interrupted || permissionRejected || formCancelled) continue\n flushStep()\n emittedError = true\n process.exitCode = 1\n if (!emit(\"error\", time, { error: event.data.error })) UI.error(event.data.error.message)\n continue\n }\n if (event.type === \"session.execution.failed\") {\n if (input.compatibility === \"v1\" && (v1InvalidOutput || permissionRejected || formCancelled)) return\n flushStep()\n if (!emittedError && !formCancelled) {\n emittedError = true\n process.exitCode = 1\n if (!emit(\"error\", time, { error: event.data.error })) UI.error(event.data.error.message)\n }\n return\n }\n if (event.type === \"session.execution.interrupted\") {\n if (input.compatibility === \"v1\" && (permissionRejected || formCancelled)) return\n if (event.data.reason === \"user\" && interrupted) process.exitCode = 130\n if (event.data.reason !== \"user\" && !emittedError) {\n emittedError = true\n process.exitCode = 1\n const error = { type: \"aborted\" as const, message: `Session interrupted: ${event.data.reason}` }\n if (!emit(\"error\", time, { error })) UI.error(error.message)\n }\n return\n }\n if (event.type === \"session.execution.succeeded\") return\n }\n }\n\n const interrupt = () => {\n if (interrupted) process.exit(130)\n interrupted = true\n process.exitCode = 130\n admission?.abort()\n void input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n process.on(\"SIGINT\", interrupt)\n\n let completed: Promise<void> | undefined\n try {\n if (input.agent) {\n await input.client.session.switchAgent({ sessionID: input.sessionID, agent: input.agent })\n }\n const selected = input.model\n ? { providerID: input.model.providerID, id: input.model.modelID, variant: input.variant }\n : input.variant\n ? await input.client.session\n .get({ sessionID: input.sessionID })\n .then((result) => result.model)\n .then(async (model) => {\n if (model) return { ...model, variant: input.variant }\n const result = await input.client.model.default()\n const fallback = result.data\n return fallback ? { providerID: fallback.providerID, id: fallback.id, variant: input.variant } : undefined\n })\n : undefined\n if (input.variant && !selected) throw new Error(\"Cannot select a variant before selecting a model\")\n if (selected) {\n await input.client.session.switchModel({ sessionID: input.sessionID, model: selected })\n }\n\n const prepared = await Promise.all(input.files.map(prepareFile))\n if (interrupted) return\n submitted = true\n completed = consume()\n admission = new AbortController()\n const response = await input.client.session\n .prompt(\n {\n sessionID: input.sessionID,\n id: messageID,\n text: [input.message, ...prepared.flatMap((file) => (file.text ? [file.text] : []))].join(\"\\n\\n\"),\n files: prepared.flatMap((file) => (file.attachment ? [file.attachment] : [])),\n delivery: \"steer\",\n },\n { signal: admission.signal },\n )\n .catch(async (error) => {\n if (interrupted) {\n await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n controller.abort()\n await completed?.catch(() => {})\n if (interrupted || emittedError) return undefined\n throw error\n })\n admission = undefined\n if (!response) return\n if (interrupted) await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n\n const [permissions, forms, globals] = await Promise.all([\n input.client.permission.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.client.form.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.attached\n ? Promise.resolve(undefined)\n : input.client.form.request\n .list({\n location: { directory: input.location.directory, workspace: input.location.workspaceID },\n })\n .catch(() => undefined),\n ])\n await Promise.all([\n ...(permissions ?? []).map(replyPermission),\n ...(forms ?? []).map(cancelForm),\n ...(globals && sameLocation(globals.location, input.location)\n ? globals.data.filter((form) => form.sessionID === GLOBAL_FORM_SESSION_ID).map(cancelForm)\n : []),\n ])\n await completed\n } finally {\n process.off(\"SIGINT\", interrupt)\n controller.abort()\n await stream.return?.(undefined).catch(() => {})\n }\n}\n\nfunction sameLocation(left: LocationRef | undefined, right: LocationRef) {\n return !!left && left.directory === right.directory && left.workspaceID === right.workspaceID\n}\n\nfunction formRequestOptions(location: LocationRef | undefined): [] | [{ headers: Record<string, string> }] {\n if (!location) return []\n return [\n {\n headers: {\n \"x-opencode-directory\": encodeURIComponent(location.directory),\n ...(location.workspaceID ? { \"x-opencode-workspace\": location.workspaceID } : {}),\n },\n },\n ]\n}\n\nfunction formAlreadySettled(error: unknown) {\n return !!error && typeof error === \"object\" && Reflect.get(error, \"_tag\") === \"FormAlreadySettledError\"\n}\n\nfunction partID(eventID: string) {\n return `prt_${eventID.replace(/^evt_/, \"\")}`\n}\n\nfunction toolKey(messageID: string, callID: string) {\n return `${messageID}\\u0000${callID}`\n}\n\nfunction fallbackTool(event: {\n id: string\n created: number\n data: { assistantMessageID: string; callID: string }\n}): ToolState {\n return {\n id: partID(event.id),\n timestamp: toMillis(event.created),\n assistantMessageID: event.data.assistantMessageID,\n tool: \"tool\",\n input: {},\n structured: {},\n content: [],\n }\n}\n\nfunction toMillis(value: unknown) {\n if (typeof value === \"number\") return value\n if (typeof value === \"string\") return new Date(value).getTime()\n return Date.now()\n}\n\nasync function prepareFile(file: File) {\n if (file.mime !== \"text/plain\") {\n const uri = file.url.startsWith(\"data:\")\n ? file.url\n : `data:${file.mime};base64,${(await readFile(new URL(file.url))).toString(\"base64\")}`\n return { attachment: { uri, name: file.filename } }\n }\n const content = file.url.startsWith(\"data:\")\n ? Buffer.from(file.url.slice(file.url.indexOf(\",\") + 1), \"base64\").toString(\"utf8\")\n : await readFile(new URL(file.url), \"utf8\")\n return { text: `<file name=\"${file.filename}\">\\n${content}\\n</file>` }\n}\n", | ||
| "import { EOL } from \"node:os\"\n\nexport const Style = {\n TEXT_DIM: \"\\x1b[90m\",\n TEXT_NORMAL: \"\\x1b[0m\",\n TEXT_WARNING_BOLD: \"\\x1b[93m\\x1b[1m\",\n TEXT_DANGER_BOLD: \"\\x1b[91m\\x1b[1m\",\n}\n\nexport function println(...message: string[]) {\n process.stderr.write(message.join(\" \") + EOL)\n}\n\nlet blank = false\n\nexport function empty() {\n if (blank) return\n println(Style.TEXT_NORMAL)\n blank = true\n}\n\nexport function error(message: string) {\n if (message.startsWith(\"Error: \")) message = message.slice(\"Error: \".length)\n println(Style.TEXT_DANGER_BOLD + \"Error: \" + Style.TEXT_NORMAL + message)\n}\n\nexport * as UI from \"./ui\"\n" | ||
| ], | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-compatible-chat.ts"], | ||
| "sourcesContent": [ | ||
| "import { Route, type RouteRoutedModelInput } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport * as OpenAIChat from \"./openai-chat\"\n\nconst ADAPTER = \"openai-compatible-chat\"\n\nexport type OpenAICompatibleChatModelInput = RouteRoutedModelInput\n\n/**\n * Route for non-OpenAI providers that expose an OpenAI Chat-compatible\n * `/chat/completions` endpoint. Reuses `OpenAIChat.protocol` end-to-end and\n * overrides only the route id so providers can be resolved per-family without\n * colliding with native OpenAI. Provider helpers configure the route endpoint\n * before model selection.\n */\nexport const route = Route.make({\n id: ADAPTER,\n providerMetadataKey: \"openai\",\n protocol: OpenAIChat.protocol,\n endpoint: Endpoint.path(\"/chat/completions\"),\n framing: Framing.sse,\n})\n\nexport * as OpenAICompatibleChat from \"./openai-compatible-chat\"\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/migrate.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\n\nexport default Runtime.handler(Commands.commands.migrate, (_input) => Effect.log(\"No migrations to run.\"))\n" | ||
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| { | ||
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| "sources": ["../core/src/installation/version.ts"], | ||
| "sourcesContent": [ | ||
| "declare global {\n const OPENCODE_VERSION: string\n const OPENCODE_CHANNEL: string\n}\n\nexport const InstallationVersion = typeof OPENCODE_VERSION === \"string\" ? OPENCODE_VERSION : \"local\"\nexport const InstallationChannel = typeof OPENCODE_CHANNEL === \"string\" ? OPENCODE_CHANNEL : \"local\"\nexport const InstallationLocal = InstallationChannel === \"local\"\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openai-compatible.ts"], | ||
| "sourcesContent": [ | ||
| "import { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAICompatibleChat from \"../protocols/openai-compatible-chat\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { profiles, type OpenAICompatibleProfile } from \"./openai-compatible-profile\"\n\nexport const id = ProviderID.make(\"openai-compatible\")\n\ntype GenericModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly provider?: string\n readonly baseURL: string\n }\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL: string\n readonly provider?: string\n}\n\nexport type FamilyModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n }\n\nexport const routes = [OpenAICompatibleChat.route]\n\nexport const configure = (input: GenericModelOptions) => {\n const provider = input.provider ?? \"openai-compatible\"\n const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input\n const route = OpenAICompatibleChat.route.with({\n ...rest,\n provider,\n endpoint: { baseURL },\n auth: AuthOptions.bearer(input, []),\n })\n return {\n id: ProviderID.make(provider),\n model: (modelID: string | ModelID) => route.model({ id: modelID, provider: ProviderID.make(provider) }),\n configure,\n }\n}\n\nconst define = (profile: OpenAICompatibleProfile) => {\n const configureProfile = (input: FamilyModelOptions = {}) => {\n const facade = configure({\n ...input,\n baseURL: input.baseURL ?? profile.baseURL,\n provider: profile.provider,\n })\n return {\n id: ProviderID.make(profile.provider),\n model: facade.model,\n configure: configureProfile,\n }\n }\n return configureProfile()\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure({\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n provider: settings.provider,\n }).model(modelID)\n\nexport const baseten = define(profiles.baseten)\nexport const cerebras = define(profiles.cerebras)\nexport const deepinfra = define(profiles.deepinfra)\nexport const deepseek = define(profiles.deepseek)\nexport const fireworks = define(profiles.fireworks)\nexport const groq = define(profiles.groq)\nexport const togetherai = define(profiles.togetherai)\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/xai.ts"], | ||
| "sourcesContent": [ | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAICompatibleProfiles from \"./openai-compatible-profile\"\nimport * as OpenAICompatibleChat from \"../protocols/openai-compatible-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\n\nexport const id = ProviderID.make(\"xai\")\n\nexport type ModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n }\n\nexport const routes = [OpenAIResponses.route, OpenAICompatibleChat.route]\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => AuthOptions.bearer(options, \"XAI_API_KEY\")\n\nconst configuredResponsesRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return OpenAIResponses.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? OpenAICompatibleProfiles.profiles.xai.baseURL },\n auth: auth(input),\n })\n}\n\nconst configuredChatRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return OpenAICompatibleChat.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? OpenAICompatibleProfiles.profiles.xai.baseURL },\n auth: auth(input),\n })\n}\n\nexport const configure = (input: ModelOptions = {}) => {\n const responsesRoute = configuredResponsesRoute(input)\n const chatRoute = configuredChatRoute(input)\n const responses = (modelID: string | ModelID) => responsesRoute.model({ id: modelID })\n const chat = (modelID: string | ModelID) => chatRoute.model({ id: modelID })\n return {\n id,\n model: responses,\n responses,\n chat,\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model = provider.model\nexport const responses = provider.responses\nexport const chat = provider.chat\n" | ||
| ], | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/anthropic-messages.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type CacheHint,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ProviderMetadata,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n type ToolResultPart,\n} from \"../schema\"\nimport { JsonObject, optionalArray, optionalNull, ProviderShared } from \"./shared\"\nimport { classifyProviderFailure } from \"../provider-error\"\nimport * as Cache from \"./utils/cache\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"anthropic-messages\"\nexport const DEFAULT_BASE_URL = \"https://api.anthropic.com/v1\"\nexport const PATH = \"/messages\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst AnthropicCacheControl = Schema.Struct({\n type: Schema.tag(\"ephemeral\"),\n ttl: Schema.optional(Schema.Literals([\"5m\", \"1h\"])),\n})\n\nconst AnthropicTextBlock = Schema.Struct({\n type: Schema.tag(\"text\"),\n text: Schema.String,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicTextBlock = Schema.Schema.Type<typeof AnthropicTextBlock>\n\nconst AnthropicImageBlock = Schema.Struct({\n type: Schema.tag(\"image\"),\n source: Schema.Struct({\n type: Schema.tag(\"base64\"),\n media_type: Schema.String,\n data: Schema.String,\n }),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicImageBlock = Schema.Schema.Type<typeof AnthropicImageBlock>\n\nconst AnthropicThinkingBlock = Schema.Struct({\n type: Schema.tag(\"thinking\"),\n thinking: Schema.String,\n signature: Schema.optional(Schema.String),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\n\nconst AnthropicToolUseBlock = Schema.Struct({\n type: Schema.tag(\"tool_use\"),\n id: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicToolUseBlock = Schema.Schema.Type<typeof AnthropicToolUseBlock>\n\nconst AnthropicServerToolUseBlock = Schema.Struct({\n type: Schema.tag(\"server_tool_use\"),\n id: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicServerToolUseBlock = Schema.Schema.Type<typeof AnthropicServerToolUseBlock>\n\n// Server tool result blocks: web_search_tool_result, code_execution_tool_result,\n// and web_fetch_tool_result. The provider executes the tool and inlines the\n// structured result into the assistant turn — there is no client tool_result\n// round-trip. We round-trip the structured `content` payload as opaque JSON so\n// the next request can echo it back when continuing the conversation.\nconst AnthropicServerToolResultType = Schema.Literals([\n \"web_search_tool_result\",\n \"code_execution_tool_result\",\n \"web_fetch_tool_result\",\n])\ntype AnthropicServerToolResultType = Schema.Schema.Type<typeof AnthropicServerToolResultType>\n\nconst AnthropicServerToolResultBlock = Schema.Struct({\n type: AnthropicServerToolResultType,\n tool_use_id: Schema.String,\n content: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicServerToolResultBlock = Schema.Schema.Type<typeof AnthropicServerToolResultBlock>\n\n// Anthropic accepts either a plain string or an ordered array of text/image\n// blocks inside `tool_result.content`. The array form is required when a tool\n// returns image bytes (screenshot, image search, etc.) so they can be passed\n// to the model as proper image inputs instead of being JSON-stringified into\n// the prompt — which silently inflates context by megabytes and can push the\n// conversation over the model's token limit.\nconst AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock])\n\nconst AnthropicToolResultBlock = Schema.Struct({\n type: Schema.tag(\"tool_result\"),\n tool_use_id: Schema.String,\n content: Schema.Union([Schema.String, Schema.Array(AnthropicToolResultContent)]),\n is_error: Schema.optional(Schema.Boolean),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\n\nconst AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicToolResultBlock])\ntype AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>\nconst AnthropicAssistantBlock = Schema.Union([\n AnthropicTextBlock,\n AnthropicThinkingBlock,\n AnthropicToolUseBlock,\n AnthropicServerToolUseBlock,\n AnthropicServerToolResultBlock,\n])\ntype AnthropicAssistantBlock = Schema.Schema.Type<typeof AnthropicAssistantBlock>\ntype AnthropicToolResultBlock = Schema.Schema.Type<typeof AnthropicToolResultBlock>\n\nconst AnthropicMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"user\"), content: Schema.Array(AnthropicUserBlock) }),\n Schema.Struct({ role: Schema.Literal(\"assistant\"), content: Schema.Array(AnthropicAssistantBlock) }),\n Schema.Struct({ role: Schema.Literal(\"system\"), content: Schema.Array(AnthropicTextBlock) }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype AnthropicMessage = Schema.Schema.Type<typeof AnthropicMessage>\n\nconst AnthropicTool = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n input_schema: JsonObject,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicTool = Schema.Schema.Type<typeof AnthropicTool>\n\nconst AnthropicToolChoice = Schema.Union([\n Schema.Struct({ type: Schema.Literals([\"auto\", \"any\"]) }),\n Schema.Struct({ type: Schema.tag(\"tool\"), name: Schema.String }),\n])\n\nconst AnthropicThinking = Schema.Union([\n Schema.Struct({\n type: Schema.tag(\"enabled\"),\n budget_tokens: Schema.Number,\n }),\n Schema.Struct({\n type: Schema.tag(\"adaptive\"),\n display: Schema.optional(Schema.Literals([\"summarized\", \"omitted\"])),\n }),\n Schema.Struct({\n type: Schema.tag(\"disabled\"),\n }),\n])\n\nconst AnthropicOutputConfig = Schema.Struct({\n effort: Schema.optional(Schema.String),\n})\n\nconst AnthropicBodyFields = {\n model: Schema.String,\n system: optionalArray(AnthropicTextBlock),\n messages: Schema.Array(AnthropicMessage),\n tools: optionalArray(AnthropicTool),\n tool_choice: Schema.optional(AnthropicToolChoice),\n stream: Schema.Literal(true),\n max_tokens: Schema.Number,\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n top_k: Schema.optional(Schema.Number),\n stop_sequences: optionalArray(Schema.String),\n thinking: Schema.optional(AnthropicThinking),\n output_config: Schema.optional(AnthropicOutputConfig),\n}\nexport const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)\nexport type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>\n\nconst AnthropicUsage = Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n output_tokens: Schema.optional(Schema.Number),\n cache_creation_input_tokens: optionalNull(Schema.Number),\n cache_read_input_tokens: optionalNull(Schema.Number),\n})\ntype AnthropicUsage = Schema.Schema.Type<typeof AnthropicUsage>\n\nconst AnthropicStreamBlock = Schema.Struct({\n type: Schema.String,\n id: Schema.optional(Schema.String),\n name: Schema.optional(Schema.String),\n text: Schema.optional(Schema.String),\n thinking: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n input: Schema.optional(Schema.Unknown),\n // *_tool_result blocks arrive whole as content_block_start (no streaming\n // delta) with the structured payload in `content` and the originating\n // server_tool_use id in `tool_use_id`.\n tool_use_id: Schema.optional(Schema.String),\n content: Schema.optional(Schema.Unknown),\n})\n\nconst AnthropicStreamDelta = Schema.Struct({\n type: Schema.optional(Schema.String),\n text: Schema.optional(Schema.String),\n thinking: Schema.optional(Schema.String),\n partial_json: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n stop_reason: optionalNull(Schema.String),\n stop_sequence: optionalNull(Schema.String),\n})\n\nconst AnthropicEvent = Schema.Struct({\n type: Schema.String,\n index: Schema.optional(Schema.Number),\n message: Schema.optional(Schema.Struct({ usage: Schema.optional(AnthropicUsage) })),\n content_block: Schema.optional(AnthropicStreamBlock),\n delta: Schema.optional(AnthropicStreamDelta),\n usage: Schema.optional(AnthropicUsage),\n // `type` and `message` are both required per Anthropic's spec, but\n // OpenAI-compatible proxies and gateway translations occasionally drop one\n // or the other; mark them optional so a partial payload still parses and\n // the parser can fall back to whichever field is populated.\n error: Schema.optional(\n Schema.Struct({ type: Schema.optional(Schema.String), message: Schema.optional(Schema.String) }),\n ),\n})\ntype AnthropicEvent = Schema.Schema.Type<typeof AnthropicEvent>\n\ninterface ParserState {\n readonly tools: ToolStream.State<number>\n readonly usage?: Usage\n readonly lifecycle: Lifecycle.State\n}\n\nconst invalid = ProviderShared.invalidRequest\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\n// Anthropic accepts at most 4 explicit cache_control breakpoints per request,\n// across `tools`, `system`, and `messages`. Beyond the cap the API returns a\n// 400 — so the lowering layer counts emitted markers and silently drops any\n// that exceed it.\nconst ANTHROPIC_BREAKPOINT_CAP = 4\n\nconst EPHEMERAL_5M = { type: \"ephemeral\" as const }\nconst EPHEMERAL_1H = { type: \"ephemeral\" as const, ttl: \"1h\" as const }\n\nconst cacheControl = (breakpoints: Cache.Breakpoints, cache: CacheHint | undefined) => {\n if (cache?.type !== \"ephemeral\" && cache?.type !== \"persistent\") return undefined\n if (breakpoints.remaining <= 0) {\n breakpoints.dropped += 1\n return undefined\n }\n breakpoints.remaining -= 1\n return Cache.ttlBucket(cache.ttlSeconds) === \"1h\" ? EPHEMERAL_1H : EPHEMERAL_5M\n}\n\nconst anthropicMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ anthropic: metadata })\n\nconst signatureFromMetadata = (metadata: ProviderMetadata | undefined): string | undefined => {\n const anthropic = metadata?.anthropic\n if (!ProviderShared.isRecord(anthropic)) return undefined\n return typeof anthropic.signature === \"string\" ? anthropic.signature : undefined\n}\n\nconst lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({\n name: tool.name,\n description: tool.description,\n input_schema: inputSchema,\n cache_control: cacheControl(breakpoints, tool.cache),\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Anthropic Messages\", toolChoice, {\n auto: () => ({ type: \"auto\" as const }),\n none: () => undefined,\n required: () => ({ type: \"any\" as const }),\n tool: (name) => ({ type: \"tool\" as const, name }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): AnthropicToolUseBlock => ({\n type: \"tool_use\",\n id: part.id,\n name: part.name,\n input: part.input,\n})\n\nconst lowerServerToolCall = (part: ToolCallPart): AnthropicServerToolUseBlock => ({\n type: \"server_tool_use\",\n id: part.id,\n name: part.name,\n input: part.input,\n})\n\n// Server tool result blocks are typed by name. Anthropic ships three today;\n// extend this list when new server tools land. The block content is the\n// structured payload returned by the provider, which we round-trip as-is.\nconst serverToolResultType = (name: string): AnthropicServerToolResultType | undefined => {\n if (name === \"web_search\") return \"web_search_tool_result\"\n if (name === \"code_execution\") return \"code_execution_tool_result\"\n if (name === \"web_fetch\") return \"web_fetch_tool_result\"\n return undefined\n}\n\nconst lowerServerToolResult = Effect.fn(\"AnthropicMessages.lowerServerToolResult\")(function* (part: ToolResultPart) {\n const wireType = serverToolResultType(part.name)\n if (!wireType)\n return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)\n return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock\n})\n\nconst lowerImage = Effect.fn(\"AnthropicMessages.lowerImage\")(function* (part: MediaPart) {\n const media = yield* ProviderShared.validateMedia(\n \"Anthropic Messages\",\n part,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return {\n type: \"image\" as const,\n source: {\n type: \"base64\" as const,\n media_type: media.mime,\n data: media.base64,\n },\n } satisfies AnthropicImageBlock\n})\n\n// Tool results may carry structured text/images. Keep media as provider-native\n// content instead of JSON-stringifying base64 into a prompt string.\nconst lowerToolResultContentItem = Effect.fn(\"AnthropicMessages.lowerToolResultContentItem\")(function* (\n item: ToolContent,\n) {\n if (item.type === \"text\") return { type: \"text\" as const, text: item.text } satisfies AnthropicTextBlock\n const media = yield* ProviderShared.validateToolFile(\n \"Anthropic Messages\",\n item,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return {\n type: \"image\" as const,\n source: {\n type: \"base64\" as const,\n media_type: media.mime,\n data: media.base64,\n },\n } satisfies AnthropicImageBlock\n})\n\nconst lowerToolResultContent = Effect.fn(\"AnthropicMessages.lowerToolResultContent\")(function* (part: ToolResultPart) {\n // Text / json / error results stay as a string for backward compatibility\n // with existing cassettes and provider expectations.\n if (part.result.type !== \"content\") return ProviderShared.toolResultText(part)\n // Preserve the narrowed array element type when compiled through a consumer package.\n const content: ReadonlyArray<ToolContent> = part.result.value\n return yield* Effect.forEach(content, lowerToolResultContentItem)\n})\n\n// Mid-conversation system messages are a native Claude API feature only for\n// Opus 4.8. Other Anthropic models intentionally use the same visible wrapped-\n// user fallback as non-Anthropic routes rather than sending a role they reject.\nconst supportsNativeSystemUpdates = (request: LLMRequest) => String(request.model.id) === \"claude-opus-4-8\"\n\nconst endsInServerToolUse = (message: LLMRequest[\"messages\"][number]) => {\n const last = message.content.at(-1)\n return message.role === \"assistant\" && last?.type === \"tool-call\" && last.providerExecuted === true\n}\n\nconst canUseNativeSystemUpdate = (messages: LLMRequest[\"messages\"], index: number) => {\n const previous = messages[index - 1]\n const next = messages[index + 1]\n return (\n previous !== undefined &&\n previous.role !== \"system\" &&\n (previous.role === \"user\" || previous.role === \"tool\" || endsInServerToolUse(previous)) &&\n next?.role !== \"system\" &&\n (next === undefined || next.role === \"assistant\")\n )\n}\n\nconst splitsLocalToolResults = (messages: LLMRequest[\"messages\"], index: number) => {\n const pending = new Set<string>()\n for (const message of messages.slice(0, index)) {\n for (const part of message.content) {\n if (message.role === \"assistant\" && part.type === \"tool-call\" && part.providerExecuted !== true)\n pending.add(part.id)\n if (message.role === \"tool\" && part.type === \"tool-result\") pending.delete(part.id)\n }\n }\n return pending.size > 0\n}\n\nconst lowerNativeSystemUpdate = Effect.fn(\"AnthropicMessages.lowerNativeSystemUpdate\")(function* (\n message: LLMRequest[\"messages\"][number],\n breakpoints: Cache.Breakpoints,\n) {\n const content = yield* ProviderShared.systemUpdateText(\"Anthropic Messages\", message)\n return {\n role: \"system\" as const,\n content: content.map((part) => ({\n type: \"text\" as const,\n text: part.text,\n cache_control: cacheControl(breakpoints, part.cache),\n })),\n }\n})\n\nconst lowerMessages = Effect.fn(\"AnthropicMessages.lowerMessages\")(function* (\n request: LLMRequest,\n breakpoints: Cache.Breakpoints,\n) {\n const messages: AnthropicMessage[] = []\n\n for (const [index, message] of request.messages.entries()) {\n if (message.role === \"system\") {\n if (splitsLocalToolResults(request.messages, index))\n return yield* invalid(\"Anthropic Messages system updates cannot split a local tool call from its tool result\")\n if (supportsNativeSystemUpdates(request) && canUseNativeSystemUpdate(request.messages, index)) {\n messages.push(yield* lowerNativeSystemUpdate(message, breakpoints))\n continue\n }\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Anthropic Messages\", message)\n const block = { type: \"text\" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }\n const previous = messages.at(-1)\n if (previous?.role === \"user\")\n messages[messages.length - 1] = { role: \"user\", content: [...previous.content, block] }\n else messages.push({ role: \"user\", content: [block] })\n continue\n }\n\n if (message.role === \"user\") {\n const content: AnthropicUserBlock[] = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* lowerImage(part))\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"Anthropic Messages\", \"user\", [\"text\", \"media\"])\n }\n messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: AnthropicAssistantBlock[] = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })\n continue\n }\n if (part.type === \"reasoning\") {\n content.push({\n type: \"thinking\",\n thinking: part.text,\n signature: part.encrypted ?? signatureFromMetadata(part.providerMetadata),\n })\n continue\n }\n if (part.type === \"tool-call\") {\n content.push(part.providerExecuted ? lowerServerToolCall(part) : lowerToolCall(part))\n continue\n }\n if (part.type === \"tool-result\" && part.providerExecuted) {\n content.push(yield* lowerServerToolResult(part))\n continue\n }\n return yield* invalid(\n `Anthropic Messages assistant messages only support text, reasoning, and tool-call content for now`,\n )\n }\n messages.push({ role: \"assistant\", content })\n continue\n }\n\n const content: AnthropicToolResultBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Anthropic Messages\", \"tool\", [\"tool-result\"])\n content.push({\n type: \"tool_result\",\n tool_use_id: part.id,\n content: yield* lowerToolResultContent(part),\n is_error: part.result.type === \"error\" ? true : undefined,\n cache_control: cacheControl(breakpoints, part.cache),\n })\n }\n messages.push({ role: \"user\", content })\n }\n\n return messages\n})\n\nconst anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthropic\n\nconst lowerThinking = Effect.fn(\"AnthropicMessages.lowerThinking\")(function* (request: LLMRequest) {\n const thinking = anthropicOptions(request)?.thinking\n if (!ProviderShared.isRecord(thinking)) return undefined\n if (thinking.type === \"adaptive\") {\n const display =\n thinking.display === \"summarized\"\n ? (\"summarized\" as const)\n : thinking.display === \"omitted\"\n ? (\"omitted\" as const)\n : undefined\n return { type: \"adaptive\" as const, ...(display === undefined ? {} : { display }) }\n }\n if (thinking.type === \"disabled\") return { type: \"disabled\" as const }\n if (thinking.type !== \"enabled\") return undefined\n const budget =\n typeof thinking.budgetTokens === \"number\"\n ? thinking.budgetTokens\n : typeof thinking.budget_tokens === \"number\"\n ? thinking.budget_tokens\n : undefined\n if (budget === undefined) return yield* invalid(\"Anthropic thinking provider option requires budgetTokens\")\n return { type: \"enabled\" as const, budget_tokens: budget }\n})\n\nconst outputConfig = (request: LLMRequest) => {\n const effort = anthropicOptions(request)?.effort\n return typeof effort === \"string\" ? { effort } : undefined\n}\n\nconst fromRequest = Effect.fn(\"AnthropicMessages.fromRequest\")(function* (request: LLMRequest) {\n const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096\n // Allocate the 4-breakpoint budget in invalidation order: tools → system →\n // messages. Tools live highest in the cache hierarchy, so when callers\n // over-mark we keep their tool hints and shed the message-tail ones first.\n const breakpoints = Cache.newBreakpoints(ANTHROPIC_BREAKPOINT_CAP)\n const tools =\n request.tools.length === 0 || request.toolChoice?.type === \"none\"\n ? undefined\n : request.tools.map((tool) =>\n lowerTool(\n breakpoints,\n tool,\n ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),\n ),\n )\n const system =\n request.system.length === 0\n ? undefined\n : request.system.map((part) => ({\n type: \"text\" as const,\n text: part.text,\n cache_control: cacheControl(breakpoints, part.cache),\n }))\n const messages = yield* lowerMessages(request, breakpoints)\n if (breakpoints.dropped > 0) {\n yield* Effect.logWarning(\n `Anthropic Messages: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${ANTHROPIC_BREAKPOINT_CAP} per request.`,\n )\n }\n return {\n model: request.model.id,\n system,\n messages,\n tools,\n tool_choice: toolChoice,\n stream: true as const,\n max_tokens: generation?.maxTokens ?? outputLimit,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n top_k: generation?.topK,\n stop_sequences: generation?.stop,\n thinking: yield* lowerThinking(request),\n output_config: outputConfig(request),\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\nconst mapFinishReason = (reason: string | null | undefined): FinishReason => {\n if (reason === \"end_turn\" || reason === \"stop_sequence\" || reason === \"pause_turn\") return \"stop\"\n if (reason === \"max_tokens\") return \"length\"\n if (reason === \"tool_use\") return \"tool-calls\"\n if (reason === \"refusal\") return \"content-filter\"\n return \"unknown\"\n}\n\n// Anthropic reports the non-overlapping breakdown natively — its\n// `input_tokens` is the *non-cached* count per the Messages API docs, with\n// cache reads and writes as separate fields. We sum them to derive the\n// inclusive `inputTokens` the rest of the contract expects. Extended\n// thinking tokens are *not* broken out by Anthropic — they're billed as\n// part of `output_tokens`, so `reasoningTokens` stays `undefined` and\n// `outputTokens` carries the combined total.\nconst mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {\n if (!usage) return undefined\n const nonCached = usage.input_tokens\n const cacheRead = usage.cache_read_input_tokens ?? undefined\n const cacheWrite = usage.cache_creation_input_tokens ?? undefined\n const inputTokens = ProviderShared.sumTokens(nonCached, cacheRead, cacheWrite)\n return new Usage({\n inputTokens,\n outputTokens: usage.output_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cacheRead,\n cacheWriteInputTokens: cacheWrite,\n totalTokens: ProviderShared.totalTokens(inputTokens, usage.output_tokens, undefined),\n providerMetadata: { anthropic: usage },\n })\n}\n\n// Anthropic emits usage on `message_start` and again on `message_delta` — the\n// final delta carries the authoritative totals. Right-biased merge: each\n// field prefers `right` when defined, falls back to `left`. `inputTokens` is\n// recomputed from the merged breakdown so the inclusive total stays\n// consistent with `nonCached + cacheRead + cacheWrite`.\nconst mergeUsage = (left: Usage | undefined, right: Usage | undefined) => {\n if (!left) return right\n if (!right) return left\n const nonCachedInputTokens = right.nonCachedInputTokens ?? left.nonCachedInputTokens\n const cacheReadInputTokens = right.cacheReadInputTokens ?? left.cacheReadInputTokens\n const cacheWriteInputTokens = right.cacheWriteInputTokens ?? left.cacheWriteInputTokens\n const inputTokens = ProviderShared.sumTokens(nonCachedInputTokens, cacheReadInputTokens, cacheWriteInputTokens)\n const outputTokens = right.outputTokens ?? left.outputTokens\n return new Usage({\n inputTokens,\n outputTokens,\n nonCachedInputTokens,\n cacheReadInputTokens,\n cacheWriteInputTokens,\n totalTokens: ProviderShared.totalTokens(inputTokens, outputTokens, undefined),\n providerMetadata: {\n anthropic: {\n ...left.providerMetadata?.[\"anthropic\"],\n ...right.providerMetadata?.[\"anthropic\"],\n },\n },\n })\n}\n\n// Server tool result blocks come whole in `content_block_start` (no streaming\n// delta sequence). We convert the payload to a `tool-result` event with\n// `providerExecuted: true`. The runtime appends it to the assistant message\n// for round-trip; downstream consumers can inspect `result.value` for the\n// structured payload.\nconst SERVER_TOOL_RESULT_NAMES: Record<AnthropicServerToolResultType, string> = {\n web_search_tool_result: \"web_search\",\n code_execution_tool_result: \"code_execution\",\n web_fetch_tool_result: \"web_fetch\",\n}\n\nconst isServerToolResultType = (type: string): type is AnthropicServerToolResultType => type in SERVER_TOOL_RESULT_NAMES\n\nconst serverToolResultEvent = (block: NonNullable<AnthropicEvent[\"content_block\"]>): LLMEvent | undefined => {\n if (!block.type || !isServerToolResultType(block.type)) return undefined\n const errorPayload =\n typeof block.content === \"object\" && block.content !== null && \"type\" in block.content\n ? String((block.content as Record<string, unknown>).type)\n : \"\"\n const isError = errorPayload.endsWith(\"_tool_result_error\")\n return LLMEvent.toolResult({\n id: block.tool_use_id ?? \"\",\n name: SERVER_TOOL_RESULT_NAMES[block.type],\n result: isError ? { type: \"error\", value: block.content } : { type: \"json\", value: block.content },\n providerExecuted: true,\n providerMetadata: anthropicMetadata({ blockType: block.type }),\n })\n}\n\ntype StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]\n\nconst NO_EVENTS: StepResult[\"1\"] = []\n\nconst onMessageStart = (state: ParserState, event: AnthropicEvent): StepResult => {\n const usage = mapUsage(event.message?.usage)\n return [usage ? { ...state, usage: mergeUsage(state.usage, usage) } : state, NO_EVENTS]\n}\n\nconst onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepResult => {\n const block = event.content_block\n if (!block) return [state, NO_EVENTS]\n\n if ((block.type === \"tool_use\" || block.type === \"server_tool_use\") && event.index !== undefined) {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n tools: ToolStream.start(state.tools, event.index, {\n id: block.id ?? String(event.index),\n name: block.name ?? \"\",\n providerExecuted: block.type === \"server_tool_use\",\n }),\n },\n [\n ...events,\n LLMEvent.toolInputStart({\n id: block.id ?? String(event.index),\n name: block.name ?? \"\",\n providerExecuted: block.type === \"server_tool_use\" ? true : undefined,\n }),\n ],\n ]\n }\n\n if (block.type === \"text\" && block.text) {\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, block.text) },\n events,\n ]\n }\n\n if (block.type === \"thinking\" && block.thinking) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, block.thinking),\n },\n events,\n ]\n }\n\n const result = serverToolResultEvent(block)\n if (!result) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, [...events, result]]\n}\n\nconst onContentBlockDelta = Effect.fn(\"AnthropicMessages.onContentBlockDelta\")(function* (\n state: ParserState,\n event: AnthropicEvent,\n) {\n const delta = event.delta\n\n if (delta?.type === \"text_delta\" && delta.text) {\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, delta.text) },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"thinking_delta\" && delta.thinking) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, delta.thinking),\n },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"signature_delta\" && delta.signature) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n `reasoning-${event.index ?? 0}`,\n anthropicMetadata({ signature: delta.signature }),\n ),\n },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"input_json_delta\" && event.index !== undefined) {\n if (!delta.partial_json) return [state, NO_EVENTS] satisfies StepResult\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n event.index,\n delta.partial_json,\n \"Anthropic Messages tool argument delta is missing its tool call\",\n )\n if (ToolStream.isError(result)) return yield* result\n const events: LLMEvent[] = []\n const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...result.events)\n return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult\n }\n\n return [state, NO_EVENTS] satisfies StepResult\n})\n\nconst onContentBlockStop = Effect.fn(\"AnthropicMessages.onContentBlockStop\")(function* (\n state: ParserState,\n event: AnthropicEvent,\n) {\n if (event.index === undefined) return [state, NO_EVENTS] satisfies StepResult\n const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length\n ? Lifecycle.stepStart(state.lifecycle, events)\n : Lifecycle.reasoningEnd(\n Lifecycle.textEnd(state.lifecycle, events, `text-${event.index}`),\n events,\n `reasoning-${event.index}`,\n )\n events.push(...resultEvents)\n return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult\n})\n\nconst onMessageDelta = (state: ParserState, event: AnthropicEvent): StepResult => {\n const usage = mergeUsage(state.usage, mapUsage(event.usage))\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.finish(state.lifecycle, events, {\n reason: mapFinishReason(event.delta?.stop_reason),\n usage,\n providerMetadata: event.delta?.stop_sequence\n ? anthropicMetadata({ stopSequence: event.delta.stop_sequence })\n : undefined,\n })\n return [{ ...state, lifecycle, usage }, events]\n}\n\n// Prefix `error.type` so overloads, rate limits, and quota errors are visible\n// even when the provider message is generic or empty.\nconst providerErrorMessage = (event: AnthropicEvent): string => {\n const type = event.error?.type\n const message = event.error?.message\n if (type && message) return `${type}: ${message}`\n return message || type || \"Anthropic Messages stream error\"\n}\n\nconst onError = (event: AnthropicEvent) =>\n new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({ message: providerErrorMessage(event), code: event.error?.type }),\n })\n\nconst step = (state: ParserState, event: AnthropicEvent) => {\n if (event.type === \"message_start\") return Effect.succeed(onMessageStart(state, event))\n if (event.type === \"content_block_start\") return Effect.succeed(onContentBlockStart(state, event))\n if (event.type === \"content_block_delta\") return onContentBlockDelta(state, event)\n if (event.type === \"content_block_stop\") return onContentBlockStop(state, event)\n if (event.type === \"message_delta\") return Effect.succeed(onMessageDelta(state, event))\n if (event.type === \"error\") return onError(event)\n return Effect.succeed<StepResult>([state, NO_EVENTS])\n}\n\n// =============================================================================\n// Protocol And Anthropic Route\n// =============================================================================\n/**\n * The Anthropic Messages protocol — request body construction, body schema,\n * and the streaming-event state machine. Used by native Anthropic Cloud and\n * (once registered) Vertex Anthropic / Bedrock-hosted Anthropic passthrough.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: AnthropicMessagesBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(AnthropicEvent),\n initial: () => ({ tools: ToolStream.empty<number>(), lifecycle: Lifecycle.initial() }),\n step,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"anthropic\",\n providerMetadataKey: \"anthropic\",\n protocol,\n endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),\n auth: Auth.none,\n framing: Framing.sse,\n headers: () => ({ \"anthropic-version\": \"2023-06-01\" }),\n})\n\nexport * as AnthropicMessages from \"./anthropic-messages\"\n" | ||
| ], | ||
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| ||
| "debugId": "6373C3B53F70A55D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/run.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerConnection } from \"../../services/server-connection\"\n\nexport default Runtime.handler(Commands.commands.run, (input) =>\n Effect.gen(function* () {\n const { runNonInteractive } = yield* Effect.promise(() => import(\"../../run/run\"))\n const separator = process.argv.indexOf(\"--\", 2)\n const server = yield* ServerConnection.resolve({\n server: Option.getOrUndefined(input.server),\n standalone: input.standalone,\n })\n yield* Effect.promise(() =>\n runNonInteractive({\n server,\n message: [...input.message, ...(separator === -1 ? [] : process.argv.slice(separator + 1))],\n continue: input.continue,\n session: Option.getOrUndefined(input.session),\n fork: input.fork,\n model: Option.getOrUndefined(input.model),\n agent: Option.getOrUndefined(input.agent),\n format: input.format,\n file: [...input.file],\n title: Option.getOrUndefined(input.title),\n thinking: input.thinking,\n auto: input.auto || input.yolo,\n }),\n )\n }),\n)\n" | ||
| ], | ||
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| "debugId": "E0067C4DDA2F6F8B64756E2164756E21", | ||
| "names": [] | ||
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| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
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| "names": [] | ||
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| "version": 3, | ||
| "sources": [], | ||
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| "version": 3, | ||
| "sources": ["src/ui/timeline.tsx", "src/commands/handlers/console/login.ts"], | ||
| "sourcesContent": [ | ||
| "import { createComponent as _$createComponent } from \"@opentui/solid\";\nimport { effect as _$effect } from \"@opentui/solid\";\nimport { createTextNode as _$createTextNode } from \"@opentui/solid\";\nimport { insertNode as _$insertNode } from \"@opentui/solid\";\nimport { insert as _$insert } from \"@opentui/solid\";\nimport { setProp as _$setProp } from \"@opentui/solid\";\nimport { createElement as _$createElement } from \"@opentui/solid\";\n/** @jsxImportSource @opentui/solid */\nimport { createCliRenderer, RGBA } from \"@opentui/core\";\nimport { createScrollbackWriter, render, useKeyboard } from \"@opentui/solid\";\nimport { registerOpencodeSpinner } from \"@opencode-ai/tui/component/register-spinner\";\nimport { Show, createSignal } from \"solid-js\";\nregisterOpencodeSpinner();\nconst SPINNER_FRAMES = [\"⠋\", \"⠙\", \"⠹\", \"⠸\", \"⠼\", \"⠴\", \"⠦\", \"⠧\", \"⠇\", \"⠏\"];\nconst IDLE_TIMEOUT = 1_000;\nconst COLORS = {\n accent: RGBA.fromIndex(6),\n error: RGBA.fromIndex(1),\n foreground: RGBA.defaultForeground(),\n muted: RGBA.fromIndex(8),\n success: RGBA.fromIndex(2)\n};\nconst ROWS = {\n intro: {\n marker: \"┌\",\n color: COLORS.muted,\n connector: true\n },\n item: {\n marker: \"●\",\n color: COLORS.accent,\n connector: true\n },\n success: {\n marker: \"◇\",\n color: COLORS.success,\n connector: true\n },\n failure: {\n marker: \"■\",\n color: COLORS.error,\n connector: false\n },\n outro: {\n marker: \"└\",\n color: COLORS.muted,\n connector: false\n }\n};\nfunction row(kind, value) {\n const style = ROWS[kind];\n return createScrollbackWriter(() => (() => {\n var _el$ = _$createElement(\"box\"),\n _el$2 = _$createElement(\"box\"),\n _el$3 = _$createElement(\"text\"),\n _el$4 = _$createElement(\"text\");\n _$insertNode(_el$, _el$2);\n _$setProp(_el$, \"width\", \"100%\");\n _$setProp(_el$, \"minHeight\", 1);\n _$setProp(_el$, \"flexDirection\", \"column\");\n _$insertNode(_el$2, _el$3);\n _$insertNode(_el$2, _el$4);\n _$setProp(_el$2, \"width\", \"100%\");\n _$setProp(_el$2, \"minHeight\", 1);\n _$setProp(_el$2, \"flexDirection\", \"row\");\n _$setProp(_el$2, \"gap\", 1);\n _$setProp(_el$3, \"flexShrink\", 0);\n _$insert(_el$3, () => style.marker);\n _$setProp(_el$4, \"wrapMode\", \"word\");\n _$insert(_el$4, value);\n _$insert(_el$, _$createComponent(Show, {\n get when() {\n return style.connector;\n },\n get children() {\n var _el$5 = _$createElement(\"text\");\n _$insertNode(_el$5, _$createTextNode(`│`));\n _$effect(_$p => _$setProp(_el$5, \"fg\", COLORS.muted, _$p));\n return _el$5;\n }\n }), null);\n _$effect(_p$ => {\n var _v$ = style.color,\n _v$2 = COLORS.foreground;\n _v$ !== _p$.e && (_p$.e = _$setProp(_el$3, \"fg\", _v$, _p$.e));\n _v$2 !== _p$.t && (_p$.t = _$setProp(_el$4, \"fg\", _v$2, _p$.t));\n return _p$;\n }, {\n e: undefined,\n t: undefined\n });\n return _el$;\n })(), {\n startOnNewLine: true,\n trailingNewline: !style.connector\n });\n}\nfunction TimelineFooter(props) {\n useKeyboard(event => {\n if (event.name !== \"escape\" && !(event.ctrl && event.name === \"c\")) return;\n event.preventDefault();\n props.cancel();\n });\n return (() => {\n var _el$7 = _$createElement(\"box\");\n _$setProp(_el$7, \"width\", \"100%\");\n _$setProp(_el$7, \"height\", 1);\n _$setProp(_el$7, \"flexDirection\", \"row\");\n _$setProp(_el$7, \"gap\", 1);\n _$insert(_el$7, _$createComponent(Show, {\n get when() {\n return props.pending();\n },\n children: text => [(() => {\n var _el$8 = _$createElement(\"spinner\");\n _$setProp(_el$8, \"frames\", SPINNER_FRAMES);\n _$setProp(_el$8, \"interval\", 80);\n _$effect(_$p => _$setProp(_el$8, \"color\", COLORS.accent, _$p));\n return _el$8;\n })(), (() => {\n var _el$9 = _$createElement(\"text\");\n _$setProp(_el$9, \"wrapMode\", \"none\");\n _$setProp(_el$9, \"truncate\", true);\n _$insert(_el$9, text);\n _$effect(_$p => _$setProp(_el$9, \"fg\", COLORS.foreground, _$p));\n return _el$9;\n })()]\n }));\n return _el$7;\n })();\n}\nfunction bounded(task) {\n return new Promise(resolve => {\n const timer = setTimeout(resolve, IDLE_TIMEOUT);\n timer.unref();\n const finish = () => {\n clearTimeout(timer);\n resolve();\n };\n void task.then(finish, finish);\n });\n}\nasync function shutdown(renderer) {\n await bounded(renderer.idle());\n try {\n renderer.externalOutputMode = \"passthrough\";\n } finally {\n try {\n renderer.screenMode = \"main-screen\";\n } finally {\n if (!renderer.isDestroyed) renderer.destroy();\n }\n }\n}\nexport async function createTimelineHost() {\n const stdout = process.stdout;\n const controller = new AbortController();\n const signals = [\"SIGINT\", \"SIGHUP\", \"SIGQUIT\"];\n const cancel = () => {\n if (!controller.signal.aborted) controller.abort();\n };\n signals.forEach(signal => process.on(signal, cancel));\n if (!stdout.isTTY || !process.stdin.isTTY) {\n let closed = false;\n let writing = false;\n let active;\n let closeTask;\n const write = async (kind, text) => {\n if (closed) throw new Error(\"timeline closed\");\n if (writing) throw new Error(\"timeline write already in progress\");\n writing = true;\n try {\n const style = kind === \"pending\" ? undefined : ROWS[kind];\n const marker = kind === \"pending\" ? \".\" : ROWS[kind].marker;\n const connector = style?.connector ? \"│\\n\" : \"\";\n active = new Promise((resolve, reject) => {\n stdout.write(`${marker} ${text}\\n${connector}`, error => error ? reject(error) : resolve());\n });\n await active;\n } finally {\n writing = false;\n active = undefined;\n }\n };\n const close = () => {\n if (closeTask) return closeTask;\n closed = true;\n closeTask = (async () => {\n await active?.catch(() => {});\n signals.forEach(signal => process.off(signal, cancel));\n })();\n return closeTask;\n };\n return {\n signal: controller.signal,\n intro: text => write(\"intro\", text),\n item: text => write(\"item\", text),\n pending: text => write(\"pending\", text),\n success: text => write(\"success\", text),\n failure: text => write(\"failure\", text),\n outro: text => write(\"outro\", text),\n close\n };\n }\n let renderer;\n try {\n // Start on a fresh row so delayed SSH cursor reports cannot make\n // split-footer overwrite the shell command.\n process.stdout.write(\"\\n\");\n renderer = await createCliRenderer({\n stdin: process.stdin,\n useMouse: false,\n autoFocus: false,\n openConsoleOnError: false,\n exitOnCtrlC: false,\n exitSignals: [],\n screenMode: \"split-footer\",\n footerHeight: 1,\n externalOutputMode: \"capture-stdout\",\n consoleMode: \"disabled\",\n clearOnShutdown: false\n });\n const activeRenderer = renderer;\n const [pending, setPending] = createSignal();\n const renderTask = render(() => _$createComponent(TimelineFooter, {\n pending: pending,\n cancel: cancel\n }), activeRenderer);\n void renderTask.catch(cancel);\n await bounded(activeRenderer.idle());\n let closed = false;\n let writing = false;\n let active;\n let closeTask;\n const write = (kind, text) => {\n if (closed) return Promise.reject(new Error(\"timeline closed\"));\n if (writing) return Promise.reject(new Error(\"timeline write already in progress\"));\n writing = true;\n active = (async () => {\n if (kind === \"pending\") {\n setPending(text);\n activeRenderer.requestRender();\n } else {\n if (kind === \"success\" || kind === \"failure\" || kind === \"outro\") setPending(undefined);\n activeRenderer.writeToScrollback(row(kind, text));\n activeRenderer.requestRender();\n }\n await bounded(activeRenderer.idle());\n })().finally(() => {\n writing = false;\n active = undefined;\n });\n return active;\n };\n const close = () => {\n if (closeTask) return closeTask;\n closed = true;\n closeTask = (async () => {\n await active?.catch(() => {});\n try {\n await shutdown(activeRenderer);\n await bounded(renderTask);\n } finally {\n signals.forEach(signal => process.off(signal, cancel));\n }\n })();\n return closeTask;\n };\n return {\n signal: controller.signal,\n intro: text => write(\"intro\", text),\n item: text => write(\"item\", text),\n pending: text => write(\"pending\", text),\n success: text => write(\"success\", text),\n failure: text => write(\"failure\", text),\n outro: text => write(\"outro\", text),\n close\n };\n } catch (error) {\n try {\n if (renderer) await shutdown(renderer);\n } finally {\n signals.forEach(signal => process.off(signal, cancel));\n }\n throw error;\n }\n}", | ||
| "import { Cause, Effect, Exit, Option } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { AppProcess } from \"@opencode-ai/core/process\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { createTimelineHost, type TimelineHost } from \"../../../ui/timeline\"\n\nconst integrationID = \"opencode\"\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.console.commands.login,\n Effect.fn(\"cli.console.login\")(function* (input) {\n const timeline = yield* Effect.acquireRelease(\n Effect.promise(() => createTimelineHost()),\n (value) => request(() => value.close()).pipe(Effect.ignore),\n )\n const exit = yield* login(timeline, Option.getOrUndefined(input.url)).pipe(\n Effect.raceFirst(AppProcess.waitForAbort(timeline.signal)),\n Effect.exit,\n )\n if (Exit.isSuccess(exit)) return\n\n const cancelled = timeline.signal.aborted\n yield* request(() => timeline.failure(cancelled ? \"Authorization cancelled\" : errorMessage(exit.cause))).pipe(\n Effect.ignore,\n )\n process.exitCode = cancelled ? 130 : 1\n }),\n)\n\nconst login = Effect.fn(\"cli.console.login.run\")(function* (timeline: TimelineHost, server?: string) {\n yield* request(() => timeline.intro(\"Log in\"))\n yield* request(() => timeline.pending(\"Connecting to OpenCode...\"))\n\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const found = yield* request((signal) => client.integration.get({ integrationID, location }, { signal }))\n const integration = yield* required(found.data, \"OpenCode Console integration is unavailable\")\n const method = yield* required(\n integration.methods.find((candidate) => candidate.type === \"oauth\"),\n \"OpenCode Console login is unavailable\",\n )\n\n yield* request(() => timeline.pending(\"Starting authorization...\"))\n const started = yield* request((signal) =>\n client.integration.oauth.connect(\n {\n integrationID,\n methodID: method.id,\n inputs: server ? { server } : {},\n location,\n },\n { signal },\n ),\n )\n const attempt = started.data\n yield* Effect.addFinalizer(() =>\n request(() =>\n client.integration.oauth.cancel(\n { integrationID, attemptID: attempt.attemptID, location },\n { signal: AbortSignal.timeout(5_000) },\n ),\n ).pipe(Effect.ignore),\n )\n if (attempt.mode !== \"auto\") yield* Effect.fail(new Error(\"OpenCode Console requires a device login\"))\n\n yield* request(() => timeline.item(`Go to: ${attempt.url}`))\n yield* request(() => timeline.item(attempt.instructions))\n yield* request(async () => {\n const { default: open } = await import(\"open\")\n await open(attempt.url)\n }).pipe(Effect.ignore)\n yield* request(() => timeline.pending(\"Waiting for authorization...\"))\n\n const status = yield* waitForConsoleLogin(client, integrationID, attempt.attemptID)\n if (status.status === \"failed\") yield* Effect.fail(new Error(status.message))\n if (status.status === \"expired\") yield* Effect.fail(new Error(\"Device code expired\"))\n\n yield* request(() => timeline.success(\"Connected to OpenCode Console\"))\n yield* request(() => timeline.outro(\"Done\"))\n})\n\nconst waitForConsoleLogin = Effect.fn(\"cli.console.login.wait\")(function* (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n) {\n while (true) {\n const response = yield* request((signal) =>\n client.integration.oauth.status({ integrationID, attemptID, location }, { signal }),\n )\n if (response.data.status !== \"pending\") return response.data\n yield* Effect.sleep(500)\n }\n})\n\nfunction request<A>(task: (signal: AbortSignal) => Promise<A>) {\n return Effect.tryPromise({\n try: task,\n catch: (cause) => cause,\n })\n}\n\nfunction required<A>(value: A | null | undefined, message: string) {\n return value === null || value === undefined ? Effect.fail(new Error(message)) : Effect.succeed(value)\n}\n\nfunction errorMessage(cause: Cause.Cause<unknown>) {\n const error = Cause.squash(cause)\n if (error instanceof Error) return error.message\n if (typeof error === \"object\" && error !== null && \"message\" in error && typeof error.message === \"string\") {\n return error.message\n }\n return String(error)\n}\n" | ||
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| ||
| "debugId": "E0474FCDFADBEF1364756E2164756E21", | ||
| "names": [] | ||
| } |
+1
-1
| { | ||
| "name": "@opencode-ai/cli-linux-arm64", | ||
| "version": "0.0.0-next-15840", | ||
| "version": "0.0.0-next-15847", | ||
| "license": "MIT", | ||
@@ -5,0 +5,0 @@ "repository": { |
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| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/frontend/actions.ts", "../simulation/src/recording.ts", "../simulation/src/frontend/renderer.ts", "../simulation/src/frontend/semantics.ts", "../simulation/src/frontend/server.ts", "../simulation/src/frontend/simulation.ts"], | ||
| "sourcesContent": [ | ||
| "import { tmpdir } from \"node:os\"\nimport { extname, join, resolve } from \"node:path\"\nimport type { CliRenderer, Renderable } from \"@opentui/core\"\nimport {\n createMockKeys,\n createMockMouse,\n KeyCodes,\n type KeyInput,\n type MockInput,\n type MockMouse,\n} from \"@opentui/core/testing\"\nimport { Config, Effect, FileSystem, Schema } from \"effect\"\nimport { SimulationProtocol } from \"../protocol\"\nimport { SimulationRenderer } from \"./renderer\"\nimport { SimulationSemantics } from \"./semantics\"\n\nexport type Action = SimulationProtocol.Frontend.Action\nexport type Element = SimulationProtocol.Frontend.Element\n\nexport interface Harness {\n readonly renderer: CliRenderer\n readonly mockInput: MockInput\n readonly mockMouse: MockMouse\n readonly resize: (cols: number, rows: number) => void\n readonly renderOnce: () => Promise<void>\n readonly screen: () => string\n}\n\ntype RenderBuffer = {\n readonly width: number\n readonly height: number\n getRealCharBytes(includeAnsi?: boolean): Uint8Array\n}\n\nconst decoder = new TextDecoder()\n\nfunction isKeyCode(key: string): key is keyof typeof KeyCodes {\n return Object.hasOwn(KeyCodes, key)\n}\n\nfunction keyInput(key: string): KeyInput {\n const named = key.toUpperCase()\n return isKeyCode(named) ? named : key\n}\n\nfunction children(renderable: Renderable) {\n return renderable.getChildren().filter((child): child is Renderable => \"num\" in child)\n}\n\nfunction all(renderable: Renderable): Renderable[] {\n return [renderable, ...children(renderable).flatMap(all)]\n}\n\nfunction mouseListeners(renderable: Renderable) {\n const general = Reflect.get(renderable, \"_mouseListener\")\n const specific = Reflect.get(renderable, \"_mouseListeners\")\n return Boolean(general) || (specific && typeof specific === \"object\" && Object.keys(specific).length > 0)\n}\n\nfunction hit(renderer: CliRenderer, renderable: Renderable) {\n if (renderable.width <= 0 || renderable.height <= 0) return false\n const x = Math.floor(renderable.screenX + renderable.width / 2)\n const y = Math.floor(renderable.screenY + renderable.height / 2)\n const target = renderer.hitTest(x, y)\n return all(renderable).some((item) => item.num === target)\n}\n\n/**\n * Builds the harness the simulation server drives.\n *\n * When the renderer is the headless simulation renderer, its TestRendererSetup\n * provides the supported testing APIs. For the visible terminal renderer the\n * harness falls back to `requestRender` + `idle` and reading the private\n * `currentRenderBuffer`.\n */\nexport function createHarness(renderer: CliRenderer): Harness {\n const setup = SimulationRenderer.setupFor(renderer)\n return {\n renderer,\n mockInput: setup?.mockInput ?? createMockKeys(renderer),\n mockMouse: setup?.mockMouse ?? createMockMouse(renderer),\n resize: setup?.resize ?? ((cols, rows) => renderer.resize(cols, rows)),\n renderOnce:\n setup?.renderOnce ??\n (async () => {\n renderer.requestRender()\n await renderer.idle()\n }),\n // captureCharFrame follows the test renderer's output sink. Recording\n // redirects that sink to the timeline, so read the live render buffer\n // instead; it is also the source used by screenshots.\n screen: () => decoder.decode((Reflect.get(renderer, \"currentRenderBuffer\") as RenderBuffer).getRealCharBytes()),\n }\n}\n\nexport function elements(renderer: CliRenderer): Element[] {\n return all(renderer.root)\n .filter((renderable) => renderable.visible && !renderable.isDestroyed)\n .map((renderable) => {\n const clickable = mouseListeners(renderable) && hit(renderer, renderable)\n return {\n id: renderable.id,\n num: renderable.num,\n x: renderable.screenX,\n y: renderable.screenY,\n width: renderable.width,\n height: renderable.height,\n focusable: renderable.focusable,\n focused: renderable.focused,\n clickable,\n editor: renderer.currentFocusedEditor === renderable,\n } satisfies Element\n })\n .filter((element) => element.focusable || element.clickable || element.editor)\n}\n\nexport function state(harness: Harness) {\n return {\n focused: {\n renderable: harness.renderer.currentFocusedRenderable?.num,\n editor: Boolean(harness.renderer.currentFocusedEditor),\n },\n elements: elements(harness.renderer),\n }\n}\n\nexport function snapshot(harness: Harness): SimulationProtocol.Frontend.SemanticSnapshot {\n const ids = new Set<string>()\n const visit = (renderable: Renderable, parent?: string): SimulationProtocol.Frontend.SemanticNode[] => {\n if (!renderable.visible || renderable.isDestroyed) return []\n const definition = SimulationSemantics.read(renderable)?.()\n if (definition && ids.has(renderable.id)) throw new Error(`duplicate semantic UI id: ${renderable.id}`)\n if (definition) ids.add(renderable.id)\n const node = definition\n ? [{ id: renderable.id, ...definition, ...(parent === undefined ? {} : { parent }), element: renderable.num }]\n : []\n const ancestor = definition ? renderable.id : parent\n return [...node, ...children(renderable).flatMap((child) => visit(child, ancestor))]\n }\n return Schema.decodeUnknownSync(SimulationProtocol.Frontend.SemanticSnapshot)({\n format: \"opencode-ui-snapshot-v1\",\n nodes: visit(harness.renderer.root),\n })\n}\n\nexport function matches(harness: Pick<Harness, \"screen\">, text: string) {\n return harness.screen().includes(text)\n}\n\nexport const capture = Effect.fn(\"SimulationActions.capture\")(function* (harness: Harness) {\n yield* Effect.tryPromise(() => harness.renderOnce())\n const buffer = harness.renderer.currentRenderBuffer\n return {\n cols: buffer.width,\n rows: buffer.height,\n cursor: [0, 0] as const,\n lines: buffer.getSpanLines().map((line) => ({\n spans: line.spans.map((span) => ({\n text: span.text,\n fg: span.fg.toInts(),\n bg: span.bg.toInts(),\n attributes: span.attributes,\n width: span.width,\n })),\n })),\n } satisfies SimulationProtocol.Frontend.CapturedFrame\n})\n\nexport const screenshot = Effect.fn(\"SimulationActions.screenshot\")(function* (harness: Harness, name?: string) {\n const filename = name ?? `screenshot-${crypto.randomUUID()}`\n if (!filename || filename.includes(\"/\") || filename.includes(\"\\\\\") || extname(filename))\n return yield* Effect.fail(new Error(\"screenshot name must not contain a path or extension\"))\n yield* Effect.tryPromise(() => harness.renderOnce())\n const { SimulationPng } = yield* Effect.promise(() => import(\"./png\"))\n const image = SimulationPng.screenshot(harness.renderer)\n const directory = resolve(\n yield* Config.string(\"OPENCODE_DRIVE_MEDIA_DIR\").pipe(\n Config.withDefault(join(tmpdir(), \"opencode-drive\", \"output\")),\n ),\n )\n const fs = yield* FileSystem.FileSystem\n yield* fs.makeDirectory(directory, { recursive: true })\n const path = join(directory, `${filename}.png`)\n yield* fs.writeFile(path, image.data)\n return path\n})\n\nexport const execute = Effect.fn(\"SimulationActions.execute\")(function* (harness: Harness, action: Action) {\n switch (action.type) {\n case \"ui.type\":\n yield* Effect.tryPromise(() => harness.mockInput.typeText(action.text))\n break\n case \"ui.press\":\n harness.mockInput.pressKey(keyInput(action.key), action.modifiers)\n break\n case \"ui.enter\":\n harness.mockInput.pressEnter()\n break\n case \"ui.arrow\":\n harness.mockInput.pressArrow(action.direction)\n break\n case \"ui.focus\":\n all(harness.renderer.root)\n .find((item) => item.num === action.target)\n ?.focus()\n break\n case \"ui.click\": {\n const target = all(harness.renderer.root).find((item) => item.num === action.target)\n if (!target || !target.visible || target.isDestroyed)\n return yield* Effect.fail(new Error(`click target is stale or unavailable: ${action.target}`))\n if (action.semantic) {\n const current = snapshot(harness).nodes.find((node) => node.element === action.target)\n if (\n current?.id !== action.semantic.id ||\n current.instance !== action.semantic.instance ||\n current.element !== action.semantic.element\n )\n return yield* Effect.fail(new Error(`semantic click target is stale or unavailable: ${action.semantic.id}`))\n }\n if (\n !Number.isFinite(action.x) ||\n action.x < 0 ||\n action.x >= target.width ||\n !Number.isFinite(action.y) ||\n action.y < 0 ||\n action.y >= target.height\n )\n return yield* Effect.fail(new Error(\"click position must be within the target element\"))\n yield* Effect.tryPromise(() => harness.mockMouse.click(target.screenX + action.x, target.screenY + action.y))\n break\n }\n case \"ui.resize\":\n if (\n !Number.isSafeInteger(action.cols) ||\n action.cols <= 0 ||\n !Number.isSafeInteger(action.rows) ||\n action.rows <= 0\n ) {\n return yield* Effect.fail(new Error(\"resize cols and rows must be positive integers\"))\n }\n harness.resize(action.cols, action.rows)\n SimulationRenderer.recordResize(harness.renderer, action.cols, action.rows)\n break\n }\n yield* Effect.tryPromise(() => harness.renderOnce())\n return state(harness)\n})\n\nexport * as SimulationActions from \"./actions\"\n", | ||
| "import { createWriteStream, type WriteStream } from \"node:fs\"\nimport { mkdir } from \"node:fs/promises\"\nimport { dirname } from \"node:path\"\nimport { Writable } from \"node:stream\"\nimport { finished } from \"node:stream/promises\"\nimport { Schema } from \"effect\"\n\nexport const Header = Schema.Struct({\n type: Schema.Literal(\"header\"),\n version: Schema.Literal(1),\n cols: Schema.Number,\n rows: Schema.Number,\n encoding: Schema.Literal(\"base64\"),\n})\nexport interface Header extends Schema.Schema.Type<typeof Header> {}\n\nexport const Output = Schema.Struct({\n type: Schema.Literal(\"output\"),\n at_ms: Schema.Number,\n data: Schema.String,\n})\nexport interface Output extends Schema.Schema.Type<typeof Output> {}\n\nexport const Resize = Schema.Struct({\n type: Schema.Literal(\"resize\"),\n at_ms: Schema.Number,\n cols: Schema.Number,\n rows: Schema.Number,\n})\nexport interface Resize extends Schema.Schema.Type<typeof Resize> {}\n\nexport const Event = Schema.Union([Header, Output, Resize])\nexport type Event = Schema.Schema.Type<typeof Event>\n\nexport class Timeline extends Writable {\n readonly isTTY = true\n readonly path: string\n readonly columns: number\n readonly rows: number\n private readonly output: WriteStream\n private readonly started = performance.now()\n private readonly timestamps: number[] = []\n private done?: Promise<string>\n\n private constructor(path: string, cols: number, rows: number, output: WriteStream) {\n super()\n this.path = path\n this.columns = cols\n this.rows = rows\n this.output = output\n // finish() reports stream failures; keep Writable from also throwing them process-wide.\n this.on(\"error\", () => {})\n output.on(\"error\", (error) => this.destroy(error))\n }\n\n static async create(path: string, cols: number, rows: number) {\n await mkdir(dirname(path), { recursive: true })\n const output = createWriteStream(path)\n const timeline = new Timeline(path, cols, rows, output)\n await new Promise<void>((resolve, reject) => {\n output.write(\n `${JSON.stringify({ type: \"header\", version: 1, cols, rows, encoding: \"base64\" } satisfies Header)}\\n`,\n (error) => (error ? reject(error) : resolve()),\n )\n })\n return timeline\n }\n\n getColorDepth() {\n return 24\n }\n\n override write(chunk: unknown, callback?: (error?: Error | null) => void): boolean\n override write(chunk: unknown, encoding: BufferEncoding, callback?: (error?: Error | null) => void): boolean\n override write(\n chunk: unknown,\n encoding?: BufferEncoding | ((error?: Error | null) => void),\n callback?: (error?: Error | null) => void,\n ) {\n if (!this.writableEnded) {\n this.timestamps.push(this.elapsed())\n if (typeof encoding === \"function\") return super.write(chunk, encoding)\n if (encoding === undefined) return super.write(chunk, callback)\n return super.write(chunk, encoding, callback)\n }\n const done = typeof encoding === \"function\" ? encoding : callback\n queueMicrotask(() => done?.(null))\n return true\n }\n\n override _write(chunk: Buffer, _encoding: BufferEncoding, callback: (error?: Error | null) => void) {\n this.writeOutput(chunk, this.timestamps.shift() ?? this.elapsed(), callback)\n }\n\n override _final(callback: (error?: Error | null) => void) {\n this.writeOutput(Buffer.alloc(0), this.elapsed(), (error) => {\n if (error) return callback(error)\n this.output.end(callback)\n })\n }\n\n finish() {\n if (this.done) return this.done\n this.end()\n this.done = finished(this).then(() => this.path)\n return this.done\n }\n\n resize(cols: number, rows: number) {\n if (this.writableEnded) return\n const event = { type: \"resize\", at_ms: this.elapsed(), cols, rows } satisfies Resize\n this.output.write(`${JSON.stringify(event)}\\n`)\n }\n\n private elapsed() {\n return Math.max(0, Math.round(performance.now() - this.started))\n }\n\n private writeOutput(data: Buffer, at_ms: number, callback: (error?: Error | null) => void) {\n const event = {\n type: \"output\",\n at_ms,\n data: data.toString(\"base64\"),\n } satisfies Output\n this.output.write(`${JSON.stringify(event)}\\n`, callback)\n }\n}\n\nexport * as SimulationRecording from \"./recording\"\n", | ||
| "import type { CliRenderer, CliRendererConfig } from \"@opentui/core\"\nimport { createTestRenderer, type TestRendererSetup } from \"@opentui/core/testing\"\nimport { Effect } from \"effect\"\nimport { Timeline } from \"../recording\"\n\nconst setups = new WeakMap<CliRenderer, TestRendererSetup>()\nconst recordings = new WeakMap<CliRenderer, Timeline>()\n\n/**\n * Creates a headless renderer with optional recording: a real CliRenderer\n * backed by an in-memory screen buffer. The TestRendererSetup is kept\n * module-side so the harness can use supported testing APIs without app\n * code carrying it around.\n */\nexport interface Viewport {\n readonly cols: number\n readonly rows: number\n}\n\nexport const create = Effect.fn(\"SimulationRenderer.create\")(function* (\n options: CliRendererConfig,\n path?: string,\n viewport?: Viewport,\n) {\n const cols = viewport?.cols ?? 100\n const rows = viewport?.rows ?? 40\n const recording = path\n ? yield* Effect.acquireRelease(\n Effect.tryPromise(() => Timeline.create(path, cols, rows)),\n (recording) =>\n Effect.tryPromise(() => recording.finish()).pipe(\n Effect.catch((error) =>\n Effect.sync(() => process.stderr.write(`Failed to finish UI recording: ${error}\\n`)),\n ),\n ),\n )\n : undefined\n const setup = yield* Effect.acquireRelease(\n Effect.tryPromise(() =>\n createTestRenderer({\n ...options,\n width: cols,\n height: rows,\n ...(recording\n ? {\n stdout: recording as unknown as NodeJS.WriteStream,\n bufferedOutput: \"stdout\" as const,\n }\n : {}),\n }),\n ),\n (setup) =>\n Effect.sync(() => {\n if (!setup.renderer.isDestroyed) setup.renderer.destroy()\n }),\n )\n setups.set(setup.renderer, setup)\n if (recording) recordings.set(setup.renderer, recording)\n return setup.renderer\n})\n\nexport function recordResize(renderer: CliRenderer, cols: number, rows: number) {\n recordings.get(renderer)?.resize(cols, rows)\n}\n\nexport function setupFor(renderer: CliRenderer): TestRendererSetup | undefined {\n return setups.get(renderer)\n}\n\nexport function finish(renderer: CliRenderer) {\n const recording = recordings.get(renderer)\n if (!recording) return Effect.fail(new Error(\"UI recording is not available\"))\n return Effect.tryPromise(() => recording.finish())\n}\n\nexport * as SimulationRenderer from \"./renderer\"\n", | ||
| "import type { Renderable } from \"@opentui/core\"\nimport type { SimulationProtocol } from \"../protocol\"\n\n// Semantic renderables set an explicit stable OpenTUI id so ui.state and\n// ui.snapshot expose the same identity. Hierarchy and element handles come\n// from the live render tree.\nexport type Definition = Omit<SimulationProtocol.Frontend.SemanticNode, \"id\" | \"element\" | \"parent\">\n\nconst key = Symbol.for(\"opencode.simulation.semantics\")\n\nconst bind = (definition: () => Definition) => (renderable: Renderable) => {\n Object.defineProperty(renderable, key, { value: definition, configurable: true })\n}\n\nexport const read = (renderable: Renderable) => {\n const definition: unknown = Reflect.get(renderable, key)\n return typeof definition === \"function\" ? (definition as () => Definition) : undefined\n}\n\nexport const SimulationSemantics = { bind, read }\n", | ||
| "import { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Effect } from \"effect\"\nimport { SimulationControlServer } from \"../control-server\"\nimport { SimulationProtocol } from \"../protocol\"\nimport { SimulationActions, type Harness } from \"./actions\"\nimport { SimulationRenderer } from \"./renderer\"\n\nfunction handle(harness: Harness, request: SimulationProtocol.Frontend.Request) {\n switch (request.method) {\n case \"simulation.handshake\":\n return SimulationProtocol.Handshake.dispatch(\n {\n role: \"ui\",\n server: { name: \"opencode\", version: InstallationVersion },\n capabilities: SimulationProtocol.Frontend.Capabilities,\n },\n request.params,\n )\n case \"ui.capture\":\n return SimulationActions.capture(harness)\n case \"ui.screenshot\":\n return SimulationActions.screenshot(harness, request.params?.name)\n case \"ui.state\":\n return Effect.sync(() => SimulationActions.state(harness))\n case \"ui.snapshot\":\n return Effect.sync(() => SimulationActions.snapshot(harness))\n case \"ui.matches\":\n return Effect.sync(() => SimulationActions.matches(harness, request.params.text))\n case \"ui.recording.finish\":\n return SimulationRenderer.finish(harness.renderer)\n case \"ui.type\":\n return SimulationActions.execute(harness, { type: \"ui.type\", text: request.params.text })\n case \"ui.enter\":\n return SimulationActions.execute(harness, { type: \"ui.enter\" })\n case \"ui.press\":\n return SimulationActions.execute(harness, {\n type: \"ui.press\",\n key: request.params.key,\n modifiers: request.params.modifiers,\n })\n case \"ui.arrow\":\n return SimulationActions.execute(harness, { type: \"ui.arrow\", direction: request.params.direction })\n case \"ui.focus\":\n return SimulationActions.execute(harness, { type: \"ui.focus\", target: request.params.target })\n case \"ui.click\":\n return SimulationActions.execute(harness, {\n type: \"ui.click\",\n target: request.params.target,\n x: request.params.x,\n y: request.params.y,\n semantic: request.params.semantic,\n })\n case \"ui.resize\":\n return SimulationActions.execute(harness, {\n type: \"ui.resize\",\n cols: request.params.cols,\n rows: request.params.rows,\n })\n }\n}\n\nexport const start = Effect.fn(\"SimulationServer.start\")(function* (harness: Harness, endpoint: string) {\n return yield* SimulationControlServer.start({\n endpoint,\n label: \"opencode drive ui websocket\",\n data: () => ({ drive: true as const }),\n decode: SimulationProtocol.Frontend.decodeRequestEffect,\n handle: (_socket, request) => handle(harness, request),\n })\n})\n\nexport * as SimulationServer from \"./server\"\n", | ||
| "import { createCliRenderer, type CliRendererConfig } from \"@opentui/core\"\nimport { Config, Effect } from \"effect\"\nimport { DriveManifest } from \"../manifest\"\nimport { SimulationActions } from \"./actions\"\nimport { SimulationRenderer } from \"./renderer\"\nimport { SimulationServer } from \"./server\"\n\n/** Drive-mode renderer and control-server acquisition. */\nexport const create = Effect.fn(\"Drive.create\")(function* (options: CliRendererConfig) {\n const headless = (yield* Config.string(\"OPENCODE_DRIVE_RENDERER\").pipe(Config.withDefault(\"visible\"))) === \"headless\"\n const manifest = yield* DriveManifest.resolve()\n const renderer = headless\n ? yield* SimulationRenderer.create(options, manifest.recording?.timeline, manifest.viewport)\n : yield* Effect.acquireRelease(\n Effect.tryPromise(() => createCliRenderer(options)),\n (renderer) =>\n Effect.sync(() => {\n if (!renderer.isDestroyed) renderer.destroy()\n }),\n )\n if (!headless && manifest.viewport) renderer.resize(manifest.viewport.cols, manifest.viewport.rows)\n const server = yield* SimulationServer.start(SimulationActions.createHarness(renderer), manifest.endpoints.ui)\n yield* Effect.sync(() => process.stderr.write(`opencode drive ui websocket: ${server.url}\\n`))\n return renderer\n})\n\nexport * as Drive from \"./simulation\"\n" | ||
| ], | ||
| "mappings": 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| ||
| "debugId": "CC64734843CBF5CE64756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/auth/connect.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type IntegrationCommandStatusOutput, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.auth.commands.connect,\n Effect.fn(\"cli.auth.connect\")(function* (input) {\n process.stdout.write(\"Connecting...\" + EOL + EOL)\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n yield* request(() => client.integration.wellknown.add({ url: input.url, location }))\n const integrationID = input.url.replace(/\\/+$/, \"\")\n const started = yield* request(() =>\n client.integration.command.connect({ integrationID, methodID: \"login\", location }),\n )\n yield* Effect.addFinalizer(() =>\n request(() =>\n client.integration.command.cancel({ integrationID, attemptID: started.data.attemptID, location }),\n ).pipe(Effect.ignore),\n )\n\n const status = yield* wait(client, integrationID, started.data.attemptID)\n if (status.status === \"failed\") return yield* Effect.fail(new Error(status.message))\n if (status.status === \"expired\") return yield* Effect.fail(new Error(\"Authentication expired\"))\n process.stdout.write(\"Connected\" + EOL)\n }),\n)\n\nconst wait = (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n shown = false,\n): Effect.Effect<Exclude<IntegrationCommandStatusOutput[\"data\"], { status: \"pending\" }>, unknown> =>\n Effect.gen(function* () {\n const response = yield* request(() => client.integration.command.status({ integrationID, attemptID, location }))\n if (response.data.status !== \"pending\") return response.data\n const output = response.data.message?.trim()\n if (!shown && output) process.stdout.write(output + EOL + EOL)\n yield* Effect.sleep(500)\n return yield* wait(client, integrationID, attemptID, shown || !!output)\n })\n\nfunction request<A>(task: () => Promise<A>) {\n return Effect.tryPromise({ try: task, catch: (cause) => cause })\n}\n" | ||
| ], | ||
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| "debugId": "589492F6965D34DC64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/plugin/list.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.plugin.commands.list,\n Effect.fn(\"cli.plugin.list\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.plugin.list({ location: { directory: process.cwd() } }))\n const plugins = response.data.toSorted((a, b) => a.id.localeCompare(b.id))\n if (plugins.length === 0) {\n process.stdout.write(\"No plugins loaded\" + EOL)\n return\n }\n process.stdout.write(plugins.map((plugin) => plugin.id).join(EOL) + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "9FA00D09A102DFA664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/anthropic-messages.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type CacheHint,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ProviderMetadata,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n type ToolResultPart,\n} from \"../schema\"\nimport { JsonObject, optionalArray, optionalNull, ProviderShared } from \"./shared\"\nimport { classifyProviderFailure } from \"../provider-error\"\nimport * as Cache from \"./utils/cache\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"anthropic-messages\"\nexport const DEFAULT_BASE_URL = \"https://api.anthropic.com/v1\"\nexport const PATH = \"/messages\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst AnthropicCacheControl = Schema.Struct({\n type: Schema.tag(\"ephemeral\"),\n ttl: Schema.optional(Schema.Literals([\"5m\", \"1h\"])),\n})\n\nconst AnthropicTextBlock = Schema.Struct({\n type: Schema.tag(\"text\"),\n text: Schema.String,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicTextBlock = Schema.Schema.Type<typeof AnthropicTextBlock>\n\nconst AnthropicImageBlock = Schema.Struct({\n type: Schema.tag(\"image\"),\n source: Schema.Struct({\n type: Schema.tag(\"base64\"),\n media_type: Schema.String,\n data: Schema.String,\n }),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicImageBlock = Schema.Schema.Type<typeof AnthropicImageBlock>\n\nconst AnthropicThinkingBlock = Schema.Struct({\n type: Schema.tag(\"thinking\"),\n thinking: Schema.String,\n signature: Schema.optional(Schema.String),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\n\nconst AnthropicToolUseBlock = Schema.Struct({\n type: Schema.tag(\"tool_use\"),\n id: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicToolUseBlock = Schema.Schema.Type<typeof AnthropicToolUseBlock>\n\nconst AnthropicServerToolUseBlock = Schema.Struct({\n type: Schema.tag(\"server_tool_use\"),\n id: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicServerToolUseBlock = Schema.Schema.Type<typeof AnthropicServerToolUseBlock>\n\n// Server tool result blocks: web_search_tool_result, code_execution_tool_result,\n// and web_fetch_tool_result. The provider executes the tool and inlines the\n// structured result into the assistant turn — there is no client tool_result\n// round-trip. We round-trip the structured `content` payload as opaque JSON so\n// the next request can echo it back when continuing the conversation.\nconst AnthropicServerToolResultType = Schema.Literals([\n \"web_search_tool_result\",\n \"code_execution_tool_result\",\n \"web_fetch_tool_result\",\n])\ntype AnthropicServerToolResultType = Schema.Schema.Type<typeof AnthropicServerToolResultType>\n\nconst AnthropicServerToolResultBlock = Schema.Struct({\n type: AnthropicServerToolResultType,\n tool_use_id: Schema.String,\n content: Schema.Unknown,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicServerToolResultBlock = Schema.Schema.Type<typeof AnthropicServerToolResultBlock>\n\n// Anthropic accepts either a plain string or an ordered array of text/image\n// blocks inside `tool_result.content`. The array form is required when a tool\n// returns image bytes (screenshot, image search, etc.) so they can be passed\n// to the model as proper image inputs instead of being JSON-stringified into\n// the prompt — which silently inflates context by megabytes and can push the\n// conversation over the model's token limit.\nconst AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock])\n\nconst AnthropicToolResultBlock = Schema.Struct({\n type: Schema.tag(\"tool_result\"),\n tool_use_id: Schema.String,\n content: Schema.Union([Schema.String, Schema.Array(AnthropicToolResultContent)]),\n is_error: Schema.optional(Schema.Boolean),\n cache_control: Schema.optional(AnthropicCacheControl),\n})\n\nconst AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicToolResultBlock])\ntype AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>\nconst AnthropicAssistantBlock = Schema.Union([\n AnthropicTextBlock,\n AnthropicThinkingBlock,\n AnthropicToolUseBlock,\n AnthropicServerToolUseBlock,\n AnthropicServerToolResultBlock,\n])\ntype AnthropicAssistantBlock = Schema.Schema.Type<typeof AnthropicAssistantBlock>\ntype AnthropicToolResultBlock = Schema.Schema.Type<typeof AnthropicToolResultBlock>\n\nconst AnthropicMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"user\"), content: Schema.Array(AnthropicUserBlock) }),\n Schema.Struct({ role: Schema.Literal(\"assistant\"), content: Schema.Array(AnthropicAssistantBlock) }),\n Schema.Struct({ role: Schema.Literal(\"system\"), content: Schema.Array(AnthropicTextBlock) }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype AnthropicMessage = Schema.Schema.Type<typeof AnthropicMessage>\n\nconst AnthropicTool = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n input_schema: JsonObject,\n cache_control: Schema.optional(AnthropicCacheControl),\n})\ntype AnthropicTool = Schema.Schema.Type<typeof AnthropicTool>\n\nconst AnthropicToolChoice = Schema.Union([\n Schema.Struct({ type: Schema.Literals([\"auto\", \"any\"]) }),\n Schema.Struct({ type: Schema.tag(\"tool\"), name: Schema.String }),\n])\n\nconst AnthropicThinking = Schema.Union([\n Schema.Struct({\n type: Schema.tag(\"enabled\"),\n budget_tokens: Schema.Number,\n }),\n Schema.Struct({\n type: Schema.tag(\"adaptive\"),\n display: Schema.optional(Schema.Literals([\"summarized\", \"omitted\"])),\n }),\n Schema.Struct({\n type: Schema.tag(\"disabled\"),\n }),\n])\n\nconst AnthropicOutputConfig = Schema.Struct({\n effort: Schema.optional(Schema.String),\n})\n\nconst AnthropicBodyFields = {\n model: Schema.String,\n system: optionalArray(AnthropicTextBlock),\n messages: Schema.Array(AnthropicMessage),\n tools: optionalArray(AnthropicTool),\n tool_choice: Schema.optional(AnthropicToolChoice),\n stream: Schema.Literal(true),\n max_tokens: Schema.Number,\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n top_k: Schema.optional(Schema.Number),\n stop_sequences: optionalArray(Schema.String),\n thinking: Schema.optional(AnthropicThinking),\n output_config: Schema.optional(AnthropicOutputConfig),\n}\nexport const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)\nexport type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>\n\nconst AnthropicUsage = Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n output_tokens: Schema.optional(Schema.Number),\n cache_creation_input_tokens: optionalNull(Schema.Number),\n cache_read_input_tokens: optionalNull(Schema.Number),\n})\ntype AnthropicUsage = Schema.Schema.Type<typeof AnthropicUsage>\n\nconst AnthropicStreamBlock = Schema.Struct({\n type: Schema.String,\n id: Schema.optional(Schema.String),\n name: Schema.optional(Schema.String),\n text: Schema.optional(Schema.String),\n thinking: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n input: Schema.optional(Schema.Unknown),\n // *_tool_result blocks arrive whole as content_block_start (no streaming\n // delta) with the structured payload in `content` and the originating\n // server_tool_use id in `tool_use_id`.\n tool_use_id: Schema.optional(Schema.String),\n content: Schema.optional(Schema.Unknown),\n})\n\nconst AnthropicStreamDelta = Schema.Struct({\n type: Schema.optional(Schema.String),\n text: Schema.optional(Schema.String),\n thinking: Schema.optional(Schema.String),\n partial_json: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n stop_reason: optionalNull(Schema.String),\n stop_sequence: optionalNull(Schema.String),\n})\n\nconst AnthropicEvent = Schema.Struct({\n type: Schema.String,\n index: Schema.optional(Schema.Number),\n message: Schema.optional(Schema.Struct({ usage: Schema.optional(AnthropicUsage) })),\n content_block: Schema.optional(AnthropicStreamBlock),\n delta: Schema.optional(AnthropicStreamDelta),\n usage: Schema.optional(AnthropicUsage),\n // `type` and `message` are both required per Anthropic's spec, but\n // OpenAI-compatible proxies and gateway translations occasionally drop one\n // or the other; mark them optional so a partial payload still parses and\n // the parser can fall back to whichever field is populated.\n error: Schema.optional(\n Schema.Struct({ type: Schema.optional(Schema.String), message: Schema.optional(Schema.String) }),\n ),\n})\ntype AnthropicEvent = Schema.Schema.Type<typeof AnthropicEvent>\n\ninterface ParserState {\n readonly tools: ToolStream.State<number>\n readonly usage?: Usage\n readonly lifecycle: Lifecycle.State\n}\n\nconst invalid = ProviderShared.invalidRequest\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\n// Anthropic accepts at most 4 explicit cache_control breakpoints per request,\n// across `tools`, `system`, and `messages`. Beyond the cap the API returns a\n// 400 — so the lowering layer counts emitted markers and silently drops any\n// that exceed it.\nconst ANTHROPIC_BREAKPOINT_CAP = 4\n\nconst EPHEMERAL_5M = { type: \"ephemeral\" as const }\nconst EPHEMERAL_1H = { type: \"ephemeral\" as const, ttl: \"1h\" as const }\n\nconst cacheControl = (breakpoints: Cache.Breakpoints, cache: CacheHint | undefined) => {\n if (cache?.type !== \"ephemeral\" && cache?.type !== \"persistent\") return undefined\n if (breakpoints.remaining <= 0) {\n breakpoints.dropped += 1\n return undefined\n }\n breakpoints.remaining -= 1\n return Cache.ttlBucket(cache.ttlSeconds) === \"1h\" ? EPHEMERAL_1H : EPHEMERAL_5M\n}\n\nconst anthropicMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ anthropic: metadata })\n\nconst signatureFromMetadata = (metadata: ProviderMetadata | undefined): string | undefined => {\n const anthropic = metadata?.anthropic\n if (!ProviderShared.isRecord(anthropic)) return undefined\n return typeof anthropic.signature === \"string\" ? anthropic.signature : undefined\n}\n\nconst lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({\n name: tool.name,\n description: tool.description,\n input_schema: inputSchema,\n cache_control: cacheControl(breakpoints, tool.cache),\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Anthropic Messages\", toolChoice, {\n auto: () => ({ type: \"auto\" as const }),\n none: () => undefined,\n required: () => ({ type: \"any\" as const }),\n tool: (name) => ({ type: \"tool\" as const, name }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): AnthropicToolUseBlock => ({\n type: \"tool_use\",\n id: part.id,\n name: part.name,\n input: part.input,\n})\n\nconst lowerServerToolCall = (part: ToolCallPart): AnthropicServerToolUseBlock => ({\n type: \"server_tool_use\",\n id: part.id,\n name: part.name,\n input: part.input,\n})\n\n// Server tool result blocks are typed by name. Anthropic ships three today;\n// extend this list when new server tools land. The block content is the\n// structured payload returned by the provider, which we round-trip as-is.\nconst serverToolResultType = (name: string): AnthropicServerToolResultType | undefined => {\n if (name === \"web_search\") return \"web_search_tool_result\"\n if (name === \"code_execution\") return \"code_execution_tool_result\"\n if (name === \"web_fetch\") return \"web_fetch_tool_result\"\n return undefined\n}\n\nconst lowerServerToolResult = Effect.fn(\"AnthropicMessages.lowerServerToolResult\")(function* (part: ToolResultPart) {\n const wireType = serverToolResultType(part.name)\n if (!wireType)\n return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)\n return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock\n})\n\nconst lowerImage = Effect.fn(\"AnthropicMessages.lowerImage\")(function* (part: MediaPart) {\n const media = yield* ProviderShared.validateMedia(\n \"Anthropic Messages\",\n part,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return {\n type: \"image\" as const,\n source: {\n type: \"base64\" as const,\n media_type: media.mime,\n data: media.base64,\n },\n } satisfies AnthropicImageBlock\n})\n\n// Tool results may carry structured text/images. Keep media as provider-native\n// content instead of JSON-stringifying base64 into a prompt string.\nconst lowerToolResultContentItem = Effect.fn(\"AnthropicMessages.lowerToolResultContentItem\")(function* (\n item: ToolContent,\n) {\n if (item.type === \"text\") return { type: \"text\" as const, text: item.text } satisfies AnthropicTextBlock\n const media = yield* ProviderShared.validateToolFile(\n \"Anthropic Messages\",\n item,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return {\n type: \"image\" as const,\n source: {\n type: \"base64\" as const,\n media_type: media.mime,\n data: media.base64,\n },\n } satisfies AnthropicImageBlock\n})\n\nconst lowerToolResultContent = Effect.fn(\"AnthropicMessages.lowerToolResultContent\")(function* (part: ToolResultPart) {\n // Text / json / error results stay as a string for backward compatibility\n // with existing cassettes and provider expectations.\n if (part.result.type !== \"content\") return ProviderShared.toolResultText(part)\n // Preserve the narrowed array element type when compiled through a consumer package.\n const content: ReadonlyArray<ToolContent> = part.result.value\n return yield* Effect.forEach(content, lowerToolResultContentItem)\n})\n\n// Mid-conversation system messages are a native Claude API feature only for\n// Opus 4.8. Other Anthropic models intentionally use the same visible wrapped-\n// user fallback as non-Anthropic routes rather than sending a role they reject.\nconst supportsNativeSystemUpdates = (request: LLMRequest) => String(request.model.id) === \"claude-opus-4-8\"\n\nconst endsInServerToolUse = (message: LLMRequest[\"messages\"][number]) => {\n const last = message.content.at(-1)\n return message.role === \"assistant\" && last?.type === \"tool-call\" && last.providerExecuted === true\n}\n\nconst canUseNativeSystemUpdate = (messages: LLMRequest[\"messages\"], index: number) => {\n const previous = messages[index - 1]\n const next = messages[index + 1]\n return (\n previous !== undefined &&\n previous.role !== \"system\" &&\n (previous.role === \"user\" || previous.role === \"tool\" || endsInServerToolUse(previous)) &&\n next?.role !== \"system\" &&\n (next === undefined || next.role === \"assistant\")\n )\n}\n\nconst splitsLocalToolResults = (messages: LLMRequest[\"messages\"], index: number) => {\n const pending = new Set<string>()\n for (const message of messages.slice(0, index)) {\n for (const part of message.content) {\n if (message.role === \"assistant\" && part.type === \"tool-call\" && part.providerExecuted !== true)\n pending.add(part.id)\n if (message.role === \"tool\" && part.type === \"tool-result\") pending.delete(part.id)\n }\n }\n return pending.size > 0\n}\n\nconst lowerNativeSystemUpdate = Effect.fn(\"AnthropicMessages.lowerNativeSystemUpdate\")(function* (\n message: LLMRequest[\"messages\"][number],\n breakpoints: Cache.Breakpoints,\n) {\n const content = yield* ProviderShared.systemUpdateText(\"Anthropic Messages\", message)\n return {\n role: \"system\" as const,\n content: content.map((part) => ({\n type: \"text\" as const,\n text: part.text,\n cache_control: cacheControl(breakpoints, part.cache),\n })),\n }\n})\n\nconst lowerMessages = Effect.fn(\"AnthropicMessages.lowerMessages\")(function* (\n request: LLMRequest,\n breakpoints: Cache.Breakpoints,\n) {\n const messages: AnthropicMessage[] = []\n\n for (const [index, message] of request.messages.entries()) {\n if (message.role === \"system\") {\n if (splitsLocalToolResults(request.messages, index))\n return yield* invalid(\"Anthropic Messages system updates cannot split a local tool call from its tool result\")\n if (supportsNativeSystemUpdates(request) && canUseNativeSystemUpdate(request.messages, index)) {\n messages.push(yield* lowerNativeSystemUpdate(message, breakpoints))\n continue\n }\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Anthropic Messages\", message)\n const block = { type: \"text\" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }\n const previous = messages.at(-1)\n if (previous?.role === \"user\")\n messages[messages.length - 1] = { role: \"user\", content: [...previous.content, block] }\n else messages.push({ role: \"user\", content: [block] })\n continue\n }\n\n if (message.role === \"user\") {\n const content: AnthropicUserBlock[] = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* lowerImage(part))\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"Anthropic Messages\", \"user\", [\"text\", \"media\"])\n }\n messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: AnthropicAssistantBlock[] = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })\n continue\n }\n if (part.type === \"reasoning\") {\n content.push({\n type: \"thinking\",\n thinking: part.text,\n signature: part.encrypted ?? signatureFromMetadata(part.providerMetadata),\n })\n continue\n }\n if (part.type === \"tool-call\") {\n content.push(part.providerExecuted ? lowerServerToolCall(part) : lowerToolCall(part))\n continue\n }\n if (part.type === \"tool-result\" && part.providerExecuted) {\n content.push(yield* lowerServerToolResult(part))\n continue\n }\n return yield* invalid(\n `Anthropic Messages assistant messages only support text, reasoning, and tool-call content for now`,\n )\n }\n messages.push({ role: \"assistant\", content })\n continue\n }\n\n const content: AnthropicToolResultBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Anthropic Messages\", \"tool\", [\"tool-result\"])\n content.push({\n type: \"tool_result\",\n tool_use_id: part.id,\n content: yield* lowerToolResultContent(part),\n is_error: part.result.type === \"error\" ? true : undefined,\n cache_control: cacheControl(breakpoints, part.cache),\n })\n }\n messages.push({ role: \"user\", content })\n }\n\n return messages\n})\n\nconst anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthropic\n\nconst lowerThinking = Effect.fn(\"AnthropicMessages.lowerThinking\")(function* (request: LLMRequest) {\n const thinking = anthropicOptions(request)?.thinking\n if (!ProviderShared.isRecord(thinking)) return undefined\n if (thinking.type === \"adaptive\") {\n const display =\n thinking.display === \"summarized\"\n ? (\"summarized\" as const)\n : thinking.display === \"omitted\"\n ? (\"omitted\" as const)\n : undefined\n return { type: \"adaptive\" as const, ...(display === undefined ? {} : { display }) }\n }\n if (thinking.type === \"disabled\") return { type: \"disabled\" as const }\n if (thinking.type !== \"enabled\") return undefined\n const budget =\n typeof thinking.budgetTokens === \"number\"\n ? thinking.budgetTokens\n : typeof thinking.budget_tokens === \"number\"\n ? thinking.budget_tokens\n : undefined\n if (budget === undefined) return yield* invalid(\"Anthropic thinking provider option requires budgetTokens\")\n return { type: \"enabled\" as const, budget_tokens: budget }\n})\n\nconst outputConfig = (request: LLMRequest) => {\n const effort = anthropicOptions(request)?.effort\n return typeof effort === \"string\" ? { effort } : undefined\n}\n\nconst fromRequest = Effect.fn(\"AnthropicMessages.fromRequest\")(function* (request: LLMRequest) {\n const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096\n // Allocate the 4-breakpoint budget in invalidation order: tools → system →\n // messages. Tools live highest in the cache hierarchy, so when callers\n // over-mark we keep their tool hints and shed the message-tail ones first.\n const breakpoints = Cache.newBreakpoints(ANTHROPIC_BREAKPOINT_CAP)\n const tools =\n request.tools.length === 0 || request.toolChoice?.type === \"none\"\n ? undefined\n : request.tools.map((tool) =>\n lowerTool(\n breakpoints,\n tool,\n ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),\n ),\n )\n const system =\n request.system.length === 0\n ? undefined\n : request.system.map((part) => ({\n type: \"text\" as const,\n text: part.text,\n cache_control: cacheControl(breakpoints, part.cache),\n }))\n const messages = yield* lowerMessages(request, breakpoints)\n if (breakpoints.dropped > 0) {\n yield* Effect.logWarning(\n `Anthropic Messages: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${ANTHROPIC_BREAKPOINT_CAP} per request.`,\n )\n }\n return {\n model: request.model.id,\n system,\n messages,\n tools,\n tool_choice: toolChoice,\n stream: true as const,\n max_tokens: generation?.maxTokens ?? outputLimit,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n top_k: generation?.topK,\n stop_sequences: generation?.stop,\n thinking: yield* lowerThinking(request),\n output_config: outputConfig(request),\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\nconst mapFinishReason = (reason: string | null | undefined): FinishReason => {\n if (reason === \"end_turn\" || reason === \"stop_sequence\" || reason === \"pause_turn\") return \"stop\"\n if (reason === \"max_tokens\") return \"length\"\n if (reason === \"tool_use\") return \"tool-calls\"\n if (reason === \"refusal\") return \"content-filter\"\n return \"unknown\"\n}\n\n// Anthropic reports the non-overlapping breakdown natively — its\n// `input_tokens` is the *non-cached* count per the Messages API docs, with\n// cache reads and writes as separate fields. We sum them to derive the\n// inclusive `inputTokens` the rest of the contract expects. Extended\n// thinking tokens are *not* broken out by Anthropic — they're billed as\n// part of `output_tokens`, so `reasoningTokens` stays `undefined` and\n// `outputTokens` carries the combined total.\nconst mapUsage = (usage: AnthropicUsage | undefined): Usage | undefined => {\n if (!usage) return undefined\n const nonCached = usage.input_tokens\n const cacheRead = usage.cache_read_input_tokens ?? undefined\n const cacheWrite = usage.cache_creation_input_tokens ?? undefined\n const inputTokens = ProviderShared.sumTokens(nonCached, cacheRead, cacheWrite)\n return new Usage({\n inputTokens,\n outputTokens: usage.output_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cacheRead,\n cacheWriteInputTokens: cacheWrite,\n totalTokens: ProviderShared.totalTokens(inputTokens, usage.output_tokens, undefined),\n providerMetadata: { anthropic: usage },\n })\n}\n\n// Anthropic emits usage on `message_start` and again on `message_delta` — the\n// final delta carries the authoritative totals. Right-biased merge: each\n// field prefers `right` when defined, falls back to `left`. `inputTokens` is\n// recomputed from the merged breakdown so the inclusive total stays\n// consistent with `nonCached + cacheRead + cacheWrite`.\nconst mergeUsage = (left: Usage | undefined, right: Usage | undefined) => {\n if (!left) return right\n if (!right) return left\n const nonCachedInputTokens = right.nonCachedInputTokens ?? left.nonCachedInputTokens\n const cacheReadInputTokens = right.cacheReadInputTokens ?? left.cacheReadInputTokens\n const cacheWriteInputTokens = right.cacheWriteInputTokens ?? left.cacheWriteInputTokens\n const inputTokens = ProviderShared.sumTokens(nonCachedInputTokens, cacheReadInputTokens, cacheWriteInputTokens)\n const outputTokens = right.outputTokens ?? left.outputTokens\n return new Usage({\n inputTokens,\n outputTokens,\n nonCachedInputTokens,\n cacheReadInputTokens,\n cacheWriteInputTokens,\n totalTokens: ProviderShared.totalTokens(inputTokens, outputTokens, undefined),\n providerMetadata: {\n anthropic: {\n ...left.providerMetadata?.[\"anthropic\"],\n ...right.providerMetadata?.[\"anthropic\"],\n },\n },\n })\n}\n\n// Server tool result blocks come whole in `content_block_start` (no streaming\n// delta sequence). We convert the payload to a `tool-result` event with\n// `providerExecuted: true`. The runtime appends it to the assistant message\n// for round-trip; downstream consumers can inspect `result.value` for the\n// structured payload.\nconst SERVER_TOOL_RESULT_NAMES: Record<AnthropicServerToolResultType, string> = {\n web_search_tool_result: \"web_search\",\n code_execution_tool_result: \"code_execution\",\n web_fetch_tool_result: \"web_fetch\",\n}\n\nconst isServerToolResultType = (type: string): type is AnthropicServerToolResultType => type in SERVER_TOOL_RESULT_NAMES\n\nconst serverToolResultEvent = (block: NonNullable<AnthropicEvent[\"content_block\"]>): LLMEvent | undefined => {\n if (!block.type || !isServerToolResultType(block.type)) return undefined\n const errorPayload =\n typeof block.content === \"object\" && block.content !== null && \"type\" in block.content\n ? String((block.content as Record<string, unknown>).type)\n : \"\"\n const isError = errorPayload.endsWith(\"_tool_result_error\")\n return LLMEvent.toolResult({\n id: block.tool_use_id ?? \"\",\n name: SERVER_TOOL_RESULT_NAMES[block.type],\n result: isError ? { type: \"error\", value: block.content } : { type: \"json\", value: block.content },\n providerExecuted: true,\n providerMetadata: anthropicMetadata({ blockType: block.type }),\n })\n}\n\ntype StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]\n\nconst NO_EVENTS: StepResult[\"1\"] = []\n\nconst onMessageStart = (state: ParserState, event: AnthropicEvent): StepResult => {\n const usage = mapUsage(event.message?.usage)\n return [usage ? { ...state, usage: mergeUsage(state.usage, usage) } : state, NO_EVENTS]\n}\n\nconst onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepResult => {\n const block = event.content_block\n if (!block) return [state, NO_EVENTS]\n\n if ((block.type === \"tool_use\" || block.type === \"server_tool_use\") && event.index !== undefined) {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n tools: ToolStream.start(state.tools, event.index, {\n id: block.id ?? String(event.index),\n name: block.name ?? \"\",\n providerExecuted: block.type === \"server_tool_use\",\n }),\n },\n [\n ...events,\n LLMEvent.toolInputStart({\n id: block.id ?? String(event.index),\n name: block.name ?? \"\",\n providerExecuted: block.type === \"server_tool_use\" ? true : undefined,\n }),\n ],\n ]\n }\n\n if (block.type === \"text\" && block.text) {\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, block.text) },\n events,\n ]\n }\n\n if (block.type === \"thinking\" && block.thinking) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, block.thinking),\n },\n events,\n ]\n }\n\n const result = serverToolResultEvent(block)\n if (!result) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, [...events, result]]\n}\n\nconst onContentBlockDelta = Effect.fn(\"AnthropicMessages.onContentBlockDelta\")(function* (\n state: ParserState,\n event: AnthropicEvent,\n) {\n const delta = event.delta\n\n if (delta?.type === \"text_delta\" && delta.text) {\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, `text-${event.index ?? 0}`, delta.text) },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"thinking_delta\" && delta.thinking) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${event.index ?? 0}`, delta.thinking),\n },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"signature_delta\" && delta.signature) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n `reasoning-${event.index ?? 0}`,\n anthropicMetadata({ signature: delta.signature }),\n ),\n },\n events,\n ] satisfies StepResult\n }\n\n if (delta?.type === \"input_json_delta\" && event.index !== undefined) {\n if (!delta.partial_json) return [state, NO_EVENTS] satisfies StepResult\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n event.index,\n delta.partial_json,\n \"Anthropic Messages tool argument delta is missing its tool call\",\n )\n if (ToolStream.isError(result)) return yield* result\n const events: LLMEvent[] = []\n const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...result.events)\n return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult\n }\n\n return [state, NO_EVENTS] satisfies StepResult\n})\n\nconst onContentBlockStop = Effect.fn(\"AnthropicMessages.onContentBlockStop\")(function* (\n state: ParserState,\n event: AnthropicEvent,\n) {\n if (event.index === undefined) return [state, NO_EVENTS] satisfies StepResult\n const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length\n ? Lifecycle.stepStart(state.lifecycle, events)\n : Lifecycle.reasoningEnd(\n Lifecycle.textEnd(state.lifecycle, events, `text-${event.index}`),\n events,\n `reasoning-${event.index}`,\n )\n events.push(...resultEvents)\n return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult\n})\n\nconst onMessageDelta = (state: ParserState, event: AnthropicEvent): StepResult => {\n const usage = mergeUsage(state.usage, mapUsage(event.usage))\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.finish(state.lifecycle, events, {\n reason: mapFinishReason(event.delta?.stop_reason),\n usage,\n providerMetadata: event.delta?.stop_sequence\n ? anthropicMetadata({ stopSequence: event.delta.stop_sequence })\n : undefined,\n })\n return [{ ...state, lifecycle, usage }, events]\n}\n\n// Prefix `error.type` so overloads, rate limits, and quota errors are visible\n// even when the provider message is generic or empty.\nconst providerErrorMessage = (event: AnthropicEvent): string => {\n const type = event.error?.type\n const message = event.error?.message\n if (type && message) return `${type}: ${message}`\n return message || type || \"Anthropic Messages stream error\"\n}\n\nconst onError = (event: AnthropicEvent) =>\n new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({ message: providerErrorMessage(event), code: event.error?.type }),\n })\n\nconst step = (state: ParserState, event: AnthropicEvent) => {\n if (event.type === \"message_start\") return Effect.succeed(onMessageStart(state, event))\n if (event.type === \"content_block_start\") return Effect.succeed(onContentBlockStart(state, event))\n if (event.type === \"content_block_delta\") return onContentBlockDelta(state, event)\n if (event.type === \"content_block_stop\") return onContentBlockStop(state, event)\n if (event.type === \"message_delta\") return Effect.succeed(onMessageDelta(state, event))\n if (event.type === \"error\") return onError(event)\n return Effect.succeed<StepResult>([state, NO_EVENTS])\n}\n\n// =============================================================================\n// Protocol And Anthropic Route\n// =============================================================================\n/**\n * The Anthropic Messages protocol — request body construction, body schema,\n * and the streaming-event state machine. Used by native Anthropic Cloud and\n * (once registered) Vertex Anthropic / Bedrock-hosted Anthropic passthrough.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: AnthropicMessagesBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(AnthropicEvent),\n initial: () => ({ tools: ToolStream.empty<number>(), lifecycle: Lifecycle.initial() }),\n step,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"anthropic\",\n providerMetadataKey: \"anthropic\",\n protocol,\n endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),\n auth: Auth.none,\n framing: Framing.sse,\n headers: () => ({ \"anthropic-version\": \"2023-06-01\" }),\n})\n\nexport * as AnthropicMessages from \"./anthropic-messages\"\n" | ||
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| ||
| "debugId": "6373C3B53F70A55D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/add.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport path from \"node:path\"\nimport { readFile, stat, writeFile } from \"node:fs/promises\"\nimport { Effect, Option } from \"effect\"\nimport { applyEdits, modify } from \"jsonc-parser\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.add,\n Effect.fn(\"cli.mcp.add\")(function* (input) {\n const url = Option.getOrUndefined(input.url)\n const headers = Option.getOrUndefined(input.header)\n const environment = Option.getOrUndefined(input.env)\n // The CLI framework strands `--` operands on the root command, so read the local server command\n // straight from argv after `--`. This also lets the command carry its own flags (e.g. `npx -y`).\n const dash = process.argv.indexOf(\"--\")\n const command = dash === -1 ? [...input.command] : process.argv.slice(dash + 1)\n\n const hasCommand = command.length > 0\n if (url && hasCommand)\n return yield* Effect.fail(new Error(\"Provide either --url <url> or a command after --, not both\"))\n if (!url && !hasCommand) return yield* Effect.fail(new Error(\"Provide either --url <url> or a command after --\"))\n if (url && !URL.canParse(url)) return yield* Effect.fail(new Error(`Invalid URL: ${url}`))\n if (url && environment) return yield* Effect.fail(new Error(\"--env is only valid for local MCP servers\"))\n if (hasCommand && headers) return yield* Effect.fail(new Error(\"--header is only valid for remote MCP servers\"))\n\n const server = url\n ? { type: \"remote\" as const, url, ...(headers ? { headers } : {}) }\n : { type: \"local\" as const, command, ...(environment ? { environment } : {}) }\n\n const configPath = yield* Effect.promise(() => resolveConfigPath(input.global ? Global.Path.config : process.cwd()))\n yield* Effect.promise(() => write(configPath, input.name, server))\n process.stdout.write(`MCP server \"${input.name}\" added to ${configPath}` + EOL)\n }),\n)\n\nexport async function resolveConfigPath(directory: string) {\n const candidates = [\n path.join(directory, \"opencode.json\"),\n path.join(directory, \"opencode.jsonc\"),\n path.join(directory, \".opencode\", \"opencode.json\"),\n path.join(directory, \".opencode\", \"opencode.jsonc\"),\n ]\n for (const candidate of candidates) {\n if (\n await stat(candidate).then(\n (info) => info.isFile(),\n () => false,\n )\n )\n return candidate\n }\n return candidates[0]\n}\n\nasync function write(configPath: string, name: string, server: unknown) {\n const text = await readFile(configPath, \"utf8\").catch((error) => {\n if (typeof error === \"object\" && error !== null && \"code\" in error && error.code === \"ENOENT\") return \"{}\"\n throw error\n })\n const edits = modify(text, [\"mcp\", \"servers\", name], server, {\n formattingOptions: { tabSize: 2, insertSpaces: true },\n })\n await writeFile(configPath, applyEdits(text, edits))\n}\n" | ||
| ], | ||
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| "debugId": "FA6D85F8E5CAAD8D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/lifecycle.ts", "../ai/src/protocols/utils/gemini-tool-schema.ts", "../ai/src/protocols/utils/tool-schema.ts"], | ||
| "sourcesContent": [ | ||
| "import { LLMEvent, type FinishReason, type ProviderMetadata, type Usage } from \"../../schema\"\n\nexport interface State {\n readonly stepStarted: boolean\n readonly text: ReadonlySet<string>\n readonly reasoning: ReadonlySet<string>\n}\n\nexport const initial = (): State => ({ stepStarted: false, text: new Set(), reasoning: new Set() })\n\nexport const stepStart = (state: State, events: LLMEvent[]): State => {\n if (state.stepStarted) return state\n events.push(LLMEvent.stepStart({ index: 0 }))\n return { ...state, stepStarted: true }\n}\n\nexport const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {\n const stepped = stepStart(state, events)\n if (stepped.text.has(id)) {\n events.push(LLMEvent.textDelta({ id, text }))\n return stepped\n }\n events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))\n return { ...stepped, text: new Set([...stepped.text, id]) }\n}\n\nexport const reasoningStart = (\n state: State,\n events: LLMEvent[],\n id: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n if (state.reasoning.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.reasoningStart({ id, providerMetadata }))\n return { ...stepped, reasoning: new Set([...stepped.reasoning, id]) }\n}\n\nexport const reasoningDelta = (\n state: State,\n events: LLMEvent[],\n id: string,\n text: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n const started = reasoningStart(state, events, id, providerMetadata)\n events.push(LLMEvent.reasoningDelta({ id, text }))\n return started\n}\n\nexport const reasoningEnd = (\n state: State,\n events: LLMEvent[],\n id: string,\n providerMetadata?: ProviderMetadata,\n): State => {\n if (!state.reasoning.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.reasoningEnd({ id, providerMetadata }))\n const reasoning = new Set(stepped.reasoning)\n reasoning.delete(id)\n return { ...stepped, reasoning }\n}\n\nexport const textEnd = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {\n if (!state.text.has(id)) return state\n const stepped = stepStart(state, events)\n events.push(LLMEvent.textEnd({ id, providerMetadata }))\n const text = new Set(stepped.text)\n text.delete(id)\n return { ...stepped, text }\n}\n\nconst closeOpenBlocks = (state: State, events: LLMEvent[]): State => {\n for (const id of state.reasoning) events.push(LLMEvent.reasoningEnd({ id }))\n for (const id of state.text) events.push(LLMEvent.textEnd({ id }))\n return { ...state, text: new Set(), reasoning: new Set() }\n}\n\nexport const finish = (\n state: State,\n events: LLMEvent[],\n input: {\n readonly reason: FinishReason\n readonly usage?: Usage\n readonly providerMetadata?: ProviderMetadata\n },\n): State => {\n const stepped = closeOpenBlocks(stepStart(state, events), events)\n events.push(\n LLMEvent.stepFinish({\n index: 0,\n reason: input.reason,\n usage: input.usage,\n providerMetadata: input.providerMetadata,\n }),\n LLMEvent.finish(input),\n )\n return { ...stepped, stepStarted: false }\n}\n\nexport * as Lifecycle from \"./lifecycle\"\n", | ||
| "import { isRecord } from \"../../utils/record\"\n\n// Gemini accepts a JSON Schema-like dialect for tool parameters, but rejects a\n// handful of common JSON Schema shapes. Keep this projection isolated so the\n// Gemini protocol file still reads like the other protocol modules.\nconst SCHEMA_INTENT_KEYS = [\n \"type\",\n \"properties\",\n \"items\",\n \"prefixItems\",\n \"enum\",\n \"const\",\n \"$ref\",\n \"additionalProperties\",\n \"patternProperties\",\n \"required\",\n \"not\",\n \"if\",\n \"then\",\n \"else\",\n]\n\nconst hasCombiner = (schema: unknown) =>\n isRecord(schema) && (Array.isArray(schema.anyOf) || Array.isArray(schema.oneOf) || Array.isArray(schema.allOf))\n\nconst hasSchemaIntent = (schema: unknown) =>\n isRecord(schema) && (hasCombiner(schema) || SCHEMA_INTENT_KEYS.some((key) => key in schema))\n\nconst sanitizeNode = (schema: unknown): unknown => {\n if (!isRecord(schema)) return Array.isArray(schema) ? schema.map(sanitizeNode) : schema\n\n const result: Record<string, unknown> = Object.fromEntries(\n Object.entries(schema).map(([key, value]) => [\n key,\n key === \"enum\" && Array.isArray(value) ? value.map(String) : sanitizeNode(value),\n ]),\n )\n\n if (Array.isArray(result.enum) && (result.type === \"integer\" || result.type === \"number\")) result.type = \"string\"\n\n const properties = result.properties\n if (result.type === \"object\" && isRecord(properties) && Array.isArray(result.required)) {\n result.required = result.required.filter((field) => typeof field === \"string\" && field in properties)\n }\n\n if (result.type === \"array\" && !hasCombiner(result)) {\n result.items = result.items ?? {}\n if (isRecord(result.items) && !hasSchemaIntent(result.items)) result.items = { ...result.items, type: \"string\" }\n }\n\n if (typeof result.type === \"string\" && result.type !== \"object\" && !hasCombiner(result)) {\n delete result.properties\n delete result.required\n }\n\n return result\n}\n\nconst emptyObjectSchema = (schema: Record<string, unknown>) =>\n schema.type === \"object\" &&\n (!isRecord(schema.properties) || Object.keys(schema.properties).length === 0) &&\n !schema.additionalProperties\n\nconst projectNode = (schema: unknown): Record<string, unknown> | undefined => {\n if (!isRecord(schema)) return undefined\n if (emptyObjectSchema(schema)) return undefined\n return Object.fromEntries(\n [\n [\"description\", schema.description],\n [\"required\", schema.required],\n [\"format\", schema.format],\n [\"type\", Array.isArray(schema.type) ? schema.type.filter((type) => type !== \"null\")[0] : schema.type],\n [\"nullable\", Array.isArray(schema.type) && schema.type.includes(\"null\") ? true : undefined],\n [\"enum\", schema.const !== undefined ? [schema.const] : schema.enum],\n [\n \"properties\",\n isRecord(schema.properties)\n ? Object.fromEntries(Object.entries(schema.properties).map(([key, value]) => [key, projectNode(value)]))\n : undefined,\n ],\n [\n \"items\",\n Array.isArray(schema.items)\n ? schema.items.map(projectNode)\n : schema.items === undefined\n ? undefined\n : projectNode(schema.items),\n ],\n [\"allOf\", Array.isArray(schema.allOf) ? schema.allOf.map(projectNode) : undefined],\n [\"anyOf\", Array.isArray(schema.anyOf) ? schema.anyOf.map(projectNode) : undefined],\n [\"oneOf\", Array.isArray(schema.oneOf) ? schema.oneOf.map(projectNode) : undefined],\n [\"minLength\", schema.minLength],\n ].filter((entry) => entry[1] !== undefined),\n )\n}\n\nexport const convert = (schema: unknown) => projectNode(sanitizeNode(schema))\n\nexport * as GeminiToolSchema from \"./gemini-tool-schema\"\n", | ||
| "import type { JsonSchema, ModelToolSchemaCompatibility } from \"../../schema\"\nimport { isRecord } from \"../../utils/record\"\nimport { GeminiToolSchema } from \"./gemini-tool-schema\"\n\nconst removeNullSchemas = (value: unknown): unknown => {\n if (Array.isArray(value)) return value.map(removeNullSchemas)\n if (!isRecord(value)) return value\n const fields = Object.fromEntries(\n Object.entries(value)\n .filter(([key]) => key !== \"anyOf\")\n .map(([key, field]) => [key, removeNullSchemas(field)]),\n )\n if (!Array.isArray(value.anyOf)) return fields\n const variants = value.anyOf.filter((variant) => !isRecord(variant) || variant.type !== \"null\").map(removeNullSchemas)\n if (variants.length === 1 && isRecord(variants[0])) return { ...fields, ...variants[0] }\n return { ...fields, anyOf: variants }\n}\n\nconst tupleItemsSchema = (items: ReadonlyArray<unknown>) => {\n const projected = items.map(moonshotNode)\n if (projected.length === 0) return {}\n if (projected.length === 1) return projected[0]\n return { anyOf: projected }\n}\n\nconst moonshotNode = (schema: unknown): unknown => {\n if (Array.isArray(schema)) return schema.map(moonshotNode)\n if (!isRecord(schema)) return schema\n if (typeof schema.$ref === \"string\") return { $ref: schema.$ref }\n return Object.fromEntries(\n Object.entries(schema).flatMap(([key, value]) => {\n if (key === \"items\" && Array.isArray(value)) return [[key, tupleItemsSchema(value)]]\n if (key === \"prefixItems\") {\n if (\"items\" in schema) return []\n return [[\"items\", tupleItemsSchema(Array.isArray(value) ? value : [])]]\n }\n if (key === \"unevaluatedItems\") return []\n return [[key, moonshotNode(value)]]\n }),\n )\n}\n\nconst moonshot = (schema: JsonSchema): JsonSchema => {\n const projected = moonshotNode(schema)\n return isRecord(projected) ? projected : {}\n}\n\nconst openAI = (schema: JsonSchema): JsonSchema => {\n const variants = Array.isArray(schema.anyOf) ? schema.anyOf.filter(isRecord) : []\n const flattened =\n variants.length === 0\n ? { ...schema, type: \"object\" }\n : {\n ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== \"anyOf\")),\n type: \"object\",\n properties: variants.reduce(\n (properties, variant) => ({ ...(isRecord(variant.properties) ? variant.properties : {}), ...properties }),\n {},\n ),\n additionalProperties: false,\n }\n const normalized = removeNullSchemas(flattened)\n return isRecord(normalized) ? normalized : { type: \"object\" }\n}\n\nconst gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}\n\nconst modelCompatibility = (\n schema: JsonSchema,\n compatibility: ModelToolSchemaCompatibility | undefined,\n): JsonSchema => {\n if (compatibility === undefined) return schema\n switch (compatibility) {\n case \"gemini\":\n return gemini(schema)\n case \"moonshot\":\n return moonshot(schema)\n }\n}\n\nexport const ToolSchemaProjection = {\n gemini,\n modelCompatibility,\n moonshot,\n openAI,\n} as const\n" | ||
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| } |
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| { | ||
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| { | ||
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| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.start,\n Effect.fn(\"cli.service.start\")(function* () {\n const transport = yield* Service.ensure(yield* ServiceConfig.options())\n process.stdout.write(transport.url + EOL)\n }),\n)\n" | ||
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| { | ||
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| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.set,\n Effect.fn(\"cli.service.set\")(function* (input) {\n yield* ServiceConfig.set(input.key, input.value)\n }),\n)\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/anthropic-compatible.ts", "../ai/src/providers/anthropic.ts"], | ||
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| "import type { ProviderPackage } from \"../provider-package\"\nimport { AnthropicMessages } from \"../protocols/anthropic-messages\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { ProviderID, type ModelID } from \"../schema\"\n\nexport const id = ProviderID.make(\"anthropic-compatible\")\n\nexport type Config = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly provider?: string\n readonly baseURL: string\n }\n\nexport type Settings = ProviderPackage.Settings &\n (\n | { readonly apiKey?: string; readonly authToken?: never }\n | { readonly apiKey?: never; readonly authToken?: string }\n ) & {\n readonly baseURL: string\n readonly provider?: string\n }\n\nexport const routes = [AnthropicMessages.route]\n\nconst auth = (input: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in input && input.auth) return input.auth\n return Auth.optional(\"apiKey\" in input ? input.apiKey : undefined, \"apiKey\").pipe(Auth.header(\"x-api-key\"))\n}\n\nexport const configure = (input: Config) => {\n if (!input.baseURL) throw new Error(\"Anthropic-compatible providers require a baseURL\")\n const provider = input.provider ?? \"anthropic-compatible\"\n const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input\n const route = AnthropicMessages.route.with({\n ...rest,\n provider,\n endpoint: { baseURL },\n auth: auth(input),\n })\n return {\n id: ProviderID.make(provider),\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.apiKey !== undefined && settings.authToken !== undefined)\n throw new Error(\"Anthropic-compatible apiKey cannot be combined with authToken\")\n return configure({\n ...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n provider: settings.provider,\n }).model(modelID)\n}\n\nexport * as AnthropicCompatible from \"./anthropic-compatible\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport { AnthropicMessages } from \"../protocols/anthropic-messages\"\nimport { AnthropicCompatible } from \"./anthropic-compatible\"\n\nexport const id = ProviderID.make(\"anthropic\")\n\nexport const routes = [AnthropicMessages.route]\n\nexport type Config = RouteDefaultsInput & ProviderAuthOption<\"optional\"> & { readonly baseURL?: string }\n\nexport type Settings = ProviderPackage.Settings &\n (\n | { readonly apiKey?: string; readonly authToken?: never }\n | { readonly apiKey?: never; readonly authToken?: string }\n ) & {\n readonly baseURL?: string\n }\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in options && options.auth) return options.auth\n return Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"ANTHROPIC_API_KEY\"))\n .pipe(Auth.header(\"x-api-key\"))\n}\n\nexport const configure = (input: Config = {}) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n const compatible = AnthropicCompatible.configure({\n ...rest,\n auth: auth(input),\n baseURL: baseURL ?? AnthropicMessages.DEFAULT_BASE_URL,\n provider: id,\n })\n return {\n id,\n model: (modelID: string | ModelID) => compatible.model(modelID),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.apiKey !== undefined && settings.authToken !== undefined)\n throw new Error(\"Anthropic apiKey cannot be combined with authToken\")\n return configure({\n ...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n }).model(modelID)\n}\n" | ||
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| "debugId": "921AD181817D91B164756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/image/photon-wasm.bun.ts", "../core/src/image/photon.ts"], | ||
| "sourcesContent": [ | ||
| "// @ts-ignore Bun embeds static file imports when compiling the CLI.\nimport photonWasm from \"@silvia-odwyer/photon-node/photon_rs_bg.wasm\" with { type: \"file\" }\n\nexport default photonWasm\n", | ||
| "import photonWasm from \"#photon-wasm\"\nimport { Effect } from \"effect\"\nimport path from \"node:path\"\nimport { fileURLToPath } from \"node:url\"\nimport { FileSystem } from \"../filesystem\"\nimport { DecodeError, ResizerUnavailableError, SizeError } from \"../image\"\n\nconst JPEG_QUALITIES = [80, 85, 70, 55, 40]\n\nexport const make = Effect.gen(function* () {\n ;(globalThis as typeof globalThis & { __OPENCODE_PHOTON_WASM_PATH?: string }).__OPENCODE_PHOTON_WASM_PATH =\n path.isAbsolute(photonWasm) ? photonWasm : fileURLToPath(new URL(photonWasm, import.meta.url))\n const loadPhoton = yield* Effect.cached(\n Effect.tryPromise({\n try: () => import(\"@silvia-odwyer/photon-node\"),\n catch: () => new ResizerUnavailableError(),\n }),\n )\n return Effect.fn(\"Image.Photon.normalize\")(function* (\n resource: string,\n content: FileSystem.Content & { readonly encoding: \"base64\" },\n limits: {\n readonly autoResize: boolean\n readonly maxWidth: number\n readonly maxHeight: number\n readonly maxBase64Bytes: number\n },\n ) {\n const photon = yield* loadPhoton\n const decoded = yield* Effect.try({\n try: () => photon.PhotonImage.new_from_byteslice(Buffer.from(content.content, \"base64\")),\n catch: () => new DecodeError({ resource }),\n })\n try {\n const width = decoded.get_width()\n const height = decoded.get_height()\n const bytes = Buffer.byteLength(content.content, \"utf-8\")\n if (width <= limits.maxWidth && height <= limits.maxHeight && bytes <= limits.maxBase64Bytes) return content\n if (!limits.autoResize)\n return yield* new SizeError({\n resource,\n width,\n height,\n bytes,\n maxWidth: limits.maxWidth,\n maxHeight: limits.maxHeight,\n maxBytes: limits.maxBase64Bytes,\n })\n const scale = Math.min(1, limits.maxWidth / width, limits.maxHeight / height)\n const sizes = Array.from({ length: 32 }).reduce<Array<{ width: number; height: number }>>((acc) => {\n const previous = acc.at(-1) ?? {\n width: Math.max(1, Math.round(width * scale)),\n height: Math.max(1, Math.round(height * scale)),\n }\n const next =\n acc.length === 0\n ? previous\n : {\n width: previous.width === 1 ? 1 : Math.max(1, Math.floor(previous.width * 0.75)),\n height: previous.height === 1 ? 1 : Math.max(1, Math.floor(previous.height * 0.75)),\n }\n return acc.some((item) => item.width === next.width && item.height === next.height) ? acc : [...acc, next]\n }, [])\n for (const size of sizes) {\n const resized = photon.resize(decoded, size.width, size.height, photon.SamplingFilter.Lanczos3)\n try {\n const encoders: Array<readonly [mime: string, encode: () => Uint8Array]> = [\n [\"image/png\", () => resized.get_bytes()],\n ...JPEG_QUALITIES.map((quality) => [\"image/jpeg\", () => resized.get_bytes_jpeg(quality)] as const),\n ]\n for (const [mime, encode] of encoders) {\n const candidate = Buffer.from(encode()).toString(\"base64\")\n if (Buffer.byteLength(candidate, \"utf-8\") <= limits.maxBase64Bytes)\n return { ...content, content: candidate, encoding: \"base64\" as const, mime }\n }\n } finally {\n resized.free()\n }\n }\n return yield* new SizeError({\n resource,\n width,\n height,\n bytes,\n maxWidth: limits.maxWidth,\n maxHeight: limits.maxHeight,\n maxBytes: limits.maxBase64Bytes,\n })\n } finally {\n decoded.free()\n }\n })\n})\n" | ||
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| "debugId": "92AEAA819F9D70A664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mini.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Effect, FileSystem, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerConnection } from \"../../services/server-connection\"\nimport { Config } from \"../../config\"\nimport { resolve } from \"@opencode-ai/tui/config\"\n\nexport default Runtime.handler(Commands.commands.mini, (input) =>\n Effect.gen(function* () {\n const { runMini, validateMiniTerminal } = yield* Effect.promise(() => import(\"../../mini\"))\n yield* Effect.promise(async () => validateMiniTerminal())\n const serverURL = Option.getOrUndefined(input.server)\n const server = yield* ServerConnection.resolve({ server: serverURL, standalone: input.standalone })\n const config = yield* Config.Service\n const resolved = resolve(yield* config.get(), { terminalSuspend: process.platform !== \"win32\" })\n const fileSystem = yield* FileSystem.FileSystem\n const runServicePromise = Effect.runPromiseWith(Context.make(FileSystem.FileSystem, fileSystem))\n const service = server.service\n yield* Effect.promise(() =>\n runMini({\n server: {\n endpoint: server.endpoint,\n reconnect: service ? (signal) => runServicePromise(service.reconnect(), { signal }) : undefined,\n },\n continue: input.continue,\n session: Option.getOrUndefined(input.session),\n fork: input.fork,\n model: Option.getOrUndefined(input.model),\n agent: Option.getOrUndefined(input.agent),\n prompt: Option.getOrUndefined(input.prompt),\n replay: input.replay,\n replayLimit: Option.getOrUndefined(input.replayLimit),\n demo: input.demo,\n tuiConfig: resolved,\n }),\n )\n }),\n)\n" | ||
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| "debugId": "E7D7103A627E1D9364756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-images.ts", "../ai/src/providers/openai.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Encoding, Schema } from \"effect\"\nimport { Headers, HttpClientRequest } from \"effect/unstable/http\"\nimport {\n ImageModel,\n GeneratedImage,\n ImageResponse,\n type ImageRequest,\n type ImageModelDefaults,\n type ImageRoute,\n} from \"../image\"\nimport { Auth, type Definition as AuthDefinition } from \"../route/auth\"\nimport { InvalidProviderOutputReason, LLMError, Usage, mergeHttpOptions, mergeJsonRecords } from \"../schema\"\nimport { ProviderShared } from \"./shared\"\nimport { OpenAIImage } from \"./utils/openai-image\"\n\nconst ADAPTER = \"openai-images\"\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/images/generations\"\n\nexport interface OpenAIImageOptions {\n readonly quality?: \"auto\" | \"low\" | \"medium\" | \"high\"\n readonly background?: \"auto\" | \"opaque\" | \"transparent\"\n readonly moderation?: \"auto\" | \"low\"\n readonly outputFormat?: \"png\" | \"jpeg\" | \"webp\"\n readonly outputCompression?: number\n}\n\nconst OpenAIImageBody = Schema.Struct({\n model: Schema.String,\n prompt: Schema.String,\n n: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),\n size: Schema.optional(Schema.String),\n quality: Schema.optional(Schema.Literals([\"auto\", \"low\", \"medium\", \"high\"])),\n background: Schema.optional(Schema.Literals([\"auto\", \"opaque\", \"transparent\"])),\n moderation: Schema.optional(Schema.Literals([\"auto\", \"low\"])),\n output_format: Schema.optional(Schema.Literals([\"png\", \"jpeg\", \"webp\"])),\n output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),\n})\nexport type OpenAIImageBody = Schema.Schema.Type<typeof OpenAIImageBody>\n\nconst OpenAIImageResponse = Schema.Struct({\n data: Schema.Array(\n Schema.Struct({\n b64_json: Schema.optional(Schema.String),\n url: Schema.optional(Schema.String),\n revised_prompt: Schema.optional(Schema.String),\n }),\n ),\n output_format: Schema.optional(Schema.String),\n usage: Schema.optional(\n Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n output_tokens: Schema.optional(Schema.Number),\n total_tokens: Schema.optional(Schema.Number),\n input_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n }),\n ),\n})\n\nexport interface ModelInput {\n readonly id: string\n readonly auth: AuthDefinition\n readonly baseURL?: string\n readonly headers?: Record<string, string>\n readonly defaults?: ImageModelDefaults\n}\n\nconst providerOptions = (request: ImageRequest): OpenAIImageOptions => ({\n ...request.model.defaults?.providerOptions?.openai,\n ...request.providerOptions?.openai,\n})\n\nconst body = (request: ImageRequest): OpenAIImageBody => {\n const options = providerOptions(request)\n return {\n model: request.model.id,\n prompt: request.prompt,\n n: request.count,\n size: request.size === undefined ? undefined : `${request.size.width}x${request.size.height}`,\n quality: options.quality,\n background: options.background,\n moderation: options.moderation,\n output_format: options.outputFormat,\n output_compression: options.outputCompression,\n }\n}\n\nconst invalidOutput = (message: string) =>\n new LLMError({\n module: ADAPTER,\n method: \"generate\",\n reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),\n })\n\nconst applyQuery = (url: string, query: Record<string, string> | undefined) => {\n if (!query) return url\n const next = new URL(url)\n Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))\n return next.toString()\n}\n\nconst PROTOCOL_BODY_FIELDS = new Set([\n \"model\",\n \"prompt\",\n \"n\",\n \"size\",\n \"quality\",\n \"background\",\n \"moderation\",\n \"output_format\",\n \"output_compression\",\n])\n\nconst bodyWithOverlay = Effect.fn(\"OpenAIImages.bodyWithOverlay\")(function* (\n imageBody: OpenAIImageBody,\n overlay: Record<string, unknown> | undefined,\n) {\n if (!overlay) return imageBody\n const reserved = Object.keys(overlay).filter((key) => PROTOCOL_BODY_FIELDS.has(key))\n if (reserved.length > 0)\n return yield* ProviderShared.invalidRequest(\n `http.body cannot overlay protocol-owned field(s): ${reserved.join(\", \")}`,\n )\n return mergeJsonRecords(imageBody, overlay) ?? imageBody\n})\n\nexport const model = (input: ModelInput) => {\n const route: ImageRoute = {\n id: ADAPTER,\n generate: Effect.fn(\"OpenAIImages.generate\")(function* (request: ImageRequest, execute) {\n if (request.aspectRatio !== undefined)\n return yield* ProviderShared.invalidRequest(\"OpenAI Images does not support the common aspectRatio option\")\n if (request.seed !== undefined)\n return yield* ProviderShared.invalidRequest(\"OpenAI Images does not support the common seed option\")\n\n const requestBody = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIImageBody))(body(request))\n const http = mergeHttpOptions(request.model.defaults?.http, request.http)\n const overlaidBody = yield* bodyWithOverlay(requestBody, http?.body)\n const text = ProviderShared.encodeJson(overlaidBody)\n const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\\/$/, \"\")}${PATH}`, http?.query)\n const headers = yield* Auth.toEffect(input.auth)({\n request,\n method: \"POST\",\n url,\n body: text,\n headers: Headers.fromInput({ ...input.headers, ...http?.headers }),\n })\n const response = yield* execute(\n HttpClientRequest.post(url).pipe(\n HttpClientRequest.setHeaders(headers),\n HttpClientRequest.bodyText(text, \"application/json\"),\n ),\n )\n const payload = yield* response.json.pipe(\n Effect.mapError(() => invalidOutput(\"Failed to read the OpenAI Images response\")),\n )\n const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(\n Effect.mapError(() => invalidOutput(\"OpenAI Images returned an invalid response\")),\n )\n const format = decoded.output_format ?? providerOptions(request).outputFormat ?? \"png\"\n const images = yield* Effect.forEach(decoded.data, (item, index) => {\n if (item.b64_json)\n return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(\n Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),\n Effect.map(\n (data) =>\n new GeneratedImage({\n mediaType: `image/${format}`,\n data,\n providerMetadata:\n item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },\n }),\n ),\n )\n if (item.url)\n return Effect.succeed(\n new GeneratedImage({\n mediaType: `image/${format}`,\n data: item.url,\n providerMetadata:\n item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },\n }),\n )\n return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))\n })\n if (images.length === 0) return yield* invalidOutput(\"OpenAI Images returned no images\")\n return new ImageResponse({\n images,\n usage:\n decoded.usage === undefined\n ? undefined\n : new Usage({\n inputTokens: decoded.usage.input_tokens,\n outputTokens: decoded.usage.output_tokens,\n totalTokens: decoded.usage.total_tokens,\n providerMetadata: { openai: decoded.usage },\n }),\n providerMetadata: { openai: { outputFormat: format } },\n })\n }),\n }\n return ImageModel.make({ id: input.id, provider: \"openai\", route, defaults: input.defaults })\n}\n\nexport const OpenAIImages = {\n model,\n} as const\n", | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route, RouteDefaultsInput } from \"../route/client\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { HttpOptions, ProviderID, ToolDefinition, mergeHttpOptions, type ModelID } from \"../schema\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\nimport { withOpenAIOptions, type OpenAIProviderOptionsInput } from \"./openai-options\"\nimport { OpenAIImages, type OpenAIImageOptions } from \"../protocols/openai-images\"\n\nexport type { OpenAIOptionsInput, OpenAIResponseIncludable } from \"./openai-options\"\nexport type { OpenAIImageOptions } from \"../protocols/openai-images\"\n\nexport const id = ProviderID.make(\"openai\")\n\nexport const routes = [OpenAIResponses.route, OpenAIResponses.webSocketRoute, OpenAIChat.route]\n\n// This provider facade wraps the lower-level Responses and Chat model factories\n// with OpenAI-specific conveniences: typed options, API-key sugar, env fallback,\n// and default option normalization.\nexport type Config = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n readonly queryParams?: Record<string, string>\n readonly providerOptions?: OpenAIProviderOptionsInput\n readonly image?: ImageConfig\n }\n\nexport interface ImageConfig {\n readonly providerOptions?: OpenAIImageOptions\n}\n\nexport interface ImageGenerationOptions {\n readonly action?: \"auto\" | \"generate\" | \"edit\"\n readonly background?: \"auto\" | \"opaque\" | \"transparent\"\n readonly inputFidelity?: \"low\" | \"high\"\n readonly outputCompression?: number\n readonly outputFormat?: \"png\" | \"jpeg\" | \"webp\"\n readonly partialImages?: number\n readonly quality?: \"auto\" | \"low\" | \"medium\" | \"high\"\n readonly size?: string\n}\n\nexport const imageGeneration = (options: ImageGenerationOptions = {}) =>\n ToolDefinition.make({\n name: \"image_generation\",\n description: \"Generate or edit an image using OpenAI's hosted image generation tool.\",\n inputSchema: { type: \"object\", properties: {}, additionalProperties: false },\n native: {\n openai: {\n type: \"image_generation\",\n action: options.action,\n background: options.background,\n input_fidelity: options.inputFidelity,\n output_compression: options.outputCompression,\n output_format: options.outputFormat,\n partial_images: options.partialImages,\n quality: options.quality,\n size: options.size,\n },\n },\n })\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL?: string\n readonly organization?: string\n readonly project?: string\n readonly queryParams?: Readonly<Record<string, string>>\n readonly transport?: \"http\" | \"websocket\"\n readonly providerOptions?: OpenAIProviderOptionsInput\n}\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => AuthOptions.bearer(options, \"OPENAI_API_KEY\")\n\nconst defaults = (input: Config) => {\n const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, image: _image, ...rest } = input\n return rest\n}\n\nconst configuredRoute = <Body, Prepared>(route: Route<Body, Prepared>, input: Config) =>\n route.with({\n auth: auth(input),\n endpoint: { baseURL: input.baseURL, query: input.queryParams },\n })\n\nexport const configure = (input: Config = {}) => {\n const responsesRoute = configuredRoute(OpenAIResponses.route, input)\n const responsesWebSocketRoute = configuredRoute(OpenAIResponses.webSocketRoute, input)\n const chatRoute = configuredRoute(OpenAIChat.route, input)\n const modelDefaults = defaults(input)\n const responses = (id: string | ModelID) =>\n responsesRoute.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true })).model({ id })\n const responsesWebSocket = (id: string | ModelID) =>\n responsesWebSocketRoute.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true })).model({ id })\n const chat = (id: string | ModelID) => chatRoute.with(withOpenAIOptions(id, modelDefaults)).model({ id })\n const image = (modelID: string | ModelID) =>\n OpenAIImages.model({\n id: modelID,\n auth: auth(input),\n baseURL: input.baseURL,\n headers: input.headers,\n defaults: {\n providerOptions:\n input.image?.providerOptions === undefined ? undefined : { openai: { ...input.image.providerOptions } },\n http: mergeHttpOptions(\n input.http === undefined ? undefined : HttpOptions.make(input.http),\n input.queryParams === undefined ? undefined : new HttpOptions({ query: input.queryParams }),\n ),\n },\n })\n\n return {\n id,\n model: responses,\n responses,\n responsesWebSocket,\n chat,\n image,\n configure,\n }\n}\n\nexport const provider = configure()\n\nconst config = (settings: Settings): Config => {\n const headers = {\n ...(settings.organization === undefined ? {} : { \"OpenAI-Organization\": settings.organization }),\n ...(settings.project === undefined ? {} : { \"OpenAI-Project\": settings.project }),\n ...settings.headers,\n }\n return {\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: Object.keys(headers).length === 0 ? undefined : headers,\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n queryParams: settings.queryParams === undefined ? undefined : { ...settings.queryParams },\n }\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n const configured = configure(config(settings))\n if (settings.transport === undefined || settings.transport === \"http\") return configured.responses(modelID)\n if (settings.transport === \"websocket\") return configured.responsesWebSocket(modelID)\n throw new Error(`Unsupported OpenAI Responses transport: ${String(settings.transport)}`)\n}\n\nexport const chatModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).chat(modelID)\nexport const responses = provider.responses\nexport const responsesWebSocket = provider.responsesWebSocket\nexport const chat = provider.chat\nexport const image = provider.image\n" | ||
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| "debugId": "CA36003241B49D1D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/debug/agents.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.debug.commands.agents,\n Effect.fn(\"cli.debug.agents\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.agent.list({ location: { directory: process.cwd() } }))\n process.stdout.write(\n JSON.stringify(\n response.data.toSorted((a, b) => a.id.localeCompare(b.id)),\n null,\n 2,\n ) + EOL,\n )\n }),\n)\n" | ||
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Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openai-compatible.ts"], | ||
| "sourcesContent": [ | ||
| "import { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAICompatibleChat from \"../protocols/openai-compatible-chat\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { profiles, type OpenAICompatibleProfile } from \"./openai-compatible-profile\"\n\nexport const id = ProviderID.make(\"openai-compatible\")\n\ntype GenericModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly provider?: string\n readonly baseURL: string\n }\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL: string\n readonly provider?: string\n}\n\nexport type FamilyModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n }\n\nexport const routes = [OpenAICompatibleChat.route]\n\nexport const configure = (input: GenericModelOptions) => {\n const provider = input.provider ?? \"openai-compatible\"\n const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input\n const route = OpenAICompatibleChat.route.with({\n ...rest,\n provider,\n endpoint: { baseURL },\n auth: AuthOptions.bearer(input, []),\n })\n return {\n id: ProviderID.make(provider),\n model: (modelID: string | ModelID) => route.model({ id: modelID, provider: ProviderID.make(provider) }),\n configure,\n }\n}\n\nconst define = (profile: OpenAICompatibleProfile) => {\n const configureProfile = (input: FamilyModelOptions = {}) => {\n const facade = configure({\n ...input,\n baseURL: input.baseURL ?? profile.baseURL,\n provider: profile.provider,\n })\n return {\n id: ProviderID.make(profile.provider),\n model: facade.model,\n configure: configureProfile,\n }\n }\n return configureProfile()\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure({\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n provider: settings.provider,\n }).model(modelID)\n\nexport const baseten = define(profiles.baseten)\nexport const cerebras = define(profiles.cerebras)\nexport const deepinfra = define(profiles.deepinfra)\nexport const deepseek = define(profiles.deepseek)\nexport const fireworks = define(profiles.fireworks)\nexport const groq = define(profiles.groq)\nexport const togetherai = define(profiles.togetherai)\n" | ||
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| "debugId": "4B3FF2D186F43AED64756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/status.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.status,\n Effect.fn(\"cli.service.status\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover({ ...options, version: undefined })\n process.stdout.write((found?.url ?? \"stopped\") + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "C2DAED3B09D4DC8964756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/image-client.ts", "../ai/src/image.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Effect, Layer } from \"effect\"\nimport { RequestExecutor } from \"./route/executor\"\nimport type { ImageRequest, ImageResponse } from \"./image\"\nimport type { LLMError } from \"./schema\"\n\nexport type Execute = RequestExecutor.Interface[\"execute\"]\n\nexport interface Interface {\n readonly generate: (request: ImageRequest) => Effect.Effect<ImageResponse, LLMError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/ImageClient\") {}\n\nexport const generate = (request: ImageRequest): Effect.Effect<ImageResponse, LLMError> =>\n Effect.gen(function* () {\n const client = yield* Service\n return yield* client.generate(request)\n }) as Effect.Effect<ImageResponse, LLMError>\n\nexport const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(\n Service,\n Effect.gen(function* () {\n const executor = yield* RequestExecutor.Service\n return Service.of({\n generate: (request) => request.model.route.generate(request, executor.execute),\n })\n }),\n)\n\nexport const ImageClient = {\n Service,\n layer,\n generate,\n} as const\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from \"./schema\"\nimport { ImageClient, type Execute as ImageExecute } from \"./image-client\"\n\nexport interface ImageRoute {\n readonly id: string\n readonly generate: (request: ImageRequest, execute: ImageExecute) => Effect.Effect<ImageResponse, LLMError>\n}\n\nexport class ImageModel {\n readonly id: ModelID\n readonly provider: ProviderID\n readonly route: ImageRoute\n readonly defaults?: ImageModelDefaults\n\n constructor(input: ImageModel.Input) {\n this.id = input.id\n this.provider = input.provider\n this.route = input.route\n this.defaults = input.defaults\n }\n\n static make(input: ImageModel.MakeInput) {\n return new ImageModel({\n id: ModelID.make(input.id),\n provider: ProviderID.make(input.provider),\n route: input.route,\n defaults: input.defaults,\n })\n }\n}\n\nexport namespace ImageModel {\n export interface Input {\n readonly id: ModelID\n readonly provider: ProviderID\n readonly route: ImageRoute\n readonly defaults?: ImageModelDefaults\n }\n\n export interface MakeInput extends Omit<Input, \"id\" | \"provider\"> {\n readonly id: string | ModelID\n readonly provider: string | ProviderID\n }\n}\n\nexport interface ImageModelDefaults {\n readonly providerOptions?: Record<string, Record<string, unknown>>\n readonly http?: HttpOptions\n}\n\nexport const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {\n expected: \"Image.Model\",\n})\n\nexport const ImageSize = Schema.Struct({\n width: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),\n height: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),\n}).annotate({ identifier: \"Image.Size\" })\nexport type ImageSize = Schema.Schema.Type<typeof ImageSize>\n\nexport class ImageRequest extends Schema.Class<ImageRequest>(\"Image.Request\")({\n model: ImageModelSchema,\n prompt: Schema.String,\n count: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),\n size: Schema.optional(ImageSize),\n aspectRatio: Schema.optional(Schema.String),\n seed: Schema.optional(Schema.Number),\n providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),\n http: Schema.optional(HttpOptions),\n metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n}) {}\n\nexport type ImageRequestInput = Omit<ConstructorParameters<typeof ImageRequest>[0], \"http\"> & {\n readonly http?: HttpOptions.Input\n}\n\nexport class GeneratedImage extends Schema.Class<GeneratedImage>(\"Image.Generated\")({\n mediaType: Schema.String,\n data: Schema.Union([Schema.String, Schema.Uint8Array]),\n providerMetadata: Schema.optional(ProviderMetadata),\n}) {}\n\nexport class ImageResponse extends Schema.Class<ImageResponse>(\"Image.Response\")({\n images: Schema.Array(GeneratedImage),\n usage: Schema.optional(Usage),\n providerMetadata: Schema.optional(ProviderMetadata),\n}) {\n get image() {\n return this.images[0]\n }\n}\n\nexport const request = (input: ImageRequest | ImageRequestInput) => {\n if (input instanceof ImageRequest) return input\n return new ImageRequest({\n ...input,\n http: input.http === undefined ? undefined : HttpOptions.make(input.http),\n })\n}\n\nexport const generate = (input: ImageRequest | ImageRequestInput) =>\n Effect.try({\n try: () => request(input),\n catch: (error) =>\n new LLMError({\n module: \"Image\",\n method: \"generate\",\n reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),\n }),\n }).pipe(Effect.flatMap(ImageClient.generate))\n\nexport const Image = {\n request,\n generate,\n} as const\n" | ||
| ], | ||
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| "debugId": "B5C9F17CF053109564756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/run/run.ts", "src/run/noninteractive.ts", "src/run/ui.ts"], | ||
| "sourcesContent": [ | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient, type SessionMessageAssistantTool } from \"@opencode-ai/client/promise\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { open } from \"node:fs/promises\"\nimport path from \"node:path\"\nimport { readStdin } from \"../util/io\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { waitForCatalogReady } from \"../services/catalog\"\nimport { parseSessionTargetModel, resolveSessionTarget } from \"../session-target\"\nimport { toolInlineInfo } from \"@opencode-ai/tui/mini/tool\"\nimport { runNonInteractivePrompt } from \"./noninteractive\"\nimport { UI } from \"./ui\"\n\nexport type RunCommandInput = {\n server: ServerConnection.Resolved\n message: string[]\n continue?: boolean\n session?: string\n fork?: boolean\n model?: string\n agent?: string\n format: \"default\" | \"json\"\n file: string[]\n title?: string\n thinking?: boolean\n auto?: boolean\n}\n\ntype FilePart = {\n url: string\n filename: string\n mime: string\n}\n\ntype Prepared = {\n directory?: string\n message: string\n files: FilePart[]\n}\n\ntype ExecutionOptions = {\n root?: string\n directory?: string\n useServerDirectory?: boolean\n variant?: string\n attached?: boolean\n compatibility?: \"v1\"\n}\n\nclass RunTargetError extends Error {\n constructor(\n message: string,\n readonly sessionID?: string,\n ) {\n super(message)\n }\n}\n\nconst ATTACH_FILE_MAX_BYTES = 10 * 1024 * 1024\n\nexport function runNonInteractive(input: RunCommandInput) {\n return runNonInteractiveWithOptions(input, {})\n}\n\n/** @internal Used only by the V1 command boundary. */\nexport function runNonInteractiveWithOptions(input: RunCommandInput, options: ExecutionOptions) {\n return run(input, options).catch((error) => reportRunError(input, errorMessage(error)))\n}\n\nasync function run(input: RunCommandInput, options: ExecutionOptions) {\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n const root = options.root ?? process.env.PWD ?? process.cwd()\n const local = localDirectory(root)\n const directory = options.useServerDirectory ? undefined : (options.directory ?? local)\n const message = mergeInput(formatMessage(input.message), process.stdin.isTTY ? undefined : await readStdin())\n if (!message?.trim()) fail(\"You must provide a message\")\n const files = await Promise.all(input.file.map((file) => prepareFile(file, root, options)))\n const prepared = { directory, message, files }\n return execute(input, prepared, input.server.endpoint, options)\n}\n\nasync function execute(input: RunCommandInput, prepared: Prepared, endpoint: Endpoint, options: ExecutionOptions) {\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const explicit = parseRunModel(input.model)\n const target = await resolveSessionTarget({\n client,\n location: prepared.directory ? { directory: prepared.directory } : undefined,\n continue: input.continue,\n session: input.session,\n fork: input.fork,\n model: explicit\n ? { providerID: explicit.model.providerID, id: explicit.model.modelID, variant: explicit.variant }\n : undefined,\n agent: input.agent,\n prepare: async (next) => {\n const selected =\n next.model ??\n (await client.model\n .default({ location: { directory: next.location.directory, workspace: next.location.workspaceID } })\n .then((result) => result.data))\n const model = selected\n ? {\n providerID: selected.providerID,\n id: selected.id,\n variant: options.variant ?? (\"variant\" in selected ? selected.variant : undefined),\n }\n : undefined\n if ((options.variant ?? explicit?.variant) && !model)\n throw new RunTargetError(\"Cannot select a variant before selecting a model\", next.session?.id)\n if (model) {\n await waitForCatalogReady({\n sdk: client,\n directory: next.location.directory,\n workspace: next.location.workspaceID,\n model: { providerID: model.providerID, modelID: model.id },\n })\n const available = await client.model.list({\n location: { directory: next.location.directory, workspace: next.location.workspaceID },\n })\n if (!available.data.some((item) => item.providerID === model.providerID && item.id === model.id))\n throw new RunTargetError(`Model unavailable: ${model.providerID}/${model.id}`, next.session?.id)\n }\n return {\n model,\n agent: input.agent\n ? await validateAgent(client, next.location.directory, next.location.workspaceID, input.agent)\n : next.agent,\n }\n },\n }).catch((error) => {\n if (!(error instanceof RunTargetError)) throw error\n reportRunError(input, error.message, error.sessionID)\n return undefined\n })\n if (!target) return\n const model = target.model ? { providerID: target.model.providerID, modelID: target.model.id } : undefined\n const variant = target.model?.variant\n if (!target.resume && input.title !== undefined) {\n await client.session.rename({\n sessionID: target.session.id,\n title: input.title || prepared.message.slice(0, 50) + (prepared.message.length > 50 ? \"...\" : \"\"),\n })\n }\n\n await runNonInteractivePrompt({\n client,\n sessionID: target.session.id,\n location: target.location,\n message: prepared.message,\n files: prepared.files,\n agent: target.agent,\n model,\n variant,\n thinking: input.thinking ?? false,\n format: input.format,\n auto: input.auto ?? false,\n attached: options.attached ?? true,\n compatibility: options.compatibility,\n renderTool: (part) => renderTool(part, target.location.directory),\n renderToolError: (part) => renderToolError(part, target.location.directory),\n }).catch((error) => reportRunError(input, errorMessage(error), target.session.id))\n}\n\nexport function mergeInput(message: string | undefined, piped: string | undefined) {\n if (!message) return piped || undefined\n if (!piped) return message\n return message + \"\\n\" + piped\n}\n\nfunction formatMessage(message: string[]) {\n const value = message.map((part) => (part.includes(\" \") ? `\"${part.replace(/\"/g, '\\\\\"')}\"` : part)).join(\" \")\n return value || undefined\n}\n\nfunction localDirectory(root: string) {\n try {\n process.chdir(root)\n return process.cwd()\n } catch {\n fail(`Failed to change directory to ${root}`)\n }\n}\n\nexport function parseRunModel(value?: string) {\n const ref = parseSessionTargetModel(value)\n if (!ref) return\n return {\n model: { providerID: ref.providerID, modelID: ref.id },\n variant: ref.variant,\n }\n}\n\nasync function validateAgent(client: OpenCodeClient, directory: string, workspace: string | undefined, name?: string) {\n if (!name) return\n const agents = await client.agent\n .list({ location: { directory, workspace } })\n .then((result) => result.data)\n .catch(() => undefined)\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n const agent = agents.find((item) => item.id === name)\n if (!agent) {\n warning(`agent \"${name}\" not found. Falling back to default agent`)\n return\n }\n if (agent.mode === \"subagent\") {\n warning(`agent \"${name}\" is a subagent, not a primary agent. Falling back to default agent`)\n return\n }\n return name\n}\n\nasync function prepareFile(input: string, directory: string, options: ExecutionOptions): Promise<FilePart> {\n const file = path.resolve(directory, input)\n const handle = await open(file, \"r\").catch(() => fail(`File not found: ${input}`))\n try {\n const stat = await handle.stat()\n if (options.compatibility === \"v1\" && options.attached && stat.isDirectory())\n fail(`Cannot attach local directory without a shared filesystem: ${input}`)\n if (!stat.isFile() || stat.size > ATTACH_FILE_MAX_BYTES)\n fail(`Cannot attach a directory, special file, or file larger than 10 MiB: ${input}`)\n const content = Buffer.alloc(Number(stat.size))\n let offset = 0\n while (offset < content.length) {\n const read = await handle.read(content, offset, content.length - offset, offset)\n if (read.bytesRead === 0) break\n offset += read.bytesRead\n }\n const bytes = content.subarray(0, offset)\n const detected = FSUtil.mimeType(file)\n const text = bytes.toString(\"utf8\")\n const mime =\n detected.startsWith(\"image/\") || detected === \"application/pdf\"\n ? detected\n : !isBinaryContent(bytes) && Buffer.from(text, \"utf8\").equals(bytes)\n ? \"text/plain\"\n : detected\n return {\n url: `data:${mime};base64,${bytes.toString(\"base64\")}`,\n filename: path.basename(file),\n mime,\n }\n } finally {\n await handle.close()\n }\n}\n\nfunction isBinaryContent(bytes: Uint8Array) {\n if (bytes.length === 0) return false\n if (bytes.includes(0)) return true\n return bytes.reduce((count, byte) => count + Number(byte < 9 || (byte > 13 && byte < 32)), 0) / bytes.length > 0.3\n}\n\nasync function renderTool(part: SessionMessageAssistantTool, directory: string) {\n const info = toolInlineInfo(part, directory)\n if (info.mode === \"block\") {\n UI.empty()\n UI.println(UI.Style.TEXT_NORMAL + info.icon, UI.Style.TEXT_NORMAL + info.title)\n if (info.body?.trim()) UI.println(info.body)\n UI.empty()\n return\n }\n UI.println(\n UI.Style.TEXT_NORMAL + info.icon,\n UI.Style.TEXT_NORMAL + info.title,\n info.description ? UI.Style.TEXT_DIM + info.description + UI.Style.TEXT_NORMAL : \"\",\n )\n}\n\nasync function renderToolError(part: SessionMessageAssistantTool, directory: string) {\n const info = toolInlineInfo(part, directory)\n UI.println(UI.Style.TEXT_NORMAL + \"✗\", UI.Style.TEXT_NORMAL + `${info.title} failed`)\n}\n\nfunction warning(message: string) {\n UI.println(UI.Style.TEXT_WARNING_BOLD + \"!\", UI.Style.TEXT_NORMAL, message)\n}\n\nfunction errorMessage(error: unknown) {\n if (error instanceof Error) return error.message\n if (typeof error === \"object\" && error !== null && \"message\" in error && typeof error.message === \"string\")\n return error.message\n return String(error)\n}\n\n/** @internal Used by the V1 command boundary before a Session exists. */\nexport function reportRunError(input: Pick<RunCommandInput, \"format\">, message: string, sessionID?: string) {\n process.exitCode = 1\n if (input.format === \"json\") {\n process.stdout.write(\n JSON.stringify({\n type: \"error\",\n timestamp: Date.now(),\n sessionID: sessionID ?? \"\",\n error: { type: \"unknown\", message },\n }) + \"\\n\",\n )\n return\n }\n UI.error(message)\n}\n\nfunction fail(message: string): never {\n throw new Error(message)\n}\n", | ||
| "import type {\n EventSubscribeOutput,\n JsonValue,\n LLMToolContent,\n LocationRef,\n OpenCodeClient,\n SessionMessageAssistantTool,\n} from \"@opencode-ai/client/promise\"\nimport { SessionMessage } from \"@opencode-ai/schema/session-message\"\nimport { EOL } from \"node:os\"\nimport { readFile } from \"node:fs/promises\"\nimport { toolOutputText, type MiniToolPart } from \"@opencode-ai/tui/mini/tool\"\nimport { UI } from \"./ui\"\n\ntype Model = {\n providerID: string\n modelID: string\n}\n\ntype File = {\n url: string\n filename: string\n mime: string\n}\n\ntype Input = {\n client: OpenCodeClient\n sessionID: string\n location: LocationRef\n message: string\n files: File[]\n agent?: string\n model?: Model\n variant?: string\n thinking: boolean\n format: \"default\" | \"json\"\n auto: boolean\n /** True when the client is attached to a shared server rather than an exclusive in-process one. */\n attached: boolean\n compatibility?: \"v1\"\n renderTool: (part: SessionMessageAssistantTool) => Promise<void>\n renderToolError: (part: SessionMessageAssistantTool) => Promise<void>\n}\n\ntype StartedPart = {\n id: string\n timestamp: number\n}\n\ntype ToolState = StartedPart & {\n assistantMessageID: string\n tool: string\n input: Record<string, JsonValue>\n raw?: string\n provider?: unknown\n providerState?: SessionMessageAssistantTool[\"providerState\"]\n structured: Record<string, JsonValue>\n content: LLMToolContent[]\n}\n\ntype V2Event = EventSubscribeOutput\ntype FormRequest = Extract<V2Event, { type: \"form.created\" }>[\"data\"][\"form\"]\n\n// MCP elicitations are temporarily owned by the \"global\" sentinel instead of a real\n// session. An exclusive local process may treat them as this run's blockers; an\n// attached client must not cancel input that may belong to another session.\nconst GLOBAL_FORM_SESSION_ID = \"global\"\n\nexport async function runNonInteractivePrompt(input: Input) {\n const controller = new AbortController()\n const stream = input.client.event.subscribe({ signal: controller.signal })[Symbol.asyncIterator]()\n const connected = await stream.next()\n if (connected.done) throw new Error(\"Event stream disconnected before prompt admission\")\n\n const messageID = SessionMessage.ID.create()\n const starts = new Map<string, StartedPart>()\n const tools = new Map<string, ToolState>()\n let submitted = false\n let promoted = false\n let emittedError = false\n let permissionRejected = false\n let formCancelled = false\n let interrupted = false\n let v1InvalidOutput = false\n let admission: AbortController | undefined\n let pendingStep: { timestamp: number; part: Record<string, unknown>; label: string } | undefined\n\n const emit = (type: string, timestamp: number, data: Record<string, unknown>) => {\n if (input.format !== \"json\") return false\n process.stdout.write(JSON.stringify({ type, timestamp, sessionID: input.sessionID, ...data }) + EOL)\n return true\n }\n\n const writeText = (part: { text: string; [key: string]: unknown }, timestamp: number) => {\n if (emit(\"text\", timestamp, { part })) return\n const text = part.text.trim()\n if (!text) return\n if (!process.stdout.isTTY) {\n process.stdout.write(text + EOL)\n return\n }\n UI.empty()\n UI.println(text)\n UI.empty()\n }\n\n const flushStep = () => {\n if (!pendingStep) return\n const value = pendingStep\n pendingStep = undefined\n if (!emit(\"step_start\", value.timestamp, { part: value.part }) && input.format !== \"json\") {\n UI.empty()\n UI.println(value.label)\n UI.empty()\n }\n }\n\n const replyPermission = async (request: { id: string; action: string; resources: ReadonlyArray<string> }) => {\n if (!input.auto) {\n permissionRejected = true\n UI.println(\n UI.Style.TEXT_WARNING_BOLD + \"!\",\n UI.Style.TEXT_NORMAL +\n `permission requested: ${request.action} (${request.resources.join(\", \")}); auto-rejecting`,\n )\n }\n await input.client.permission\n .reply({\n sessionID: input.sessionID,\n requestID: request.id,\n reply: input.auto ? \"once\" : \"reject\",\n })\n .catch(() => {})\n if (!input.auto) {\n await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n }\n\n const cancelForm = async (request: Pick<FormRequest, \"id\" | \"sessionID\">) => {\n try {\n await input.client.form.cancel(\n { sessionID: request.sessionID, formID: request.id },\n ...formRequestOptions(request.sessionID === GLOBAL_FORM_SESSION_ID ? input.location : undefined),\n )\n } catch (error) {\n if (!formAlreadySettled(error)) throw error\n }\n formCancelled = true\n }\n\n const consume = async () => {\n while (!controller.signal.aborted) {\n const next = await stream.next().catch((error) => {\n if (!emittedError) throw error\n return { done: true as const, value: undefined }\n })\n if (next.done) {\n if (emittedError) return\n throw new Error(\"Event stream disconnected during prompt execution\")\n }\n const event = next.value\n\n if (event.type === \"permission.v2.asked\" && submitted && event.data.sessionID === input.sessionID) {\n await replyPermission(event.data)\n continue\n }\n if (\n event.type === \"form.created\" &&\n submitted &&\n (event.data.form.sessionID === input.sessionID ||\n (!input.attached &&\n event.data.form.sessionID === GLOBAL_FORM_SESSION_ID &&\n sameLocation(event.location, input.location)))\n ) {\n await cancelForm(event.data.form)\n continue\n }\n if (!(\"sessionID\" in event.data) || event.data.sessionID !== input.sessionID) continue\n const time = toMillis(\"created\" in event ? event.created : undefined)\n\n if (event.type === \"session.input.promoted\") {\n if (event.data.inputID === messageID) {\n promoted = true\n continue\n }\n }\n if (\n event.type === \"session.execution.interrupted\" &&\n event.data.reason === \"user\" &&\n (interrupted || permissionRejected || formCancelled)\n ) {\n return\n }\n if (!promoted) continue\n\n if (event.type === \"session.step.started\") {\n const part = {\n id: partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"step-start\",\n snapshot: event.data.snapshot,\n }\n if (input.compatibility === \"v1\") {\n pendingStep = {\n timestamp: time,\n part,\n label: `> ${event.data.agent} · ${event.data.model.id}`,\n }\n continue\n }\n if (!emit(\"step_start\", time, { part }) && input.format !== \"json\") {\n UI.empty()\n UI.println(`> ${event.data.agent} · ${event.data.model.id}`)\n UI.empty()\n }\n continue\n }\n\n if (event.type === \"session.text.started\") {\n flushStep()\n starts.set(\"text\", { id: partID(event.id), timestamp: time })\n continue\n }\n if (event.type === \"session.text.ended\") {\n const started = starts.get(\"text\")\n starts.delete(\"text\")\n const part = {\n id: started?.id ?? partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"text\",\n text: event.data.text,\n time: { start: started?.timestamp ?? time, end: time },\n }\n writeText(part, time)\n continue\n }\n\n if (event.type === \"session.reasoning.started\") {\n flushStep()\n starts.set(\"reasoning\", { id: partID(event.id), timestamp: time })\n continue\n }\n if (event.type === \"session.reasoning.ended\" && input.thinking) {\n const started = starts.get(\"reasoning\")\n starts.delete(\"reasoning\")\n const part = {\n id: started?.id ?? partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"reasoning\",\n text: event.data.text,\n metadata: event.data.state,\n time: { start: started?.timestamp ?? time, end: time },\n }\n if (emit(\"reasoning\", time, { part })) continue\n const text = part.text.trim()\n if (!text) continue\n const line = `Thinking: ${text}`\n if (!process.stdout.isTTY) {\n process.stdout.write(line + EOL)\n continue\n }\n UI.empty()\n UI.println(`${UI.Style.TEXT_DIM}\\u001b[3m${line}\\u001b[0m${UI.Style.TEXT_NORMAL}`)\n UI.empty()\n continue\n }\n\n if (event.type === \"session.tool.input.started\") {\n flushStep()\n tools.set(toolKey(event.data.assistantMessageID, event.data.callID), {\n id: partID(event.id),\n timestamp: time,\n assistantMessageID: event.data.assistantMessageID,\n tool: event.data.name,\n input: {},\n structured: {},\n content: [],\n })\n continue\n }\n if (event.type === \"session.tool.input.ended\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) current.raw = event.data.text\n continue\n }\n if (event.type === \"session.tool.input.delta\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) current.raw = (current.raw ?? \"\") + event.data.delta\n continue\n }\n if (event.type === \"session.tool.called\") {\n flushStep()\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key)\n tools.set(key, {\n id: current?.id ?? partID(event.id),\n timestamp: current?.timestamp ?? time,\n assistantMessageID: event.data.assistantMessageID,\n tool: current?.tool ?? \"tool\",\n input: event.data.input,\n raw: current?.raw,\n provider: { executed: event.data.executed, state: event.data.state },\n providerState: event.data.state,\n structured: {},\n content: [],\n })\n continue\n }\n if (event.type === \"session.tool.progress\") {\n const current = tools.get(toolKey(event.data.assistantMessageID, event.data.callID))\n if (current) {\n current.structured = event.data.structured\n current.content = event.data.content\n }\n continue\n }\n if (event.type === \"session.tool.success\") {\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key) ?? fallbackTool(event)\n const tool: SessionMessageAssistantTool = {\n type: \"tool\",\n id: event.data.callID,\n name: current.tool,\n executed: event.data.executed,\n providerState: current.providerState,\n providerResultState: event.data.resultState,\n state: {\n status: \"completed\",\n input: current.input,\n structured: event.data.structured,\n content: event.data.content,\n result: event.data.result,\n },\n time: { created: current.timestamp, ran: current.timestamp, completed: time },\n }\n const part: MiniToolPart = {\n id: current.id,\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"tool\",\n callID: event.data.callID,\n tool: current.tool,\n state: {\n status: \"completed\",\n input: current.input,\n output: toolOutputText(current.tool, event.data.content),\n title: current.tool,\n metadata: {\n structured: event.data.structured,\n content: event.data.content,\n result: event.data.result,\n providerCall: current.provider,\n providerResult: { executed: event.data.executed, state: event.data.resultState },\n rawInput: current.raw,\n },\n time: { start: current.timestamp, end: time },\n },\n }\n tools.delete(key)\n if (!emit(\"tool_use\", time, { part })) await input.renderTool(tool)\n continue\n }\n if (event.type === \"session.tool.failed\") {\n const key = toolKey(event.data.assistantMessageID, event.data.callID)\n const current = tools.get(key) ?? fallbackTool(event)\n const error = event.data.error.message\n const tool: SessionMessageAssistantTool = {\n type: \"tool\",\n id: event.data.callID,\n name: current.tool,\n executed: event.data.executed,\n providerState: current.providerState,\n providerResultState: event.data.resultState,\n state: {\n status: \"error\",\n input: current.input,\n structured: current.structured,\n content: current.content,\n error: event.data.error,\n result: event.data.result,\n },\n time: { created: current.timestamp, ran: current.timestamp, completed: time },\n }\n const part: MiniToolPart = {\n id: current.id,\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"tool\",\n callID: event.data.callID,\n tool: current.tool,\n state: {\n status: \"error\",\n input: current.input,\n error,\n metadata: {\n result: event.data.result,\n providerCall: current.provider,\n providerResult: { executed: event.data.executed, state: event.data.resultState },\n rawInput: current.raw,\n },\n time: { start: current.timestamp, end: time },\n },\n }\n tools.delete(key)\n if (input.compatibility === \"v1\" && (permissionRejected || formCancelled)) continue\n if (!emit(\"tool_use\", time, { part })) {\n if (toolOutputText(current.tool, current.content).trim())\n await input.renderTool({\n ...tool,\n state: {\n status: \"completed\",\n input: current.input,\n structured: current.structured,\n content: current.content,\n result: event.data.result,\n },\n })\n await input.renderToolError(tool)\n UI.error(error)\n }\n continue\n }\n\n if (event.type === \"session.step.ended\") {\n flushStep()\n const part = {\n id: partID(event.id),\n sessionID: input.sessionID,\n messageID: event.data.assistantMessageID,\n type: \"step-finish\",\n reason: event.data.finish,\n snapshot: event.data.snapshot,\n cost: event.data.cost,\n tokens: event.data.tokens,\n }\n emit(\"step_finish\", time, { part })\n continue\n }\n if (event.type === \"session.step.failed\") {\n if (\n input.compatibility === \"v1\" &&\n event.data.error.message === \"Provider stream ended without a terminal finish event\"\n ) {\n pendingStep = undefined\n v1InvalidOutput = true\n continue\n }\n if (interrupted || permissionRejected || formCancelled) continue\n flushStep()\n emittedError = true\n process.exitCode = 1\n if (!emit(\"error\", time, { error: event.data.error })) UI.error(event.data.error.message)\n continue\n }\n if (event.type === \"session.execution.failed\") {\n if (input.compatibility === \"v1\" && (v1InvalidOutput || permissionRejected || formCancelled)) return\n flushStep()\n if (!emittedError && !formCancelled) {\n emittedError = true\n process.exitCode = 1\n if (!emit(\"error\", time, { error: event.data.error })) UI.error(event.data.error.message)\n }\n return\n }\n if (event.type === \"session.execution.interrupted\") {\n if (input.compatibility === \"v1\" && (permissionRejected || formCancelled)) return\n if (event.data.reason === \"user\" && interrupted) process.exitCode = 130\n if (event.data.reason !== \"user\" && !emittedError) {\n emittedError = true\n process.exitCode = 1\n const error = { type: \"aborted\" as const, message: `Session interrupted: ${event.data.reason}` }\n if (!emit(\"error\", time, { error })) UI.error(error.message)\n }\n return\n }\n if (event.type === \"session.execution.succeeded\") return\n }\n }\n\n const interrupt = () => {\n if (interrupted) process.exit(130)\n interrupted = true\n process.exitCode = 130\n admission?.abort()\n void input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n process.on(\"SIGINT\", interrupt)\n\n let completed: Promise<void> | undefined\n try {\n if (input.agent) {\n await input.client.session.switchAgent({ sessionID: input.sessionID, agent: input.agent })\n }\n const selected = input.model\n ? { providerID: input.model.providerID, id: input.model.modelID, variant: input.variant }\n : input.variant\n ? await input.client.session\n .get({ sessionID: input.sessionID })\n .then((result) => result.model)\n .then(async (model) => {\n if (model) return { ...model, variant: input.variant }\n const result = await input.client.model.default()\n const fallback = result.data\n return fallback ? { providerID: fallback.providerID, id: fallback.id, variant: input.variant } : undefined\n })\n : undefined\n if (input.variant && !selected) throw new Error(\"Cannot select a variant before selecting a model\")\n if (selected) {\n await input.client.session.switchModel({ sessionID: input.sessionID, model: selected })\n }\n\n const prepared = await Promise.all(input.files.map(prepareFile))\n if (interrupted) return\n submitted = true\n completed = consume()\n admission = new AbortController()\n const response = await input.client.session\n .prompt(\n {\n sessionID: input.sessionID,\n id: messageID,\n text: [input.message, ...prepared.flatMap((file) => (file.text ? [file.text] : []))].join(\"\\n\\n\"),\n files: prepared.flatMap((file) => (file.attachment ? [file.attachment] : [])),\n delivery: \"steer\",\n },\n { signal: admission.signal },\n )\n .catch(async (error) => {\n if (interrupted) {\n await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n }\n controller.abort()\n await completed?.catch(() => {})\n if (interrupted || emittedError) return undefined\n throw error\n })\n admission = undefined\n if (!response) return\n if (interrupted) await input.client.session.interrupt({ sessionID: input.sessionID }).catch(() => {})\n\n const [permissions, forms, globals] = await Promise.all([\n input.client.permission.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.client.form.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.attached\n ? Promise.resolve(undefined)\n : input.client.form.request\n .list({\n location: { directory: input.location.directory, workspace: input.location.workspaceID },\n })\n .catch(() => undefined),\n ])\n await Promise.all([\n ...(permissions ?? []).map(replyPermission),\n ...(forms ?? []).map(cancelForm),\n ...(globals && sameLocation(globals.location, input.location)\n ? globals.data.filter((form) => form.sessionID === GLOBAL_FORM_SESSION_ID).map(cancelForm)\n : []),\n ])\n await completed\n } finally {\n process.off(\"SIGINT\", interrupt)\n controller.abort()\n await stream.return?.(undefined).catch(() => {})\n }\n}\n\nfunction sameLocation(left: LocationRef | undefined, right: LocationRef) {\n return !!left && left.directory === right.directory && left.workspaceID === right.workspaceID\n}\n\nfunction formRequestOptions(location: LocationRef | undefined): [] | [{ headers: Record<string, string> }] {\n if (!location) return []\n return [\n {\n headers: {\n \"x-opencode-directory\": encodeURIComponent(location.directory),\n ...(location.workspaceID ? { \"x-opencode-workspace\": location.workspaceID } : {}),\n },\n },\n ]\n}\n\nfunction formAlreadySettled(error: unknown) {\n return !!error && typeof error === \"object\" && Reflect.get(error, \"_tag\") === \"FormAlreadySettledError\"\n}\n\nfunction partID(eventID: string) {\n return `prt_${eventID.replace(/^evt_/, \"\")}`\n}\n\nfunction toolKey(messageID: string, callID: string) {\n return `${messageID}\\u0000${callID}`\n}\n\nfunction fallbackTool(event: {\n id: string\n created: number\n data: { assistantMessageID: string; callID: string }\n}): ToolState {\n return {\n id: partID(event.id),\n timestamp: toMillis(event.created),\n assistantMessageID: event.data.assistantMessageID,\n tool: \"tool\",\n input: {},\n structured: {},\n content: [],\n }\n}\n\nfunction toMillis(value: unknown) {\n if (typeof value === \"number\") return value\n if (typeof value === \"string\") return new Date(value).getTime()\n return Date.now()\n}\n\nasync function prepareFile(file: File) {\n if (file.mime !== \"text/plain\") {\n const uri = file.url.startsWith(\"data:\")\n ? file.url\n : `data:${file.mime};base64,${(await readFile(new URL(file.url))).toString(\"base64\")}`\n return { attachment: { uri, name: file.filename } }\n }\n const content = file.url.startsWith(\"data:\")\n ? Buffer.from(file.url.slice(file.url.indexOf(\",\") + 1), \"base64\").toString(\"utf8\")\n : await readFile(new URL(file.url), \"utf8\")\n return { text: `<file name=\"${file.filename}\">\\n${content}\\n</file>` }\n}\n", | ||
| "import { EOL } from \"node:os\"\n\nexport const Style = {\n TEXT_DIM: \"\\x1b[90m\",\n TEXT_NORMAL: \"\\x1b[0m\",\n TEXT_WARNING_BOLD: \"\\x1b[93m\\x1b[1m\",\n TEXT_DANGER_BOLD: \"\\x1b[91m\\x1b[1m\",\n}\n\nexport function println(...message: string[]) {\n process.stderr.write(message.join(\" \") + EOL)\n}\n\nlet blank = false\n\nexport function empty() {\n if (blank) return\n println(Style.TEXT_NORMAL)\n blank = true\n}\n\nexport function error(message: string) {\n if (message.startsWith(\"Error: \")) message = message.slice(\"Error: \".length)\n println(Style.TEXT_DANGER_BOLD + \"Error: \" + Style.TEXT_NORMAL + message)\n}\n\nexport * as UI from \"./ui\"\n" | ||
| ], | ||
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| "import type { ProviderOptions, ReasoningEffort, TextVerbosity } from \"../schema\"\nimport { mergeProviderOptions } from \"../schema\"\nimport type { OpenAIResponseIncludable, OpenAIServiceTier } from \"../protocols/utils/openai-options\"\n\nexport type { OpenAIResponseIncludable, OpenAIServiceTier } from \"../protocols/utils/openai-options\"\n\nexport interface OpenAIOptionsInput {\n readonly [key: string]: unknown\n readonly store?: boolean\n readonly promptCacheKey?: string\n readonly reasoningEffort?: ReasoningEffort\n readonly reasoningSummary?: \"auto\"\n // OpenAI Responses `include` wire field. Mirrors the official SDK's\n // `ResponseIncludable[]` union exactly so AI SDK callers and direct\n // native-SDK callers share one shape and no translation is required.\n readonly include?: ReadonlyArray<OpenAIResponseIncludable>\n readonly textVerbosity?: TextVerbosity\n readonly serviceTier?: OpenAIServiceTier\n}\n\nexport type OpenAIProviderOptionsInput = ProviderOptions & {\n readonly openai?: OpenAIOptionsInput\n}\n\nconst definedEntries = (input: Record<string, unknown>) =>\n Object.entries(input).filter((entry) => entry[1] !== undefined)\n\nconst openAIProviderOptions = (options: OpenAIOptionsInput | undefined): ProviderOptions | undefined => {\n const openai = Object.fromEntries(\n definedEntries({\n store: options?.store,\n promptCacheKey: options?.promptCacheKey,\n reasoningEffort: options?.reasoningEffort,\n reasoningSummary: options?.reasoningSummary,\n include: options?.include,\n textVerbosity: options?.textVerbosity,\n serviceTier: options?.serviceTier,\n }),\n )\n if (Object.keys(openai).length === 0) return undefined\n return { openai }\n}\n\nexport const gpt5DefaultOptions = (\n modelID: string,\n options: { readonly textVerbosity?: boolean } = {},\n): ProviderOptions | undefined => {\n const id = modelID.toLowerCase()\n if (!id.includes(\"gpt-5\") || id.includes(\"gpt-5-chat\") || id.includes(\"gpt-5-pro\")) return undefined\n return openAIProviderOptions({\n reasoningEffort: \"medium\",\n reasoningSummary: \"auto\",\n // GPT-5 reasoning models are configured stateless (`store: false`) by\n // `openAIDefaultOptions` below, so the only way a follow-up turn can\n // carry reasoning state is via the encrypted reasoning include. Without\n // this, callers using the default model facade get reasoning summaries\n // they cannot replay statelessly.\n include: [\"reasoning.encrypted_content\"],\n textVerbosity:\n options.textVerbosity === true && id.includes(\"gpt-5.\") && !id.includes(\"codex\") && !id.includes(\"-chat\")\n ? \"low\"\n : undefined,\n })\n}\n\nexport const openAIDefaultOptions = (\n modelID: string,\n options: { readonly textVerbosity?: boolean } = {},\n): ProviderOptions | undefined =>\n mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID, options))\n\nexport const withOpenAIOptions = <Options extends { readonly providerOptions?: OpenAIProviderOptionsInput }>(\n modelID: string,\n options: Options,\n defaults: { readonly textVerbosity?: boolean } = {},\n): Omit<Options, \"providerOptions\"> & { readonly providerOptions?: ProviderOptions } => {\n return {\n ...options,\n providerOptions: mergeProviderOptions(openAIDefaultOptions(modelID, defaults), options.providerOptions),\n }\n}\n\nexport * as OpenAIProviderOptions from \"./openai-options\"\n" | ||
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| "sources": ["src/commands/handlers/mcp/logout.ts"], | ||
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| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { resolveIntegration } from \"./resolve\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.logout,\n Effect.fn(\"cli.mcp.logout\")(function* (input) {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n\n const integration = yield* resolveIntegration(client, input.name, location)\n if (!integration) {\n process.stdout.write(`No stored credentials for ${input.name}` + EOL)\n return\n }\n\n const credentials = integration.connections.filter((connection) => connection.type === \"credential\")\n if (credentials.length === 0) {\n process.stdout.write(`No stored credentials for ${input.name}` + EOL)\n return\n }\n\n yield* Effect.forEach(\n credentials,\n (connection) => Effect.promise(() => client.credential.remove({ credentialID: connection.id, location })),\n { discard: true },\n )\n process.stdout.write(`Removed OAuth credentials for ${input.name}` + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "954D0B48E5B5B12A64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
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| "debugId": "C7447D167BAAF80264756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/services/service-config.ts", "src/util/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Global } from \"@opencode-ai/core/global\"\nimport { InstallationChannel, InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Hash } from \"@opencode-ai/core/util/hash\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Effect, FileSystem, Option, Schema } from \"effect\"\nimport { randomBytes } from \"crypto\"\nimport path from \"path\"\nimport { selfCommand } from \"../util/process\"\n\n// The CLI's service configuration file, plus the Service.EnsureOptions binding that\n// points the client package's service operations at this CLI: which\n// registration file (by channel), which version, and how to spawn opencode.\n\nexport const Info = Schema.Struct({\n hostname: Schema.optional(Schema.String),\n port: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1), Schema.isLessThanOrEqualTo(65_535))),\n password: Schema.optional(Schema.String),\n})\nexport type Info = typeof Info.Type\n\nconst keys = [\"hostname\", \"port\", \"password\"] as const\ntype Key = (typeof keys)[number]\n\nconst decodeInfo = Schema.decodeUnknownEffect(Schema.fromJsonString(Info))\nconst decodeRegistration = Schema.decodeUnknownEffect(Schema.fromJsonString(Service.Info))\n\nexport function filename(channel = InstallationChannel) {\n if (channel === \"latest\") return \"service.json\"\n if (channel === \"local\") return \"service-local.json\"\n return `service-${Hash.fast(channel)}.json`\n}\n\nexport function defaultPort(channel = InstallationChannel) {\n if (channel === \"latest\") return 0xc0de\n if (channel === \"local\") return 0xc0df\n return 10_000 + (Number.parseInt(Hash.fast(channel).slice(0, 8), 16) % 50_000)\n}\n\nexport function versionBelongsToChannel(\n version: string | undefined,\n channel = InstallationChannel,\n installedVersion = InstallationVersion,\n) {\n if (version === undefined) return false\n if (version === installedVersion) return true\n const prefix = `0.0.0-${channel}-`\n if (!version.startsWith(prefix)) return false\n return /^\\d+(?:\\.\\d+)?$/.test(version.slice(prefix.length))\n}\n\nexport const migrateRegistration = Effect.fnUntraced(function* (\n legacy: string,\n file: string,\n channel = InstallationChannel,\n installedVersion = InstallationVersion,\n) {\n if (channel === \"latest\" || channel === \"local\") return\n const fs = yield* FileSystem.FileSystem\n const text = yield* fs.readFileString(legacy).pipe(Effect.option)\n if (Option.isNone(text)) return\n const registration = yield* decodeRegistration(text.value).pipe(Effect.option)\n if (Option.isNone(registration)) return\n if (!versionBelongsToChannel(registration.value.version, channel, installedVersion)) return\n yield* fs.writeFileString(file, text.value, { flag: \"wx\", mode: 0o600 }).pipe(Effect.ignore)\n})\n\nfunction configKey(key: string): Key {\n if (key === \"hostname\" || key === \"port\" || key === \"password\") return key\n throw new Error(`Unknown service config key: ${key}`)\n}\n\nconst paths = Effect.gen(function* () {\n const fs = yield* FileSystem.FileSystem\n const global = yield* Global.Service\n const name = filename()\n const file = path.join(global.state, name)\n return {\n fs,\n file,\n legacyFile: path.join(global.state, \"service.json\"),\n configFile: path.join(global.config, name),\n }\n})\n\nexport const options = Effect.fnUntraced(function* () {\n const { file, legacyFile } = yield* paths\n yield* migrateRegistration(legacyFile, file)\n return {\n file,\n version: InstallationVersion,\n command: [...selfCommand(), \"serve\", \"--service\"],\n }\n})\n\nexport const read = Effect.fn(\"cli.service-config.read\")(function* () {\n const { fs, configFile } = yield* paths\n return yield* fs.readFileString(configFile).pipe(\n Effect.flatMap(decodeInfo),\n Effect.catch(() => Effect.succeed({} as Info)),\n )\n})\n\nconst write = Effect.fn(\"cli.service-config.write\")(function* (value: Info) {\n const { fs, configFile } = yield* paths\n const temp = configFile + \".tmp\"\n yield* fs.makeDirectory(path.dirname(configFile), { recursive: true })\n yield* fs.writeFileString(temp, JSON.stringify(value, null, 2) + \"\\n\", { mode: 0o600 })\n yield* fs.rename(temp, configFile)\n})\n\nexport const password = Effect.fn(\"cli.service-config.password\")(function* (value?: string) {\n const existing = yield* read()\n if (value === undefined && existing.password) return existing.password\n const next = value ?? randomBytes(32).toString(\"base64url\")\n\n // Keep one private credential across server restarts so discovered clients\n // can reconnect without exposing a password flag or environment variable.\n yield* write({ ...existing, password: next })\n return next\n})\n\nexport const get = Effect.fn(\"cli.service-config.get\")(function* (key?: string) {\n if (key === undefined) {\n const { password: _password, ...safe } = yield* read()\n return JSON.stringify(safe, null, 2)\n }\n switch (configKey(key)) {\n case \"hostname\": {\n return (yield* read()).hostname ?? \"\"\n }\n case \"port\": {\n const port = (yield* read()).port\n return port === undefined ? \"\" : String(port)\n }\n case \"password\": {\n return yield* password()\n }\n }\n throw new Error(`Unknown service config key: ${key}`)\n})\n\nexport const set = Effect.fn(\"cli.service-config.set\")(function* (key: string, value: string) {\n switch (configKey(key)) {\n case \"hostname\": {\n yield* Service.stop(yield* options())\n yield* write({ ...(yield* read()), hostname: value })\n return\n }\n case \"port\": {\n const port = Number(value)\n if (!Number.isInteger(port) || port < 1 || port > 65_535) throw new Error(\"Port must be between 1 and 65535\")\n yield* Service.stop(yield* options())\n yield* write({ ...(yield* read()), port })\n return\n }\n case \"password\": {\n yield* Service.stop(yield* options())\n yield* password(value)\n return\n }\n }\n})\n\nexport const unset = Effect.fn(\"cli.service-config.unset\")(function* (key: string) {\n switch (configKey(key)) {\n case \"hostname\": {\n yield* Service.stop(yield* options())\n const { hostname: _hostname, ...next } = yield* read()\n yield* write(next)\n return\n }\n case \"port\": {\n yield* Service.stop(yield* options())\n const { port: _port, ...next } = yield* read()\n yield* write(next)\n return\n }\n case \"password\": {\n yield* Service.stop(yield* options())\n const { password: _password, ...next } = yield* read()\n yield* write(next)\n return\n }\n }\n})\n\nexport * as ServiceConfig from \"./service-config\"\n", | ||
| "import path from \"node:path\"\n\nexport function selfCommand() {\n const runtime = path.basename(process.execPath, path.extname(process.execPath)).toLowerCase()\n if (runtime !== \"bun\" && runtime !== \"node\" && runtime !== \"nodejs\") return [process.execPath]\n if (!process.argv[1]) throw new Error(\"Failed to resolve CLI entrypoint\")\n if (runtime === \"node\" || runtime === \"nodejs\") return [process.execPath, ...nodeFlags(), process.argv[1]]\n return [process.execPath, process.argv[1]]\n}\n\nfunction nodeFlags() {\n return process.execArgv.flatMap((arg, index, args) => {\n if (index > 0 && args[index - 1] === \"--conditions\") return []\n if (arg === \"--conditions\") return args[index + 1] ? [arg, args[index + 1]] : []\n if (arg.startsWith(\"--conditions=\")) return [arg]\n if (\n arg === \"--experimental-ffi\" ||\n arg === \"--use-system-ca\" ||\n arg === \"--enable-source-maps\" ||\n arg === \"--no-addons\"\n )\n return [arg]\n if (arg === \"--no-warnings\" || arg.startsWith(\"--disable-warning=\")) return [arg]\n return []\n })\n}\n" | ||
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| "debugId": "E754D4C3DC5C8CD264756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/auth.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport {\n OpenCode,\n type IntegrationAttemptStatus,\n type IntegrationOAuthMethod,\n type OpenCodeClient,\n} from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { resolveIntegration } from \"./resolve\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.auth,\n Effect.fn(\"cli.mcp.auth\")(function* (input) {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n\n const integration = yield* resolveIntegration(client, input.name, location)\n if (!integration)\n return yield* Effect.fail(new Error(`MCP server \"${input.name}\" is not an OAuth-capable remote server`))\n const method = integration.methods.find(\n (candidate): candidate is IntegrationOAuthMethod => candidate.type === \"oauth\",\n )\n if (!method)\n return yield* Effect.fail(new Error(`MCP server \"${input.name}\" is not an OAuth-capable remote server`))\n\n const started = yield* Effect.promise(() =>\n client.integration.oauth.connect({ integrationID: integration.id, methodID: method.id, inputs: {}, location }),\n )\n const attempt = started.data\n if (attempt.mode === \"code\")\n return yield* Effect.fail(new Error(\"This server requires manual code entry, which the CLI does not support\"))\n\n process.stdout.write(attempt.instructions + EOL + attempt.url + EOL)\n\n const result = yield* poll(client, integration.id, attempt.attemptID)\n if (result.status === \"complete\") {\n process.stdout.write(`Authenticated with ${input.name}` + EOL)\n return\n }\n const reason = result.status === \"failed\" ? `: ${result.message}` : \"\"\n return yield* Effect.fail(new Error(`Authentication ${result.status}${reason}`))\n }),\n)\n\nconst poll = (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n): Effect.Effect<Exclude<IntegrationAttemptStatus, { status: \"pending\" }>> =>\n Effect.gen(function* () {\n const status = yield* Effect.promise(() =>\n client.integration.oauth.status({ integrationID, attemptID, location }),\n ).pipe(Effect.map((result) => result.data))\n if (status.status === \"pending\") {\n yield* Effect.sleep(\"1 second\")\n return yield* poll(client, integrationID, attemptID)\n }\n return status\n })\n" | ||
| ], | ||
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| "debugId": "DF90C063B3CED6DA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/api.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { ServerConnection } from \"../../services/server-connection\"\n\nconst methods = new Set([\"delete\", \"get\", \"head\", \"options\", \"patch\", \"post\", \"put\"])\n\ntype Operation = {\n operationId?: string\n}\n\ntype OpenApi = {\n paths?: Record<string, Record<string, Operation>>\n}\n\nexport default Runtime.handler(\n Commands.commands.api,\n Effect.fn(\"cli.api\")(function* (input) {\n const server = yield* ServerConnection.resolve({\n server: Option.getOrUndefined(input.server),\n standalone: input.standalone,\n mismatch: \"ignore\",\n })\n const endpoint = server.endpoint\n const params = Option.getOrElse(input.param, () => ({}))\n const request = yield* resolveRequest(endpoint, input.request, params)\n const headers = new Headers(Service.headers(endpoint))\n for (const header of input.header) {\n const index = header.indexOf(\":\")\n if (index < 1) return yield* Effect.fail(new Error(`Invalid header, expected name:value: ${header}`))\n headers.set(header.slice(0, index).trim(), header.slice(index + 1).trim())\n }\n const body = Option.getOrUndefined(input.data)\n if (body !== undefined && !headers.has(\"content-type\")) headers.set(\"content-type\", \"application/json\")\n\n const response = yield* Effect.tryPromise(() =>\n fetch(new URL(request.path, endpoint.url), {\n method: request.method,\n headers,\n body,\n }),\n )\n const output = yield* Effect.promise(() => response.text())\n if (output) process.stdout.write(output + (output.endsWith(EOL) ? \"\" : EOL))\n }),\n)\n\nexport function resolveOperation(spec: OpenApi, operationID: string, params: Record<string, string>) {\n for (const [path, operations] of Object.entries(spec.paths ?? {})) {\n for (const [method, operation] of Object.entries(operations)) {\n if (!methods.has(method) || operation.operationId !== operationID) continue\n return { method: method.toUpperCase(), path: interpolate(path, params) }\n }\n }\n throw new Error(`Operation not found: ${operationID}`)\n}\n\nexport function rawRequest(input: readonly string[]) {\n if (input.length !== 2 || !methods.has(input[0].toLowerCase()) || !input[1].startsWith(\"/\")) return\n return { method: input[0].toUpperCase(), path: input[1] }\n}\n\nfunction resolveRequest(endpoint: Endpoint, input: readonly string[], params: Record<string, string>) {\n const raw = rawRequest(input)\n if (raw) return Effect.succeed(raw)\n if (input.length !== 1) return Effect.fail(new Error(\"Expected an operation name or an HTTP method and path\"))\n return Effect.tryPromise(async () => {\n const response = await fetch(new URL(\"/openapi.json\", endpoint.url), { headers: Service.headers(endpoint) })\n if (!response.ok) throw new Error(`Failed to load OpenAPI document: HTTP ${response.status}`)\n return resolveOperation((await response.json()) as OpenApi, input[0], params)\n })\n}\n\nfunction interpolate(path: string, params: Record<string, string>) {\n const used = new Set<string>()\n const pathname = path.replaceAll(/\\{([^}]+)\\}/g, (_, name: string) => {\n const value = params[name]\n if (value === undefined) throw new Error(`Missing path parameter: ${name}`)\n used.add(name)\n return encodeURIComponent(value)\n })\n const query = new URLSearchParams(Object.entries(params).filter(([name]) => !used.has(name))).toString()\n return query ? `${pathname}?${query}` : pathname\n}\n" | ||
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| "debugId": "31B96FF3E4B8ACB964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/stop.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.stop,\n Effect.fn(\"cli.service.stop\")(function* () {\n yield* Service.stop(yield* ServiceConfig.options())\n }),\n)\n" | ||
| ], | ||
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| "debugId": "5D5938320845FF7164756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
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| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-compatible-chat.ts"], | ||
| "sourcesContent": [ | ||
| "import { Route, type RouteRoutedModelInput } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport * as OpenAIChat from \"./openai-chat\"\n\nconst ADAPTER = \"openai-compatible-chat\"\n\nexport type OpenAICompatibleChatModelInput = RouteRoutedModelInput\n\n/**\n * Route for non-OpenAI providers that expose an OpenAI Chat-compatible\n * `/chat/completions` endpoint. Reuses `OpenAIChat.protocol` end-to-end and\n * overrides only the route id so providers can be resolved per-family without\n * colliding with native OpenAI. Provider helpers configure the route endpoint\n * before model selection.\n */\nexport const route = Route.make({\n id: ADAPTER,\n providerMetadataKey: \"openai\",\n protocol: OpenAIChat.protocol,\n endpoint: Endpoint.path(\"/chat/completions\"),\n framing: Framing.sse,\n})\n\nexport * as OpenAICompatibleChat from \"./openai-compatible-chat\"\n" | ||
| ], | ||
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| "debugId": "55D6846C07C7DC4964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/plugin/sdk.ts", "../plugin/src/v2/effect/tool.ts", "../plugin/src/v2/effect/plugin.ts", "../schema/src/session.ts", "../schema/src/command.ts", "../schema/src/reference.ts"], | ||
| "sourcesContent": [ | ||
| "export * as SdkPlugins from \"./sdk\"\n\nimport type { Plugin } from \"@opencode-ai/plugin/v2/effect/plugin\"\nimport { Context, Effect, Layer } from \"effect\"\nimport { makeGlobalNode } from \"../effect/app-node\"\nimport { EventV2 } from \"../event\"\nimport type { PluginV2 } from \"../plugin\"\n\nexport const Updated = EventV2.ephemeral({ type: \"sdk.plugin.updated\", schema: {} })\n\n/**\n * Holds the plugins an embedder (the `@opencode-ai/sdk-next` host) contributes,\n * so `PluginSupervisor` can add them on every Location boot through the ordinary\n * generation path that `PluginSupervisor` uses for plugins discovered from\n * config. Registration publishes an unlocated update so every booted Location\n * reloads its plugin generation from the shared store.\n *\n * Each host-global layer owns one private store. Location graphs reuse that\n * layer through Effect's memoization, so separate hosts remain isolated while\n * every Location in one host sees the same registrations.\n */\nexport interface Interface {\n readonly register: (plugin: Plugin) => Effect.Effect<void>\n readonly all: () => readonly PluginV2.Versioned[]\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/SdkPlugins\") {}\n\nexport const layer = Layer.effect(\n Service,\n Effect.gen(function* () {\n const events = yield* EventV2.Service\n const plugins = new Map<string, PluginV2.Versioned>()\n let revision = 0\n return Service.of({\n register: (plugin) =>\n Effect.sync(() => {\n plugins.set(plugin.id, { ...plugin, version: String(++revision) })\n }).pipe(Effect.andThen(events.publish(Updated, {})), Effect.asVoid),\n all: () => [...plugins.values()],\n })\n }),\n)\n\nexport const node = makeGlobalNode({ service: Service, layer, deps: [EventV2.node] })\n", | ||
| "export * as Tool from \"./tool.js\"\n\nimport { Agent } from \"@opencode-ai/schema/agent\"\nimport type { LLM } from \"@opencode-ai/schema/llm\"\nimport { Session } from \"@opencode-ai/schema/session\"\nimport { SessionMessage } from \"@opencode-ai/schema/session-message\"\nimport type { StandardJSONSchemaV1, StandardSchemaV1 } from \"@standard-schema/spec\"\nimport { Effect, JsonSchema, Schema } from \"effect\"\nimport type { Hooks, Transform } from \"./registration.js\"\n\nexport interface Context {\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n readonly progress: (update: Progress) => Effect.Effect<void>\n}\n\nexport interface Progress {\n readonly structured: Readonly<Record<string, unknown>>\n readonly content?: ReadonlyArray<Content>\n}\n\nexport type StandardSchemaType<Input = unknown, Output = Input> = StandardSchemaV1<Input, Output> &\n StandardJSONSchemaV1<Input, Output>\nexport type SchemaType<A> = Schema.Codec<A, any> | StandardSchemaType<any, A>\ntype IsAny<A> = 0 extends 1 & A ? true : false\nexport type InputValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<infer A, any>\n ? A\n : S extends StandardSchemaV1<any, infer A>\n ? A\n : never\nexport type OutputValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<infer A, any>\n ? A\n : S extends StandardSchemaV1<infer A, any>\n ? A\n : never\nexport type EncodedValue<S> =\n IsAny<S> extends true\n ? any\n : S extends Schema.Codec<any, infer A>\n ? A\n : S extends StandardSchemaV1<any, infer A>\n ? A\n : never\n\ntype ToolDefinition = {\n readonly name: string\n readonly description: string\n readonly inputSchema: JsonSchema.JsonSchema\n readonly outputSchema?: JsonSchema.JsonSchema\n}\n\ntype ToolCall = {\n readonly input: unknown\n readonly [key: string]: unknown\n}\n\ntype ToolResultValue =\n | { readonly type: \"json\"; readonly value: unknown }\n | { readonly type: \"text\"; readonly value: unknown }\n | { readonly type: \"error\"; readonly value: unknown }\n | { readonly type: \"content\"; readonly value: ReadonlyArray<LLM.ToolContent> }\n\ntype ToolOutput = {\n readonly structured: unknown\n readonly content: ReadonlyArray<LLM.ToolContent>\n}\n\nexport class Failure extends Schema.TaggedErrorClass<Failure>()(\"LLM.ToolFailure\", {\n message: Schema.String,\n error: Schema.optional(Schema.Defect()),\n metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),\n}) {}\n\nexport class RegistrationError extends Schema.TaggedErrorClass<RegistrationError>()(\"Tool.RegistrationError\", {\n name: Schema.String,\n message: Schema.String,\n}) {}\n\nexport type Content =\n | { readonly type: \"text\"; readonly text: string }\n | { readonly type: \"file\"; readonly data: string; readonly mime: string; readonly name?: string }\n\nexport type Definition<\n Input extends SchemaType<any>,\n Structured extends SchemaType<any>,\n Output extends SchemaType<any> = any,\n> = {\n readonly description: string\n readonly input: Input\n readonly output: Output\n readonly structured?: Structured\n readonly permission?: string\n readonly toStructuredOutput?: (input: {\n readonly input: InputValue<Input>\n readonly output: EncodedValue<Output>\n }) => OutputValue<Structured>\n readonly execute: (input: InputValue<Input>, context: Context) => Effect.Effect<OutputValue<Output>, Failure>\n readonly toModelOutput?: (input: {\n readonly input: InputValue<Input>\n readonly output: EncodedValue<Output>\n }) => ReadonlyArray<Content>\n}\n\nexport type DynamicOutput = {\n readonly structured: unknown\n readonly content: ReadonlyArray<Content>\n}\n\n/**\n * Config for a tool whose input shape is a raw JSON Schema not known at compile\n * time (MCP servers, plugin manifests). Input is passed through as `unknown`;\n * `execute` returns the already-projected structured value and model content.\n */\nexport type DynamicDefinition = {\n readonly description: string\n readonly jsonSchema: JsonSchema.JsonSchema\n readonly outputSchema?: JsonSchema.JsonSchema\n readonly permission?: string\n readonly execute: (input: unknown, context: Context) => Effect.Effect<DynamicOutput, Failure>\n}\n\nexport type AnyTool = Definition<any, any> | DynamicDefinition\n\nexport function make<\n Input extends SchemaType<any>,\n Output extends SchemaType<any>,\n Structured extends SchemaType<any> = Output,\n>(config: Definition<Input, Structured, Output>): Definition<Input, Structured, Output>\nexport function make(config: DynamicDefinition): DynamicDefinition\nexport function make(config: AnyTool): AnyTool\nexport function make(config: AnyTool): AnyTool {\n return config\n}\n\nfunction toModelContent(part: Content) {\n if (part.type === \"text\") return { type: \"text\" as const, text: part.text }\n return { type: \"file\" as const, uri: `data:${part.mime};base64,${part.data}`, mime: part.mime, name: part.name }\n}\n\nexport const validateName = (name: string) =>\n /^[A-Za-z][A-Za-z0-9_-]{0,63}$/.test(name)\n ? Effect.void\n : Effect.fail(new RegistrationError({ name, message: `Invalid tool name: ${name}` }))\n\nexport const registrationEntries = (tools: Readonly<Record<string, AnyTool>>, namespace?: string) =>\n Object.entries(tools).map(([name, tool]) => {\n const normalized = name.replace(/[^a-zA-Z0-9_-]/g, \"_\")\n return {\n key: namespace === undefined ? normalized : `${namespace.replaceAll(\".\", \"_\")}_${normalized}`,\n name: normalized,\n namespace,\n tool,\n }\n })\n\nexport const validateNamespace = (namespace: string) =>\n namespace.split(\".\").every((segment) => /^[A-Za-z][A-Za-z0-9_-]{0,63}$/.test(segment))\n ? Effect.void\n : Effect.fail(\n new RegistrationError({ name: namespace, message: `Invalid tool namespace: ${JSON.stringify(namespace)}` }),\n )\n\nexport const withPermission = <T extends AnyTool>(\n tool: T,\n permission: string,\n): Omit<T, \"permission\"> & {\n readonly permission: string\n} => ({ ...tool, permission })\n\nexport const permission = (tool: AnyTool, name: string) => tool.permission ?? name\n\nexport const definition = (name: string, tool: AnyTool): ToolDefinition =>\n \"jsonSchema\" in tool\n ? {\n name,\n description: tool.description,\n inputSchema: tool.jsonSchema,\n outputSchema: tool.outputSchema,\n }\n : {\n name,\n description: tool.description,\n inputSchema: inputJsonSchema(tool.input),\n outputSchema: outputJsonSchema(tool.structured ?? tool.output),\n }\n\nexport const settle = (tool: AnyTool, call: ToolCall, context: Context): Effect.Effect<ToolOutput, Failure> =>\n Effect.gen(function* () {\n if (\"jsonSchema\" in tool) {\n const output = yield* tool.execute(call.input, context)\n return { structured: output.structured, content: output.content.map(toModelContent) }\n }\n\n const input = yield* decodeInput(tool.input, call.input)\n const value = yield* tool.execute(input, context)\n const output = yield* encodeOutput(tool.output, value)\n const structured =\n tool.structured && tool.toStructuredOutput\n ? yield* encodeOutput(tool.structured, tool.toStructuredOutput({ input, output }))\n : output\n return {\n structured,\n content:\n tool.toModelOutput?.({ input, output }).map(toModelContent) ??\n (typeof output === \"string\" ? [{ type: \"text\" as const, text: output }] : []),\n }\n })\n\nfunction decodeInput(schema: SchemaType<any>, value: unknown): Effect.Effect<any, Failure> {\n if (Schema.isSchema(schema))\n return Schema.decodeUnknownEffect(schema)(value).pipe(\n Effect.mapError((error) => new Failure({ message: `Invalid tool input: ${error.message}` })),\n )\n return validateStandard(schema, value, \"Invalid tool input\")\n}\n\nfunction encodeOutput(schema: SchemaType<any>, value: unknown): Effect.Effect<any, Failure> {\n if (Schema.isSchema(schema))\n return Schema.encodeEffect(schema)(value).pipe(\n Effect.mapError(\n (error) => new Failure({ message: `Tool returned an invalid value for its output schema: ${error.message}` }),\n ),\n )\n return validateStandard(schema, value, \"Tool returned an invalid value for its output schema\")\n}\n\nfunction validateStandard(schema: StandardSchemaType, value: unknown, prefix: string): Effect.Effect<unknown, Failure> {\n return Effect.gen(function* () {\n const pending = yield* Effect.try({\n try: () => schema[\"~standard\"].validate(value),\n catch: (error) => standardFailure(prefix, error),\n })\n const result =\n pending instanceof Promise\n ? yield* Effect.tryPromise({ try: () => pending, catch: (error) => standardFailure(prefix, error) })\n : pending\n if (result.issues)\n return yield* Effect.fail(\n new Failure({ message: `${prefix}: ${result.issues.map((issue) => issue.message).join(\", \")}` }),\n )\n return result.value\n })\n}\n\nfunction standardFailure(prefix: string, error: unknown) {\n return new Failure({ message: `${prefix}: ${error instanceof Error ? error.message : String(error)}` })\n}\n\nfunction inputJsonSchema(schema: SchemaType<any>): JsonSchema.JsonSchema {\n if (!Schema.isSchema(schema))\n return schema[\"~standard\"].jsonSchema.input({ target: \"draft-2020-12\" }) as JsonSchema.JsonSchema\n return toJsonSchema(schema)\n}\n\nfunction outputJsonSchema(schema: SchemaType<any>): JsonSchema.JsonSchema {\n if (!Schema.isSchema(schema))\n return schema[\"~standard\"].jsonSchema.output({ target: \"draft-2020-12\" }) as JsonSchema.JsonSchema\n return toJsonSchema(schema)\n}\n\nfunction toJsonSchema(schema: Schema.Top): JsonSchema.JsonSchema {\n const document = Schema.toJsonSchemaDocument(schema)\n if (Object.keys(document.definitions).length === 0) return document.schema\n return { ...document.schema, $defs: document.definitions }\n}\n\nexport interface ToolExecuteBeforeEvent {\n readonly tool: string\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n input: unknown\n}\n\nexport interface ToolExecuteAfterEvent {\n readonly tool: string\n readonly sessionID: Session.ID\n readonly agent: Agent.ID\n readonly messageID: SessionMessage.ID\n readonly callID: string\n readonly input: unknown\n result: ToolResultValue\n output?: ToolOutput\n outputPaths?: ReadonlyArray<string>\n}\n\nexport interface RegisterOptions {\n readonly namespace?: string\n /** Defaults to true. False exposes the tool directly to the provider. */\n readonly codemode?: boolean\n}\n\nexport interface ToolDraft {\n add(name: string, tool: AnyTool, options?: RegisterOptions): void\n}\n\nexport interface ToolHooks {\n readonly \"execute.before\": ToolExecuteBeforeEvent\n readonly \"execute.after\": ToolExecuteAfterEvent\n}\n\nexport interface ToolDomain {\n readonly transform: Transform<ToolDraft>\n readonly hook: Hooks<ToolHooks>\n}\n", | ||
| "import type { PluginApi } from \"@opencode-ai/client/effect/api\"\nimport type { Effect, Scope } from \"effect\"\nimport type { PluginOptions } from \"../options.js\"\nimport type { AgentDomain } from \"./agent.js\"\nimport type { AISDKDomain } from \"./aisdk.js\"\nimport type { CatalogDomain } from \"./catalog.js\"\nimport type { CommandDomain } from \"./command.js\"\nimport type { EventDomain } from \"./event.js\"\nimport type { IntegrationDomain } from \"./integration.js\"\nimport type { ReferenceDomain } from \"./reference.js\"\nimport type { SessionDomain } from \"./session.js\"\nimport type { SkillDomain } from \"./skill.js\"\nimport type { ToolDomain } from \"./tool.js\"\n\nexport interface Context {\n readonly options: PluginOptions\n readonly agent: AgentDomain\n readonly aisdk: AISDKDomain\n readonly catalog: CatalogDomain\n readonly command: CommandDomain\n readonly event: EventDomain\n readonly integration: IntegrationDomain\n readonly plugin: PluginApi<unknown>\n readonly reference: ReferenceDomain\n readonly session: SessionDomain\n readonly skill: SkillDomain\n readonly tool: ToolDomain\n}\n\nexport interface Plugin<R = Scope.Scope> {\n readonly id: string\n readonly effect: (context: Context) => Effect.Effect<void, never, R>\n}\n\nexport function define<R = Scope.Scope>(plugin: Plugin<R>) {\n return plugin\n}\n", | ||
| "export * as Session from \"./session.js\"\n\nimport { Schema } from \"effect\"\nimport { Agent } from \"./agent.js\"\nimport { Location } from \"./location.js\"\nimport { Model } from \"./model.js\"\nimport { Project } from \"./project.js\"\nimport { DateTimeUtcFromMillis, optional, RelativePath } from \"./schema.js\"\nimport { SessionEvent } from \"./session-event.js\"\nimport { SessionID } from \"./session-id.js\"\nimport { SessionMessage } from \"./session-message.js\"\nimport { Money } from \"./money.js\"\nimport { TokenUsage } from \"./token-usage.js\"\nimport { Revert } from \"./session-revert.js\"\n\nexport const ID = SessionID\nexport type ID = SessionID\n\nexport const Event = SessionEvent\n\nexport { Revert }\n\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\nexport const Info = Schema.Struct({\n id: ID,\n parentID: ID.pipe(optional),\n fork: Schema.Struct({\n sessionID: ID,\n /** Messages before this exclusive boundary are copied into the fork. */\n messageID: SessionMessage.ID.pipe(optional),\n }).pipe(optional),\n projectID: Project.ID,\n agent: Agent.ID.pipe(optional),\n model: Model.Ref.pipe(optional),\n cost: Money.USD,\n tokens: TokenUsage.Info,\n time: Schema.Struct({\n created: DateTimeUtcFromMillis,\n updated: DateTimeUtcFromMillis,\n archived: DateTimeUtcFromMillis.pipe(optional),\n }),\n title: Schema.String,\n location: Location.Ref,\n subpath: RelativePath.pipe(optional),\n revert: Revert.pipe(optional),\n}).annotate({ identifier: \"Session.Info\" })\n\nexport const ListAnchor = Schema.Struct({\n id: ID,\n time: Schema.Finite,\n direction: Schema.Literals([\"previous\", \"next\"]),\n}).annotate({ identifier: \"Session.ListAnchor\" })\nexport interface ListAnchor extends Schema.Schema.Type<typeof ListAnchor> {}\n", | ||
| "export * as Command from \"./command.js\"\n\nimport { Schema } from \"effect\"\nimport { ephemeral, inventory } from \"./event.js\"\nimport { optional } from \"./schema.js\"\nimport { Model } from \"./model.js\"\nimport { Agent } from \"./agent.js\"\n\nconst Updated = ephemeral({ type: \"command.updated\", schema: {} })\n\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\nexport const Info = Schema.Struct({\n name: Schema.String,\n template: Schema.String,\n description: Schema.String.pipe(optional),\n agent: Agent.ID.pipe(optional),\n model: Model.Ref.pipe(optional),\n subtask: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Command.Info\" })\n\nexport const Event = {\n Updated,\n Definitions: inventory(Updated),\n}\n", | ||
| "export * as Reference from \"./reference.js\"\n\nimport { Schema } from \"effect\"\nimport { optional } from \"./schema.js\"\nimport { ephemeral, inventory } from \"./event.js\"\nimport { AbsolutePath } from \"./schema.js\"\n\nconst Updated = ephemeral({ type: \"reference.updated\", schema: {} })\nexport const Event = { Updated, Definitions: inventory(Updated) }\n\nexport interface LocalSource extends Schema.Schema.Type<typeof LocalSource> {}\nexport const LocalSource = Schema.Struct({\n type: Schema.Literal(\"local\"),\n path: AbsolutePath,\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Reference.LocalSource\" })\n\nexport interface GitSource extends Schema.Schema.Type<typeof GitSource> {}\nexport const GitSource = Schema.Struct({\n type: Schema.Literal(\"git\"),\n repository: Schema.String,\n branch: Schema.String.pipe(optional),\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n}).annotate({ identifier: \"Reference.GitSource\" })\n\nexport const Source = Schema.Union([LocalSource, GitSource])\n .pipe(Schema.toTaggedUnion(\"type\"))\n .annotate({ identifier: \"Reference.Source\" })\nexport type Source = typeof Source.Type\n\nexport const Info = Schema.Struct({\n name: Schema.String,\n path: AbsolutePath,\n description: Schema.String.pipe(optional),\n hidden: Schema.Boolean.pipe(optional),\n source: Source,\n}).annotate({ identifier: \"Reference.Info\" })\nexport interface Info extends Schema.Schema.Type<typeof Info> {}\n" | ||
| ], | ||
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| ||
| "debugId": "A56DEA607909CE8A64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/unset.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.unset,\n Effect.fn(\"cli.service.unset\")(function* (input) {\n yield* ServiceConfig.unset(input.key)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "551B74A27E285C3964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openrouter.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route, type RouteDefaultsInput } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport { ProviderID, type ModelID, type ProviderOptions } from \"../schema\"\nimport * as OpenAICompatibleProfiles from \"./openai-compatible-profile\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport { isRecord } from \"../protocols/shared\"\n\nexport const profile = OpenAICompatibleProfiles.profiles.openrouter\nexport const id = ProviderID.make(profile.provider)\nconst ADAPTER = \"openrouter\"\n\nexport interface OpenRouterOptions {\n readonly [key: string]: unknown\n readonly usage?: boolean | Record<string, unknown>\n readonly reasoning?: Record<string, unknown>\n readonly promptCacheKey?: string\n}\n\nexport type OpenRouterProviderOptionsInput = ProviderOptions & {\n readonly openrouter?: OpenRouterOptions\n}\n\nexport type ModelOptions = Omit<RouteDefaultsInput, \"providerOptions\"> &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n readonly providerOptions?: OpenRouterProviderOptionsInput\n }\n\nconst OpenRouterBody = Schema.StructWithRest(Schema.Struct(OpenAIChat.bodyFields), [\n Schema.Record(Schema.String, Schema.Any),\n])\nexport type OpenRouterBody = Schema.Schema.Type<typeof OpenRouterBody>\n\nexport const protocol = Protocol.make({\n id: \"openrouter-chat\",\n body: {\n schema: OpenRouterBody,\n from: (request) =>\n OpenAIChat.protocol.body.from(request).pipe(\n Effect.map(\n (body) =>\n ({\n ...body,\n ...bodyOptions(request.providerOptions?.openrouter),\n }) as OpenRouterBody,\n ),\n ),\n },\n stream: OpenAIChat.protocol.stream,\n})\n\nconst bodyOptions = (input: unknown) => {\n const openrouter = isRecord(input) ? input : {}\n return {\n ...(openrouter.usage === true\n ? { usage: { include: true } }\n : isRecord(openrouter.usage)\n ? { usage: openrouter.usage }\n : {}),\n ...(isRecord(openrouter.reasoning) ? { reasoning: openrouter.reasoning } : {}),\n ...(typeof openrouter.promptCacheKey === \"string\" ? { prompt_cache_key: openrouter.promptCacheKey } : {}),\n }\n}\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: profile.provider,\n protocol,\n endpoint: Endpoint.path(\"/chat/completions\", { baseURL: profile.baseURL }),\n framing: Framing.sse,\n})\n\nexport const routes = [route]\n\nconst configuredRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return route.with({\n ...rest,\n endpoint: { baseURL: baseURL ?? profile.baseURL },\n auth: AuthOptions.bearer(input, \"OPENROUTER_API_KEY\"),\n })\n}\n\nexport const configure = (input: ModelOptions = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model = provider.model\n" | ||
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| "debugId": "14EF1035E3D3620264756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/get.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect, Option } from \"effect\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.get,\n Effect.fn(\"cli.service.get\")(function* (input) {\n process.stdout.write((yield* ServiceConfig.get(Option.getOrUndefined(input.key))) + EOL)\n }),\n)\n" | ||
| ], | ||
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| "debugId": "2B0B3A459E6BA6D664756E2164756E21", | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/list.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode, type McpServer } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.list,\n Effect.fn(\"cli.mcp.list\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.mcp.list({ location: { directory: process.cwd() } }))\n const servers = response.data.toSorted((a, b) => a.name.localeCompare(b.name))\n if (servers.length === 0) {\n process.stdout.write(\"No MCP servers configured\" + EOL)\n return\n }\n const width = Math.max(...servers.map((server) => server.name.length))\n const lines = servers.map(\n (server) => `${icon(server.status)} ${server.name.padEnd(width)} ${describe(server.status)}`,\n )\n process.stdout.write(lines.join(EOL) + EOL)\n }),\n)\n\nfunction icon(status: McpServer[\"status\"]) {\n switch (status.status) {\n case \"connected\":\n return \"✓\"\n case \"needs_auth\":\n return \"⚠\"\n case \"failed\":\n case \"needs_client_registration\":\n return \"✗\"\n default:\n return \"○\"\n }\n}\n\nfunction describe(status: McpServer[\"status\"]) {\n switch (status.status) {\n case \"needs_auth\":\n return \"needs authentication\"\n case \"needs_client_registration\":\n return `needs client registration: ${status.error}`\n case \"failed\":\n return `failed: ${status.error}`\n default:\n return status.status\n }\n}\n" | ||
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| "debugId": "E83E7FEDA85AE99B64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/service/restart.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.service.commands.restart,\n Effect.fn(\"cli.service.restart\")(function* () {\n const options = yield* ServiceConfig.options()\n yield* Service.stop(options)\n const transport = yield* Service.ensure(options)\n process.stdout.write(transport.url + EOL)\n }),\n)\n" | ||
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| "debugId": "FA8EC57862A8CA3764756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/xai.ts"], | ||
| "sourcesContent": [ | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { RouteDefaultsInput } from \"../route/client\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAICompatibleProfiles from \"./openai-compatible-profile\"\nimport * as OpenAICompatibleChat from \"../protocols/openai-compatible-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\n\nexport const id = ProviderID.make(\"xai\")\n\nexport type ModelOptions = RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly baseURL?: string\n }\n\nexport const routes = [OpenAIResponses.route, OpenAICompatibleChat.route]\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => AuthOptions.bearer(options, \"XAI_API_KEY\")\n\nconst configuredResponsesRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return OpenAIResponses.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? OpenAICompatibleProfiles.profiles.xai.baseURL },\n auth: auth(input),\n })\n}\n\nconst configuredChatRoute = (input: ModelOptions) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return OpenAICompatibleChat.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? OpenAICompatibleProfiles.profiles.xai.baseURL },\n auth: auth(input),\n })\n}\n\nexport const configure = (input: ModelOptions = {}) => {\n const responsesRoute = configuredResponsesRoute(input)\n const chatRoute = configuredChatRoute(input)\n const responses = (modelID: string | ModelID) => responsesRoute.model({ id: modelID })\n const chat = (modelID: string | ModelID) => chatRoute.model({ id: modelID })\n return {\n id,\n model: responses,\n responses,\n chat,\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model = provider.model\nexport const responses = provider.responses\nexport const chat = provider.chat\n" | ||
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| "debugId": "3D8F521F37A4DA7464756E2164756E21", | ||
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| } |
Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["src/services/standalone.ts", "src/services/server-connection.ts"], | ||
| "sourcesContent": [ | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { CrossSpawnSpawner } from \"@opencode-ai/core/cross-spawn-spawner\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { Deferred, Effect, Schema, Stream } from \"effect\"\nimport { ChildProcess, ChildProcessSpawner } from \"effect/unstable/process\"\nimport { randomBytes } from \"node:crypto\"\nimport { selfCommand } from \"../util/process\"\n\nconst Ready = Schema.Struct({ url: Schema.String })\nconst decodeReady = Schema.decodeUnknownPromise(Schema.fromJsonString(Ready))\n\ntype Options = {\n readonly command?: ReadonlyArray<string>\n}\n\nfunction command(password: string, options: Options) {\n const [executable, ...args] = options.command ?? [...selfCommand(), \"serve\"]\n if (!executable) throw new Error(\"Failed to resolve standalone server command\")\n return ChildProcess.make(executable, [...args, \"--stdio\", \"--port\", \"0\"], {\n cwd: process.cwd(),\n // Explicit entry wins over anything inherited, so a user-exported\n // OPENCODE_PASSWORD cannot shadow the child's lease credential.\n env: { OPENCODE_PASSWORD: password },\n extendEnv: true,\n // The server treats EOF on this pipe as the end of its ownership lease.\n // The OS closes it even when the TUI is killed before Effect finalizers run.\n stdin: \"pipe\",\n stderr: \"ignore\",\n killSignal: \"SIGTERM\",\n forceKillAfter: \"3 seconds\",\n })\n}\n\nconst makeEndpoint = Effect.fn(\"cli.standalone.endpoint\")(\n function* (options: Options) {\n const password = randomBytes(32).toString(\"base64url\")\n const spawner = yield* ChildProcessSpawner.ChildProcessSpawner\n const proc = yield* spawner.spawn(command(password, options))\n const readyLine = yield* Deferred.make<string, Error>()\n // Keep draining stdout after readiness so later server writes cannot hit EPIPE.\n yield* proc.stdout.pipe(\n Stream.decodeText(),\n Stream.splitLines,\n Stream.runForEach((line) => Deferred.succeed(readyLine, line)),\n Effect.ensuring(Deferred.fail(readyLine, new Error(\"Standalone server exited before reporting readiness\"))),\n Effect.forkScoped,\n )\n const output = yield* Deferred.await(readyLine)\n const ready = yield* Effect.tryPromise(() => decodeReady(output))\n return {\n url: ready.url,\n auth: { type: \"basic\" as const, username: \"opencode\", password },\n pid: proc.pid,\n } satisfies Endpoint & { readonly pid: number }\n },\n Effect.provide(LayerNode.compile(CrossSpawnSpawner.node)),\n)\n\nexport function start(options: Options = {}) {\n return makeEndpoint(options)\n}\n\nexport * as Standalone from \"./standalone\"\n", | ||
| "import { Service, type Endpoint, type EnsureOptions } from \"@opencode-ai/client/effect/service\"\nimport { ClientError, isUnauthorizedError, OpenCode } from \"@opencode-ai/client/promise\"\nimport { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Effect, Redacted } from \"effect\"\nimport { Env } from \"../env\"\nimport { ServiceConfig } from \"./service-config\"\nimport { Standalone } from \"./standalone\"\n\nexport type Args = {\n readonly server?: string\n readonly standalone?: boolean\n readonly mismatch?: \"replace\" | \"ignore\" | \"error\"\n readonly onStart?: EnsureOptions[\"onStart\"]\n}\n\nexport type Resolved = {\n readonly endpoint: Endpoint\n readonly service?: ReturnType<typeof managedService>\n}\n\nexport const resolve = Effect.fn(\"cli.server-connection.resolve\")(function* (args: Args) {\n if (args.server !== undefined && args.standalone)\n return yield* Effect.fail(new Error(\"--server and --standalone cannot be combined\"))\n if (args.server !== undefined) {\n const password = yield* Env.password\n const endpoint = {\n url: args.server,\n auth: password ? { type: \"basic\" as const, username: \"opencode\", password: Redacted.value(password) } : undefined,\n } satisfies Endpoint\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const health = yield* Effect.tryPromise({\n try: () => client.health.get({ signal: AbortSignal.timeout(5_000) }),\n catch: (cause) => connectError(endpoint, cause),\n })\n if (health.version !== InstallationVersion)\n process.stderr.write(\n `Warning: Server at ${endpoint.url} has version ${health.version}; this client is ${InstallationVersion}. Continuing anyway.\\n`,\n )\n return { endpoint } satisfies Resolved\n }\n if (args.standalone) {\n return { endpoint: yield* Standalone.start() } satisfies Resolved\n }\n\n const options = yield* ServiceConfig.options()\n return {\n endpoint: yield* resolveManaged({ ...options, onStart: args.onStart }, args.mismatch ?? \"replace\"),\n service: managedService(options),\n } satisfies Resolved\n})\n\nfunction managedService(options: EnsureOptions) {\n const reconnectOptions = { ...options, version: undefined }\n return {\n reconnect: () => Service.ensure(reconnectOptions),\n restart: () =>\n Effect.gen(function* () {\n yield* Service.stop(options)\n yield* Service.ensure(reconnectOptions)\n }),\n }\n}\n\nconst resolveManaged = Effect.fnUntraced(function* (\n options: EnsureOptions,\n mismatch: NonNullable<Args[\"mismatch\"]>,\n) {\n if (mismatch === \"replace\") return yield* Service.ensure(options)\n if (mismatch === \"ignore\") return yield* Service.ensure({ ...options, version: undefined })\n\n const compatible = yield* Service.discover(options)\n if (compatible !== undefined) return compatible\n const existing = yield* Service.discover({ ...options, version: undefined })\n if (existing !== undefined)\n return yield* Effect.fail(new Error(\"Background server version does not match this client\"))\n return yield* Service.ensure(options)\n})\n\nfunction connectError(endpoint: Endpoint, cause: unknown) {\n if (isUnauthorizedError(cause)) {\n return new Error(\n endpoint.auth === undefined\n ? `Server at ${endpoint.url} requires a password; set OPENCODE_PASSWORD`\n : `Server at ${endpoint.url} rejected the password`,\n { cause },\n )\n }\n if (cause instanceof ClientError && cause.reason === \"Transport\")\n return new Error(`Could not reach server at ${endpoint.url}`, { cause })\n return new Error(`Server at ${endpoint.url} did not provide a compatible V2 health response`, { cause })\n}\n\nexport * as ServerConnection from \"./server-connection\"\n" | ||
| ], | ||
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| "debugId": "F26947B2DAD7477C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/ui/timeline.tsx", "src/commands/handlers/console/login.ts"], | ||
| "sourcesContent": [ | ||
| "import { createComponent as _$createComponent } from \"@opentui/solid\";\nimport { effect as _$effect } from \"@opentui/solid\";\nimport { createTextNode as _$createTextNode } from \"@opentui/solid\";\nimport { insertNode as _$insertNode } from \"@opentui/solid\";\nimport { insert as _$insert } from \"@opentui/solid\";\nimport { setProp as _$setProp } from \"@opentui/solid\";\nimport { createElement as _$createElement } from \"@opentui/solid\";\n/** @jsxImportSource @opentui/solid */\nimport { createCliRenderer, RGBA } from \"@opentui/core\";\nimport { createScrollbackWriter, render, useKeyboard } from \"@opentui/solid\";\nimport { registerOpencodeSpinner } from \"@opencode-ai/tui/component/register-spinner\";\nimport { Show, createSignal } from \"solid-js\";\nregisterOpencodeSpinner();\nconst SPINNER_FRAMES = [\"⠋\", \"⠙\", \"⠹\", \"⠸\", \"⠼\", \"⠴\", \"⠦\", \"⠧\", \"⠇\", \"⠏\"];\nconst IDLE_TIMEOUT = 1_000;\nconst COLORS = {\n accent: RGBA.fromIndex(6),\n error: RGBA.fromIndex(1),\n foreground: RGBA.defaultForeground(),\n muted: RGBA.fromIndex(8),\n success: RGBA.fromIndex(2)\n};\nconst ROWS = {\n intro: {\n marker: \"┌\",\n color: COLORS.muted,\n connector: true\n },\n item: {\n marker: \"●\",\n color: COLORS.accent,\n connector: true\n },\n success: {\n marker: \"◇\",\n color: COLORS.success,\n connector: true\n },\n failure: {\n marker: \"■\",\n color: COLORS.error,\n connector: false\n },\n outro: {\n marker: \"└\",\n color: COLORS.muted,\n connector: false\n }\n};\nfunction row(kind, value) {\n const style = ROWS[kind];\n return createScrollbackWriter(() => (() => {\n var _el$ = _$createElement(\"box\"),\n _el$2 = _$createElement(\"box\"),\n _el$3 = _$createElement(\"text\"),\n _el$4 = _$createElement(\"text\");\n _$insertNode(_el$, _el$2);\n _$setProp(_el$, \"width\", \"100%\");\n _$setProp(_el$, \"minHeight\", 1);\n _$setProp(_el$, \"flexDirection\", \"column\");\n _$insertNode(_el$2, _el$3);\n _$insertNode(_el$2, _el$4);\n _$setProp(_el$2, \"width\", \"100%\");\n _$setProp(_el$2, \"minHeight\", 1);\n _$setProp(_el$2, \"flexDirection\", \"row\");\n _$setProp(_el$2, \"gap\", 1);\n _$setProp(_el$3, \"flexShrink\", 0);\n _$insert(_el$3, () => style.marker);\n _$setProp(_el$4, \"wrapMode\", \"word\");\n _$insert(_el$4, value);\n _$insert(_el$, _$createComponent(Show, {\n get when() {\n return style.connector;\n },\n get children() {\n var _el$5 = _$createElement(\"text\");\n _$insertNode(_el$5, _$createTextNode(`│`));\n _$effect(_$p => _$setProp(_el$5, \"fg\", COLORS.muted, _$p));\n return _el$5;\n }\n }), null);\n _$effect(_p$ => {\n var _v$ = style.color,\n _v$2 = COLORS.foreground;\n _v$ !== _p$.e && (_p$.e = _$setProp(_el$3, \"fg\", _v$, _p$.e));\n _v$2 !== _p$.t && (_p$.t = _$setProp(_el$4, \"fg\", _v$2, _p$.t));\n return _p$;\n }, {\n e: undefined,\n t: undefined\n });\n return _el$;\n })(), {\n startOnNewLine: true,\n trailingNewline: !style.connector\n });\n}\nfunction TimelineFooter(props) {\n useKeyboard(event => {\n if (event.name !== \"escape\" && !(event.ctrl && event.name === \"c\")) return;\n event.preventDefault();\n props.cancel();\n });\n return (() => {\n var _el$7 = _$createElement(\"box\");\n _$setProp(_el$7, \"width\", \"100%\");\n _$setProp(_el$7, \"height\", 1);\n _$setProp(_el$7, \"flexDirection\", \"row\");\n _$setProp(_el$7, \"gap\", 1);\n _$insert(_el$7, _$createComponent(Show, {\n get when() {\n return props.pending();\n },\n children: text => [(() => {\n var _el$8 = _$createElement(\"spinner\");\n _$setProp(_el$8, \"frames\", SPINNER_FRAMES);\n _$setProp(_el$8, \"interval\", 80);\n _$effect(_$p => _$setProp(_el$8, \"color\", COLORS.accent, _$p));\n return _el$8;\n })(), (() => {\n var _el$9 = _$createElement(\"text\");\n _$setProp(_el$9, \"wrapMode\", \"none\");\n _$setProp(_el$9, \"truncate\", true);\n _$insert(_el$9, text);\n _$effect(_$p => _$setProp(_el$9, \"fg\", COLORS.foreground, _$p));\n return _el$9;\n })()]\n }));\n return _el$7;\n })();\n}\nfunction bounded(task) {\n return new Promise(resolve => {\n const timer = setTimeout(resolve, IDLE_TIMEOUT);\n timer.unref();\n const finish = () => {\n clearTimeout(timer);\n resolve();\n };\n void task.then(finish, finish);\n });\n}\nasync function shutdown(renderer) {\n await bounded(renderer.idle());\n try {\n renderer.externalOutputMode = \"passthrough\";\n } finally {\n try {\n renderer.screenMode = \"main-screen\";\n } finally {\n if (!renderer.isDestroyed) renderer.destroy();\n }\n }\n}\nexport async function createTimelineHost() {\n const stdout = process.stdout;\n const controller = new AbortController();\n const signals = [\"SIGINT\", \"SIGHUP\", \"SIGQUIT\"];\n const cancel = () => {\n if (!controller.signal.aborted) controller.abort();\n };\n signals.forEach(signal => process.on(signal, cancel));\n if (!stdout.isTTY || !process.stdin.isTTY) {\n let closed = false;\n let writing = false;\n let active;\n let closeTask;\n const write = async (kind, text) => {\n if (closed) throw new Error(\"timeline closed\");\n if (writing) throw new Error(\"timeline write already in progress\");\n writing = true;\n try {\n const style = kind === \"pending\" ? undefined : ROWS[kind];\n const marker = kind === \"pending\" ? \".\" : ROWS[kind].marker;\n const connector = style?.connector ? \"│\\n\" : \"\";\n active = new Promise((resolve, reject) => {\n stdout.write(`${marker} ${text}\\n${connector}`, error => error ? reject(error) : resolve());\n });\n await active;\n } finally {\n writing = false;\n active = undefined;\n }\n };\n const close = () => {\n if (closeTask) return closeTask;\n closed = true;\n closeTask = (async () => {\n await active?.catch(() => {});\n signals.forEach(signal => process.off(signal, cancel));\n })();\n return closeTask;\n };\n return {\n signal: controller.signal,\n intro: text => write(\"intro\", text),\n item: text => write(\"item\", text),\n pending: text => write(\"pending\", text),\n success: text => write(\"success\", text),\n failure: text => write(\"failure\", text),\n outro: text => write(\"outro\", text),\n close\n };\n }\n let renderer;\n try {\n // Start on a fresh row so delayed SSH cursor reports cannot make\n // split-footer overwrite the shell command.\n process.stdout.write(\"\\n\");\n renderer = await createCliRenderer({\n stdin: process.stdin,\n useMouse: false,\n autoFocus: false,\n openConsoleOnError: false,\n exitOnCtrlC: false,\n exitSignals: [],\n screenMode: \"split-footer\",\n footerHeight: 1,\n externalOutputMode: \"capture-stdout\",\n consoleMode: \"disabled\",\n clearOnShutdown: false\n });\n const activeRenderer = renderer;\n const [pending, setPending] = createSignal();\n const renderTask = render(() => _$createComponent(TimelineFooter, {\n pending: pending,\n cancel: cancel\n }), activeRenderer);\n void renderTask.catch(cancel);\n await bounded(activeRenderer.idle());\n let closed = false;\n let writing = false;\n let active;\n let closeTask;\n const write = (kind, text) => {\n if (closed) return Promise.reject(new Error(\"timeline closed\"));\n if (writing) return Promise.reject(new Error(\"timeline write already in progress\"));\n writing = true;\n active = (async () => {\n if (kind === \"pending\") {\n setPending(text);\n activeRenderer.requestRender();\n } else {\n if (kind === \"success\" || kind === \"failure\" || kind === \"outro\") setPending(undefined);\n activeRenderer.writeToScrollback(row(kind, text));\n activeRenderer.requestRender();\n }\n await bounded(activeRenderer.idle());\n })().finally(() => {\n writing = false;\n active = undefined;\n });\n return active;\n };\n const close = () => {\n if (closeTask) return closeTask;\n closed = true;\n closeTask = (async () => {\n await active?.catch(() => {});\n try {\n await shutdown(activeRenderer);\n await bounded(renderTask);\n } finally {\n signals.forEach(signal => process.off(signal, cancel));\n }\n })();\n return closeTask;\n };\n return {\n signal: controller.signal,\n intro: text => write(\"intro\", text),\n item: text => write(\"item\", text),\n pending: text => write(\"pending\", text),\n success: text => write(\"success\", text),\n failure: text => write(\"failure\", text),\n outro: text => write(\"outro\", text),\n close\n };\n } catch (error) {\n try {\n if (renderer) await shutdown(renderer);\n } finally {\n signals.forEach(signal => process.off(signal, cancel));\n }\n throw error;\n }\n}", | ||
| "import { Cause, Effect, Exit, Option } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { AppProcess } from \"@opencode-ai/core/process\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { createTimelineHost, type TimelineHost } from \"../../../ui/timeline\"\n\nconst integrationID = \"opencode\"\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.console.commands.login,\n Effect.fn(\"cli.console.login\")(function* (input) {\n const timeline = yield* Effect.acquireRelease(\n Effect.promise(() => createTimelineHost()),\n (value) => request(() => value.close()).pipe(Effect.ignore),\n )\n const exit = yield* login(timeline, Option.getOrUndefined(input.url)).pipe(\n Effect.raceFirst(AppProcess.waitForAbort(timeline.signal)),\n Effect.exit,\n )\n if (Exit.isSuccess(exit)) return\n\n const cancelled = timeline.signal.aborted\n yield* request(() => timeline.failure(cancelled ? \"Authorization cancelled\" : errorMessage(exit.cause))).pipe(\n Effect.ignore,\n )\n process.exitCode = cancelled ? 130 : 1\n }),\n)\n\nconst login = Effect.fn(\"cli.console.login.run\")(function* (timeline: TimelineHost, server?: string) {\n yield* request(() => timeline.intro(\"Log in\"))\n yield* request(() => timeline.pending(\"Connecting to OpenCode...\"))\n\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const found = yield* request((signal) => client.integration.get({ integrationID, location }, { signal }))\n const integration = yield* required(found.data, \"OpenCode Console integration is unavailable\")\n const method = yield* required(\n integration.methods.find((candidate) => candidate.type === \"oauth\"),\n \"OpenCode Console login is unavailable\",\n )\n\n yield* request(() => timeline.pending(\"Starting authorization...\"))\n const started = yield* request((signal) =>\n client.integration.oauth.connect(\n {\n integrationID,\n methodID: method.id,\n inputs: server ? { server } : {},\n location,\n },\n { signal },\n ),\n )\n const attempt = started.data\n yield* Effect.addFinalizer(() =>\n request(() =>\n client.integration.oauth.cancel(\n { integrationID, attemptID: attempt.attemptID, location },\n { signal: AbortSignal.timeout(5_000) },\n ),\n ).pipe(Effect.ignore),\n )\n if (attempt.mode !== \"auto\") yield* Effect.fail(new Error(\"OpenCode Console requires a device login\"))\n\n yield* request(() => timeline.item(`Go to: ${attempt.url}`))\n yield* request(() => timeline.item(attempt.instructions))\n yield* request(async () => {\n const { default: open } = await import(\"open\")\n await open(attempt.url)\n }).pipe(Effect.ignore)\n yield* request(() => timeline.pending(\"Waiting for authorization...\"))\n\n const status = yield* waitForConsoleLogin(client, integrationID, attempt.attemptID)\n if (status.status === \"failed\") yield* Effect.fail(new Error(status.message))\n if (status.status === \"expired\") yield* Effect.fail(new Error(\"Device code expired\"))\n\n yield* request(() => timeline.success(\"Connected to OpenCode Console\"))\n yield* request(() => timeline.outro(\"Done\"))\n})\n\nconst waitForConsoleLogin = Effect.fn(\"cli.console.login.wait\")(function* (\n client: OpenCodeClient,\n integrationID: string,\n attemptID: string,\n) {\n while (true) {\n const response = yield* request((signal) =>\n client.integration.oauth.status({ integrationID, attemptID, location }, { signal }),\n )\n if (response.data.status !== \"pending\") return response.data\n yield* Effect.sleep(500)\n }\n})\n\nfunction request<A>(task: (signal: AbortSignal) => Promise<A>) {\n return Effect.tryPromise({\n try: task,\n catch: (cause) => cause,\n })\n}\n\nfunction required<A>(value: A | null | undefined, message: string) {\n return value === null || value === undefined ? Effect.fail(new Error(message)) : Effect.succeed(value)\n}\n\nfunction errorMessage(cause: Cause.Cause<unknown>) {\n const error = Cause.squash(cause)\n if (error instanceof Error) return error.message\n if (typeof error === \"object\" && error !== null && \"message\" in error && typeof error.message === \"string\") {\n return error.message\n }\n return String(error)\n}\n" | ||
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| ||
| "debugId": "E0474FCDFADBEF1364756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/installation/version.ts"], | ||
| "sourcesContent": [ | ||
| "declare global {\n const OPENCODE_VERSION: string\n const OPENCODE_CHANNEL: string\n}\n\nexport const InstallationVersion = typeof OPENCODE_VERSION === \"string\" ? OPENCODE_VERSION : \"local\"\nexport const InstallationChannel = typeof OPENCODE_CHANNEL === \"string\" ? OPENCODE_CHANNEL : \"local\"\nexport const InstallationLocal = InstallationChannel === \"local\"\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
| ], | ||
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| "debugId": "D23F9068723AC17864756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/migrate.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\n\nexport default Runtime.handler(Commands.commands.migrate, (_input) => Effect.log(\"No migrations to run.\"))\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/route/auth-options.ts"], | ||
| "sourcesContent": [ | ||
| "import type { Config, Redacted } from \"effect\"\nimport { Auth } from \"./auth\"\n\nexport type ApiKeyMode = \"optional\" | \"required\"\n\nexport type AuthOverride = {\n readonly auth: Auth.Definition\n readonly apiKey?: never\n}\n\nexport type OptionalApiKeyAuth = {\n readonly apiKey?: string | Redacted.Redacted<string> | Config.Config<string | Redacted.Redacted<string>>\n readonly auth?: never\n}\n\nexport type RequiredApiKeyAuth = {\n readonly apiKey: string | Redacted.Redacted<string> | Config.Config<string | Redacted.Redacted<string>>\n readonly auth?: never\n}\n\nexport type ProviderAuthOption<Mode extends ApiKeyMode> =\n | AuthOverride\n | (Mode extends \"optional\" ? OptionalApiKeyAuth : RequiredApiKeyAuth)\n\nexport type ModelOptions<Base, Mode extends ApiKeyMode> = Omit<Base, \"apiKey\" | \"auth\"> & ProviderAuthOption<Mode>\n\nexport type ModelArgs<Base, Mode extends ApiKeyMode> = Mode extends \"optional\"\n ? readonly [options?: ModelOptions<Base, Mode>]\n : readonly [options: ModelOptions<Base, Mode>]\n\nexport type ModelFactory<Base, Mode extends ApiKeyMode, Model> = (id: string, ...args: ModelArgs<Base, Mode>) => Model\n\n/**\n * Require at least one of the keys in `T`. Use for option shapes where any\n * subset of fields is acceptable but at least one must be present (e.g. Azure\n * accepts `resourceName` or `baseURL`).\n */\nexport type AtLeastOne<T> = {\n [K in keyof T]: Required<Pick<T, K>> & Partial<Omit<T, K>>\n}[keyof T]\n\n/**\n * Standard bearer-auth resolution for providers: honor an explicit `auth`\n * override, otherwise resolve `apiKey` (option > config var) and apply it as\n * a bearer token.\n */\nexport const bearer = (\n options: ProviderAuthOption<\"optional\">,\n envVar: string | ReadonlyArray<string>,\n): Auth.Definition => {\n if (\"auth\" in options && options.auth) return options.auth\n return (Array.isArray(envVar) ? envVar : [envVar])\n .reduce(\n (auth, name) => auth.orElse(Auth.config(name)),\n Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\"),\n )\n .bearer()\n}\n\nexport * as AuthOptions from \"./auth-options\"\n" | ||
| ], | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/server-process.ts", "src/commands/handlers/serve.ts"], | ||
| "sourcesContent": [ | ||
| "export * as ServerProcess from \"./server-process\"\n\nimport { NodeServices } from \"@effect/platform-node\"\nimport { Service, type DiscoverOptions, type Info } from \"@opencode-ai/client/effect/service\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { AppProcess } from \"@opencode-ai/core/process\"\nimport { randomBytes, randomUUID } from \"node:crypto\"\nimport path from \"node:path\"\nimport { Effect, FileSystem, Logger, Option, Redacted, Schedule, Schema } from \"effect\"\nimport { HttpServer } from \"effect/unstable/http\"\nimport { Env } from \"./env\"\nimport { ServiceConfig } from \"./services/service-config\"\nimport { Updater } from \"./services/updater\"\n\nexport type Mode = \"default\" | \"service\" | \"stdio\"\n\nexport type Options = {\n readonly mode: Mode\n readonly hostname?: string\n readonly port?: number\n}\n\n// The process effect lives until server shutdown; tracing it would parent every request to one process-lifetime trace.\nexport const run = Effect.fnUntraced(function* (options: Options) {\n return yield* processEffect(options).pipe(\n Effect.provide(Updater.layer),\n Effect.provide(LayerNode.compile(LayerNode.group([Global.node, AppProcess.node]))),\n Effect.provide(NodeServices.layer),\n )\n})\n\nconst processEffect = Effect.fnUntraced(function* (options: Options) {\n if (options.mode === \"service\") yield* Effect.sync(() => process.chdir(Global.Path.home))\n return yield* Effect.scoped(\n Effect.gen(function* () {\n const serviceOptions = options.mode === \"service\" ? yield* ServiceConfig.options() : undefined\n const config = options.mode === \"service\" ? yield* ServiceConfig.read() : {}\n const hostname = options.hostname ?? config.hostname ?? \"127.0.0.1\"\n const port = options.port ?? config.port ?? (options.mode === \"service\" ? ServiceConfig.defaultPort() : undefined)\n if (\n serviceOptions !== undefined &&\n port !== undefined &&\n (yield* Service.incumbent({ ...serviceOptions, url: serviceURL(hostname, port) })) !== undefined\n )\n return\n const { start } = yield* Effect.promise(() => import(\"@opencode-ai/server/process\"))\n const environmentPassword = yield* Env.password\n // Keep the lease credential out of the environment inherited by tools.\n if (options.mode === \"stdio\") {\n delete process.env.OPENCODE_PASSWORD\n delete process.env.OPENCODE_SERVER_PASSWORD\n }\n const password =\n options.mode === \"service\"\n ? config.password || randomBytes(32).toString(\"base64url\")\n : environmentPassword\n ? Redacted.value(environmentPassword)\n : randomBytes(32).toString(\"base64url\")\n if (!password) return yield* Effect.fail(new Error(\"Missing server password\"))\n const instanceID = randomUUID()\n const server = yield* start({\n hostname,\n port: Option.fromNullishOr(port),\n password,\n instanceID,\n service:\n serviceOptions === undefined\n ? undefined\n : {\n onListen: (address, shutdown) =>\n Effect.gen(function* () {\n if (!config.password) yield* ServiceConfig.password(password)\n return yield* register(address, password, instanceID, serviceOptions.file, shutdown)\n }),\n },\n }).pipe(\n Effect.provide(Logger.layer([], { mergeWithExisting: false })),\n Effect.catch((error) => {\n if (serviceOptions === undefined || port === undefined || !addressInUse(error)) return Effect.fail(error)\n return recognizeIncumbent(serviceOptions, hostname, port).pipe(\n Effect.flatMap((found) =>\n found\n ? Effect.void\n : Effect.fail(\n new Error(\n `Managed service port ${port} on ${hostname} is already in use by another process. ` +\n \"Configure another port with `opencode service set port <port>` and start the service again.\",\n { cause: error },\n ),\n ),\n ),\n )\n }),\n )\n if (server === undefined) return\n const url = HttpServer.formatAddress(server.address)\n console.log(options.mode === \"stdio\" ? JSON.stringify({ url }) : `server listening on ${url}`)\n if (options.mode === \"default\" && !environmentPassword) console.log(`server password ${password}`)\n const updater = yield* Updater.Service\n yield* updater.check().pipe(Effect.schedule(Schedule.spaced(\"10 minutes\")), Effect.forkScoped)\n return yield* options.mode === \"service\"\n ? server.shutdown\n : options.mode === \"stdio\"\n ? waitForStdinClose()\n : Effect.never\n }).pipe(Effect.annotateLogs({ role: \"server\" })),\n )\n})\n\nconst infoJson = Schema.fromJsonString(Service.Info)\nconst encodeInfo = Schema.encodeEffect(infoJson)\nconst decodeInfo = Schema.decodeUnknownEffect(infoJson)\n\nconst register = Effect.fnUntraced(function* (\n address: HttpServer.Address,\n password: string,\n id: string,\n file: string,\n shutdown: Effect.Effect<void>,\n) {\n const fs = yield* FileSystem.FileSystem\n const temp = file + \".\" + id + \".tmp\"\n yield* fs.makeDirectory(path.dirname(file), { recursive: true })\n const info = {\n id,\n version: InstallationVersion,\n url: HttpServer.formatAddress(address),\n pid: process.pid,\n password,\n }\n const encoded = yield* encodeInfo(info)\n const current = fs.readFileString(file).pipe(\n Effect.flatMap(decodeInfo),\n Effect.orElseSucceed(() => undefined),\n )\n const owns = (found: Info | undefined) =>\n found?.id === info.id &&\n found.version === info.version &&\n found.url === info.url &&\n found.pid === info.pid &&\n found.password === info.password\n yield* fs.writeFileString(temp, encoded, { mode: 0o600 }).pipe(Effect.andThen(fs.rename(temp, file)))\n yield* current.pipe(\n Effect.filterOrFail(owns),\n Effect.repeat(Schedule.spaced(\"5 seconds\")),\n Effect.ignore,\n Effect.andThen(shutdown),\n Effect.forkScoped,\n )\n return current.pipe(\n Effect.flatMap((found) => (owns(found) ? fs.remove(file) : Effect.void)),\n Effect.ignore,\n )\n})\n\nconst recognizeIncumbent = Effect.fnUntraced(function* (options: DiscoverOptions, hostname: string, port: number) {\n const found = yield* Service.incumbent({ ...options, url: serviceURL(hostname, port) }).pipe(\n Effect.filterOrFail((value) => value !== undefined),\n Effect.retry(Schedule.spaced(\"100 millis\")),\n Effect.timeoutOption(\"15 seconds\"),\n )\n return Option.isSome(found)\n})\n\nfunction serviceURL(hostname: string, port: number) {\n return `http://${hostname.includes(\":\") ? `[${hostname}]` : hostname}:${port}`\n}\n\nfunction addressInUse(error: unknown): boolean {\n if (typeof error !== \"object\" || error === null) return false\n if (\"code\" in error && error.code === \"EADDRINUSE\") return true\n return \"cause\" in error && addressInUse(error.cause)\n}\n\nfunction waitForStdinClose() {\n return Effect.callback<void>((resume) => {\n const close = () => resume(Effect.void)\n process.stdin.once(\"end\", close)\n process.stdin.once(\"close\", close)\n process.stdin.resume()\n if (process.stdin.readableEnded || process.stdin.destroyed) close()\n return Effect.sync(() => {\n process.stdin.off(\"end\", close)\n process.stdin.off(\"close\", close)\n process.stdin.pause()\n })\n })\n}\n", | ||
| "import { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerProcess } from \"../../server-process\"\n\nexport default Runtime.handler(\n Commands.commands.serve,\n Effect.fnUntraced(function* (input) {\n if (input.service && input.stdio) return yield* Effect.fail(new Error(\"--service and --stdio cannot be combined\"))\n return yield* ServerProcess.run({\n mode: input.service ? \"service\" : input.stdio ? \"stdio\" : \"default\",\n hostname: Option.getOrUndefined(input.hostname),\n port: Option.getOrUndefined(input.port),\n })\n }),\n)\n" | ||
| ], | ||
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| "debugId": "5B8384E95259DB6D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/openai-options.ts", "../ai/src/protocols/openai-chat.ts"], | ||
| "sourcesContent": [ | ||
| "import { Schema } from \"effect\"\nimport type { LLMRequest, TextVerbosity as TextVerbosityValue } from \"../../schema\"\nimport { ReasoningEfforts, TextVerbosity } from \"../../schema\"\n\nexport const OpenAIReasoningEfforts = ReasoningEfforts\nexport type OpenAIReasoningEffort = string\n\n// Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this\n// in lockstep with `openai-node/src/resources/responses/responses.ts`.\nexport const OpenAIResponseIncludables = [\n \"file_search_call.results\",\n \"web_search_call.results\",\n \"web_search_call.action.sources\",\n \"message.input_image.image_url\",\n \"computer_call_output.output.image_url\",\n \"code_interpreter_call.outputs\",\n \"reasoning.encrypted_content\",\n \"message.output_text.logprobs\",\n] as const\nexport type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number]\nexport const OpenAIServiceTiers = [\"auto\", \"default\", \"flex\", \"priority\"] as const\nexport type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]\n\nconst TEXT_VERBOSITY = new Set<string>([\"low\", \"medium\", \"high\"])\nconst INCLUDABLES = new Set<string>(OpenAIResponseIncludables)\nconst SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)\n\nexport const OpenAIReasoningEffort = Schema.String\nexport const OpenAITextVerbosity = TextVerbosity\nexport const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)\nexport const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)\n\nexport const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === \"string\"\n\nconst isTextVerbosity = (value: unknown): value is TextVerbosityValue =>\n typeof value === \"string\" && TEXT_VERBOSITY.has(value)\n\nconst options = (request: LLMRequest) => request.providerOptions?.openai\n\nexport const store = (request: LLMRequest): boolean | undefined => {\n const value = options(request)?.store\n return typeof value === \"boolean\" ? value : undefined\n}\n\nexport const reasoningEffort = (request: LLMRequest): string | undefined => {\n const value = options(request)?.reasoningEffort\n return typeof value === \"string\" ? value : undefined\n}\n\nexport const reasoningSummary = (request: LLMRequest): \"auto\" | undefined =>\n options(request)?.reasoningSummary === \"auto\" ? \"auto\" : undefined\n\n// Resolve the OpenAI Responses `include` field. Filters out unknown\n// includable values defensively so a typo in upstream config drops the\n// invalid entry instead of poisoning the wire body. An empty array (either\n// passed directly or produced by filtering) is treated as \"no include\" and\n// returns undefined so the request body omits the field entirely.\nexport const include = (request: LLMRequest): ReadonlyArray<OpenAIResponseIncludable> | undefined => {\n const value = options(request)?.include\n if (!Array.isArray(value)) return undefined\n const filtered = value.filter((entry): entry is OpenAIResponseIncludable => INCLUDABLES.has(entry))\n return filtered.length > 0 ? filtered : undefined\n}\n\nexport const promptCacheKey = (request: LLMRequest) => {\n const value = options(request)?.promptCacheKey\n return typeof value === \"string\" ? value : undefined\n}\n\nexport const textVerbosity = (request: LLMRequest) => {\n const value = options(request)?.textVerbosity\n return isTextVerbosity(value) ? value : undefined\n}\n\nexport const serviceTier = (request: LLMRequest) => {\n const value = options(request)?.serviceTier\n return typeof value === \"string\" && SERVICE_TIERS.has(value) ? (value as OpenAIServiceTier) : undefined\n}\n\nexport const instructions = (request: LLMRequest) => {\n const value = options(request)?.instructions\n return typeof value === \"string\" ? value : undefined\n}\n\nexport * as OpenAIOptions from \"./openai-options\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { HttpTransport } from \"../route/transport\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ReasoningPart,\n type TextPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n} from \"../schema\"\nimport { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from \"./shared\"\nimport { OpenAIOptions } from \"./utils/openai-options\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"openai-chat\"\nconst IMAGE_MIMES = new Set<string>(ProviderShared.IMAGE_MIMES)\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/chat/completions\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\n// The body schema is the provider-native JSON body. `fromRequest` below builds\n// this shape from the common `LLMRequest`, then `Route.make` validates and\n// JSON-encodes it before transport.\nconst OpenAIChatFunction = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n parameters: JsonObject,\n})\n\nconst OpenAIChatTool = Schema.Struct({\n type: Schema.tag(\"function\"),\n function: OpenAIChatFunction,\n})\ntype OpenAIChatTool = Schema.Schema.Type<typeof OpenAIChatTool>\n\nconst OpenAIChatAssistantToolCall = Schema.Struct({\n id: Schema.String,\n type: Schema.tag(\"function\"),\n function: Schema.Struct({\n name: Schema.String,\n arguments: Schema.String,\n }),\n})\ntype OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>\n\nconst OpenAIChatUserContent = Schema.Union([\n Schema.Struct({ type: Schema.Literal(\"text\"), text: Schema.String }),\n Schema.Struct({\n type: Schema.Literal(\"image_url\"),\n image_url: Schema.Struct({ url: Schema.String }),\n }),\n])\n\nconst OpenAIChatMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"system\"), content: Schema.String }),\n Schema.Struct({\n role: Schema.Literal(\"user\"),\n content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),\n }),\n Schema.Struct({\n role: Schema.Literal(\"assistant\"),\n content: Schema.NullOr(Schema.String),\n tool_calls: optionalArray(OpenAIChatAssistantToolCall),\n reasoning_content: Schema.optional(Schema.String),\n reasoning: Schema.optional(Schema.String),\n reasoning_text: Schema.optional(Schema.String),\n }),\n Schema.Struct({ role: Schema.Literal(\"tool\"), tool_call_id: Schema.String, content: Schema.String }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype OpenAIChatMessage = Schema.Schema.Type<typeof OpenAIChatMessage>\n\nconst OpenAIChatToolChoice = Schema.Union([\n Schema.Literals([\"auto\", \"none\", \"required\"]),\n Schema.Struct({\n type: Schema.tag(\"function\"),\n function: Schema.Struct({ name: Schema.String }),\n }),\n])\n\nexport const bodyFields = {\n model: Schema.String,\n messages: Schema.Array(OpenAIChatMessage),\n tools: optionalArray(OpenAIChatTool),\n tool_choice: Schema.optional(OpenAIChatToolChoice),\n stream: Schema.Literal(true),\n stream_options: Schema.optional(Schema.Struct({ include_usage: Schema.Boolean })),\n store: Schema.optional(Schema.Boolean),\n reasoning_effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),\n max_tokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n frequency_penalty: Schema.optional(Schema.Number),\n presence_penalty: Schema.optional(Schema.Number),\n seed: Schema.optional(Schema.Number),\n stop: optionalArray(Schema.String),\n}\nconst OpenAIChatBody = Schema.Struct(bodyFields)\nexport type OpenAIChatBody = Schema.Schema.Type<typeof OpenAIChatBody>\n\n// =============================================================================\n// Streaming Event Schema\n// =============================================================================\n// The event schema is one decoded SSE `data:` payload. `Framing.sse` splits the\n// byte stream into strings, then `Protocol.jsonEvent` decodes each string into\n// this provider-native event shape.\nconst OpenAIChatUsage = Schema.Struct({\n prompt_tokens: Schema.optional(Schema.Number),\n completion_tokens: Schema.optional(Schema.Number),\n total_tokens: Schema.optional(Schema.Number),\n prompt_tokens_details: optionalNull(\n Schema.Struct({\n cached_tokens: Schema.optional(Schema.Number),\n }),\n ),\n completion_tokens_details: optionalNull(\n Schema.Struct({\n reasoning_tokens: Schema.optional(Schema.Number),\n }),\n ),\n})\n\nconst OpenAIChatToolCallDeltaFunction = Schema.Struct({\n name: optionalNull(Schema.String),\n arguments: optionalNull(Schema.String),\n})\n\nconst OpenAIChatToolCallDelta = Schema.Struct({\n index: Schema.Number,\n id: optionalNull(Schema.String),\n function: optionalNull(OpenAIChatToolCallDeltaFunction),\n})\ntype OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta>\n\nconst OpenAIChatDelta = Schema.Struct({\n content: optionalNull(Schema.String),\n reasoning_content: optionalNull(Schema.String),\n reasoning: optionalNull(Schema.String),\n reasoning_text: optionalNull(Schema.String),\n tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),\n})\n\nconst OpenAIChatChoice = Schema.Struct({\n delta: optionalNull(OpenAIChatDelta),\n finish_reason: optionalNull(Schema.String),\n})\n\nexport const OpenAIChatEvent = Schema.Struct({\n choices: Schema.Array(OpenAIChatChoice),\n usage: optionalNull(OpenAIChatUsage),\n})\nexport type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>\ntype OpenAIChatRequestMessage = LLMRequest[\"messages\"][number]\n\nexport interface ParserState {\n readonly tools: ToolStream.State<number>\n readonly toolCallEvents: ReadonlyArray<LLMEvent>\n readonly usage?: Usage\n readonly finishReason?: FinishReason\n readonly lifecycle: Lifecycle.State\n readonly reasoningField?: \"reasoning\" | \"reasoning_content\" | \"reasoning_text\"\n}\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\n// Lowering is the only place that knows how common LLM messages map onto the\n// OpenAI Chat wire format. Keep provider quirks here instead of leaking native\n// fields into `LLMRequest`.\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIChatTool => ({\n type: \"function\",\n function: {\n name: tool.name,\n description: tool.description,\n parameters: ToolSchemaProjection.openAI(inputSchema),\n },\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"OpenAI Chat\", toolChoice, {\n auto: () => \"auto\" as const,\n none: () => \"none\" as const,\n required: () => \"required\" as const,\n tool: (name) => ({ type: \"function\" as const, function: { name } }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): OpenAIChatAssistantToolCall => ({\n id: part.id,\n type: \"function\",\n function: {\n name: part.name,\n arguments: ProviderShared.encodeJson(part.input),\n },\n})\n\nconst lowerMedia = Effect.fn(\"OpenAIChat.lowerMedia\")(function* (part: MediaPart) {\n const media = yield* ProviderShared.validateMedia(\"OpenAI Chat\", part, IMAGE_MIMES)\n return { type: \"image_url\" as const, image_url: { url: media.dataUrl } }\n})\n\nconst openAICompatibleReasoningContent = (native: unknown) =>\n isRecord(native) && typeof native.reasoning_content === \"string\" ? native.reasoning_content : undefined\n\nconst reasoningField = (part: ReasoningPart) => {\n const field = part.providerMetadata?.openai?.reasoningField\n if (field === \"reasoning\" || field === \"reasoning_content\" || field === \"reasoning_text\") return field\n return \"reasoning_content\"\n}\n\nconst lowerUserMessage = Effect.fn(\"OpenAIChat.lowerUserMessage\")(function* (message: OpenAIChatRequestMessage) {\n const content: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push({ type: \"text\", text: part.text })\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* lowerMedia(part))\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"user\", [\"text\", \"media\"])\n }\n if (content.every((part) => part.type === \"text\"))\n return { role: \"user\" as const, content: content.map((part) => part.text).join(\"\") }\n return { role: \"user\" as const, content }\n})\n\nconst lowerAssistantMessage = Effect.fn(\"OpenAIChat.lowerAssistantMessage\")(function* (\n message: OpenAIChatRequestMessage,\n) {\n const content: TextPart[] = []\n const reasoning: ReasoningPart[] = []\n const toolCalls: OpenAIChatAssistantToolCall[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"assistant\", [\"text\", \"reasoning\", \"tool-call\"])\n if (part.type === \"text\") {\n content.push(part)\n continue\n }\n if (part.type === \"reasoning\") {\n reasoning.push(part)\n continue\n }\n if (part.type === \"tool-call\") {\n toolCalls.push(lowerToolCall(part))\n continue\n }\n }\n const text = reasoning.map((part) => part.text).join(\"\")\n const field = reasoning[0] ? reasoningField(reasoning[0]) : \"reasoning_content\"\n return {\n role: \"assistant\" as const,\n content: content.length === 0 ? null : ProviderShared.joinText(content),\n tool_calls: toolCalls.length === 0 ? undefined : toolCalls,\n reasoning_content:\n reasoning.length === 0\n ? openAICompatibleReasoningContent(message.native?.openaiCompatible)\n : field === \"reasoning_content\"\n ? text\n : undefined,\n reasoning: reasoning.length > 0 && field === \"reasoning\" ? text : undefined,\n reasoning_text: reasoning.length > 0 && field === \"reasoning_text\" ? text : undefined,\n }\n})\n\nconst lowerToolMessages = Effect.fn(\"OpenAIChat.lowerToolMessages\")(function* (message: OpenAIChatRequestMessage) {\n const messages: OpenAIChatMessage[] = []\n const images: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Chat\", \"tool\", [\"tool-result\"])\n if (part.result.type !== \"content\") {\n messages.push({ role: \"tool\", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })\n continue\n }\n const content: ReadonlyArray<ToolContent> = part.result.value\n const text = content.filter((item) => item.type === \"text\").map((item) => item.text)\n messages.push({ role: \"tool\", tool_call_id: part.id, content: text.join(\"\\n\") })\n const files = content.filter((item) => item.type === \"file\")\n images.push(\n ...(yield* Effect.forEach(files, (item) =>\n lowerMedia({ type: \"media\", mediaType: item.mime, data: item.uri, filename: item.name }),\n )),\n )\n }\n return { messages, images }\n})\n\nconst lowerMessage = Effect.fn(\"OpenAIChat.lowerMessage\")(function* (message: OpenAIChatRequestMessage) {\n if (message.role === \"user\") return [yield* lowerUserMessage(message)]\n if (message.role === \"assistant\") return [yield* lowerAssistantMessage(message)]\n return (yield* lowerToolMessages(message)).messages\n})\n\nconst lowerMessages = Effect.fn(\"OpenAIChat.lowerMessages\")(function* (request: LLMRequest) {\n const system: OpenAIChatMessage[] =\n request.system.length === 0 ? [] : [{ role: \"system\", content: ProviderShared.joinText(request.system) }]\n const messages = [...system]\n const pendingImages: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []\n const flushImages = () => {\n if (pendingImages.length === 0) return\n messages.push({ role: \"user\", content: pendingImages.splice(0) })\n }\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"OpenAI Chat\", message)\n if (pendingImages.length > 0) {\n messages.push({ role: \"user\", content: [...pendingImages.splice(0), { type: \"text\", text: part.text }] })\n continue\n }\n const previous = messages.at(-1)\n if (previous?.role === \"user\" && typeof previous.content === \"string\")\n messages[messages.length - 1] = { role: \"user\", content: `${previous.content}\\n${part.text}` }\n else if (previous?.role === \"user\" && Array.isArray(previous.content))\n messages[messages.length - 1] = {\n role: \"user\",\n content: [...previous.content, { type: \"text\", text: part.text }],\n }\n else messages.push({ role: \"user\", content: part.text })\n continue\n }\n if (message.role === \"tool\") {\n const lowered = yield* lowerToolMessages(message)\n messages.push(...lowered.messages)\n pendingImages.push(...lowered.images)\n continue\n }\n flushImages()\n messages.push(...(yield* lowerMessage(message)))\n }\n flushImages()\n return messages\n})\n\nconst lowerOptions = Effect.fn(\"OpenAIChat.lowerOptions\")(function* (request: LLMRequest) {\n const store = OpenAIOptions.store(request)\n const reasoningEffort = OpenAIOptions.reasoningEffort(request)\n return {\n ...(store !== undefined ? { store } : {}),\n ...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),\n }\n})\n\nconst fromRequest = Effect.fn(\"OpenAIChat.fromRequest\")(function* (request: LLMRequest) {\n // `fromRequest` returns the provider body only. Endpoint, auth, framing,\n // validation, and HTTP execution are composed by `Route.make`.\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n return {\n model: request.model.id,\n messages: yield* lowerMessages(request),\n tools:\n request.tools.length === 0\n ? undefined\n : request.tools.map((tool) =>\n lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),\n ),\n tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,\n stream: true as const,\n stream_options: { include_usage: true },\n max_tokens: generation?.maxTokens,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n frequency_penalty: generation?.frequencyPenalty,\n presence_penalty: generation?.presencePenalty,\n seed: generation?.seed,\n stop: generation?.stop,\n ...(yield* lowerOptions(request)),\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// Streaming parsers are small state machines: every event returns a new state\n// plus the common `LLMEvent`s produced by that event. Tool calls are accumulated\n// because OpenAI streams JSON arguments across multiple deltas.\nconst mapFinishReason = (reason: string | null | undefined): FinishReason => {\n if (reason === \"stop\") return \"stop\"\n if (reason === \"length\") return \"length\"\n if (reason === \"content_filter\") return \"content-filter\"\n if (reason === \"function_call\" || reason === \"tool_calls\") return \"tool-calls\"\n return \"unknown\"\n}\n\n// OpenAI Chat reports `prompt_tokens` (inclusive total) with a\n// `cached_tokens` subset, and `completion_tokens` (inclusive total) with\n// a `reasoning_tokens` subset. We pass the inclusive totals through and\n// derive the non-cached breakdown so the `LLM.Usage` contract is\n// satisfied on both sides.\nconst mapUsage = (usage: OpenAIChatEvent[\"usage\"]): Usage | undefined => {\n if (!usage) return undefined\n const cached = usage.prompt_tokens_details?.cached_tokens\n const reasoning = usage.completion_tokens_details?.reasoning_tokens\n const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, cached)\n return new Usage({\n inputTokens: usage.prompt_tokens,\n outputTokens: usage.completion_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: reasoning,\n totalTokens: ProviderShared.totalTokens(usage.prompt_tokens, usage.completion_tokens, usage.total_tokens),\n providerMetadata: { openai: usage },\n })\n}\n\nconst reasoningDelta = (delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null | undefined) => {\n if (delta?.reasoning_content) return { field: \"reasoning_content\", text: delta.reasoning_content } as const\n if (delta?.reasoning) return { field: \"reasoning\", text: delta.reasoning } as const\n if (delta?.reasoning_text) return { field: \"reasoning_text\", text: delta.reasoning_text } as const\n}\n\nconst step = (state: ParserState, event: OpenAIChatEvent) =>\n Effect.gen(function* () {\n const events: LLMEvent[] = []\n const usage = mapUsage(event.usage) ?? state.usage\n const choice = event.choices[0]\n const finishReason = choice?.finish_reason ? mapFinishReason(choice.finish_reason) : state.finishReason\n const delta = choice?.delta\n const toolDeltas = delta?.tool_calls ?? []\n let tools = state.tools\n\n let lifecycle = state.lifecycle\n\n const reasoning = reasoningDelta(delta)\n const reasoningField = state.reasoningField ?? reasoning?.field\n if (reasoning)\n lifecycle = Lifecycle.reasoningDelta(lifecycle, events, \"reasoning-0\", reasoning.text, {\n openai: { reasoningField: reasoningField ?? reasoning.field },\n })\n\n if (delta?.content) {\n lifecycle = Lifecycle.reasoningEnd(lifecycle, events, \"reasoning-0\")\n lifecycle = Lifecycle.textDelta(lifecycle, events, \"text-0\", delta.content)\n }\n\n if (toolDeltas.length) lifecycle = Lifecycle.reasoningEnd(lifecycle, events, \"reasoning-0\")\n\n for (const tool of toolDeltas) {\n const result = ToolStream.appendOrStart(\n ADAPTER,\n tools,\n tool.index,\n { id: tool.id ?? undefined, name: tool.function?.name ?? undefined, text: tool.function?.arguments ?? \"\" },\n \"OpenAI Chat tool call delta is missing id or name\",\n )\n if (ToolStream.isError(result)) return yield* result\n tools = result.tools\n if (result.events.length) lifecycle = Lifecycle.stepStart(lifecycle, events)\n events.push(...result.events)\n }\n\n // Finalize accumulated tool inputs eagerly when finish_reason arrives so\n // valid calls and malformed local calls settle independently.\n const finished =\n finishReason !== undefined && state.finishReason === undefined && Object.keys(tools).length > 0\n ? yield* ToolStream.finishAll(ADAPTER, tools)\n : undefined\n\n return [\n {\n tools: finished?.tools ?? tools,\n toolCallEvents: finished?.events ?? state.toolCallEvents,\n usage,\n finishReason,\n lifecycle,\n reasoningField,\n },\n events,\n ] as const\n })\n\nconst finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {\n const events: LLMEvent[] = []\n const hasToolCalls = state.toolCallEvents.length > 0\n const reason = state.finishReason === \"stop\" && hasToolCalls ? \"tool-calls\" : state.finishReason\n const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...state.toolCallEvents)\n if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })\n return events\n}\n\n// =============================================================================\n// Protocol And OpenAI Route\n// =============================================================================\n/**\n * The OpenAI Chat protocol — request body construction, body schema, and the\n * streaming-event state machine. Reused by every route that speaks OpenAI Chat\n * over HTTP+SSE: native OpenAI, DeepSeek, TogetherAI, Cerebras, Baseten,\n * Fireworks, DeepInfra, and (once added) Azure OpenAI Chat.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: OpenAIChatBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(OpenAIChatEvent),\n initial: () => ({\n tools: ToolStream.empty<number>(),\n toolCallEvents: [],\n lifecycle: Lifecycle.initial(),\n reasoningField: undefined,\n }),\n step,\n onHalt: finishEvents,\n },\n})\n\nexport const httpTransport = HttpTransport.sseJson.with<OpenAIChatBody>()\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),\n auth: Auth.none,\n transport: httpTransport,\n})\n\nexport * as OpenAIChat from \"./openai-chat\"\n" | ||
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| ||
| "debugId": "8897E6C3EE9DC00D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/bedrock-event-stream.ts", "../ai/src/protocols/utils/bedrock-auth.ts", "../ai/src/protocols/utils/bedrock-cache.ts", "../ai/src/protocols/utils/bedrock-media.ts", "../ai/src/protocols/bedrock-converse.ts", "../ai/src/providers/amazon-bedrock.ts"], | ||
| "sourcesContent": [ | ||
| "import { EventStreamCodec } from \"@smithy/eventstream-codec\"\nimport { fromUtf8, toUtf8 } from \"@smithy/util-utf8\"\nimport { Effect, Stream } from \"effect\"\nimport { Framing } from \"../route/framing\"\nimport { ProviderShared } from \"./shared\"\n\n// Bedrock streams responses using the AWS event stream binary protocol — each\n// frame is `[length:4][headers-length:4][prelude-crc:4][headers][payload][crc:4]`.\n// We use `@smithy/eventstream-codec` to validate framing and CRCs, then\n// reconstruct the JSON wrapping by `:event-type` so the chunk schema can match.\nconst eventCodec = new EventStreamCodec(toUtf8, fromUtf8)\nconst utf8 = new TextDecoder()\n\n// Cursor-tracking buffer state. Bytes accumulate in `buffer`; `offset` is the\n// read position. Reading by `subarray` is zero-copy. We only allocate a fresh\n// buffer when a new network chunk arrives and we need to append.\ninterface FrameBufferState {\n readonly buffer: Uint8Array\n readonly offset: number\n}\n\nconst initialFrameBuffer: FrameBufferState = { buffer: new Uint8Array(0), offset: 0 }\n\nconst appendChunk = (state: FrameBufferState, chunk: Uint8Array): FrameBufferState => {\n const remaining = state.buffer.length - state.offset\n // Compact: drop the consumed prefix and append the new chunk in one alloc.\n // This bounds buffer growth to at most one network chunk past the live\n // window, regardless of stream length.\n const next = new Uint8Array(remaining + chunk.length)\n next.set(state.buffer.subarray(state.offset), 0)\n next.set(chunk, remaining)\n return { buffer: next, offset: 0 }\n}\n\nconst consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8Array) =>\n Effect.gen(function* () {\n let cursor = appendChunk(state, chunk)\n const out: object[] = []\n while (cursor.buffer.length - cursor.offset >= 4) {\n const view = cursor.buffer.subarray(cursor.offset)\n const totalLength = new DataView(view.buffer, view.byteOffset, view.byteLength).getUint32(0, false)\n if (view.length < totalLength) break\n\n const decoded = yield* Effect.try({\n try: () => eventCodec.decode(view.subarray(0, totalLength)),\n catch: (error) =>\n ProviderShared.eventError(\n route,\n `Failed to decode Bedrock Converse event-stream frame: ${\n error instanceof Error ? error.message : String(error)\n }`,\n ),\n })\n cursor = { buffer: cursor.buffer, offset: cursor.offset + totalLength }\n\n if (decoded.headers[\":message-type\"]?.value !== \"event\") continue\n const eventType = decoded.headers[\":event-type\"]?.value\n if (typeof eventType !== \"string\") continue\n const payload = utf8.decode(decoded.body)\n if (!payload) continue\n // The AWS event stream pads short payloads with a `p` field. Drop it\n // before handing the object to the chunk schema. JSON decode goes\n // through the shared Schema-driven codec to satisfy the package rule\n // against ad-hoc `JSON.parse` calls.\n const parsed = (yield* ProviderShared.parseJson(\n route,\n payload,\n \"Failed to parse Bedrock Converse event-stream payload\",\n )) as Record<string, unknown>\n delete parsed.p\n out.push({ [eventType]: parsed })\n }\n return [cursor, out] as const\n })\n\n/**\n * AWS event-stream framing for Bedrock Converse. Each frame is decoded by\n * `@smithy/eventstream-codec` (length + header + payload + CRC) and rewrapped\n * under its `:event-type` header so the chunk schema can match the JSON\n * payload directly.\n */\nexport const framing = (route: string): Framing.Definition<object> => ({\n id: \"aws-event-stream\",\n frame: (bytes) => bytes.pipe(Stream.mapAccumEffect(() => initialFrameBuffer, consumeFrames(route))),\n})\n\nexport * as BedrockEventStream from \"./bedrock-event-stream\"\n", | ||
| "import { AwsV4Signer } from \"aws4fetch\"\nimport { Effect } from \"effect\"\nimport { Headers } from \"effect/unstable/http\"\nimport { Auth, type AuthInput } from \"../../route/auth\"\nimport { ProviderShared } from \"../shared\"\n\n/**\n * AWS credentials for SigV4 signing. Bedrock also supports Bearer API key auth,\n * which provider facades configure as route auth instead of SigV4. STS-vended\n * credentials should be refreshed by the consumer (rebuild the model) before\n * they expire; the route does not refresh.\n */\nexport interface Credentials {\n readonly region: string\n readonly accessKeyId: string\n readonly secretAccessKey: string\n readonly sessionToken?: string\n}\n\nconst signRequest = (input: {\n readonly url: string\n readonly body: string\n readonly headers: Headers.Headers\n readonly credentials: Credentials\n}) =>\n Effect.tryPromise({\n try: async () => {\n const signed = await new AwsV4Signer({\n url: input.url,\n method: \"POST\",\n headers: Object.entries(input.headers),\n body: input.body,\n region: input.credentials.region,\n accessKeyId: input.credentials.accessKeyId,\n secretAccessKey: input.credentials.secretAccessKey,\n sessionToken: input.credentials.sessionToken,\n service: \"bedrock\",\n }).sign()\n return Object.fromEntries(signed.headers.entries())\n },\n catch: (error) =>\n ProviderShared.invalidRequest(\n `Bedrock Converse SigV4 signing failed: ${error instanceof Error ? error.message : String(error)}`,\n ),\n })\n\n/** Sign the exact JSON bytes with SigV4 using credentials configured on the route. */\nexport const sigV4 = (credentials: Credentials | undefined) =>\n Auth.custom((input: AuthInput) => {\n return Effect.gen(function* () {\n if (!credentials) {\n return yield* ProviderShared.invalidRequest(\n \"Bedrock Converse requires either route bearer auth or AWS credentials configured on the route\",\n )\n }\n const headersForSigning = Headers.set(input.headers, \"content-type\", \"application/json\")\n const signed = yield* signRequest({\n url: input.url,\n body: input.body,\n headers: headersForSigning,\n credentials,\n })\n return Headers.setAll(headersForSigning, signed)\n })\n })\n\n/** Bedrock route auth defaults to SigV4 and expects credentials from route configuration. */\nexport const auth = sigV4(undefined)\n\nexport * as BedrockAuth from \"./bedrock-auth\"\n", | ||
| "import { Schema } from \"effect\"\nimport type { CacheHint } from \"../../schema\"\nimport { newBreakpoints, ttlBucket, type Breakpoints } from \"./cache\"\n\n// Bedrock cache markers are positional: emit a `cachePoint` block immediately\n// after the content the caller wants treated as a cacheable prefix. Bedrock\n// accepts optional `ttl: \"5m\" | \"1h\"` on cachePoint, mirroring Anthropic.\nexport const CachePointBlock = Schema.Struct({\n cachePoint: Schema.Struct({\n type: Schema.tag(\"default\"),\n ttl: Schema.optional(Schema.Literals([\"5m\", \"1h\"])),\n }),\n})\nexport type CachePointBlock = Schema.Schema.Type<typeof CachePointBlock>\n\n// Bedrock-Claude enforces the same 4-breakpoint cap as the Anthropic Messages\n// API. Callers pass a shared counter through every `block()` call site so the\n// budget is respected across `system`, `messages`, and `tools`.\nexport const BEDROCK_BREAKPOINT_CAP = 4\n\nexport type { Breakpoints } from \"./cache\"\nexport const breakpoints = () => newBreakpoints(BEDROCK_BREAKPOINT_CAP)\n\nconst DEFAULT_5M: CachePointBlock = { cachePoint: { type: \"default\" } }\nconst DEFAULT_1H: CachePointBlock = { cachePoint: { type: \"default\", ttl: \"1h\" } }\n\nexport const block = (breakpoints: Breakpoints, cache: CacheHint | undefined): CachePointBlock | undefined => {\n if (cache?.type !== \"ephemeral\" && cache?.type !== \"persistent\") return undefined\n if (breakpoints.remaining <= 0) {\n breakpoints.dropped += 1\n return undefined\n }\n breakpoints.remaining -= 1\n return ttlBucket(cache.ttlSeconds) === \"1h\" ? DEFAULT_1H : DEFAULT_5M\n}\n\nexport * as BedrockCache from \"./bedrock-cache\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport type { MediaPart } from \"../../schema\"\nimport { ProviderShared } from \"../shared\"\n\n// Bedrock Converse accepts image `format` as the file extension and\n// `source.bytes` as base64 in the JSON wire format.\nexport const ImageFormat = Schema.Literals([\"png\", \"jpeg\", \"gif\", \"webp\"])\nexport type ImageFormat = Schema.Schema.Type<typeof ImageFormat>\n\nexport const ImageBlock = Schema.Struct({\n image: Schema.Struct({\n format: ImageFormat,\n source: Schema.Struct({ bytes: Schema.String }),\n }),\n})\nexport type ImageBlock = Schema.Schema.Type<typeof ImageBlock>\n\n// Bedrock document blocks require a user-facing name so the model can refer to\n// the uploaded document.\nexport const DocumentFormat = Schema.Literals([\"pdf\", \"csv\", \"doc\", \"docx\", \"xls\", \"xlsx\", \"html\", \"txt\", \"md\"])\nexport type DocumentFormat = Schema.Schema.Type<typeof DocumentFormat>\n\nexport const DocumentBlock = Schema.Struct({\n document: Schema.Struct({\n format: DocumentFormat,\n name: Schema.String,\n source: Schema.Struct({ bytes: Schema.String }),\n }),\n})\nexport type DocumentBlock = Schema.Schema.Type<typeof DocumentBlock>\n\nconst IMAGE_FORMATS = {\n \"image/png\": \"png\",\n \"image/jpeg\": \"jpeg\",\n \"image/jpg\": \"jpeg\",\n \"image/gif\": \"gif\",\n \"image/webp\": \"webp\",\n} as const satisfies Record<string, ImageFormat>\n\nconst DOCUMENT_FORMATS = {\n \"application/pdf\": \"pdf\",\n \"text/csv\": \"csv\",\n \"application/msword\": \"doc\",\n \"application/vnd.openxmlformats-officedocument.wordprocessingml.document\": \"docx\",\n \"application/vnd.ms-excel\": \"xls\",\n \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\": \"xlsx\",\n \"text/html\": \"html\",\n \"text/plain\": \"txt\",\n \"text/markdown\": \"md\",\n} as const satisfies Record<string, DocumentFormat>\n\nconst documentBlock = (part: MediaPart, format: DocumentFormat, bytes: string): DocumentBlock => ({\n document: {\n format,\n name: part.filename ?? `document.${format}`,\n source: { bytes },\n },\n})\n\n// Route by MIME. Known image/document formats lower into a typed block; anything\n// else fails with a clear error instead of silently degrading to a malformed\n// document block. Image MIME types not in `IMAGE_FORMATS` (e.g. `image/svg+xml`)\n// get an image-specific error so the caller knows it's a format-support issue,\n// not a kind-detection issue.\nexport const lower = Effect.fn(\"BedrockMedia.lower\")(function* (part: MediaPart) {\n const mime = part.mediaType.toLowerCase()\n const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]\n if (imageFormat) {\n const media = yield* ProviderShared.validateMedia(\n \"Bedrock Converse\",\n part,\n new Set<string>(Object.keys(IMAGE_FORMATS)),\n )\n return { image: { format: imageFormat, source: { bytes: media.base64 } } } satisfies ImageBlock\n }\n if (mime.startsWith(\"image/\"))\n return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)\n const documentFormat = DOCUMENT_FORMATS[mime as keyof typeof DOCUMENT_FORMATS]\n if (documentFormat) {\n const media = yield* ProviderShared.validateMedia(\n \"Bedrock Converse\",\n part,\n new Set<string>(Object.keys(DOCUMENT_FORMATS)),\n )\n return documentBlock(part, documentFormat, media.base64)\n }\n return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)\n})\n\nexport * as BedrockMedia from \"./bedrock-media\"\n", | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type CacheHint,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type ModelToolSchemaCompatibility,\n type ProviderMetadata,\n type ReasoningPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolResultPart,\n} from \"../schema\"\nimport { BedrockEventStream } from \"./bedrock-event-stream\"\nimport { classifyProviderFailure } from \"../provider-error\"\nimport { JsonObject, optionalArray, ProviderShared } from \"./shared\"\nimport { BedrockAuth } from \"./utils/bedrock-auth\"\nimport { BedrockCache } from \"./utils/bedrock-cache\"\nimport { BedrockMedia } from \"./utils/bedrock-media\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\nimport { ToolStream } from \"./utils/tool-stream\"\n\nconst ADAPTER = \"bedrock-converse\"\n\nexport type { Credentials as BedrockCredentials } from \"./utils/bedrock-auth\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst BedrockTextBlock = Schema.Struct({\n text: Schema.String,\n})\ntype BedrockTextBlock = Schema.Schema.Type<typeof BedrockTextBlock>\n\nconst BedrockToolUseBlock = Schema.Struct({\n toolUse: Schema.Struct({\n toolUseId: Schema.String,\n name: Schema.String,\n input: Schema.Unknown,\n }),\n})\ntype BedrockToolUseBlock = Schema.Schema.Type<typeof BedrockToolUseBlock>\n\nconst BedrockToolResultContentItem = Schema.Union([\n Schema.Struct({ text: Schema.String }),\n Schema.Struct({ json: Schema.Unknown }),\n BedrockMedia.ImageBlock,\n])\n\nconst BedrockToolResultBlock = Schema.Struct({\n toolResult: Schema.Struct({\n toolUseId: Schema.String,\n content: Schema.Array(BedrockToolResultContentItem),\n status: Schema.optional(Schema.Literals([\"success\", \"error\"])),\n }),\n})\ntype BedrockToolResultBlock = Schema.Schema.Type<typeof BedrockToolResultBlock>\n\nconst BedrockReasoningBlock = Schema.Struct({\n reasoningContent: Schema.Struct({\n reasoningText: Schema.optional(\n Schema.Struct({\n text: Schema.String,\n signature: Schema.optional(Schema.String),\n }),\n ),\n }),\n})\n\nconst BedrockUserBlock = Schema.Union([\n BedrockTextBlock,\n BedrockMedia.ImageBlock,\n BedrockMedia.DocumentBlock,\n BedrockToolResultBlock,\n BedrockCache.CachePointBlock,\n])\ntype BedrockUserBlock = Schema.Schema.Type<typeof BedrockUserBlock>\n\nconst BedrockAssistantBlock = Schema.Union([\n BedrockTextBlock,\n BedrockReasoningBlock,\n BedrockToolUseBlock,\n BedrockCache.CachePointBlock,\n])\ntype BedrockAssistantBlock = Schema.Schema.Type<typeof BedrockAssistantBlock>\n\nconst BedrockMessage = Schema.Union([\n Schema.Struct({ role: Schema.Literal(\"user\"), content: Schema.Array(BedrockUserBlock) }),\n Schema.Struct({ role: Schema.Literal(\"assistant\"), content: Schema.Array(BedrockAssistantBlock) }),\n]).pipe(Schema.toTaggedUnion(\"role\"))\ntype BedrockMessage = Schema.Schema.Type<typeof BedrockMessage>\n\nconst BedrockSystemBlock = Schema.Union([BedrockTextBlock, BedrockCache.CachePointBlock])\ntype BedrockSystemBlock = Schema.Schema.Type<typeof BedrockSystemBlock>\n\nconst BedrockToolSpec = Schema.Struct({\n toolSpec: Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n inputSchema: Schema.Struct({\n json: JsonObject,\n }),\n }),\n})\ntype BedrockToolSpec = Schema.Schema.Type<typeof BedrockToolSpec>\n\nconst BedrockTool = Schema.Union([BedrockToolSpec, BedrockCache.CachePointBlock])\ntype BedrockTool = Schema.Schema.Type<typeof BedrockTool>\n\nconst BedrockToolChoice = Schema.Union([\n Schema.Struct({ auto: Schema.Struct({}) }),\n Schema.Struct({ any: Schema.Struct({}) }),\n Schema.Struct({ tool: Schema.Struct({ name: Schema.String }) }),\n])\n\nconst BedrockBodyFields = {\n modelId: Schema.String,\n messages: Schema.Array(BedrockMessage),\n system: optionalArray(BedrockSystemBlock),\n inferenceConfig: Schema.optional(\n Schema.Struct({\n maxTokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n topP: Schema.optional(Schema.Number),\n stopSequences: optionalArray(Schema.String),\n }),\n ),\n toolConfig: Schema.optional(\n Schema.Struct({\n tools: Schema.Array(BedrockTool),\n toolChoice: Schema.optional(BedrockToolChoice),\n }),\n ),\n additionalModelRequestFields: Schema.optional(JsonObject),\n}\nconst BedrockConverseBody = Schema.Struct(BedrockBodyFields)\nexport type BedrockConverseBody = Schema.Schema.Type<typeof BedrockConverseBody>\n\nconst BedrockUsageSchema = Schema.Struct({\n inputTokens: Schema.optional(Schema.Number),\n outputTokens: Schema.optional(Schema.Number),\n totalTokens: Schema.optional(Schema.Number),\n cacheReadInputTokens: Schema.optional(Schema.Number),\n cacheWriteInputTokens: Schema.optional(Schema.Number),\n})\ntype BedrockUsageSchema = Schema.Schema.Type<typeof BedrockUsageSchema>\n\n// Streaming event shape — the AWS event stream wraps each JSON payload by its\n// `:event-type` header (e.g. `messageStart`, `contentBlockDelta`). We\n// reconstruct that wrapping in `decodeFrames` below so the event schema can\n// stay a plain discriminated record.\nconst BedrockEvent = Schema.Struct({\n messageStart: Schema.optional(Schema.Struct({ role: Schema.String })),\n contentBlockStart: Schema.optional(\n Schema.Struct({\n contentBlockIndex: Schema.Number,\n start: Schema.optional(\n Schema.Struct({\n toolUse: Schema.optional(Schema.Struct({ toolUseId: Schema.String, name: Schema.String })),\n }),\n ),\n }),\n ),\n contentBlockDelta: Schema.optional(\n Schema.Struct({\n contentBlockIndex: Schema.Number,\n delta: Schema.optional(\n Schema.Struct({\n text: Schema.optional(Schema.String),\n toolUse: Schema.optional(Schema.Struct({ input: Schema.String })),\n reasoningContent: Schema.optional(\n Schema.Struct({\n text: Schema.optional(Schema.String),\n signature: Schema.optional(Schema.String),\n }),\n ),\n }),\n ),\n }),\n ),\n contentBlockStop: Schema.optional(Schema.Struct({ contentBlockIndex: Schema.Number })),\n messageStop: Schema.optional(\n Schema.Struct({\n stopReason: Schema.String,\n additionalModelResponseFields: Schema.optional(Schema.Unknown),\n }),\n ),\n metadata: Schema.optional(\n Schema.Struct({\n usage: Schema.optional(BedrockUsageSchema),\n metrics: Schema.optional(Schema.Unknown),\n }),\n ),\n internalServerException: Schema.optional(Schema.Struct({ message: Schema.String })),\n modelStreamErrorException: Schema.optional(Schema.Struct({ message: Schema.String })),\n validationException: Schema.optional(Schema.Struct({ message: Schema.String })),\n throttlingException: Schema.optional(Schema.Struct({ message: Schema.String })),\n serviceUnavailableException: Schema.optional(Schema.Struct({ message: Schema.String })),\n})\ntype BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({\n toolSpec: {\n name: tool.name,\n description: tool.description,\n inputSchema: { json: inputSchema },\n },\n})\n\nconst lowerTools = (\n compatibility: ModelToolSchemaCompatibility | undefined,\n breakpoints: BedrockCache.Breakpoints,\n tools: ReadonlyArray<ToolDefinition>,\n): BedrockTool[] => {\n const result: BedrockTool[] = []\n for (const tool of tools) {\n result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, compatibility)))\n const cachePoint = BedrockCache.block(breakpoints, tool.cache)\n if (cachePoint) result.push(cachePoint)\n }\n return result\n}\n\nconst textWithCache = (\n breakpoints: BedrockCache.Breakpoints,\n text: string,\n cache: CacheHint | undefined,\n): Array<BedrockTextBlock | BedrockCache.CachePointBlock> => {\n const cachePoint = BedrockCache.block(breakpoints, cache)\n return cachePoint ? [{ text }, cachePoint] : [{ text }]\n}\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Bedrock Converse\", toolChoice, {\n auto: () => ({ auto: {} }) as const,\n none: () => undefined,\n required: () => ({ any: {} }) as const,\n tool: (name) => ({ tool: { name } }) as const,\n })\n\nconst bedrockMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ bedrock: metadata })\n\nconst reasoningSignature = (part: ReasoningPart) => {\n const bedrock = part.providerMetadata?.bedrock\n return (\n part.encrypted ??\n (ProviderShared.isRecord(bedrock) && typeof bedrock.signature === \"string\" ? bedrock.signature : undefined)\n )\n}\n\nconst lowerToolCall = (part: ToolCallPart): BedrockToolUseBlock => ({\n toolUse: {\n toolUseId: part.id,\n name: part.name,\n input: part.input,\n },\n})\n\nconst lowerToolResultContent = Effect.fn(\"BedrockConverse.lowerToolResultContent\")(function* (part: ToolResultPart) {\n if (part.result.type === \"text\" || part.result.type === \"error\")\n return [{ text: ProviderShared.toolResultText(part) }]\n if (part.result.type === \"json\") return [{ json: part.result.value }]\n\n const content: Array<Schema.Schema.Type<typeof BedrockToolResultContentItem>> = []\n for (const item of part.result.value) {\n if (item.type === \"text\") {\n content.push({ text: item.text })\n continue\n }\n const media = yield* BedrockMedia.lower({\n type: \"media\",\n mediaType: item.mime,\n data: item.uri,\n filename: item.name,\n })\n if (!(\"image\" in media))\n return yield* ProviderShared.invalidRequest(\"Bedrock Converse only supports image media in tool results\")\n content.push(media)\n }\n return content\n})\n\nconst lowerToolResult = Effect.fn(\"BedrockConverse.lowerToolResult\")(function* (part: ToolResultPart) {\n return {\n toolResult: {\n toolUseId: part.id,\n content: yield* lowerToolResultContent(part),\n status: part.result.type === \"error\" ? \"error\" : \"success\",\n },\n } satisfies BedrockToolResultBlock\n})\n\nconst lowerMessages = Effect.fn(\"BedrockConverse.lowerMessages\")(function* (\n request: LLMRequest,\n breakpoints: BedrockCache.Breakpoints,\n) {\n const messages: BedrockMessage[] = []\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Bedrock Converse\", message)\n const content = textWithCache(breakpoints, part.text, part.cache)\n const previous = messages.at(-1)\n if (previous?.role === \"user\")\n messages[messages.length - 1] = { role: \"user\", content: [...previous.content, ...content] }\n else messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"user\") {\n const content: BedrockUserBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"media\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"user\", [\"text\", \"media\"])\n if (part.type === \"text\") {\n content.push(...textWithCache(breakpoints, part.text, part.cache))\n continue\n }\n if (part.type === \"media\") {\n content.push(yield* BedrockMedia.lower(part))\n continue\n }\n }\n messages.push({ role: \"user\", content })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: BedrockAssistantBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"assistant\", [\n \"text\",\n \"reasoning\",\n \"tool-call\",\n ])\n if (part.type === \"text\") {\n content.push(...textWithCache(breakpoints, part.text, part.cache))\n continue\n }\n if (part.type === \"reasoning\") {\n content.push({\n reasoningContent: {\n reasoningText: { text: part.text, signature: reasoningSignature(part) },\n },\n })\n continue\n }\n if (part.type === \"tool-call\") {\n content.push(lowerToolCall(part))\n continue\n }\n }\n messages.push({ role: \"assistant\", content })\n continue\n }\n\n const content: BedrockUserBlock[] = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Bedrock Converse\", \"tool\", [\"tool-result\"])\n content.push(yield* lowerToolResult(part))\n const cachePoint = BedrockCache.block(breakpoints, part.cache)\n if (cachePoint) content.push(cachePoint)\n }\n messages.push({ role: \"user\", content })\n }\n\n return messages\n})\n\n// System prompts share the cache-point convention: emit the text block, then\n// optionally a positional `cachePoint` marker.\nconst lowerSystem = (\n breakpoints: BedrockCache.Breakpoints,\n system: ReadonlyArray<LLMRequest[\"system\"][number]>,\n): BedrockSystemBlock[] => system.flatMap((part) => textWithCache(breakpoints, part.text, part.cache))\n\nconst fromRequest = Effect.fn(\"BedrockConverse.fromRequest\")(function* (request: LLMRequest) {\n const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined\n const generation = request.generation\n // Bedrock-Claude shares Anthropic's 4-breakpoint cap. Spend the budget in\n // tools → system → messages order to favour the highest-impact prefixes.\n const breakpoints = BedrockCache.breakpoints()\n const toolConfig =\n request.tools.length > 0 && request.toolChoice?.type !== \"none\"\n ? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }\n : undefined\n const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)\n const messages = yield* lowerMessages(request, breakpoints)\n if (breakpoints.dropped > 0) {\n yield* Effect.logWarning(\n `Bedrock Converse: dropped ${breakpoints.dropped} cache breakpoint(s); the API allows at most ${BedrockCache.BEDROCK_BREAKPOINT_CAP} per request.`,\n )\n }\n return {\n modelId: request.model.id,\n messages,\n system,\n inferenceConfig:\n generation?.maxTokens === undefined &&\n generation?.temperature === undefined &&\n generation?.topP === undefined &&\n (generation?.stop === undefined || generation.stop.length === 0)\n ? undefined\n : {\n maxTokens: generation?.maxTokens,\n temperature: generation?.temperature,\n topP: generation?.topP,\n stopSequences: generation?.stop,\n },\n toolConfig,\n // Converse's base inferenceConfig has no topK; Anthropic/Nova accept it\n // as a model-specific field, so it goes through additionalModelRequestFields.\n additionalModelRequestFields: generation?.topK === undefined ? undefined : { top_k: generation.topK },\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\nconst mapFinishReason = (reason: string): FinishReason => {\n if (reason === \"end_turn\" || reason === \"stop_sequence\") return \"stop\"\n if (reason === \"max_tokens\") return \"length\"\n if (reason === \"tool_use\") return \"tool-calls\"\n if (reason === \"content_filtered\" || reason === \"guardrail_intervened\") return \"content-filter\"\n return \"unknown\"\n}\n\n// AWS Bedrock Converse reports `inputTokens` (inclusive total) with\n// `cacheReadInputTokens` and `cacheWriteInputTokens` as subsets. Pass\n// the total through and derive the non-cached breakdown. Bedrock does\n// not break reasoning out of `outputTokens` for any current model.\nconst mapUsage = (usage: BedrockUsageSchema | undefined): Usage | undefined => {\n if (!usage) return undefined\n const cacheTotal = (usage.cacheReadInputTokens ?? 0) + (usage.cacheWriteInputTokens ?? 0)\n const nonCached = ProviderShared.subtractTokens(usage.inputTokens, cacheTotal)\n return new Usage({\n inputTokens: usage.inputTokens,\n outputTokens: usage.outputTokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: usage.cacheReadInputTokens,\n cacheWriteInputTokens: usage.cacheWriteInputTokens,\n totalTokens: ProviderShared.totalTokens(usage.inputTokens, usage.outputTokens, usage.totalTokens),\n providerMetadata: { bedrock: usage },\n })\n}\n\ninterface ParserState {\n readonly tools: ToolStream.State<number>\n // Bedrock splits the finish into `messageStop` (carries `stopReason`) and\n // `metadata` (carries usage). Hold the terminal event in state so `onHalt`\n // can emit exactly one finish after both chunks have had a chance to arrive.\n readonly pendingFinish: { readonly reason: FinishReason; readonly usage?: Usage } | undefined\n readonly hasToolCalls: boolean\n readonly lifecycle: Lifecycle.State\n readonly reasoningSignatures: Readonly<Record<number, string>>\n}\n\nconst step = (state: ParserState, event: BedrockEvent) =>\n Effect.gen(function* () {\n if (event.contentBlockStart?.start?.toolUse) {\n const index = event.contentBlockStart.contentBlockIndex\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n tools: ToolStream.start(state.tools, index, {\n id: event.contentBlockStart.start.toolUse.toolUseId,\n name: event.contentBlockStart.start.toolUse.name,\n }),\n },\n [\n ...events,\n LLMEvent.toolInputStart({\n id: event.contentBlockStart.start.toolUse.toolUseId,\n name: event.contentBlockStart.start.toolUse.name,\n }),\n ],\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.text) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.textDelta(\n state.lifecycle,\n events,\n `text-${event.contentBlockDelta.contentBlockIndex}`,\n event.contentBlockDelta.delta.text,\n ),\n },\n events,\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.reasoningContent) {\n const index = event.contentBlockDelta.contentBlockIndex\n const reasoning = event.contentBlockDelta.delta.reasoningContent\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: reasoning.text\n ? Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text)\n : state.lifecycle,\n reasoningSignatures: reasoning.signature\n ? { ...state.reasoningSignatures, [index]: reasoning.signature }\n : state.reasoningSignatures,\n },\n events,\n ] as const\n }\n\n if (event.contentBlockDelta?.delta?.toolUse) {\n const index = event.contentBlockDelta.contentBlockIndex\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n index,\n event.contentBlockDelta.delta.toolUse.input,\n \"Bedrock Converse tool delta is missing its tool call\",\n )\n if (ToolStream.isError(result)) return yield* result\n const events: LLMEvent[] = []\n const lifecycle = result.events.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...result.events)\n return [{ ...state, lifecycle, tools: result.tools }, events] as const\n }\n\n if (event.contentBlockStop) {\n const index = event.contentBlockStop.contentBlockIndex\n const result = yield* ToolStream.finish(ADAPTER, state.tools, index)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length\n ? Lifecycle.stepStart(state.lifecycle, events)\n : Lifecycle.reasoningEnd(\n Lifecycle.textEnd(state.lifecycle, events, `text-${index}`),\n events,\n `reasoning-${index}`,\n state.reasoningSignatures[index]\n ? bedrockMetadata({ signature: state.reasoningSignatures[index] })\n : undefined,\n )\n events.push(...resultEvents)\n return [\n {\n ...state,\n hasToolCalls:\n resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||\n state.hasToolCalls,\n lifecycle,\n tools: result.tools,\n reasoningSignatures: Object.fromEntries(\n Object.entries(state.reasoningSignatures).filter(([key]) => key !== String(index)),\n ),\n },\n events,\n ] as const\n }\n\n if (event.messageStop) {\n return [\n {\n ...state,\n pendingFinish: { reason: mapFinishReason(event.messageStop.stopReason), usage: state.pendingFinish?.usage },\n },\n [],\n ] as const\n }\n\n if (event.metadata) {\n const usage = mapUsage(event.metadata.usage)\n return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? \"stop\", usage } }, []] as const\n }\n\n const exception = (\n [\n [\"internalServerException\", event.internalServerException],\n [\"modelStreamErrorException\", event.modelStreamErrorException],\n [\"serviceUnavailableException\", event.serviceUnavailableException],\n [\"throttlingException\", event.throttlingException],\n [\"validationException\", event.validationException],\n ] as const\n ).find((entry) => entry[1] !== undefined)\n if (exception) {\n return yield* new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({\n message: exception[1]?.message ?? \"Bedrock Converse stream error\",\n code: exception[0],\n }),\n })\n }\n\n return [state, []] as const\n })\n\nconst framing = BedrockEventStream.framing(ADAPTER)\n\nconst onHalt = (state: ParserState): ReadonlyArray<LLMEvent> =>\n state.pendingFinish\n ? (() => {\n const events: LLMEvent[] = []\n Lifecycle.finish(state.lifecycle, events, {\n reason:\n state.pendingFinish.reason === \"stop\" && state.hasToolCalls ? \"tool-calls\" : state.pendingFinish.reason,\n usage: state.pendingFinish.usage,\n })\n return events\n })()\n : []\n\n// =============================================================================\n// Protocol And Bedrock Route\n// =============================================================================\n/**\n * The Bedrock Converse protocol — request body construction, body schema, and\n * the streaming-event state machine.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: BedrockConverseBody,\n from: fromRequest,\n },\n stream: {\n event: BedrockEvent,\n initial: () => ({\n tools: ToolStream.empty<number>(),\n pendingFinish: undefined,\n hasToolCalls: false,\n lifecycle: Lifecycle.initial(),\n reasoningSignatures: {},\n }),\n step,\n onHalt,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"bedrock\",\n providerMetadataKey: \"bedrock\",\n protocol,\n // Bedrock's URL embeds the region in the route endpoint host and the\n // validated modelId in the path. We read the validated body so the URL\n // matches the body that gets signed.\n endpoint: Endpoint.path<BedrockConverseBody>(\n ({ body }) => `/model/${encodeURIComponent(body.modelId)}/converse-stream`,\n ),\n auth: BedrockAuth.auth,\n framing,\n})\n\nexport const sigV4Auth = BedrockAuth.sigV4\n\nexport * as BedrockConverse from \"./bedrock-converse\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as BedrockConverse from \"../protocols/bedrock-converse\"\nimport type { BedrockCredentials } from \"../protocols/bedrock-converse\"\n\nexport const id = ProviderID.make(\"amazon-bedrock\")\n\nexport type Config = RouteDefaultsInput & {\n readonly apiKey?: string\n readonly headers?: Record<string, string>\n readonly credentials?: BedrockCredentials\n /** AWS region. Defaults to `us-east-1` when neither this nor `credentials.region` is set. */\n readonly region?: string\n /** Override the computed `https://bedrock-runtime.<region>.amazonaws.com` URL. */\n readonly baseURL?: string\n}\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly auth?: \"bearer\" | \"sigv4\"\n readonly baseURL?: string\n readonly credentials?: BedrockCredentials\n readonly region?: string\n readonly topP?: number\n}\nexport const routes = [BedrockConverse.route]\n\nconst bedrockBaseURL = (region: string) => `https://bedrock-runtime.${region}.amazonaws.com`\n\nconst configuredRoute = (input: Config) => {\n const { apiKey, credentials, region, baseURL, ...rest } = input\n const resolvedRegion = region ?? credentials?.region ?? \"us-east-1\"\n return BedrockConverse.route.with({\n ...rest,\n provider: id,\n endpoint: { baseURL: baseURL ?? bedrockBaseURL(resolvedRegion) },\n auth: apiKey === undefined ? BedrockConverse.sigV4Auth(credentials) : Auth.bearer(apiKey),\n })\n}\n\nexport const configure = (input: Config = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) => {\n if (settings.auth === \"bearer\" && settings.apiKey === undefined)\n throw new Error(\"Amazon Bedrock bearer auth requires apiKey\")\n if (settings.auth === \"sigv4\" && settings.apiKey !== undefined)\n throw new Error(\"Amazon Bedrock SigV4 auth does not accept apiKey\")\n return configure({\n apiKey: settings.auth === \"sigv4\" ? undefined : settings.apiKey,\n baseURL: settings.baseURL,\n credentials: settings.credentials,\n generation: settings.topP === undefined ? undefined : { topP: settings.topP },\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n region: settings.region,\n }).model(modelID)\n}\n" | ||
| ], | ||
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| ||
| "debugId": "E48145E7836170B164756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/azure.ts"], | ||
| "sourcesContent": [ | ||
| "import { Auth } from \"../route/auth\"\nimport { type AtLeastOne, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route as RouteDef, RouteDefaultsInput } from \"../route/client\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID } from \"../schema\"\nimport * as OpenAIChat from \"../protocols/openai-chat\"\nimport * as OpenAIResponses from \"../protocols/openai-responses\"\nimport { withOpenAIOptions, type OpenAIProviderOptionsInput } from \"./openai-options\"\n\nexport const id = ProviderID.make(\"azure\")\nconst routeAuth = Auth.remove(\"authorization\")\n\n// Azure needs the customer's resource URL; supply either `resourceName`\n// (helper builds the URL) or `baseURL` directly.\ntype AzureURL = AtLeastOne<{ readonly resourceName: string; readonly baseURL: string }>\n\nexport type ModelOptions = AzureURL &\n RouteDefaultsInput &\n ProviderAuthOption<\"optional\"> & {\n readonly apiVersion?: string\n readonly queryParams?: Record<string, string>\n readonly useCompletionUrls?: boolean\n readonly providerOptions?: OpenAIProviderOptionsInput\n }\nexport type Config = ModelOptions\n\nexport type Settings = ProviderPackage.Settings &\n AzureURL & {\n readonly apiKey?: string\n readonly apiVersion?: string\n readonly queryParams?: Readonly<Record<string, string>>\n readonly providerOptions?: OpenAIProviderOptionsInput\n }\n\nconst resourceBaseURL = (resourceName: string) => `https://${resourceName.trim()}.openai.azure.com/openai/v1`\n\nconst responsesRoute = OpenAIResponses.route.with({\n id: \"azure-openai-responses\",\n provider: id,\n auth: routeAuth,\n endpoint: {\n query: { \"api-version\": \"v1\" },\n },\n})\n\nconst chatRoute = OpenAIChat.route.with({\n id: \"azure-openai-chat\",\n provider: id,\n auth: routeAuth,\n endpoint: {\n query: { \"api-version\": \"v1\" },\n },\n})\n\nexport const routes = [responsesRoute, chatRoute]\n\nconst defaults = (input: Config) => {\n const {\n apiKey: _,\n apiVersion: _apiVersion,\n resourceName: _resourceName,\n useCompletionUrls: _useCompletionUrls,\n baseURL: _baseURL,\n queryParams: _queryParams,\n ...rest\n } = input\n if (\"auth\" in rest) {\n const { auth: _, ...withoutAuth } = rest\n return withoutAuth\n }\n return rest\n}\n\nconst auth = (input: Config) => {\n if (\"auth\" in input && input.auth) return input.auth\n return Auth.remove(\"authorization\").andThen(\n Auth.optional(\"apiKey\" in input ? input.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"AZURE_OPENAI_API_KEY\"))\n .pipe(Auth.header(\"api-key\")),\n )\n}\n\nconst configuredRoute = <Body, Prepared>(route: RouteDef<Body, Prepared>, input: Config) =>\n route.with({\n auth: auth(input),\n endpoint: {\n // AtLeastOne guarantees at least one is set; baseURL wins if both are.\n baseURL: input.baseURL ?? resourceBaseURL(input.resourceName!),\n query: {\n ...(input.apiVersion ? { \"api-version\": input.apiVersion } : {}),\n ...input.queryParams,\n },\n },\n })\n\nexport const configure = (input: Config) => {\n const configuredResponsesRoute = configuredRoute(responsesRoute, input)\n const configuredChatRoute = configuredRoute(chatRoute, input)\n const modelDefaults = defaults(input)\n\n const responses = (modelID: string | ModelID) =>\n configuredResponsesRoute.with(withOpenAIOptions(modelID, modelDefaults)).model({ id: modelID })\n\n const chat = (modelID: string | ModelID) =>\n configuredChatRoute.with(withOpenAIOptions(modelID, modelDefaults)).model({ id: modelID })\n\n return {\n id,\n model: (modelID: string | ModelID) => (input.useCompletionUrls === true ? chat(modelID) : responses(modelID)),\n responses,\n chat,\n configure,\n }\n}\n\nexport const provider = {\n id,\n configure,\n}\n\nconst config = (settings: Settings): Config => {\n const common = {\n apiKey: settings.apiKey,\n apiVersion: settings.apiVersion,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n queryParams: settings.queryParams === undefined ? undefined : { ...settings.queryParams },\n }\n if (settings.baseURL !== undefined) return { ...common, baseURL: settings.baseURL }\n if (settings.resourceName !== undefined) return { ...common, resourceName: settings.resourceName }\n throw new Error(\"Azure requires resourceName or baseURL\")\n}\n\nexport const responsesModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).responses(modelID)\nexport const chatModel: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure(config(settings)).chat(modelID)\nexport const model = responsesModel\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/pair.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"os\"\nimport { Effect } from \"effect\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode } from \"@opencode-ai/client/promise\"\nimport { renderUnicodeCompact } from \"uqr\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServiceConfig } from \"../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.pair,\n Effect.fn(\"cli.pair\")(function* () {\n const endpoint = yield* Service.ensure(yield* ServiceConfig.options())\n const password = yield* ServiceConfig.password()\n const server = yield* Effect.tryPromise(() =>\n OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) }).server.get(),\n )\n const info = { urls: server.urls, username: \"opencode\", password }\n process.stdout.write(\n [\n \"\",\n ` URLs ${info.urls[0] ?? \"(none)\"}`,\n ...info.urls.slice(1).map((url) => ` ${url}`),\n ` Username ${info.username}`,\n ` Password ${info.password}`,\n \"\",\n \" Scan to pair\",\n \"\",\n renderUnicodeCompact(JSON.stringify(info), { border: 2 })\n .split(EOL)\n .map((line) => \" \" + line)\n .join(EOL),\n \"\",\n ].join(EOL) + EOL,\n )\n\n const hostname = new URL(endpoint.url).hostname\n if (![\"localhost\", \"127.0.0.1\", \"[::1]\"].includes(hostname)) return\n process.stderr.write(\n ` Run \\`opencode service set hostname 0.0.0.0\\` to access the service remotely.${EOL}${EOL}`,\n )\n }),\n)\n" | ||
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/gemini.ts", "../ai/src/providers/google.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { Framing } from \"../route/framing\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type MediaPart,\n type ProviderMetadata,\n type TextPart,\n type ToolCallPart,\n type ToolDefinition,\n type ToolContent,\n} from \"../schema\"\nimport { JsonObject, optionalArray, ProviderShared } from \"./shared\"\nimport { GeminiToolSchema } from \"./utils/gemini-tool-schema\"\nimport { Lifecycle } from \"./utils/lifecycle\"\nimport { ToolSchemaProjection } from \"./utils/tool-schema\"\n\nconst ADAPTER = \"gemini\"\nconst MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)\nexport const DEFAULT_BASE_URL = \"https://generativelanguage.googleapis.com/v1beta\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst GeminiTextPart = Schema.Struct({\n text: Schema.String,\n thought: Schema.optional(Schema.Boolean),\n thoughtSignature: Schema.optional(Schema.String),\n})\n\nconst GeminiInlineDataPart = Schema.Struct({\n inlineData: Schema.Struct({\n mimeType: Schema.String,\n data: Schema.String,\n }),\n})\n\nconst GeminiFunctionCallPart = Schema.Struct({\n functionCall: Schema.Struct({\n name: Schema.String,\n args: Schema.Unknown,\n }),\n thoughtSignature: Schema.optional(Schema.String),\n})\n\nconst GeminiFunctionResponsePart = Schema.Struct({\n functionResponse: Schema.Struct({\n name: Schema.String,\n response: Schema.Unknown,\n }),\n})\n\nconst GeminiContentPart = Schema.Union([\n GeminiTextPart,\n GeminiInlineDataPart,\n GeminiFunctionCallPart,\n GeminiFunctionResponsePart,\n])\n\nconst GeminiContent = Schema.Struct({\n role: Schema.Literals([\"user\", \"model\"]),\n parts: Schema.Array(GeminiContentPart),\n})\ntype GeminiContent = Schema.Schema.Type<typeof GeminiContent>\n\nconst GeminiSystemInstruction = Schema.Struct({\n parts: Schema.Array(Schema.Struct({ text: Schema.String })),\n})\n\nconst GeminiFunctionDeclaration = Schema.Struct({\n name: Schema.String,\n description: Schema.String,\n parameters: Schema.optional(JsonObject),\n})\n\nconst GeminiTool = Schema.Struct({\n functionDeclarations: Schema.Array(GeminiFunctionDeclaration),\n})\n\nconst GeminiToolConfig = Schema.Struct({\n functionCallingConfig: Schema.Struct({\n mode: Schema.Literals([\"AUTO\", \"NONE\", \"ANY\"]),\n allowedFunctionNames: optionalArray(Schema.String),\n }),\n})\n\nconst GeminiThinkingConfig = Schema.Struct({\n thinkingBudget: Schema.optional(Schema.Number),\n includeThoughts: Schema.optional(Schema.Boolean),\n})\n\nconst GeminiGenerationConfig = Schema.Struct({\n maxOutputTokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n topP: Schema.optional(Schema.Number),\n topK: Schema.optional(Schema.Number),\n stopSequences: optionalArray(Schema.String),\n thinkingConfig: Schema.optional(GeminiThinkingConfig),\n})\n\nconst GeminiBodyFields = {\n contents: Schema.Array(GeminiContent),\n systemInstruction: Schema.optional(GeminiSystemInstruction),\n tools: optionalArray(GeminiTool),\n toolConfig: Schema.optional(GeminiToolConfig),\n generationConfig: Schema.optional(GeminiGenerationConfig),\n}\nconst GeminiBody = Schema.Struct(GeminiBodyFields)\nexport type GeminiBody = Schema.Schema.Type<typeof GeminiBody>\n\nconst GeminiUsage = Schema.Struct({\n cachedContentTokenCount: Schema.optional(Schema.Number),\n thoughtsTokenCount: Schema.optional(Schema.Number),\n promptTokenCount: Schema.optional(Schema.Number),\n candidatesTokenCount: Schema.optional(Schema.Number),\n totalTokenCount: Schema.optional(Schema.Number),\n})\ntype GeminiUsage = Schema.Schema.Type<typeof GeminiUsage>\n\nconst GeminiCandidate = Schema.Struct({\n content: Schema.optional(GeminiContent),\n finishReason: Schema.optional(Schema.String),\n})\n\nconst GeminiEvent = Schema.Struct({\n candidates: optionalArray(GeminiCandidate),\n usageMetadata: Schema.optional(GeminiUsage),\n})\ntype GeminiEvent = Schema.Schema.Type<typeof GeminiEvent>\n\ninterface ParserState {\n readonly finishReason?: string\n readonly hasToolCalls: boolean\n readonly nextToolCallId: number\n readonly usage?: Usage\n readonly lifecycle: Lifecycle.State\n readonly reasoningSignature?: string\n}\n\n// =============================================================================\n// Tool Schema Conversion\n// =============================================================================\n// Tool-schema conversion has two distinct concerns:\n//\n// 1. Sanitize — fix common authoring mistakes Gemini rejects: integer/number\n// enums (must be strings), `required` entries that don't match a property,\n// untyped arrays (`items` must be present), and `properties`/`required`\n// keys on non-object scalars. Mirrors OpenCode's historical Gemini rules.\n//\n// 2. Project — lossy mapping from JSON Schema to Gemini's schema dialect:\n// drop empty objects, derive `nullable: true` from `type: [..., \"null\"]`,\n// coerce `const` to `[const]` enum, recurse properties/items, propagate\n// only an allowlisted set of keys (description, required, format, type,\n// properties, items, allOf, anyOf, oneOf, minLength). Anything outside the\n// allowlist (e.g. `additionalProperties`, `$ref`) is silently dropped.\n//\n// Sanitize runs first, then project. The implementation lives in\n// `utils/gemini-tool-schema` so this protocol keeps the same shape as the other\n// provider protocols.\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema) => ({\n name: tool.name,\n description: tool.description,\n parameters: GeminiToolSchema.convert(inputSchema),\n})\n\nconst lowerToolConfig = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"Gemini\", toolChoice, {\n auto: () => ({ functionCallingConfig: { mode: \"AUTO\" as const } }),\n none: () => ({ functionCallingConfig: { mode: \"NONE\" as const } }),\n required: () => ({ functionCallingConfig: { mode: \"ANY\" as const } }),\n tool: (name) => ({ functionCallingConfig: { mode: \"ANY\" as const, allowedFunctionNames: [name] } }),\n })\n\nconst lowerUserPart = Effect.fn(\"Gemini.lowerUserPart\")(function* (part: TextPart | MediaPart) {\n if (part.type === \"text\") return { text: part.text }\n const media = yield* ProviderShared.validateMedia(\"Gemini\", part, MEDIA_MIMES)\n return { inlineData: { mimeType: media.mime, data: media.base64 } }\n})\n\nconst googleMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ google: metadata })\n\nconst thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {\n const google = providerMetadata?.google\n return ProviderShared.isRecord(google) && typeof google.thoughtSignature === \"string\"\n ? google.thoughtSignature\n : undefined\n}\n\nconst lowerToolCall = (part: ToolCallPart) => ({\n functionCall: { name: part.name, args: part.input },\n thoughtSignature: thoughtSignature(part.providerMetadata),\n})\n\nconst lowerMessages = Effect.fn(\"Gemini.lowerMessages\")(function* (request: LLMRequest) {\n const contents: GeminiContent[] = []\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"Gemini\", message)\n const previous = contents.at(-1)\n if (previous?.role === \"user\")\n contents[contents.length - 1] = { role: \"user\", parts: [...previous.parts, { text: part.text }] }\n else contents.push({ role: \"user\", parts: [{ text: part.text }] })\n continue\n }\n\n if (message.role === \"user\") {\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"media\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"user\", [\"text\", \"media\"])\n parts.push(yield* lowerUserPart(part))\n }\n contents.push({ role: \"user\", parts })\n continue\n }\n\n if (message.role === \"assistant\") {\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"text\", \"reasoning\", \"tool-call\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"assistant\", [\"text\", \"reasoning\", \"tool-call\"])\n if (part.type === \"text\") {\n parts.push({ text: part.text })\n continue\n }\n if (part.type === \"reasoning\") {\n parts.push({ text: part.text, thought: true, thoughtSignature: thoughtSignature(part.providerMetadata) })\n continue\n }\n if (part.type === \"tool-call\") {\n parts.push(lowerToolCall(part))\n continue\n }\n }\n contents.push({ role: \"model\", parts })\n continue\n }\n\n const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"Gemini\", \"tool\", [\"tool-result\"])\n if (part.result.type !== \"content\") {\n parts.push({\n functionResponse: {\n name: part.name,\n response: {\n name: part.name,\n content: ProviderShared.toolResultText(part),\n },\n },\n })\n continue\n }\n const content: ReadonlyArray<ToolContent> = part.result.value\n const text = content.filter((item) => item.type === \"text\").map((item) => item.text)\n parts.push({\n functionResponse: {\n name: part.name,\n response: {\n name: part.name,\n content: text.join(\"\\n\"),\n },\n },\n })\n for (const item of content) {\n if (item.type === \"text\") continue\n const media = yield* ProviderShared.validateToolFile(\"Gemini\", item, MEDIA_MIMES)\n parts.push({ inlineData: { mimeType: media.mime, data: media.base64 } })\n }\n }\n contents.push({ role: \"user\", parts })\n }\n\n return contents\n})\n\nconst geminiOptions = (request: LLMRequest) => request.providerOptions?.gemini\n\nconst thinkingConfig = (request: LLMRequest) => {\n const value = geminiOptions(request)?.thinkingConfig\n if (!ProviderShared.isRecord(value)) return undefined\n const result = {\n thinkingBudget: typeof value.thinkingBudget === \"number\" ? value.thinkingBudget : undefined,\n includeThoughts: typeof value.includeThoughts === \"boolean\" ? value.includeThoughts : undefined,\n }\n return Object.values(result).some((item) => item !== undefined) ? result : undefined\n}\n\nconst fromRequest = Effect.fn(\"Gemini.fromRequest\")(function* (request: LLMRequest) {\n const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== \"none\"\n const generation = request.generation\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n const generationConfig = {\n maxOutputTokens: generation?.maxTokens,\n temperature: generation?.temperature,\n topP: generation?.topP,\n topK: generation?.topK,\n stopSequences: generation?.stop,\n thinkingConfig: thinkingConfig(request),\n }\n\n return {\n contents: yield* lowerMessages(request),\n systemInstruction:\n request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },\n tools: toolsEnabled\n ? [\n {\n functionDeclarations: request.tools.map((tool) =>\n lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),\n ),\n },\n ]\n : undefined,\n toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,\n generationConfig: Object.values(generationConfig).some((value) => value !== undefined)\n ? generationConfig\n : undefined,\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// Gemini reports `promptTokenCount` (inclusive total) with a\n// `cachedContentTokenCount` subset. `candidatesTokenCount` is *exclusive*\n// of `thoughtsTokenCount` — visible-only, not a total — so we sum the two\n// to produce the inclusive `outputTokens` the rest of the contract expects.\nconst mapUsage = (usage: GeminiUsage | undefined) => {\n if (!usage) return undefined\n const cached = usage.cachedContentTokenCount\n const nonCached = ProviderShared.subtractTokens(usage.promptTokenCount, cached)\n // `candidatesTokenCount` is visible-only; sum with thoughts to produce the\n // inclusive `outputTokens` the contract expects. Only compute the total\n // when the visible component is reported — otherwise we'd fabricate an\n // inclusive number from a partial breakdown.\n const outputTokens =\n usage.candidatesTokenCount !== undefined ? usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0) : undefined\n return new Usage({\n inputTokens: usage.promptTokenCount,\n outputTokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: usage.thoughtsTokenCount,\n totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),\n providerMetadata: { google: usage },\n })\n}\n\nconst mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean): FinishReason => {\n if (finishReason === \"STOP\") return hasToolCalls ? \"tool-calls\" : \"stop\"\n if (finishReason === \"MAX_TOKENS\") return \"length\"\n if (\n finishReason === \"IMAGE_SAFETY\" ||\n finishReason === \"RECITATION\" ||\n finishReason === \"SAFETY\" ||\n finishReason === \"BLOCKLIST\" ||\n finishReason === \"PROHIBITED_CONTENT\" ||\n finishReason === \"SPII\"\n )\n return \"content-filter\"\n if (finishReason === \"MALFORMED_FUNCTION_CALL\") return \"error\"\n return \"unknown\"\n}\n\nconst finish = (state: ParserState): ReadonlyArray<LLMEvent> =>\n state.finishReason || state.usage\n ? (() => {\n const events: LLMEvent[] = []\n const lifecycle = state.reasoningSignature\n ? Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n \"reasoning-0\",\n googleMetadata({ thoughtSignature: state.reasoningSignature }),\n )\n : state.lifecycle\n Lifecycle.finish(lifecycle, events, {\n reason: mapFinishReason(state.finishReason, state.hasToolCalls),\n usage: state.usage,\n })\n return events\n })()\n : []\n\nconst step = (state: ParserState, event: GeminiEvent) => {\n const nextState = {\n ...state,\n usage: event.usageMetadata ? (mapUsage(event.usageMetadata) ?? state.usage) : state.usage,\n }\n const candidate = event.candidates?.[0]\n if (!candidate?.content)\n return Effect.succeed([\n { ...nextState, finishReason: candidate?.finishReason ?? nextState.finishReason },\n [],\n ] as const)\n\n const events: LLMEvent[] = []\n let hasToolCalls = nextState.hasToolCalls\n let lifecycle = nextState.lifecycle\n let nextToolCallId = nextState.nextToolCallId\n let reasoningSignature = nextState.reasoningSignature\n\n for (const part of candidate.content.parts) {\n if (\"thoughtSignature\" in part && part.thoughtSignature && \"thought\" in part && part.thought)\n reasoningSignature = part.thoughtSignature\n if (\"text\" in part && part.text.length > 0) {\n if (part.thought) {\n lifecycle = Lifecycle.reasoningDelta(\n lifecycle,\n events,\n \"reasoning-0\",\n part.text,\n part.thoughtSignature ? googleMetadata({ thoughtSignature: part.thoughtSignature }) : undefined,\n )\n continue\n }\n lifecycle = Lifecycle.reasoningEnd(\n lifecycle,\n events,\n \"reasoning-0\",\n reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,\n )\n lifecycle = Lifecycle.textDelta(lifecycle, events, \"text-0\", part.text)\n continue\n }\n\n if (\"functionCall\" in part) {\n const input = part.functionCall.args\n const id = `tool_${nextToolCallId++}`\n lifecycle = Lifecycle.reasoningEnd(\n lifecycle,\n events,\n \"reasoning-0\",\n reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,\n )\n lifecycle = Lifecycle.stepStart(lifecycle, events)\n events.push(\n LLMEvent.toolCall({\n id,\n name: part.functionCall.name,\n input,\n providerMetadata: part.thoughtSignature\n ? googleMetadata({ thoughtSignature: part.thoughtSignature })\n : undefined,\n }),\n )\n hasToolCalls = true\n }\n }\n\n return Effect.succeed([\n {\n ...nextState,\n hasToolCalls,\n lifecycle,\n nextToolCallId,\n reasoningSignature,\n finishReason: candidate.finishReason ?? nextState.finishReason,\n },\n events,\n ] as const)\n}\n\n// =============================================================================\n// Protocol And Gemini Route\n// =============================================================================\n/**\n * The Gemini protocol — request body construction, body schema, and the\n * streaming-event state machine. Used by Google AI Studio Gemini and (once\n * registered) Vertex Gemini.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: GeminiBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(GeminiEvent),\n initial: () => ({ hasToolCalls: false, nextToolCallId: 0, lifecycle: Lifecycle.initial() }),\n step,\n onHalt: finish,\n },\n})\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"google\",\n providerMetadataKey: \"google\",\n protocol,\n // Gemini's path embeds the model id and pins SSE framing at the URL level.\n endpoint: Endpoint.path(({ request }) => `/models/${request.model.id}:streamGenerateContent?alt=sse`, {\n baseURL: DEFAULT_BASE_URL,\n }),\n auth: Auth.none,\n framing: Framing.sse,\n})\n\nexport * as Gemini from \"./gemini\"\n", | ||
| "import type { RouteDefaultsInput } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport type { ProviderAuthOption } from \"../route/auth-options\"\nimport type { ProviderPackage } from \"../provider-package\"\nimport { ProviderID, type ModelID, type ProviderOptions } from \"../schema\"\nimport * as Gemini from \"../protocols/gemini\"\n\nexport const id = ProviderID.make(\"google\")\n\nexport const routes = [Gemini.route]\n\nexport type Config = RouteDefaultsInput & ProviderAuthOption<\"optional\"> & { readonly baseURL?: string }\n\nexport interface Settings extends ProviderPackage.Settings {\n readonly apiKey?: string\n readonly baseURL?: string\n readonly providerOptions?: ProviderOptions\n}\n\nconst auth = (options: ProviderAuthOption<\"optional\">) => {\n if (\"auth\" in options && options.auth) return options.auth\n return Auth.optional(\"apiKey\" in options ? options.apiKey : undefined, \"apiKey\")\n .orElse(Auth.config(\"GOOGLE_GENERATIVE_AI_API_KEY\"))\n .pipe(Auth.header(\"x-goog-api-key\"))\n}\n\nconst configuredRoute = (input: Config) => {\n const { apiKey: _, auth: _auth, baseURL, ...rest } = input\n return Gemini.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })\n}\n\nexport const configure = (input: Config = {}) => {\n const route = configuredRoute(input)\n return {\n id,\n model: (modelID: string | ModelID) => route.model({ id: modelID }),\n configure,\n }\n}\n\nexport const provider = configure()\nexport const model: ProviderPackage.Definition<Settings>[\"model\"] = (modelID, settings) =>\n configure({\n apiKey: settings.apiKey,\n baseURL: settings.baseURL,\n headers: settings.headers === undefined ? undefined : { ...settings.headers },\n http: settings.body === undefined ? undefined : { body: { ...settings.body } },\n limits: settings.limits,\n providerOptions: settings.providerOptions,\n }).model(modelID)\n" | ||
| ], | ||
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| ||
| "debugId": "C8E1B08CE6B6397664756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/utils/tool-stream.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect } from \"effect\"\nimport { LLMError, LLMEvent, type ProviderMetadata, type ToolCall, type ToolInputError } from \"../../schema\"\nimport { eventError, parseToolInput, type ToolAccumulator } from \"../shared\"\n\ntype StreamKey = string | number\n\n/**\n * One pending streamed tool call. Providers emit the tool identity and JSON\n * argument text across separate chunks; `input` is the raw JSON string collected\n * so far, not the parsed object.\n */\nexport interface PendingTool extends ToolAccumulator {\n readonly providerExecuted?: boolean\n readonly providerMetadata?: ProviderMetadata\n}\n\n/**\n * Sparse parser state keyed by the provider's stream-local tool identifier.\n *\n * This key is not the final tool-call id (`call_...`). It is the id/index the\n * provider uses while streaming a partial call: OpenAI Chat / Anthropic /\n * Bedrock use numeric content indexes, while OpenAI Responses uses string\n * `item_id`s. The generic keeps each protocol internally consistent.\n */\nexport type State<K extends StreamKey> = Partial<Record<K, PendingTool>>\n\n/**\n * Result of adding argument text to one pending tool call. It returns both the\n * next `tools` state and the updated `tool` because parsers often need the\n * current id/name immediately. `events` contains lifecycle and delta events\n * produced by the append; metadata-only deltas update identity without output.\n */\nexport interface AppendOutcome<K extends StreamKey> {\n readonly tools: State<K>\n readonly tool: PendingTool\n readonly events: ReadonlyArray<LLMEvent>\n}\n\n/** Create empty accumulator state for one provider stream. */\nexport const empty = <K extends StreamKey>(): State<K> => ({})\n\nconst withTool = <K extends StreamKey>(tools: State<K>, key: K, tool: PendingTool): State<K> => {\n return { ...tools, [key]: tool }\n}\n\nconst withoutTool = <K extends StreamKey>(tools: State<K>, key: K): State<K> => {\n const next = { ...tools }\n delete next[key]\n return next\n}\n\nconst inputStart = (tool: PendingTool) =>\n LLMEvent.toolInputStart({\n id: tool.id,\n name: tool.name,\n providerExecuted: tool.providerExecuted ? true : undefined,\n providerMetadata: tool.providerMetadata,\n })\n\nconst inputDelta = (tool: PendingTool, text: string) =>\n LLMEvent.toolInputDelta({\n id: tool.id,\n name: tool.name,\n text,\n })\n\nconst toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {\n const raw = inputOverride ?? tool.input\n return parseToolInput(route, tool.name, raw).pipe(\n Effect.map((input): ToolCall | ToolInputError =>\n LLMEvent.toolCall({\n id: tool.id,\n name: tool.name,\n input,\n providerExecuted: tool.providerExecuted ? true : undefined,\n providerMetadata: tool.providerMetadata,\n }),\n ),\n Effect.catch((error) =>\n tool.providerExecuted\n ? Effect.fail(error)\n : Effect.succeed(\n LLMEvent.toolInputError({\n id: tool.id,\n name: tool.name,\n raw,\n }),\n ),\n ),\n )\n}\n\nconst finishEvents = (tool: PendingTool, event: ToolCall | ToolInputError): ReadonlyArray<LLMEvent> =>\n event.type === \"tool-input-error\"\n ? [event]\n : [LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }), event]\n\n/** Store the updated tool and produce the optional public delta event. */\nconst appendTool = <K extends StreamKey>(\n tools: State<K>,\n key: K,\n tool: PendingTool,\n text: string,\n): AppendOutcome<K> => {\n const events: LLMEvent[] = []\n if (!tools[key]) events.push(inputStart(tool))\n if (text.length > 0) events.push(inputDelta(tool, text))\n return {\n tools: withTool(tools, key, tool),\n tool,\n events,\n }\n}\n\nexport const isError = <K extends StreamKey>(result: AppendOutcome<K> | LLMError): result is LLMError =>\n result instanceof LLMError\n\n/**\n * Register a tool call whose start event arrived before any argument deltas.\n * Used by Anthropic `content_block_start`, Bedrock `contentBlockStart`, and\n * OpenAI Responses `response.output_item.added`.\n */\nexport const start = <K extends StreamKey>(\n tools: State<K>,\n key: K,\n tool: Omit<PendingTool, \"input\"> & { readonly input?: string },\n) => withTool(tools, key, { ...tool, input: tool.input ?? \"\" })\n\n/**\n * Append a streamed argument delta, starting the tool if this provider encodes\n * identity on the first delta instead of a separate start event. OpenAI Chat has\n * this shape: `tool_calls[].index` is the stream key, and `id` / `name` may only\n * appear on the first delta for that index.\n */\nexport const appendOrStart = <K extends StreamKey>(\n route: string,\n tools: State<K>,\n key: K,\n delta: { readonly id?: string; readonly name?: string; readonly text: string },\n missingToolMessage: string,\n): AppendOutcome<K> | LLMError => {\n const current = tools[key]\n const id = delta.id ?? current?.id\n const name = delta.name ?? current?.name\n if (!id || !name) return eventError(route, missingToolMessage)\n\n const tool = {\n id,\n name,\n input: `${current?.input ?? \"\"}${delta.text}`,\n providerExecuted: current?.providerExecuted,\n providerMetadata: current?.providerMetadata,\n }\n if (current && delta.text.length === 0 && current.id === id && current.name === name)\n return { tools, tool: current, events: [] }\n return appendTool(tools, key, tool, delta.text)\n}\n\n/**\n * Append argument text to a tool that must already have been started. This keeps\n * protocols honest when their stream grammar promises a start event before any\n * argument delta.\n */\nexport const appendExisting = <K extends StreamKey>(\n route: string,\n tools: State<K>,\n key: K,\n text: string,\n missingToolMessage: string,\n): AppendOutcome<K> | LLMError => {\n const current = tools[key]\n if (!current) return eventError(route, missingToolMessage)\n if (text.length === 0) return { tools, tool: current, events: [] }\n return appendTool(tools, key, { ...current, input: `${current.input}${text}` }, text)\n}\n\n/**\n * Finalize one pending tool call: parse the accumulated raw JSON, remove it\n * from state, and return either a call or a non-executable local input error.\n * Missing keys are a no-op because some providers emit stop events for\n * non-tool content blocks.\n */\nexport const finish = <K extends StreamKey>(route: string, tools: State<K>, key: K) =>\n Effect.gen(function* () {\n const tool = tools[key]\n if (!tool) return { tools }\n return {\n tools: withoutTool(tools, key),\n events: finishEvents(tool, yield* toolCall(route, tool)),\n }\n })\n\n/**\n * Finalize one pending tool call with an authoritative final input string.\n * OpenAI Responses can send accumulated deltas and then repeat the completed\n * arguments on `response.output_item.done`; the final value wins.\n */\nexport const finishWithInput = <K extends StreamKey>(route: string, tools: State<K>, key: K, input: string) =>\n Effect.gen(function* () {\n const tool = tools[key]\n if (!tool) return { tools }\n return {\n tools: withoutTool(tools, key),\n events: finishEvents(tool, yield* toolCall(route, tool, input)),\n }\n })\n\n/**\n * Finalize every pending tool call at once. OpenAI Chat has this shape: it does\n * not emit per-tool stop events, so all accumulated calls finish independently\n * when the choice receives a terminal `finish_reason`.\n */\nexport const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =>\n Effect.gen(function* () {\n const pending = Object.values<PendingTool | undefined>(tools).filter(\n (tool): tool is PendingTool => tool !== undefined,\n )\n return {\n tools: empty<K>(),\n events: yield* Effect.forEach(pending, (tool) =>\n toolCall(route, tool).pipe(Effect.map((event) => finishEvents(tool, event))),\n ).pipe(Effect.map((events) => events.flat())),\n }\n })\n\nexport * as ToolStream from \"./tool-stream\"\n" | ||
| ], | ||
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| "debugId": "A57A1C1E512305A164756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../core/src/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Context, Duration, Effect, Fiber, Layer, Schema, Stream } from \"effect\"\nimport type { PlatformError } from \"effect/PlatformError\"\nimport { ChildProcess } from \"effect/unstable/process\"\nimport { ChildProcessSpawner } from \"effect/unstable/process/ChildProcessSpawner\"\nimport { CrossSpawnSpawner } from \"./cross-spawn-spawner\"\nimport { makeGlobalNode } from \"./effect/app-node\"\n\nexport class AppProcessError extends Schema.TaggedErrorClass<AppProcessError>()(\"AppProcessError\", {\n command: Schema.String,\n exitCode: Schema.optional(Schema.Number),\n stderr: Schema.optional(Schema.String),\n cause: Schema.optional(Schema.Defect()),\n}) {\n override get message() {\n const detail =\n this.stderr?.trim() || (this.cause instanceof Error ? this.cause.message : this.cause && String(this.cause))\n const status = this.exitCode === undefined ? \"\" : ` (exit ${this.exitCode})`\n return `Command failed${status}: ${this.command}${detail ? `: ${detail}` : \"\"}`\n }\n}\n\nexport interface RunOptions {\n readonly combineOutput?: boolean\n readonly maxOutputBytes?: number\n readonly maxErrorBytes?: number\n readonly signal?: AbortSignal\n readonly timeout?: Duration.Input\n readonly stdin?: string | Uint8Array | Stream.Stream<Uint8Array, PlatformError>\n}\n\nexport interface RunStreamOptions {\n readonly signal?: AbortSignal\n readonly includeStderr?: boolean\n readonly okExitCodes?: ReadonlyArray<number>\n readonly maxErrorBytes?: number\n}\n\nexport interface RunResult {\n readonly command: string\n readonly exitCode: number\n readonly output?: Buffer\n readonly stdout: Buffer\n readonly stderr: Buffer\n readonly outputTruncated?: boolean\n readonly stdoutTruncated: boolean\n readonly stderrTruncated: boolean\n}\n\nexport type Interface = ChildProcessSpawner[\"Service\"] & {\n readonly run: (command: ChildProcess.Command, options?: RunOptions) => Effect.Effect<RunResult, AppProcessError>\n readonly runStream: (\n command: ChildProcess.Command,\n options?: RunStreamOptions,\n ) => Stream.Stream<string, AppProcessError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/AppProcess\") {}\n\nexport const requireSuccess = (result: RunResult): Effect.Effect<RunResult, AppProcessError> =>\n result.exitCode === 0\n ? Effect.succeed(result)\n : Effect.fail(\n new AppProcessError({\n command: result.command,\n exitCode: result.exitCode,\n stderr: result.stderr.toString(\"utf8\"),\n }),\n )\n\nexport const requireExitIn =\n (codes: ReadonlyArray<number>) =>\n (result: RunResult): Effect.Effect<RunResult, AppProcessError> =>\n codes.includes(result.exitCode)\n ? Effect.succeed(result)\n : Effect.fail(\n new AppProcessError({\n command: result.command,\n exitCode: result.exitCode,\n stderr: result.stderr.toString(\"utf8\"),\n }),\n )\n\nconst describeCommand = (command: ChildProcess.Command): string => {\n if (command._tag === \"StandardCommand\") {\n return command.args.length ? `${command.command} ${command.args.join(\" \")}` : command.command\n }\n return `${describeCommand(command.left)} | ${describeCommand(command.right)}`\n}\n\nconst wrapError = (description: string, cause: unknown): AppProcessError =>\n cause instanceof AppProcessError ? cause : new AppProcessError({ command: description, cause })\n\nexport const abortError = (signal: AbortSignal): Error => {\n const reason = signal.reason\n if (reason instanceof Error) return reason\n const err = new Error(\"Aborted\")\n err.name = \"AbortError\"\n return err\n}\n\nexport const waitForAbort = (signal: AbortSignal) =>\n Effect.callback<never, Error>((resume) => {\n if (signal.aborted) {\n resume(Effect.fail(abortError(signal)))\n return\n }\n const onabort = () => resume(Effect.fail(abortError(signal)))\n signal.addEventListener(\"abort\", onabort, { once: true })\n return Effect.sync(() => signal.removeEventListener(\"abort\", onabort))\n })\n\nconst normalizeStdin = (\n input: string | Uint8Array | Stream.Stream<Uint8Array, PlatformError>,\n): Stream.Stream<Uint8Array, PlatformError> =>\n typeof input === \"string\"\n ? Stream.make(new TextEncoder().encode(input))\n : input instanceof Uint8Array\n ? Stream.make(input)\n : input\n\nexport const collectStream = (stream: Stream.Stream<Uint8Array, PlatformError>, maxOutputBytes: number | undefined) =>\n Stream.runFold(\n stream,\n () => ({ chunks: [] as Uint8Array[], bytes: 0, truncated: false }),\n (acc, chunk) => {\n if (maxOutputBytes === undefined) {\n acc.chunks.push(chunk)\n acc.bytes += chunk.length\n return acc\n }\n const remaining = maxOutputBytes - acc.bytes\n if (remaining > 0) acc.chunks.push(remaining >= chunk.length ? chunk : chunk.slice(0, remaining))\n acc.bytes += chunk.length\n acc.truncated = acc.truncated || acc.bytes > maxOutputBytes\n return acc\n },\n ).pipe(Effect.map((x) => ({ buffer: Buffer.concat(x.chunks), truncated: x.truncated })))\n\nconst layer = Layer.effect(\n Service,\n Effect.gen(function* () {\n const spawner = yield* ChildProcessSpawner\n\n const runCommand = (command: ChildProcess.Command, options?: RunOptions) => {\n const description = describeCommand(command)\n const collect = Effect.scoped(\n Effect.gen(function* () {\n const handle = yield* spawner.spawn(command)\n if (options?.combineOutput) {\n const [output, exitCode] = yield* Effect.all(\n [collectStream(handle.all, options.maxOutputBytes), handle.exitCode],\n { concurrency: \"unbounded\" },\n )\n return {\n command: description,\n exitCode,\n output: output.buffer,\n stdout: Buffer.alloc(0),\n stderr: Buffer.alloc(0),\n outputTruncated: output.truncated,\n stdoutTruncated: false,\n stderrTruncated: false,\n } satisfies RunResult\n }\n const [stdout, stderr, exitCode] = yield* Effect.all(\n [\n collectStream(handle.stdout, options?.maxOutputBytes),\n collectStream(handle.stderr, options?.maxErrorBytes),\n handle.exitCode,\n ],\n { concurrency: \"unbounded\" },\n )\n return {\n command: description,\n exitCode,\n stdout: stdout.buffer,\n stderr: stderr.buffer,\n stdoutTruncated: stdout.truncated,\n stderrTruncated: stderr.truncated,\n } satisfies RunResult\n }),\n )\n const timed = options?.timeout\n ? Effect.timeoutOrElse(collect, {\n duration: options.timeout,\n orElse: () => Effect.fail(new AppProcessError({ command: description, cause: new Error(\"Timed out\") })),\n })\n : collect\n const aborted = options?.signal\n ? timed.pipe(\n Effect.raceFirst(\n waitForAbort(options.signal).pipe(Effect.mapError((cause) => wrapError(description, cause))),\n ),\n )\n : timed\n return aborted.pipe(Effect.catch((cause) => Effect.fail(wrapError(description, cause))))\n }\n\n const run = Effect.fn(\"AppProcess.run\")(function* (command: ChildProcess.Command, options?: RunOptions) {\n if (options?.stdin === undefined) return yield* runCommand(command, options)\n if (command._tag !== \"StandardCommand\") {\n return yield* new AppProcessError({\n command: describeCommand(command),\n cause: new Error(\"stdin option only supports StandardCommand; received PipedCommand\"),\n })\n }\n const next = ChildProcess.make(command.command, command.args, {\n ...command.options,\n stdin: normalizeStdin(options.stdin),\n })\n return yield* runCommand(next, options)\n })\n\n const runStream = (\n command: ChildProcess.Command,\n options?: RunStreamOptions,\n ): Stream.Stream<string, AppProcessError> => {\n const description = describeCommand(command)\n const okExitCodes = options?.okExitCodes\n const built: Stream.Stream<string, AppProcessError | PlatformError> = Stream.unwrap(\n Effect.gen(function* () {\n const handle = yield* spawner.spawn(command)\n const stderrFiber = yield* Effect.forkScoped(\n collectStream(handle.stderr, options?.maxErrorBytes).pipe(Effect.map((x) => x.buffer.toString(\"utf8\"))),\n )\n const source = options?.includeStderr === true ? handle.all : handle.stdout\n const lines = source.pipe(\n Stream.decodeText,\n Stream.splitLines,\n Stream.filter((line) => line.length > 0),\n )\n const tail = Stream.unwrap(\n Effect.gen(function* () {\n const code = yield* handle.exitCode\n if (okExitCodes && okExitCodes.length > 0 && !okExitCodes.includes(code)) {\n const stderr = yield* Fiber.join(stderrFiber)\n return Stream.fail(new AppProcessError({ command: description, exitCode: code, stderr }))\n }\n return Stream.empty\n }),\n )\n return Stream.concat(lines, tail) as Stream.Stream<string, AppProcessError | PlatformError>\n }),\n )\n const mapped = built.pipe(\n Stream.catch((cause): Stream.Stream<string, AppProcessError> => Stream.fail(wrapError(description, cause))),\n )\n if (!options?.signal) return mapped\n const signal = options.signal\n return mapped.pipe(\n Stream.interruptWhen(waitForAbort(signal).pipe(Effect.mapError((cause) => wrapError(description, cause)))),\n )\n }\n\n return Service.of({ ...spawner, run, runStream })\n }),\n)\n\nexport const node = makeGlobalNode({ service: Service, layer: layer, deps: [CrossSpawnSpawner.node] })\n\nexport * as AppProcess from \"./process\"\n" | ||
| ], | ||
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| "debugId": "626C5A390CEC905164756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/run.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Option } from \"effect\"\nimport { Commands } from \"../commands\"\nimport { Runtime } from \"../../framework/runtime\"\nimport { ServerConnection } from \"../../services/server-connection\"\n\nexport default Runtime.handler(Commands.commands.run, (input) =>\n Effect.gen(function* () {\n const { runNonInteractive } = yield* Effect.promise(() => import(\"../../run/run\"))\n const separator = process.argv.indexOf(\"--\", 2)\n const server = yield* ServerConnection.resolve({\n server: Option.getOrUndefined(input.server),\n standalone: input.standalone,\n })\n yield* Effect.promise(() =>\n runNonInteractive({\n server,\n message: [...input.message, ...(separator === -1 ? [] : process.argv.slice(separator + 1))],\n continue: input.continue,\n session: Option.getOrUndefined(input.session),\n fork: input.fork,\n model: Option.getOrUndefined(input.model),\n agent: Option.getOrUndefined(input.agent),\n format: input.format,\n file: [...input.file],\n title: Option.getOrUndefined(input.title),\n thinking: input.thinking,\n auto: input.auto || input.yolo,\n }),\n )\n }),\n)\n" | ||
| ], | ||
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| "names": [] | ||
| } |
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