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@opencode-ai/cli-linux-arm64
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@opencode-ai/cli-linux-arm64 - npm Package Compare versions
| { | ||
| "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" | ||
| ], | ||
| "mappings": ";y/BAAA,mBAAS,gBAOT,SAAe,SAAQ,aACrB,OAAS,cAAS,aAAQ,cAAS,WACnC,OAAO,QAAG,wBAAmB,OAAE,cAAU,OAAG,MAC1C,SAAM,OAAY,WAAO,OAAQ,YAAO,WAAO,OAAc,aAAQ,MAAC,OACtE,QAAQ,OAAO,MAAM,EAAU,IAAM,CAAG,EACzC,CACH", | ||
| "debugId": "C4100C96DB51D19664756E2164756E21", | ||
| "names": [] | ||
| } |
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Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["src/util/io.ts", "src/mini/mini.ts", "src/mini/run.ts", "src/mini/noninteractive.ts", "src/mini/ui.ts"], | ||
| "sourcesContent": [ | ||
| "import { text } from \"node:stream/consumers\"\n\nexport function readStdin() {\n return text(process.stdin)\n}\n", | ||
| "import { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { waitForCatalogReady } from \"./catalog.shared\"\nimport { INTERACTIVE_INPUT_ERROR, resolveInteractiveStdin } from \"./runtime.stdin\"\nimport type { RunInput, RunTuiConfig } from \"./types\"\nimport { readStdin } from \"../util/io\"\nimport { setTimeout } from \"node:timers/promises\"\n\nexport type MiniCommandInput = {\n server: ServerConnection.Resolved\n continue?: boolean\n session?: string\n fork?: boolean\n model?: string\n agent?: string\n prompt?: string\n replay?: boolean\n replayLimit?: number\n demo?: boolean\n tuiConfig?: RunTuiConfig | Promise<RunTuiConfig>\n}\n\ntype Session = Awaited<ReturnType<OpenCodeClient[\"session\"][\"get\"]>>\nexport async function runMini(input: MiniCommandInput) {\n validate(input)\n const initialInput = mergeInput(process.stdin.isTTY ? undefined : await readStdin(), input.prompt)\n const runtimeTask = import(\"./runtime\")\n const directory = localDirectory()\n\n try {\n const sdk = OpenCode.make({\n baseUrl: input.server.endpoint.url,\n headers: Service.headers(input.server.endpoint),\n })\n const model = parseModel(input.model)\n let agentTask: Promise<string | undefined> | undefined\n const resolveAgent = () => {\n agentTask ??= validateAgent(sdk, directory, input.agent)\n return agentTask\n }\n const resolveSession = async () => {\n const [agent, selected] = await Promise.all([resolveAgent(), selectSession(sdk, directory, input)])\n const readyModel =\n model ?? (selected?.model ? { providerID: selected.model.providerID, modelID: selected.model.id } : undefined)\n if (readyModel) await waitForCatalogReady({ sdk, directory, model: readyModel })\n const session = selected ?? (await createSession(sdk, directory, agent, model))\n return { id: session.id, title: session.title, resume: selected !== undefined }\n }\n const create = (\n _sdk: OpenCodeClient,\n next: { agent: string | undefined; model: RunInput[\"model\"]; variant: string | undefined },\n ) => createSession(sdk, directory, next.agent, next.model, next.variant)\n const runtime = await runtimeTask\n await runtime.runInteractiveDeferredMode({\n sdk,\n directory,\n resolveAgent,\n session: resolveSession,\n createSession: create,\n agent: input.agent,\n model,\n variant: undefined,\n files: [],\n initialInput,\n thinking: true,\n replay: input.replay ?? true,\n replayLimit: input.replayLimit,\n demo: input.demo,\n tuiConfig: input.tuiConfig,\n })\n } catch (error) {\n if (error instanceof Error && error.message === INTERACTIVE_INPUT_ERROR) fail(error.message)\n throw error\n }\n}\n\nexport function validateMiniTerminal() {\n if (!process.stdout.isTTY) fail(\"opencode mini requires a TTY stdout\")\n}\n\n/** @internal Exported for testing. */\nexport function mergeInput(piped: string | undefined, prompt: string | undefined) {\n if (!prompt) return piped || undefined\n if (!piped) return prompt\n return piped + \"\\n\" + prompt\n}\n\nfunction validate(input: MiniCommandInput) {\n validateMiniTerminal()\n if (input.replayLimit !== undefined && (!Number.isInteger(input.replayLimit) || input.replayLimit <= 0)) {\n fail(\"--replay-limit must be a positive integer\")\n }\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n resolveInteractiveStdin().cleanup?.()\n}\n\nfunction localDirectory(): string {\n const root = process.env.PWD ?? process.cwd()\n try {\n process.chdir(root)\n return process.cwd()\n } catch {\n fail(`Failed to change directory to ${root}`)\n }\n}\n\nfunction parseModel(value?: string): RunInput[\"model\"] {\n if (!value) return\n const [providerID, ...rest] = value.split(\"/\")\n const modelID = rest.join(\"/\")\n if (!providerID || !modelID) fail(\"--model must use the format provider/model\")\n return { providerID, modelID }\n}\n\nasync function validateAgent(sdk: OpenCodeClient, directory: string, name?: string) {\n if (!name) return\n const deadline = Date.now() + 5_000\n let agents: Awaited<ReturnType<OpenCodeClient[\"agent\"][\"list\"]>> | undefined\n while (Date.now() < deadline) {\n agents = await sdk.agent.list({ location: { directory } }).catch(() => undefined)\n const agent = agents?.data.find((item) => item.id === name)\n if (agent?.mode === \"subagent\") {\n warning(`agent \"${name}\" is a subagent, not a primary agent. Falling back to default agent`)\n return\n }\n if (agent) return name\n await setTimeout(25)\n }\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n warning(`agent \"${name}\" not found. Falling back to default agent`)\n}\n\nasync function selectSession(sdk: OpenCodeClient, directory: string, input: MiniCommandInput, preselected?: Session) {\n const selected =\n preselected ??\n (input.session\n ? await sdk.session.get({ sessionID: input.session }).catch(() => undefined)\n : input.continue\n ? await sdk.session\n .list({ directory, parentID: null, limit: 1, order: \"desc\" })\n .then((result) => result.data[0])\n : undefined)\n if (input.session && !selected) fail(\"Session not found\")\n if (!selected) return\n if (!input.fork) return selected\n return sdk.session.fork({ sessionID: selected.id })\n}\n\nasync function createSession(\n sdk: OpenCodeClient,\n directory: string,\n agent: string | undefined,\n model: RunInput[\"model\"],\n variant?: string,\n): Promise<Session> {\n if (model) await waitForCatalogReady({ sdk, directory, model })\n return sdk.session.create({\n agent,\n model: model ? { providerID: model.providerID, id: model.modelID, variant } : undefined,\n location: { directory },\n })\n}\n\nfunction warning(message: string) {\n process.stderr.write(`\\x1b[93m\\x1b[1m!\\x1b[0m ${message}\\n`)\n}\n\nfunction fail(message: string): never {\n process.stderr.write(`\\x1b[91m\\x1b[1mError: \\x1b[0m${message}\\n`)\n process.exit(1)\n}\n", | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { Model } from \"@opencode-ai/schema/model\"\nimport { open } from \"node:fs/promises\"\nimport path from \"node:path\"\nimport { readStdin } from \"../util/io\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { loadRunAgents, waitForCatalogReady } from \"./catalog.shared\"\nimport { runNonInteractivePrompt } from \"./noninteractive\"\nimport { toolInlineInfo } from \"./tool\"\nimport type { MiniToolPart } from \"./types\"\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\nconst ATTACH_FILE_MAX_BYTES = 10 * 1024 * 1024\n\nexport function runNonInteractive(input: RunCommandInput) {\n return run(input).catch((error) => reportError(input, error instanceof Error ? error.message : String(error)))\n}\n\nasync function run(input: RunCommandInput) {\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n const root = process.env.PWD ?? process.cwd()\n const directory = localDirectory(root)\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)))\n const prepared = { directory, message, files }\n return execute(input, prepared, input.server.endpoint)\n}\n\nasync function execute(input: RunCommandInput, prepared: Prepared, endpoint: Endpoint) {\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const requestedDirectory = prepared.directory ?? (await client.location.get()).directory\n if (!requestedDirectory) fail(\"Failed to resolve server directory\")\n const session = await selectSession(client, requestedDirectory, input)\n const cwd = session?.location.directory ?? requestedDirectory\n const workspace = session?.location.workspaceID\n const explicit = parseRunModel(input.model)\n const explicitModel = explicit?.model\n const variant = explicit?.variant\n const sessionModel = session?.model ? { providerID: session.model.providerID, modelID: session.model.id } : undefined\n const defaultModel =\n !explicitModel && !sessionModel\n ? await client.model\n .default({ location: { directory: cwd, workspace } })\n .then((result) => (result.data ? { providerID: result.data.providerID, modelID: result.data.id } : undefined))\n : undefined\n const model = pickRunModel(explicitModel, variant, sessionModel, defaultModel)\n if (variant && !model) return reportError(input, \"Cannot select a variant before selecting a model\", session?.id)\n if (model) {\n await waitForCatalogReady({ sdk: client, directory: cwd, workspace, model })\n const available = await client.model.list({ location: { directory: cwd, workspace } })\n if (!available.data.some((item) => item.providerID === model.providerID && item.id === model.modelID))\n return reportError(input, `Model unavailable: ${model.providerID}/${model.modelID}`, session?.id)\n }\n const agent = await validateAgent(client, cwd, input.agent)\n const selected =\n session ??\n (await client.session.create({\n agent,\n model: model ? { providerID: model.providerID, id: model.modelID, variant } : undefined,\n location: { directory: cwd },\n }))\n if (!session && input.title !== undefined) {\n await client.session.rename({\n sessionID: selected.id,\n title: input.title || prepared.message.slice(0, 50) + (prepared.message.length > 50 ? \"...\" : \"\"),\n })\n }\n\n await runNonInteractivePrompt({\n client,\n sessionID: selected.id,\n message: prepared.message,\n files: prepared.files,\n agent,\n model,\n variant,\n thinking: input.thinking ?? false,\n format: input.format,\n auto: input.auto ?? false,\n attached: true,\n renderTool,\n renderToolError,\n }).catch((error) => reportError(input, error instanceof Error ? error.message : String(error), selected.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\nexport function pickRunModel(\n explicit: { providerID: string; modelID: string } | undefined,\n variant: string | undefined,\n session: { providerID: string; modelID: string } | undefined,\n fallback: { providerID: string; modelID: string } | undefined,\n) {\n if (explicit) return explicit\n if (!variant) return\n return session ?? fallback\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 ${root}`)\n }\n}\n\nexport function parseRunModel(value?: string) {\n if (!value) return\n const ref = Model.Ref.parse(value)\n return {\n model: { providerID: ref.providerID, modelID: ref.id },\n variant: ref.variant,\n }\n}\n\nasync function validateAgent(client: OpenCodeClient, directory: string, name?: string) {\n if (!name) return\n const agents = await loadRunAgents(client, directory).catch(() => undefined)\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n const agent = agents.find((item) => item.id === name)\n if (!agent) {\n warning(`agent \"${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 selectSession(client: OpenCodeClient, directory: string, input: RunCommandInput) {\n const selected = input.session\n ? await client.session.get({ sessionID: input.session }).catch(() => undefined)\n : input.continue\n ? await client.session\n .list({ directory, parentID: null, limit: 1, order: \"desc\" })\n .then((result) => result.data[0])\n : undefined\n if (input.session && !selected) fail(\"Session not found\")\n if (!selected || !input.fork) return selected\n return client.session.fork({ sessionID: selected.id })\n}\n\nasync function prepareFile(input: string, directory: string): 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 (!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,${bytes.toString(\"base64\")}`,\n filename: path.basename(file),\n mime,\n }\n } finally {\n await handle.close()\n }\n}\n\nfunction isBinaryContent(bytes: Uint8Array) {\n if (bytes.length === 0) return false\n if (bytes.includes(0)) return true\n return bytes.reduce((count, byte) => count + Number(byte < 9 || (byte > 13 && byte < 32)), 0) / bytes.length > 0.3\n}\n\nasync function renderTool(part: MiniToolPart) {\n const info = toolInlineInfo(part)\n if (info.mode === \"block\") {\n UI.empty()\n UI.println(UI.Style.TEXT_NORMAL + info.icon, UI.Style.TEXT_NORMAL + info.title)\n if (info.body?.trim()) UI.println(info.body)\n UI.empty()\n return\n }\n UI.println(\n UI.Style.TEXT_NORMAL + info.icon,\n UI.Style.TEXT_NORMAL + info.title,\n info.description ? UI.Style.TEXT_DIM + info.description + UI.Style.TEXT_NORMAL : \"\",\n )\n}\n\nasync function renderToolError(part: MiniToolPart) {\n const info = toolInlineInfo(part)\n UI.println(UI.Style.TEXT_NORMAL + \"✗\", UI.Style.TEXT_NORMAL + `${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 reportError(input: RunCommandInput, 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 { EventSubscribeOutput, OpenCodeClient } 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 { UI } from \"./ui\"\nimport type { MiniToolPart } from \"./types\"\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 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 renderTool: (part: MiniToolPart) => Promise<void>\n renderToolError: (part: MiniToolPart) => 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, unknown>\n raw?: string\n provider?: unknown\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 questionRejected = false\n let permissionRejected = false\n let formCancelled = false\n let interrupted = false\n let admission: AbortController | 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 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 rejectQuestion = async (request: { id: string }) => {\n questionRejected = true\n await input.client.question.reject({ sessionID: input.sessionID, requestID: request.id }).catch(() => {})\n }\n\n const cancelForm = async (request: Pick<FormRequest, \"id\" | \"sessionID\">) => {\n formCancelled = true\n await input.client.form.cancel({ sessionID: request.sessionID, formID: request.id }).catch(() => {})\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 (event.type === \"question.v2.asked\" && submitted && event.data.sessionID === input.sessionID) {\n await rejectQuestion(event.data)\n continue\n }\n if (\n event.type === \"form.created\" &&\n submitted &&\n (event.data.form.sessionID === input.sessionID ||\n (!input.attached && event.data.form.sessionID === GLOBAL_FORM_SESSION_ID))\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 || questionRejected || 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 (!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 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 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 tools.set(event.data.callID, {\n id: partID(event.id),\n timestamp: time,\n assistantMessageID: event.data.assistantMessageID,\n tool: event.data.name,\n input: {},\n })\n continue\n }\n if (event.type === \"session.tool.input.ended\") {\n const current = tools.get(event.data.callID)\n if (current) current.raw = event.data.text\n continue\n }\n if (event.type === \"session.tool.called\") {\n const current = tools.get(event.data.callID)\n tools.set(event.data.callID, {\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 })\n continue\n }\n if (event.type === \"session.tool.success\") {\n const current = tools.get(event.data.callID) ?? fallbackTool(event)\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: event.data.content\n .filter((item) => item.type === \"text\")\n .map((item) => item.text)\n .join(\"\\n\"),\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(event.data.callID)\n if (!emit(\"tool_use\", time, { part })) await input.renderTool(part)\n continue\n }\n if (event.type === \"session.tool.failed\") {\n const current = tools.get(event.data.callID) ?? fallbackTool(event)\n const error = event.data.error.message\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(event.data.callID)\n if (!emit(\"tool_use\", time, { part })) {\n await input.renderToolError(part)\n UI.error(error)\n }\n continue\n }\n\n if (event.type === \"session.step.ended\") {\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 (interrupted || permissionRejected || questionRejected || formCancelled) continue\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 (!emittedError && !questionRejected && !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 (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, questions, forms] = await Promise.all([\n input.client.permission.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.client.question.list({ sessionID: input.sessionID }).catch(() => undefined),\n Promise.all(\n (input.attached ? [input.sessionID] : [input.sessionID, GLOBAL_FORM_SESSION_ID]).map((sessionID) =>\n input.client.form.list({ sessionID }).catch(() => undefined),\n ),\n ),\n ])\n await Promise.all([\n ...(permissions ?? []).map(replyPermission),\n ...(questions ?? []).map(rejectQuestion),\n ...forms.flatMap((response) => response ?? []).map(cancelForm),\n ])\n await completed\n } finally {\n process.off(\"SIGINT\", interrupt)\n controller.abort()\n await stream.return?.(undefined).catch(() => {})\n }\n}\n\nfunction partID(eventID: string) {\n return `prt_${eventID.replace(/^evt_/, \"\")}`\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 }\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, mime: file.mime, 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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| ||
| "debugId": "05C71445390B310E64756E2164756E21", | ||
| "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": "BC47EB20848E0C7764756E2164756E21", | ||
| "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": "19C66A0F9C127B2264756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "E09E42E2EB97C92E64756E2164756E21", | ||
| "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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| "debugId": "FBF66C6DA1A99D0964756E2164756E21", | ||
| "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(options)\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 ${endpoint.url} did not provide a compatible V2 health response`, { cause })\n}\n\nexport * as ServerConnection from \"./server-connection\"\n" | ||
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| "debugId": "768779241BF74DD764756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/services/service-config.ts", "src/util/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Global } from \"@opencode-ai/core/global\"\nimport { InstallationChannel, InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Hash } from \"@opencode-ai/core/util/hash\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Effect, FileSystem, Option, Schema } from \"effect\"\nimport { randomBytes } from \"crypto\"\nimport path from \"path\"\nimport { selfCommand } from \"../util/process\"\n\n// The CLI's service configuration file, plus the Service.EnsureOptions binding that\n// points the client package's service operations at this CLI: which\n// registration file (by channel), which version, and how to spawn opencode.\n\nexport const Info = Schema.Struct({\n hostname: Schema.optional(Schema.String),\n port: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1), Schema.isLessThanOrEqualTo(65_535))),\n password: Schema.optional(Schema.String),\n})\nexport type Info = typeof Info.Type\n\nconst keys = [\"hostname\", \"port\", \"password\"] as const\ntype Key = (typeof keys)[number]\n\nconst decodeInfo = Schema.decodeUnknownEffect(Schema.fromJsonString(Info))\nconst decodeRegistration = Schema.decodeUnknownEffect(Schema.fromJsonString(Service.Info))\n\nexport function filename(channel = InstallationChannel) {\n if (channel === \"latest\") return \"service.json\"\n if (channel === \"local\") return \"service-local.json\"\n return `service-${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": "896BBDE1B75FD21364756E2164756E21", | ||
| "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": "58C4FFFF967DE5CF64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openai.ts"], | ||
| "sourcesContent": [ | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route, 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 type { OpenAIOptionsInput, OpenAIResponseIncludable } from \"./openai-options\"\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 }\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, ...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\n return {\n id,\n model: responses,\n responses,\n responsesWebSocket,\n chat,\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\n" | ||
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| "debugId": "18753B65C0ABDCCA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/mini/variant.shared.ts", "src/mini/session.shared.ts", "src/mini/theme.ts"], | ||
| "sourcesContent": [ | ||
| "// Model variant resolution and persistence.\n//\n// Variants are provider-specific reasoning effort levels (e.g., \"high\", \"max\").\n// Resolution priority: CLI --variant flag > saved preference > session history.\n//\n// The saved variant persists across sessions in ~/.local/state/opencode/model.json\n// so your last-used variant sticks. Cycling (ctrl+t) updates both the active\n// variant and the persisted file.\nimport path from \"path\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { Context, Effect, Layer } from \"effect\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { makeGlobalNode } from \"@opencode-ai/core/effect/app-node\"\nimport { makeRuntime } from \"@opencode-ai/core/effect/runtime\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { createSession, sessionVariant, type RunSession, type SessionMessages } from \"./session.shared\"\nimport type { RunInput, RunProvider } from \"./types\"\n\nconst MODEL_FILE = path.join(Global.Path.state, \"model.json\")\n\ntype ModelState = Record<string, unknown> & {\n variant?: Record<string, string | undefined>\n}\ntype VariantService = {\n readonly resolveSavedVariant: (model: RunInput[\"model\"]) => Effect.Effect<string | undefined>\n readonly saveVariant: (model: RunInput[\"model\"], variant: string | undefined) => Effect.Effect<void>\n}\ntype VariantRuntime = {\n resolveSavedVariant(model: RunInput[\"model\"]): Promise<string | undefined>\n saveVariant(model: RunInput[\"model\"], variant: string | undefined): Promise<void>\n}\n\nfunction isRecord(value: unknown): value is Record<string, unknown> {\n return !!value && typeof value === \"object\" && !Array.isArray(value)\n}\n\nclass Service extends Context.Service<Service, VariantService>()(\"@opencode/RunVariant\") {}\n\nfunction modelKey(provider: string, model: string): string {\n return `${provider}/${model}`\n}\n\nfunction variantKey(model: NonNullable<RunInput[\"model\"]>): string {\n return modelKey(model.providerID, model.modelID)\n}\n\nexport function modelInfo(providers: RunProvider[] | undefined, model: NonNullable<RunInput[\"model\"]>) {\n const provider = providers?.find((item) => item.id === model.providerID)\n return {\n provider: provider?.name ?? model.providerID,\n model: provider?.models[model.modelID]?.name ?? model.modelID,\n }\n}\n\nexport function formatModelLabel(\n model: NonNullable<RunInput[\"model\"]>,\n variant: string | undefined,\n providers?: RunProvider[],\n): string {\n const names = modelInfo(providers, model)\n const label = variant ? ` · ${variant}` : \"\"\n return `${names.model} · ${names.provider}${label}`\n}\n\nexport function cycleVariant(current: string | undefined, variants: string[]): string | undefined {\n if (variants.length === 0) {\n return undefined\n }\n\n if (!current) {\n return variants[0]\n }\n\n const idx = variants.indexOf(current)\n if (idx === -1 || idx === variants.length - 1) {\n return undefined\n }\n\n return variants[idx + 1]\n}\n\nexport function pickVariant(model: RunInput[\"model\"], input: RunSession | SessionMessages): string | undefined {\n return sessionVariant(Array.isArray(input) ? createSession(input) : input, model)\n}\n\nfunction fitVariant(value: string | undefined, variants: string[]): string | undefined {\n if (!value) {\n return undefined\n }\n\n if (variants.length === 0 || variants.includes(value)) {\n return value\n }\n\n return undefined\n}\n\n// Picks the active variant. CLI flag wins, then saved preference, then session\n// history. fitVariant() checks saved and session values against the available\n// variants list -- if the provider doesn't offer a variant, it drops.\nexport function resolveVariant(\n input: string | undefined,\n session: string | undefined,\n saved: string | undefined,\n variants: string[],\n): string | undefined {\n if (input !== undefined) {\n return input\n }\n\n const fallback = fitVariant(saved, variants)\n const current = fitVariant(session, variants)\n if (current !== undefined) {\n return current\n }\n\n return fallback\n}\n\nfunction state(value: unknown): ModelState {\n if (!isRecord(value)) {\n return {}\n }\n\n const variant = isRecord(value.variant)\n ? Object.fromEntries(\n Object.entries(value.variant).flatMap(([key, item]) => {\n if (typeof item !== \"string\") {\n return []\n }\n\n return [[key, item] as const]\n }),\n )\n : undefined\n\n return {\n ...value,\n variant,\n }\n}\n\nconst layer = Layer.fresh(\n Layer.effect(\n Service,\n Effect.gen(function* () {\n const file = yield* FSUtil.Service\n\n const read = Effect.fn(\"RunVariant.read\")(function* () {\n return yield* file.readJson(MODEL_FILE).pipe(\n Effect.map(state),\n Effect.catchCause(() => Effect.succeed(state(undefined))),\n )\n })\n\n const resolveSavedVariant = Effect.fn(\"RunVariant.resolveSavedVariant\")(function* (model: RunInput[\"model\"]) {\n if (!model) {\n return undefined\n }\n\n return (yield* read()).variant?.[variantKey(model)]\n })\n\n const saveVariant = Effect.fn(\"RunVariant.saveVariant\")(function* (\n model: RunInput[\"model\"],\n variant: string | undefined,\n ) {\n if (!model) {\n return\n }\n\n const current = yield* read()\n const next = {\n ...current.variant,\n }\n const key = variantKey(model)\n if (variant) {\n next[key] = variant\n }\n\n if (!variant) {\n delete next[key]\n }\n\n yield* file\n .writeJson(MODEL_FILE, {\n ...current,\n variant: next,\n })\n .pipe(Effect.orElseSucceed(() => undefined))\n })\n\n return Service.of({\n resolveSavedVariant,\n saveVariant,\n })\n }),\n ),\n)\n\nconst node = makeGlobalNode({ service: Service, layer, deps: [FSUtil.node] })\n\n/** @internal Exported for testing. */\nexport function createVariantRuntime(replacements?: readonly LayerNode.Replacement[]): VariantRuntime {\n const runtime = makeRuntime(Service, LayerNode.compile(node, replacements))\n return {\n resolveSavedVariant: (model) => runtime.runPromise((svc) => svc.resolveSavedVariant(model)).catch(() => undefined),\n saveVariant: (model, variant) => runtime.runPromise((svc) => svc.saveVariant(model, variant)).catch(() => {}),\n }\n}\n\nconst runtime = createVariantRuntime()\n\nexport async function resolveSavedVariant(model: RunInput[\"model\"]): Promise<string | undefined> {\n return runtime.resolveSavedVariant(model)\n}\n\nexport function saveVariant(model: RunInput[\"model\"], variant: string | undefined): void {\n void runtime.saveVariant(model, variant)\n}\n", | ||
| "import type { SessionMessageInfo, SessionMessageUser } from \"@opencode-ai/client/promise\"\nimport { promptCopy, promptSame } from \"./prompt.shared\"\nimport type { RunInput, RunPrompt } from \"./types\"\n\nconst LIMIT = 200\n\nexport type SessionMessages = SessionMessageInfo[]\n\ntype Turn = {\n prompt: RunPrompt\n provider: string | undefined\n model: string | undefined\n variant: string | undefined\n}\n\nexport type RunSession = {\n first: boolean\n turns: Turn[]\n model?: NonNullable<RunInput[\"model\"]>\n variant?: string\n}\n\nfunction messagePrompt(message: SessionMessageUser): RunPrompt {\n return {\n text: message.text,\n parts: [\n ...(message.files ?? []).map((file) => ({\n type: \"file\" as const,\n url: file.source.type === \"uri\" ? file.source.uri : `data:${file.mime};base64,${file.data}`,\n mime: file.mime,\n filename: file.name,\n source: file.mention\n ? {\n type: \"file\",\n path: file.name ?? (file.source.type === \"uri\" ? file.source.uri : \"inline attachment\"),\n text: { start: file.mention.start, end: file.mention.end, value: file.mention.text },\n }\n : undefined,\n })),\n ...(message.agents ?? []).map((agent) => ({\n type: \"agent\" as const,\n name: agent.name,\n source: agent.mention\n ? { start: agent.mention.start, end: agent.mention.end, value: agent.mention.text }\n : undefined,\n })),\n ],\n }\n}\n\nexport function createSession(messages: SessionMessages): RunSession {\n return {\n first: messages.length === 0,\n turns: messages.flatMap((message) =>\n message.type === \"user\"\n ? [{ prompt: messagePrompt(message), provider: undefined, model: undefined, variant: undefined }]\n : [],\n ),\n }\n}\n\nexport async function resolveCurrentSession(\n sdk: RunInput[\"sdk\"],\n sessionID: string,\n limit = LIMIT,\n): Promise<RunSession> {\n const [response, session] = await Promise.all([\n sdk.message.list({ sessionID, limit, order: \"desc\" }),\n sdk.session.get({ sessionID }),\n ])\n const current = createSession(response.data.toReversed())\n return {\n ...current,\n turns: current.turns.map((turn) => ({\n ...turn,\n provider: session.model?.providerID,\n model: session.model?.id,\n variant: session.model?.variant,\n })),\n ...(session.model && {\n model: { providerID: session.model.providerID, modelID: session.model.id },\n variant: session.model.variant,\n }),\n }\n}\n\nexport function sessionHistory(session: RunSession, limit = LIMIT): RunPrompt[] {\n return session.turns\n .map((turn) => turn.prompt)\n .filter((prompt) => prompt.text.trim())\n .filter((prompt, index, prompts) => index === 0 || !promptSame(prompts[index - 1], prompt))\n .map(promptCopy)\n .slice(-limit)\n}\n\nexport function sessionVariant(session: RunSession, model: RunInput[\"model\"]): string | undefined {\n if (!model) return\n if (session.model?.providerID === model.providerID && session.model.modelID === model.modelID) return session.variant\n\n return session.turns.findLast((turn) => turn.provider === model.providerID && turn.model === model.modelID)?.variant\n}\n", | ||
| "// Theme resolution for direct interactive mode.\n//\n// Derives scrollback and footer colors from the terminal's actual palette.\n// resolveRunTheme() queries the renderer for the terminal's palette,\n// detects dark/light mode, builds a small system theme locally, and maps it to\n// the run footer + scrollback color model. Falls back to a hardcoded dark-mode\n// palette if detection fails.\nimport { RGBA, SyntaxStyle, type CliRenderer, type ColorInput, type TerminalColors } from \"@opentui/core\"\nimport type { TuiThemeCurrent } from \"@opencode-ai/plugin/tui\"\nimport type { EntryKind } from \"./types\"\n\ntype Tone = {\n body: ColorInput\n start?: ColorInput\n}\n\nexport type RunEntryTheme = Record<EntryKind, Tone>\n\nexport type RunSplashTheme = {\n left: ColorInput\n right: ColorInput\n leftShadow: ColorInput\n rightShadow: ColorInput\n}\n\nexport type RunFooterTheme = {\n highlight: ColorInput\n selected: ColorInput\n selectedText: ColorInput\n warning: ColorInput\n success: ColorInput\n error: ColorInput\n muted: ColorInput\n text: ColorInput\n status: ColorInput\n statusAccent: ColorInput\n shade: ColorInput\n surface: ColorInput\n pane: ColorInput\n border: ColorInput\n line: ColorInput\n}\n\nexport type RunBlockTheme = {\n highlight: ColorInput\n warning: ColorInput\n text: ColorInput\n muted: ColorInput\n syntax?: SyntaxStyle\n diffAdded: ColorInput\n diffRemoved: ColorInput\n diffAddedBg: ColorInput\n diffRemovedBg: ColorInput\n diffContextBg: ColorInput\n diffHighlightAdded: ColorInput\n diffHighlightRemoved: ColorInput\n diffLineNumber: ColorInput\n diffAddedLineNumberBg: ColorInput\n diffRemovedLineNumberBg: ColorInput\n}\n\nexport type RunTheme = {\n background: ColorInput\n footer: RunFooterTheme\n entry: RunEntryTheme\n splash: RunSplashTheme\n block: RunBlockTheme\n}\n\ntype ThemeColor = Exclude<keyof TuiThemeCurrent, \"thinkingOpacity\">\ntype HexColor = `#${string}`\ntype RefName = string\ntype Variant = {\n dark: HexColor | RefName\n light: HexColor | RefName\n}\ntype ColorValue = HexColor | RefName | Variant | RGBA | number\ntype ThemeJson = {\n defs?: Record<string, HexColor | RefName>\n theme: Omit<Record<ThemeColor, ColorValue>, \"selectedListItemText\" | \"backgroundMenu\"> & {\n selectedListItemText?: ColorValue\n backgroundMenu?: ColorValue\n thinkingOpacity?: number\n }\n}\n\ntype SharedSyntaxTheme = TuiThemeCurrent & {\n _hasSelectedListItemText: boolean\n}\n\nexport const transparent = RGBA.fromValues(0, 0, 0, 0)\n\nfunction alpha(color: RGBA, value: number): RGBA {\n return RGBA.fromValues(color.r, color.g, color.b, Math.max(0, Math.min(1, value)))\n}\n\nfunction rgba(hex: string, value?: number): RGBA {\n const color = RGBA.fromHex(hex)\n return value === undefined ? color : alpha(color, value)\n}\n\nfunction mode(bg: RGBA): \"dark\" | \"light\" {\n return luminance(bg) > 0.5 ? \"light\" : \"dark\"\n}\n\nfunction luminance(color: RGBA): number {\n return 0.299 * color.r + 0.587 * color.g + 0.114 * color.b\n}\n\nfunction fade(color: RGBA, base: RGBA, fallback: number, scale: number, limit: number): RGBA {\n if (color.a === 0) {\n return RGBA.fromValues(color.r, color.g, color.b, Math.max(0, Math.min(1, fallback)))\n }\n\n const target = Math.min(limit, color.a * scale)\n const mix = Math.min(1, target / color.a)\n\n return RGBA.fromValues(\n base.r + (color.r - base.r) * mix,\n base.g + (color.g - base.g) * mix,\n base.b + (color.b - base.b) * mix,\n color.a,\n )\n}\n\nfunction ansiToRgba(code: number): RGBA {\n if (code < 16) {\n const ansi = [\n \"#000000\",\n \"#800000\",\n \"#008000\",\n \"#808000\",\n \"#000080\",\n \"#800080\",\n \"#008080\",\n \"#c0c0c0\",\n \"#808080\",\n \"#ff0000\",\n \"#00ff00\",\n \"#ffff00\",\n \"#0000ff\",\n \"#ff00ff\",\n \"#00ffff\",\n \"#ffffff\",\n ]\n return RGBA.fromHex(ansi[code] ?? \"#000000\")\n }\n\n if (code < 232) {\n const index = code - 16\n const b = index % 6\n const g = Math.floor(index / 6) % 6\n const r = Math.floor(index / 36)\n const value = (x: number) => (x === 0 ? 0 : x * 40 + 55)\n return RGBA.fromInts(value(r), value(g), value(b))\n }\n\n if (code < 256) {\n const gray = (code - 232) * 10 + 8\n return RGBA.fromInts(gray, gray, gray)\n }\n\n return RGBA.fromInts(0, 0, 0)\n}\n\nfunction tint(base: RGBA, overlay: RGBA, value: number): RGBA {\n return RGBA.fromInts(\n Math.round((base.r + (overlay.r - base.r) * value) * 255),\n Math.round((base.g + (overlay.g - base.g) * value) * 255),\n Math.round((base.b + (overlay.b - base.b) * value) * 255),\n )\n}\n\nfunction chroma(color: RGBA) {\n return Math.max(color.r, color.g, color.b) - Math.min(color.r, color.g, color.b)\n}\n\nfunction indexedPalette(colors: TerminalColors, size: number = Math.max(colors.palette.length, 16)): RGBA[] {\n return Array.from({ length: size }, (_, index) => {\n const value = colors.palette[index]\n return RGBA.fromIndex(index, value ? RGBA.fromHex(value) : ansiToRgba(index))\n })\n}\n\nfunction srgbToLinear(value: number): number {\n if (value <= 0.04045) {\n return value / 12.92\n }\n\n return ((value + 0.055) / 1.055) ** 2.4\n}\n\nfunction oklab(color: RGBA) {\n const r = srgbToLinear(color.r)\n const g = srgbToLinear(color.g)\n const b = srgbToLinear(color.b)\n\n const l = Math.cbrt(0.4122214708 * r + 0.5363325363 * g + 0.0514459929 * b)\n const m = Math.cbrt(0.2119034982 * r + 0.6806995451 * g + 0.1073969566 * b)\n const s = Math.cbrt(0.0883024619 * r + 0.2817188376 * g + 0.6299787005 * b)\n\n return {\n l: 0.2104542553 * l + 0.793617785 * m - 0.0040720468 * s,\n a: 1.9779984951 * l - 2.428592205 * m + 0.4505937099 * s,\n b: 0.0259040371 * l + 0.7827717662 * m - 0.808675766 * s,\n }\n}\n\nfunction nearestIndexed(indexed: RGBA[], rgba: RGBA): RGBA {\n const target = oklab(rgba)\n const hit = indexed.reduce(\n (best, item) => {\n const sample = oklab(item)\n const dl = sample.l - target.l\n const da = sample.a - target.a\n const db = sample.b - target.b\n const dist = dl * dl * 2 + da * da + db * db\n if (dist >= best.dist) return best\n return {\n dist,\n item,\n }\n },\n {\n dist: Number.POSITIVE_INFINITY,\n item: indexed[0]!,\n },\n )\n\n return RGBA.clone(hit.item)\n}\n\nfunction paletteColor(colors: TerminalColors, index: number): RGBA {\n const value = colors.palette[index]\n return value ? RGBA.fromHex(value) : ansiToRgba(index)\n}\n\nfunction splashShadow(indexed: RGBA[], base: RGBA, overlay: RGBA, value: number): RGBA {\n const mixed = tint(base, overlay, value)\n return nearestIndexed(indexed, mixed)\n}\n\nexport function resolveTheme(theme: ThemeJson, pick: \"dark\" | \"light\"): TuiThemeCurrent {\n const defs = theme.defs ?? {}\n\n const resolveColor = (value: ColorValue, chain: string[] = []): RGBA => {\n if (value instanceof RGBA) return value\n\n if (typeof value === \"number\") {\n return RGBA.fromIndex(value, ansiToRgba(value))\n }\n\n if (typeof value !== \"string\") {\n return resolveColor(value[pick], chain)\n }\n\n if (value === \"transparent\" || value === \"none\") {\n return RGBA.fromInts(0, 0, 0, 0)\n }\n\n if (value.startsWith(\"#\")) {\n return RGBA.fromHex(value)\n }\n\n if (chain.includes(value)) {\n throw new Error(`Circular color reference: ${[...chain, value].join(\" -> \")}`)\n }\n\n const next = defs[value] ?? theme.theme[value as ThemeColor]\n if (next === undefined) {\n throw new Error(`Color reference \"${value}\" not found in defs or theme`)\n }\n\n return resolveColor(next, [...chain, value])\n }\n\n const resolved = Object.fromEntries(\n Object.entries(theme.theme)\n .filter(([key]) => key !== \"selectedListItemText\" && key !== \"backgroundMenu\" && key !== \"thinkingOpacity\")\n .map(([key, value]) => [key, resolveColor(value as ColorValue)]),\n ) as Partial<Record<ThemeColor, RGBA>>\n\n return {\n ...(resolved as Record<ThemeColor, RGBA>),\n selectedListItemText:\n theme.theme.selectedListItemText === undefined\n ? resolved.background!\n : resolveColor(theme.theme.selectedListItemText),\n backgroundMenu:\n theme.theme.backgroundMenu === undefined ? resolved.backgroundElement! : resolveColor(theme.theme.backgroundMenu),\n thinkingOpacity: theme.theme.thinkingOpacity ?? 0.6,\n }\n}\n\nfunction generateGrayScale(bg: RGBA, isDark: boolean, map: (rgba: RGBA) => RGBA): Record<number, RGBA> {\n const r = bg.r * 255\n const g = bg.g * 255\n const b = bg.b * 255\n const lum = 0.299 * r + 0.587 * g + 0.114 * b\n const cast = 0.25 * (1 - chroma(bg)) ** 2\n\n const gray = (level: number) => {\n const factor = level / 12\n\n if (isDark && lum < 10) {\n const value = Math.floor(factor * 0.4 * 255)\n return map(RGBA.fromInts(value, value, value))\n }\n\n if (!isDark && lum > 245) {\n const value = Math.floor(255 - factor * 0.4 * 255)\n return map(RGBA.fromInts(value, value, value))\n }\n\n const value = isDark ? lum + (255 - lum) * factor * 0.4 : lum * (1 - factor * 0.4)\n const tone = RGBA.fromInts(Math.floor(value), Math.floor(value), Math.floor(value))\n if (cast === 0) return map(tone)\n\n const ratio = lum === 0 ? 0 : value / lum\n return map(\n tint(\n tone,\n RGBA.fromInts(\n Math.floor(Math.max(0, Math.min(r * ratio, 255))),\n Math.floor(Math.max(0, Math.min(g * ratio, 255))),\n Math.floor(Math.max(0, Math.min(b * ratio, 255))),\n ),\n cast,\n ),\n )\n }\n\n return Object.fromEntries(Array.from({ length: 12 }, (_, index) => [index + 1, gray(index + 1)]))\n}\n\nfunction generateMutedTextColor(bg: RGBA, isDark: boolean, map: (rgba: RGBA) => RGBA): RGBA {\n const lum = 0.299 * bg.r * 255 + 0.587 * bg.g * 255 + 0.114 * bg.b * 255\n const gray = isDark\n ? lum < 10\n ? 180\n : Math.min(Math.floor(160 + lum * 0.3), 200)\n : lum > 245\n ? 75\n : Math.max(Math.floor(100 - (255 - lum) * 0.2), 60)\n\n return map(RGBA.fromInts(gray, gray, gray))\n}\n\nexport function generateSystem(colors: TerminalColors, pick: \"dark\" | \"light\"): ThemeJson {\n const bg_snapshot = RGBA.fromHex(colors.defaultBackground ?? colors.palette[0]!)\n const fg_snapshot = RGBA.fromHex(colors.defaultForeground ?? colors.palette[7]!)\n const bg = RGBA.defaultBackground(bg_snapshot)\n const fg = RGBA.defaultForeground(fg_snapshot)\n const isDark = pick === \"dark\"\n\n const color = (index: number) => paletteColor(colors, index)\n\n const grays = generateGrayScale(bg_snapshot, isDark, (rgba) => rgba)\n const textMuted = generateMutedTextColor(bg_snapshot, isDark, (rgba) => rgba)\n\n const ansi = {\n red: color(1),\n green: color(2),\n yellow: color(3),\n blue: color(4),\n magenta: color(5),\n cyan: color(6),\n red_bright: color(9),\n green_bright: color(10),\n }\n\n const diff_alpha = isDark ? 0.22 : 0.14\n const diff_context_bg = grays[2]\n const primary = ansi.cyan\n const secondary = ansi.magenta\n\n return {\n theme: {\n primary,\n secondary,\n accent: primary,\n error: ansi.red,\n warning: ansi.yellow,\n success: ansi.green,\n info: ansi.cyan,\n text: fg,\n textMuted,\n selectedListItemText: bg,\n background: alpha(bg, 0),\n backgroundPanel: grays[2],\n backgroundElement: grays[3],\n backgroundMenu: grays[3],\n borderSubtle: grays[6],\n border: grays[7],\n borderActive: grays[8],\n diffAdded: ansi.green,\n diffRemoved: ansi.red,\n diffContext: grays[7],\n diffHunkHeader: grays[7],\n diffHighlightAdded: ansi.green_bright,\n diffHighlightRemoved: ansi.red_bright,\n diffAddedBg: tint(bg_snapshot, ansi.green, diff_alpha),\n diffRemovedBg: tint(bg_snapshot, ansi.red, diff_alpha),\n diffContextBg: diff_context_bg,\n diffLineNumber: textMuted,\n diffAddedLineNumberBg: tint(diff_context_bg, ansi.green, diff_alpha),\n diffRemovedLineNumberBg: tint(diff_context_bg, ansi.red, diff_alpha),\n markdownText: fg,\n markdownHeading: fg,\n markdownLink: ansi.blue,\n markdownLinkText: ansi.cyan,\n markdownCode: ansi.green,\n markdownBlockQuote: ansi.yellow,\n markdownEmph: ansi.yellow,\n markdownStrong: fg,\n markdownHorizontalRule: grays[7],\n markdownListItem: ansi.blue,\n markdownListEnumeration: ansi.cyan,\n markdownImage: ansi.blue,\n markdownImageText: ansi.cyan,\n markdownCodeBlock: fg,\n syntaxComment: textMuted,\n syntaxKeyword: ansi.magenta,\n syntaxFunction: ansi.blue,\n syntaxVariable: fg,\n syntaxString: ansi.green,\n syntaxNumber: ansi.yellow,\n syntaxType: ansi.cyan,\n syntaxOperator: ansi.cyan,\n syntaxPunctuation: fg,\n },\n }\n}\n\nfunction quantizeColor(indexed: RGBA[], rgba: RGBA): RGBA {\n if (rgba.a === 0 || rgba.intent === \"default\" || rgba.intent === \"indexed\") {\n return RGBA.clone(rgba)\n }\n\n return nearestIndexed(indexed, rgba)\n}\n\nfunction quantizeTheme(theme: TuiThemeCurrent, indexed: RGBA[]): TuiThemeCurrent {\n const resolved = Object.fromEntries(\n Object.entries(theme)\n .filter(([key]) => key !== \"thinkingOpacity\")\n .map(([key, value]) => [key, quantizeColor(indexed, value as RGBA)]),\n ) as Partial<Record<ThemeColor, RGBA>>\n\n return {\n ...(resolved as Record<ThemeColor, RGBA>),\n thinkingOpacity: theme.thinkingOpacity,\n }\n}\n\nfunction splashTheme(theme: TuiThemeCurrent, indexed: RGBA[]): RunSplashTheme {\n const left = nearestIndexed(indexed, theme.textMuted)\n const right = nearestIndexed(indexed, theme.text)\n return {\n left,\n right,\n leftShadow: splashShadow(indexed, theme.background, left, 0.14),\n rightShadow: splashShadow(indexed, theme.background, right, 0.14),\n }\n}\n\nfunction map(\n footerTheme: TuiThemeCurrent,\n scrollbackTheme: TuiThemeCurrent,\n splash: RunSplashTheme,\n syntax?: SyntaxStyle,\n): RunTheme {\n const footerBackground = alpha(footerTheme.background, 1)\n const footerMode = mode(footerBackground)\n const shade = fade(footerTheme.backgroundMenu, footerTheme.background, 0.12, 0.56, 0.72)\n const surface = fade(footerTheme.backgroundMenu, footerTheme.background, 0.18, 0.76, 0.9)\n const line = fade(footerTheme.backgroundMenu, footerTheme.background, 0.24, 0.9, 0.98)\n const statusBase = tint(footerBackground, rgba(\"#000000\"), footerMode === \"dark\" ? 0.12 : 0.06)\n const statusAccentBase =\n footerMode === \"dark\" ? tint(footerBackground, rgba(\"#ffffff\"), 0.06) : tint(statusBase, rgba(\"#000000\"), 0.04)\n const collapsedStatus = footerMode === \"dark\" && luminance(statusBase) <= 0.04\n // Pure-black backgrounds need a slight lift or the row disappears into the terminal background.\n const status = collapsedStatus ? tint(statusBase, statusAccentBase, 0.7) : statusBase\n const statusAccent = collapsedStatus ? tint(status, rgba(\"#ffffff\"), 0.06) : statusAccentBase\n\n return {\n background: footerTheme.background,\n footer: {\n highlight: footerTheme.primary,\n selected: footerTheme.backgroundElement,\n selectedText: footerTheme.selectedListItemText,\n warning: footerTheme.warning,\n success: footerTheme.success,\n error: footerTheme.error,\n muted: footerTheme.textMuted,\n text: footerTheme.text,\n status,\n statusAccent,\n shade,\n surface,\n pane: footerTheme.backgroundMenu,\n border: footerTheme.border,\n line,\n },\n entry: {\n system: {\n body: scrollbackTheme.textMuted,\n },\n user: {\n body: scrollbackTheme.primary,\n },\n assistant: {\n body: scrollbackTheme.text,\n },\n reasoning: {\n body: scrollbackTheme.textMuted,\n },\n tool: {\n body: scrollbackTheme.text,\n start: scrollbackTheme.textMuted,\n },\n error: {\n body: scrollbackTheme.error,\n },\n },\n splash,\n block: {\n highlight: scrollbackTheme.primary,\n warning: scrollbackTheme.warning,\n text: scrollbackTheme.text,\n muted: scrollbackTheme.textMuted,\n syntax,\n diffAdded: scrollbackTheme.diffAdded,\n diffRemoved: scrollbackTheme.diffRemoved,\n diffAddedBg: transparent,\n diffRemovedBg: transparent,\n diffContextBg: transparent,\n diffHighlightAdded: scrollbackTheme.diffHighlightAdded,\n diffHighlightRemoved: scrollbackTheme.diffHighlightRemoved,\n diffLineNumber: scrollbackTheme.diffLineNumber,\n diffAddedLineNumberBg: scrollbackTheme.diffAddedLineNumberBg,\n diffRemovedLineNumberBg: scrollbackTheme.diffRemovedLineNumberBg,\n },\n }\n}\n\nconst seed = {\n highlight: RGBA.fromIndex(6, rgba(\"#38bdf8\")),\n muted: RGBA.fromIndex(8, rgba(\"#64748b\")),\n text: RGBA.defaultForeground(rgba(\"#f8fafc\")),\n panel: rgba(\"#0f172a\"),\n success: RGBA.fromIndex(2, rgba(\"#22c55e\")),\n warning: RGBA.fromIndex(3, rgba(\"#f59e0b\")),\n error: RGBA.fromIndex(1, rgba(\"#ef4444\")),\n}\n\nfunction tone(body: ColorInput, start?: ColorInput): Tone {\n return {\n body,\n start,\n }\n}\n\nconst fallbackSplashIndexed = Array.from({ length: 256 }, (_, index) => RGBA.fromIndex(index))\nconst fallbackSplashLeft = RGBA.fromIndex(67)\nconst fallbackSplashRight = RGBA.fromIndex(110)\n\nexport const RUN_THEME_FALLBACK: RunTheme = {\n background: RGBA.fromValues(0, 0, 0, 0),\n footer: {\n highlight: seed.highlight,\n selected: seed.text,\n selectedText: seed.panel,\n warning: seed.warning,\n success: seed.success,\n error: seed.error,\n muted: seed.muted,\n text: seed.text,\n status: tint(seed.panel, rgba(\"#000000\"), 0.12),\n statusAccent: tint(seed.panel, rgba(\"#ffffff\"), 0.06),\n shade: alpha(seed.panel, 0.68),\n surface: alpha(seed.panel, 0.86),\n pane: seed.panel,\n border: seed.muted,\n line: alpha(seed.panel, 0.96),\n },\n entry: {\n system: tone(seed.muted),\n user: tone(seed.highlight),\n assistant: tone(seed.text),\n reasoning: tone(seed.muted),\n tool: tone(seed.text, seed.muted),\n error: tone(seed.error),\n },\n splash: {\n left: fallbackSplashLeft,\n right: fallbackSplashRight,\n leftShadow: splashShadow(fallbackSplashIndexed, RGBA.fromValues(0, 0, 0, 0), fallbackSplashLeft, 0.14),\n rightShadow: splashShadow(fallbackSplashIndexed, RGBA.fromValues(0, 0, 0, 0), fallbackSplashRight, 0.14),\n },\n block: {\n highlight: seed.highlight,\n warning: seed.warning,\n text: seed.text,\n muted: seed.muted,\n diffAdded: seed.success,\n diffRemoved: seed.error,\n diffAddedBg: alpha(seed.success, 0.18),\n diffRemovedBg: alpha(seed.error, 0.18),\n diffContextBg: alpha(seed.panel, 0.72),\n diffHighlightAdded: seed.success,\n diffHighlightRemoved: seed.error,\n diffLineNumber: seed.muted,\n diffAddedLineNumberBg: alpha(seed.success, 0.12),\n diffRemovedLineNumberBg: alpha(seed.error, 0.12),\n },\n}\n\nexport async function resolveRunTheme(renderer: CliRenderer): Promise<RunTheme> {\n try {\n const colors = await renderer.getPalette({\n size: 256,\n })\n const bg = colors.defaultBackground ?? colors.palette[0]\n if (!bg) {\n return RUN_THEME_FALLBACK\n }\n\n // Palette-only terminal reloads can leave renderer.themeMode stale, but\n // ANSI slot zero is not the terminal background when OSC 11 is absent.\n const pick = colors.defaultBackground\n ? mode(RGBA.fromHex(colors.defaultBackground))\n : (renderer.themeMode ?? mode(RGBA.fromHex(bg)))\n const footerTheme = resolveTheme(generateSystem(colors, pick), pick)\n const indexed = indexedPalette(colors, 256)\n const scrollbackTheme = quantizeTheme(footerTheme, indexed)\n const shared = await import(\"@opencode-ai/tui/context/theme\")\n const syntaxTheme: SharedSyntaxTheme = {\n ...scrollbackTheme,\n _hasSelectedListItemText: true,\n }\n const syntax = shared.generateSyntax(syntaxTheme)\n return map(footerTheme, scrollbackTheme, splashTheme(scrollbackTheme, indexed), syntax)\n } catch {\n return RUN_THEME_FALLBACK\n }\n}\n" | ||
| ], | ||
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| ||
| "debugId": "80138DF5DA39BE6764756E2164756E21", | ||
| "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": "87E9EE8B3B69F0AA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/frontend/actions.ts", "../simulation/src/recording.ts", "../simulation/src/frontend/renderer.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 } from \"effect\"\nimport type { SimulationProtocol } from \"../protocol\"\nimport { SimulationRenderer } from \"./renderer\"\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 return renderer.hitTest(x, y) === renderable.num\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 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 yield* Effect.tryPromise(() => harness.mockMouse.click(action.x, action.y))\n break\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 { 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.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 })\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": "EBB3C32EC983F0D064756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mini.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.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 yield* Effect.promise(() =>\n runMini({\n server,\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 }),\n )\n }),\n)\n" | ||
| ], | ||
| "mappings": ";umCAKA,SAAe,SAAQ,aAAQ,OAAS,cAAS,UAAM,MAAC,SACtD,OAAO,SAAI,cAAU,OAAG,MACtB,SAAQ,eAAS,6BAAyB,WAAO,OAAO,aAAQ,SAAa,wCAAa,OAC1F,WAAO,OAAO,aAAQ,cAAY,OAAqB,MAAC,OACxD,SAAM,OAAY,EAAO,eAAe,EAAM,MAAM,EAC9C,EAAS,MAAO,EAAiB,QAAQ,CAAE,OAAQ,EAAW,WAAY,EAAM,UAAW,CAAC,EAClG,MAAO,EAAO,QAAQ,IACpB,EAAQ,CACN,SACA,SAAU,EAAM,SAChB,QAAS,EAAO,eAAe,EAAM,OAAO,EAC5C,KAAM,EAAM,KACZ,MAAO,EAAO,eAAe,EAAM,KAAK,EACxC,MAAO,EAAO,eAAe,EAAM,KAAK,EACxC,OAAQ,EAAO,eAAe,EAAM,MAAM,EAC1C,OAAQ,EAAM,OACd,YAAa,EAAO,eAAe,EAAM,WAAW,EACpD,KAAM,EAAM,IACd,CAAC,CACH,EACD,CACH", | ||
| "debugId": "BD71950B14C79B8D64756E2164756E21", | ||
| "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": "44C73C366C68F65D64756E2164756E21", | ||
| "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 // JSON parse failures fail the stream at the boundary rather than at halt.\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": "C3FD45C854F4240C64756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "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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| "sources": [], | ||
| "sourcesContent": [ | ||
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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 ? yield* ServiceConfig.password()\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) => register(address, password, instanceID, serviceOptions.file, shutdown),\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.max([Schedule.spaced(\"100 millis\"), Schedule.recurs(60)])),\n Effect.option,\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": "B74C79EF7C17BEE564756E2164756E21", | ||
| "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": "73810C096C678A7764756E2164756E21", | ||
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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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| "debugId": "10DC247A636E749864756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "9B7BE33529ECC63864756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-responses.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { HttpTransport, WebSocketTransport } from \"../route/transport\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type ProviderMetadata,\n type ReasoningPart,\n type TextPart,\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 { 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-responses\"\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/responses\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst OpenAIResponsesInputText = Schema.Struct({\n type: Schema.tag(\"input_text\"),\n text: Schema.String,\n})\nconst OpenAIResponsesInputImage = Schema.Struct({\n type: Schema.tag(\"input_image\"),\n image_url: Schema.String,\n})\nconst OpenAIResponsesInputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])\ntype OpenAIResponsesInputContent = Schema.Schema.Type<typeof OpenAIResponsesInputContent>\n\nconst OpenAIResponsesOutputText = Schema.Struct({\n type: Schema.tag(\"output_text\"),\n text: Schema.String,\n})\n\nconst OpenAIResponsesReasoningSummaryText = Schema.Struct({\n type: Schema.tag(\"summary_text\"),\n text: Schema.String,\n})\n\nconst OpenAIResponsesReasoningItem = Schema.Struct({\n type: Schema.tag(\"reasoning\"),\n id: Schema.optionalKey(Schema.String),\n summary: Schema.Array(OpenAIResponsesReasoningSummaryText),\n encrypted_content: optionalNull(Schema.String),\n})\n\nconst OpenAIResponsesItemReference = Schema.Struct({\n type: Schema.tag(\"item_reference\"),\n id: Schema.String,\n})\n\n// `function_call_output.output` accepts either a plain string or an ordered\n// array of content items so tools can return images in addition to text.\n// https://platform.openai.com/docs/api-reference/responses/object\nconst OpenAIResponsesFunctionCallOutputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])\n\nconst OpenAIResponsesFunctionCallOutput = Schema.Union([\n Schema.String,\n Schema.Array(OpenAIResponsesFunctionCallOutputContent),\n])\n\nconst OpenAIResponsesInputItem = Schema.Union([\n Schema.Struct({ role: Schema.tag(\"system\"), content: Schema.String }),\n Schema.Struct({ role: Schema.tag(\"user\"), content: Schema.Array(OpenAIResponsesInputContent) }),\n Schema.Struct({ role: Schema.tag(\"assistant\"), content: Schema.Array(OpenAIResponsesOutputText) }),\n OpenAIResponsesReasoningItem,\n OpenAIResponsesItemReference,\n Schema.Struct({\n type: Schema.tag(\"function_call\"),\n call_id: Schema.String,\n name: Schema.String,\n arguments: Schema.String,\n }),\n Schema.Struct({\n type: Schema.tag(\"function_call_output\"),\n call_id: Schema.String,\n output: OpenAIResponsesFunctionCallOutput,\n }),\n])\ntype OpenAIResponsesInputItem = Schema.Schema.Type<typeof OpenAIResponsesInputItem>\n\n// Mutable counterpart of the schema reasoning item so `lowerMessages` can fold\n// multiple streamed summary parts into the same item before flushing.\ntype OpenAIResponsesReasoningInput = {\n type: \"reasoning\"\n id: string\n summary: Array<{ type: \"summary_text\"; text: string }>\n encrypted_content?: string | null\n}\ntype OpenAIResponsesReasoningReplay = Omit<OpenAIResponsesReasoningInput, \"id\">\n\nconst OpenAIResponsesTool = Schema.Struct({\n type: Schema.tag(\"function\"),\n name: Schema.String,\n description: Schema.String,\n parameters: JsonObject,\n strict: Schema.optional(Schema.Boolean),\n})\ntype OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTool>\n\nconst OpenAIResponsesToolChoice = Schema.Union([\n Schema.Literals([\"auto\", \"none\", \"required\"]),\n Schema.Struct({ type: Schema.tag(\"function\"), name: Schema.String }),\n])\n\n// Fields shared between the HTTP body and the WebSocket `response.create`\n// message. The HTTP body adds `stream: true`; the WebSocket message adds\n// `type: \"response.create\"`. Defining the shared shape once keeps the two\n// transports in sync without a destructure-and-strip dance.\nconst OpenAIResponsesCoreFields = {\n model: Schema.String,\n input: Schema.Array(OpenAIResponsesInputItem),\n instructions: Schema.optional(Schema.String),\n tools: optionalArray(OpenAIResponsesTool),\n tool_choice: Schema.optional(OpenAIResponsesToolChoice),\n store: Schema.optional(Schema.Boolean),\n service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),\n prompt_cache_key: Schema.optional(Schema.String),\n include: optionalArray(OpenAIOptions.OpenAIResponseIncludable),\n reasoning: Schema.optional(\n Schema.Struct({\n effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),\n summary: Schema.optional(Schema.Literal(\"auto\")),\n }),\n ),\n text: Schema.optional(\n Schema.Struct({\n verbosity: Schema.optional(OpenAIOptions.OpenAITextVerbosity),\n }),\n ),\n max_output_tokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n}\n\nconst OpenAIResponsesBody = Schema.Struct({\n ...OpenAIResponsesCoreFields,\n stream: Schema.Literal(true),\n})\nexport type OpenAIResponsesBody = Schema.Schema.Type<typeof OpenAIResponsesBody>\n\nconst OpenAIResponsesWebSocketMessage = Schema.StructWithRest(\n Schema.Struct({\n type: Schema.tag(\"response.create\"),\n ...OpenAIResponsesCoreFields,\n }),\n [Schema.Record(Schema.String, Schema.Unknown)],\n)\ntype OpenAIResponsesWebSocketMessage = Schema.Schema.Type<typeof OpenAIResponsesWebSocketMessage>\nconst encodeWebSocketMessage = Schema.encodeSync(Schema.fromJsonString(OpenAIResponsesWebSocketMessage))\n\nconst OpenAIResponsesUsage = Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n input_tokens_details: optionalNull(Schema.Struct({ cached_tokens: Schema.optional(Schema.Number) })),\n output_tokens: Schema.optional(Schema.Number),\n output_tokens_details: optionalNull(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) })),\n total_tokens: Schema.optional(Schema.Number),\n})\ntype OpenAIResponsesUsage = Schema.Schema.Type<typeof OpenAIResponsesUsage>\n\nconst OpenAIResponsesStreamItem = Schema.Struct({\n type: Schema.String,\n id: Schema.optional(Schema.String),\n call_id: Schema.optional(Schema.String),\n name: Schema.optional(Schema.String),\n arguments: Schema.optional(Schema.String),\n // Hosted (provider-executed) tool fields. Each hosted tool item carries its\n // own subset of these — we capture them generically so we can surface the\n // call's typed input portion and round-trip the full result payload without\n // hand-rolling a per-tool schema.\n status: Schema.optional(Schema.String),\n action: Schema.optional(Schema.Unknown),\n queries: Schema.optional(Schema.Unknown),\n results: Schema.optional(Schema.Unknown),\n code: Schema.optional(Schema.String),\n container_id: Schema.optional(Schema.String),\n outputs: Schema.optional(Schema.Unknown),\n server_label: Schema.optional(Schema.String),\n output: Schema.optional(Schema.Unknown),\n error: Schema.optional(Schema.Unknown),\n encrypted_content: optionalNull(Schema.String),\n})\ntype OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>\n\n// The Responses schema puts streaming error details at the top level and\n// response failures under `response.error`. The official SDK also recognizes\n// an event-level HTTP-style `error` envelope, so accept all three shapes here.\n// https://github.com/openai/openai-openapi/blob/5162af98d3147432c14680df789e8e12d4891e6b/openapi.yaml#L67234-L67382\n// https://github.com/openai/openai-node/blob/61539248cbe04665de68a71e6fd878127ae4db87/src/core/streaming.ts#L58-L85\nconst OpenAIResponsesErrorPayload = Schema.Struct({\n code: optionalNull(Schema.String),\n message: optionalNull(Schema.String),\n param: optionalNull(Schema.String),\n})\n\nconst OpenAIResponsesEvent = Schema.Struct({\n type: Schema.String,\n delta: Schema.optional(Schema.String),\n item_id: Schema.optional(Schema.String),\n summary_index: Schema.optional(Schema.Number),\n item: Schema.optional(OpenAIResponsesStreamItem),\n response: Schema.optional(\n Schema.StructWithRest(\n Schema.Struct({\n id: Schema.optional(Schema.String),\n service_tier: optionalNull(Schema.String),\n incomplete_details: optionalNull(Schema.Struct({ reason: Schema.String })),\n usage: optionalNull(OpenAIResponsesUsage),\n error: optionalNull(OpenAIResponsesErrorPayload),\n }),\n [Schema.Record(Schema.String, Schema.Unknown)],\n ),\n ),\n code: optionalNull(Schema.String),\n message: Schema.optional(Schema.String),\n param: optionalNull(Schema.String),\n error: optionalNull(OpenAIResponsesErrorPayload),\n})\ntype OpenAIResponsesEvent = Schema.Schema.Type<typeof OpenAIResponsesEvent>\n\ninterface ParserState {\n readonly tools: ToolStream.State<string>\n readonly hasFunctionCall: boolean\n readonly lifecycle: Lifecycle.State\n readonly reasoningItems: Readonly<Record<string, ReasoningStreamItem>>\n readonly store: boolean | undefined\n}\n\ntype ReasoningSummaryStatus = \"active\" | \"can-conclude\" | \"concluded\"\n\ninterface ReasoningStreamItem {\n readonly encryptedContent: string | null | undefined\n // Keyed by OpenAI's numeric `summary_index`. JS object keys coerce to\n // strings, but typing the map as `Record<number, ...>` documents intent\n // and matches the wire field.\n readonly summaryParts: Readonly<Record<number, ReasoningSummaryStatus>>\n}\n\nconst invalid = ProviderShared.invalidRequest\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIResponsesTool => ({\n type: \"function\",\n name: tool.name,\n description: tool.description,\n parameters: ToolSchemaProjection.openAI(inputSchema),\n // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.\n strict: false,\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"OpenAI Responses\", toolChoice, {\n auto: () => \"auto\" as const,\n none: () => \"none\" as const,\n required: () => \"required\" as const,\n tool: (name) => ({ type: \"function\" as const, name }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({\n type: \"function_call\",\n call_id: part.id,\n name: part.name,\n arguments: ProviderShared.encodeJson(part.input),\n})\n\nconst lowerReasoning = (part: ReasoningPart): OpenAIResponsesReasoningInput | undefined => {\n const openai = part.providerMetadata?.openai\n if (!ProviderShared.isRecord(openai) || typeof openai.itemId !== \"string\" || openai.itemId.length === 0)\n return undefined\n const encryptedContent =\n typeof openai.reasoningEncryptedContent === \"string\"\n ? openai.reasoningEncryptedContent\n : openai.reasoningEncryptedContent === null\n ? null\n : undefined\n return {\n type: \"reasoning\",\n id: openai.itemId,\n summary: part.text.length > 0 ? [{ type: \"summary_text\", text: part.text }] : [],\n encrypted_content: encryptedContent,\n }\n}\n\nconst hostedToolItemID = (part: ToolResultPart) => {\n const openai = part.providerMetadata?.openai\n return ProviderShared.isRecord(openai) && typeof openai.itemId === \"string\" && openai.itemId.length > 0\n ? openai.itemId\n : undefined\n}\n\nconst lowerUserContent = Effect.fn(\"OpenAIResponses.lowerUserContent\")(function* (\n part: LLMRequest[\"messages\"][number][\"content\"][number],\n) {\n if (part.type === \"text\") return { type: \"input_text\" as const, text: part.text }\n if (part.type === \"media\") {\n const media = yield* ProviderShared.validateMedia(\n \"OpenAI Responses\",\n part,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return { type: \"input_image\" as const, image_url: media.dataUrl }\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"user\", [\"text\", \"media\"])\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(\"OpenAIResponses.lowerToolResultContentItem\")(function* (\n item: ToolContent,\n) {\n if (item.type === \"text\") return { type: \"input_text\" as const, text: item.text }\n const media = yield* ProviderShared.validateToolFile(\n \"OpenAI Responses\",\n item,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return { type: \"input_image\" as const, image_url: media.dataUrl }\n})\n\nconst lowerToolResultOutput = Effect.fn(\"OpenAIResponses.lowerToolResultOutput\")(function* (part: ToolResultPart) {\n // Text/json/error results are encoded as a plain string for backward\n // compatibility 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\nconst lowerMessages = Effect.fn(\"OpenAIResponses.lowerMessages\")(function* (request: LLMRequest) {\n const system: OpenAIResponsesInputItem[] =\n request.system.length === 0 ? [] : [{ role: \"system\", content: ProviderShared.joinText(request.system) }]\n const input: OpenAIResponsesInputItem[] = [...system]\n const store = OpenAIOptions.store(request)\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"OpenAI Responses\", message)\n const previous = input.at(-1)\n if (previous && \"role\" in previous && previous.role === \"user\")\n input[input.length - 1] = {\n role: \"user\",\n content: [...previous.content, { type: \"input_text\", text: part.text }],\n }\n else input.push({ role: \"user\", content: [{ type: \"input_text\", text: part.text }] })\n continue\n }\n\n if (message.role === \"user\") {\n input.push({ role: \"user\", content: yield* Effect.forEach(message.content, lowerUserContent) })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: TextPart[] = []\n const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}\n const reasoningReferences = new Set<string>()\n const hostedToolReferences = new Set<string>()\n const flushText = () => {\n if (content.length === 0) return\n input.push({ role: \"assistant\", content: content.map((part) => ({ type: \"output_text\", text: part.text })) })\n content.splice(0, content.length)\n }\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push(part)\n continue\n }\n if (part.type === \"reasoning\") {\n flushText()\n const reasoning = lowerReasoning(part)\n if (!reasoning) continue\n if (store !== false) {\n if (!reasoningReferences.has(reasoning.id)) input.push({ type: \"item_reference\", id: reasoning.id })\n reasoningReferences.add(reasoning.id)\n continue\n }\n const existing = reasoningItems[reasoning.id]\n if (existing) {\n existing.summary.push(...reasoning.summary)\n if (typeof reasoning.encrypted_content === \"string\")\n existing.encrypted_content = reasoning.encrypted_content\n continue\n }\n const replay = {\n type: reasoning.type,\n summary: reasoning.summary,\n encrypted_content: reasoning.encrypted_content,\n }\n reasoningItems[reasoning.id] = replay\n input.push(replay)\n continue\n }\n if (part.type === \"tool-call\") {\n flushText()\n if (part.providerExecuted === true) continue\n input.push(lowerToolCall(part))\n continue\n }\n if (part.type === \"tool-result\" && part.providerExecuted === true) {\n flushText()\n const itemID = hostedToolItemID(part)\n if (store !== false && itemID && !hostedToolReferences.has(itemID))\n input.push({ type: \"item_reference\", id: itemID })\n if (itemID) hostedToolReferences.add(itemID)\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"assistant\", [\n \"text\",\n \"reasoning\",\n \"tool-call\",\n \"tool-result\",\n ])\n }\n flushText()\n continue\n }\n\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"tool\", [\"tool-result\"])\n input.push({\n type: \"function_call_output\",\n call_id: part.id,\n output: yield* lowerToolResultOutput(part),\n })\n }\n }\n\n // With store:false, OpenAI only accepts previous reasoning items when the\n // complete item has encrypted state. Summary blocks for one item may carry\n // that state only on the last block, so filter after they have been joined.\n return store === false\n ? input.filter(\n (item) => !(\"type\" in item) || item.type !== \"reasoning\" || typeof item.encrypted_content === \"string\",\n )\n : input\n})\n\nconst lowerOptions = Effect.fn(\"OpenAIResponses.lowerOptions\")(function* (request: LLMRequest) {\n const store = OpenAIOptions.store(request)\n const promptCacheKey = OpenAIOptions.promptCacheKey(request)\n const effort = OpenAIOptions.reasoningEffort(request)\n const summary = OpenAIOptions.reasoningSummary(request)\n const include = OpenAIOptions.include(request)\n const verbosity = OpenAIOptions.textVerbosity(request)\n const instructions = OpenAIOptions.instructions(request)\n const serviceTier = OpenAIOptions.serviceTier(request)\n return {\n ...(instructions ? { instructions } : {}),\n ...(store !== undefined ? { store } : {}),\n ...(promptCacheKey ? { prompt_cache_key: promptCacheKey } : {}),\n ...(include ? { include } : {}),\n ...(effort || summary ? { reasoning: { effort, summary } } : {}),\n ...(verbosity ? { text: { verbosity } } : {}),\n ...(serviceTier ? { service_tier: serviceTier } : {}),\n }\n})\n\nconst fromRequest = Effect.fn(\"OpenAIResponses.fromRequest\")(function* (request: LLMRequest) {\n const generation = request.generation\n const options = yield* lowerOptions(request)\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n return {\n model: request.model.id,\n input: 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 max_output_tokens: generation?.maxTokens,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n ...options,\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// OpenAI Responses reports `input_tokens` (inclusive total) with a\n// `cached_tokens` subset, and `output_tokens` (inclusive total) with a\n// `reasoning_tokens` subset. Pass the totals through and derive the\n// non-cached breakdown.\nconst mapUsage = (usage: OpenAIResponsesUsage | null | undefined) => {\n if (!usage) return undefined\n const cached = usage.input_tokens_details?.cached_tokens\n const reasoning = usage.output_tokens_details?.reasoning_tokens\n const nonCached = ProviderShared.subtractTokens(usage.input_tokens, cached)\n return new Usage({\n inputTokens: usage.input_tokens,\n outputTokens: usage.output_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: reasoning,\n totalTokens: ProviderShared.totalTokens(usage.input_tokens, usage.output_tokens, usage.total_tokens),\n providerMetadata: { openai: usage },\n })\n}\n\nconst mapFinishReason = (event: OpenAIResponsesEvent, hasFunctionCall: boolean): FinishReason => {\n const reason = event.response?.incomplete_details?.reason\n if (reason === undefined || reason === null) return hasFunctionCall ? \"tool-calls\" : \"stop\"\n if (reason === \"max_output_tokens\") return \"length\"\n if (reason === \"content_filter\") return \"content-filter\"\n return hasFunctionCall ? \"tool-calls\" : \"unknown\"\n}\n\nconst openaiMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ openai: metadata })\n\n// Hosted tool items (provider-executed) ship their typed input + status +\n// result fields all in one item. We expose them as a `tool-call` +\n// `tool-result` pair so consumers can treat them uniformly with client tools,\n// only differentiated by `providerExecuted: true`.\n//\n// One record per OpenAI Responses item type that represents a hosted\n// (provider-executed) tool call: the common name we surface, plus an `input`\n// extractor that picks the fields the model actually populated for that tool.\n// Falling back to `{}` when an entry isn't fully typed keeps unknown tools\n// observable without rolling a per-tool schema.\nconst HOSTED_TOOLS = {\n web_search_call: { name: \"web_search\", input: (item) => item.action ?? {} },\n web_search_preview_call: { name: \"web_search_preview\", input: (item) => item.action ?? {} },\n file_search_call: { name: \"file_search\", input: (item) => ({ queries: item.queries ?? [] }) },\n code_interpreter_call: {\n name: \"code_interpreter\",\n input: (item) => ({ code: item.code, container_id: item.container_id }),\n },\n computer_use_call: { name: \"computer_use\", input: (item) => item.action ?? {} },\n image_generation_call: { name: \"image_generation\", input: () => ({}) },\n mcp_call: {\n name: \"mcp\",\n input: (item) => ({ server_label: item.server_label, name: item.name, arguments: item.arguments }),\n },\n local_shell_call: { name: \"local_shell\", input: (item) => item.action ?? {} },\n} as const satisfies Record<\n string,\n { readonly name: string; readonly input: (item: OpenAIResponsesStreamItem) => unknown }\n>\n\ntype HostedToolType = keyof typeof HOSTED_TOOLS\n\nconst isHostedToolItem = (\n item: OpenAIResponsesStreamItem,\n): item is OpenAIResponsesStreamItem & { type: HostedToolType; id: string } =>\n item.type in HOSTED_TOOLS && typeof item.id === \"string\" && item.id.length > 0\n\nconst isReasoningItem = (\n item: OpenAIResponsesStreamItem,\n): item is OpenAIResponsesStreamItem & { type: \"reasoning\"; id: string } =>\n item.type === \"reasoning\" && typeof item.id === \"string\" && item.id.length > 0\n\n// Round-trip the full item as the structured result so consumers can extract\n// outputs / sources / status without re-decoding.\nconst hostedToolResult = (item: OpenAIResponsesStreamItem) => {\n const isError = typeof item.error !== \"undefined\" && item.error !== null\n return isError ? { type: \"error\" as const, value: item.error } : { type: \"json\" as const, value: item }\n}\n\nconst hostedToolEvents = (\n item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },\n): ReadonlyArray<LLMEvent> => {\n const tool = HOSTED_TOOLS[item.type]\n const providerMetadata = openaiMetadata({ itemId: item.id })\n return [\n LLMEvent.toolCall({\n id: item.id,\n name: tool.name,\n input: tool.input(item),\n providerExecuted: true,\n providerMetadata,\n }),\n LLMEvent.toolResult({\n id: item.id,\n name: tool.name,\n result: hostedToolResult(item),\n providerExecuted: true,\n providerMetadata,\n }),\n ]\n}\n\ntype StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]\n\nconst NO_EVENTS: StepResult[\"1\"] = []\n\n// `response.completed` / `response.incomplete` are clean finishes that emit a\n// `finish` event; `response.failed` is a hard failure. All three end the stream,\n// so keep this set aligned with `step` and the protocol's terminal predicate.\nconst TERMINAL_TYPES = new Set([\"response.completed\", \"response.incomplete\", \"response.failed\"])\n\nconst onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.delta) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, event.item_id ?? \"text-0\", event.delta) },\n events,\n ]\n}\n\nconst onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const events: LLMEvent[] = []\n return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? \"text-0\") }, events]\n}\n\nconst onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.delta) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n const itemID = event.item_id ?? \"reasoning-0\"\n const id =\n event.summary_index !== undefined || state.reasoningItems[itemID] ? `${itemID}:${event.summary_index ?? 0}` : itemID\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, id, event.delta),\n },\n events,\n ]\n}\n\nconst onReasoningDone = (state: ParserState, _event: OpenAIResponsesEvent): StepResult => [state, NO_EVENTS]\n\nconst reasoningMetadata = (item: OpenAIResponsesStreamItem & { id: string }) =>\n openaiMetadata({ itemId: item.id, reasoningEncryptedContent: item.encrypted_content ?? null })\n\n// OpenAI Responses streams reasoning items in a stable order:\n// `output_item.added` (reasoning) →\n// `reasoning_summary_part.added` (index=0) →\n// `reasoning_summary_text.delta` →\n// `reasoning_summary_part.done` (index=0) →\n// (repeat for index>0) →\n// `output_item.done` (reasoning).\n// The handlers below rely on this ordering: `onOutputItemAdded` seeds the\n// per-item entry, `onReasoningSummaryPartAdded` for `summary_index === 0`\n// short-circuits when the entry already exists, and higher-index handlers\n// fold against the same entry. Behaviour for out-of-order events is\n// best-effort, not guaranteed.\nconst onOutputItemAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const item = event.item\n if (item && isReasoningItem(item)) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(state.lifecycle, events, `${item.id}:0`, reasoningMetadata(item)),\n reasoningItems: {\n ...state.reasoningItems,\n [item.id]: { encryptedContent: item.encrypted_content, summaryParts: { 0: \"active\" } },\n },\n },\n events,\n ]\n }\n if (item?.type !== \"function_call\" || !item.id) return [state, NO_EVENTS]\n const providerMetadata = openaiMetadata({ itemId: item.id })\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n hasFunctionCall: state.hasFunctionCall,\n tools: ToolStream.start(state.tools, item.id, {\n id: item.call_id ?? item.id,\n name: item.name ?? \"\",\n input: item.arguments ?? \"\",\n providerMetadata,\n }),\n },\n [...events, LLMEvent.toolInputStart({ id: item.call_id ?? item.id, name: item.name ?? \"\", providerMetadata })],\n ]\n}\n\nconst onReasoningSummaryPartAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]\n const item = state.reasoningItems[event.item_id] ?? { encryptedContent: undefined, summaryParts: {} }\n if (event.summary_index === 0) {\n if (state.reasoningItems[event.item_id]) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(\n state.lifecycle,\n events,\n `${event.item_id}:0`,\n openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: null }),\n ),\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: { ...item, summaryParts: { 0: \"active\" } },\n },\n },\n events,\n ]\n }\n\n const events: LLMEvent[] = []\n const closed = Object.entries(item.summaryParts)\n .filter((entry) => entry[1] === \"can-conclude\")\n .reduce(\n (lifecycle, entry) =>\n Lifecycle.reasoningEnd(\n lifecycle,\n events,\n `${event.item_id}:${entry[0]}`,\n openaiMetadata({ itemId: event.item_id }),\n ),\n state.lifecycle,\n )\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(\n closed,\n events,\n `${event.item_id}:${event.summary_index}`,\n openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: item.encryptedContent ?? null }),\n ),\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: {\n ...item,\n summaryParts: {\n ...Object.fromEntries(\n Object.entries(item.summaryParts).map((entry) =>\n entry[1] === \"can-conclude\" ? [entry[0], \"concluded\" as const] : entry,\n ),\n ),\n [event.summary_index]: \"active\",\n },\n },\n },\n },\n events,\n ]\n}\n\nconst onReasoningSummaryPartDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]\n const item = state.reasoningItems[event.item_id]\n if (!item) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle:\n state.store !== false\n ? Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n `${event.item_id}:${event.summary_index}`,\n openaiMetadata({ itemId: event.item_id }),\n )\n : state.lifecycle,\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: {\n ...item,\n summaryParts: {\n ...item.summaryParts,\n [event.summary_index]: state.store !== false ? \"concluded\" : \"can-conclude\",\n },\n },\n },\n },\n events,\n ]\n}\n\nconst onFunctionCallArgumentsDelta = Effect.fn(\"OpenAIResponses.onFunctionCallArgumentsDelta\")(function* (\n state: ParserState,\n event: OpenAIResponsesEvent,\n) {\n if (!event.item_id || !event.delta) return [state, NO_EVENTS] satisfies StepResult\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n event.item_id,\n event.delta,\n \"OpenAI Responses 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\nconst onOutputItemDone = Effect.fn(\"OpenAIResponses.onOutputItemDone\")(function* (\n state: ParserState,\n event: OpenAIResponsesEvent,\n) {\n const item = event.item\n if (!item) return [state, NO_EVENTS] satisfies StepResult\n\n if (item.type === \"message\" && item.id) return onOutputTextDone(state, { ...event, item_id: item.id })\n\n if (item.type === \"function_call\") {\n if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult\n const tools = state.tools[item.id]\n ? state.tools\n : ToolStream.start(state.tools, item.id, { id: item.call_id, name: item.name })\n const result =\n item.arguments === undefined\n ? yield* ToolStream.finish(ADAPTER, tools, item.id)\n : yield* ToolStream.finishWithInput(ADAPTER, tools, item.id, item.arguments)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...resultEvents)\n return [\n {\n ...state,\n lifecycle,\n hasFunctionCall: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasFunctionCall,\n tools: result.tools,\n },\n events,\n ] satisfies StepResult\n }\n\n if (isHostedToolItem(item)) {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n events.push(...hostedToolEvents(item))\n return [{ ...state, lifecycle }, events] satisfies StepResult\n }\n\n if (isReasoningItem(item)) {\n const events: LLMEvent[] = []\n const providerMetadata = reasoningMetadata(item)\n const reasoningItem = state.reasoningItems[item.id]\n if (reasoningItem) {\n const lifecycle = Object.entries(reasoningItem.summaryParts)\n .filter((entry) => entry[1] === \"active\" || entry[1] === \"can-conclude\")\n .reduce(\n (lifecycle, entry) => Lifecycle.reasoningEnd(lifecycle, events, `${item.id}:${entry[0]}`, providerMetadata),\n state.lifecycle,\n )\n const { [item.id]: _removed, ...reasoningItems } = state.reasoningItems\n return [{ ...state, lifecycle, reasoningItems }, events] satisfies StepResult\n }\n if (!state.lifecycle.reasoning.has(item.id)) {\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n events.push(LLMEvent.reasoningStart({ id: item.id, providerMetadata }))\n events.push(LLMEvent.reasoningEnd({ id: item.id, providerMetadata }))\n return [{ ...state, lifecycle }, events] satisfies StepResult\n }\n return [\n { ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, item.id, providerMetadata) },\n events,\n ] satisfies StepResult\n }\n\n return [state, NO_EVENTS] satisfies StepResult\n})\n\nconst onResponseFinish = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.finish(state.lifecycle, events, {\n reason: mapFinishReason(event, state.hasFunctionCall),\n usage: mapUsage(event.response?.usage),\n providerMetadata:\n event.response?.id || event.response?.service_tier\n ? openaiMetadata({\n responseId: event.response.id,\n serviceTier: event.response.service_tier,\n })\n : undefined,\n })\n return [{ ...state, lifecycle }, events]\n}\n\n// Build a single human-readable message from whatever the provider supplied.\n// When both code and message are present, prefix the code so consumers see\n// the failure mode (e.g. `rate_limit_exceeded: Slow down`) instead of just\n// the bare message — production rate limits and context-length failures used\n// to be indistinguishable from generic stream drops.\nconst providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): string => {\n const nested = event.error ?? event.response?.error ?? undefined\n const message = event.message || nested?.message || undefined\n const code = event.code || nested?.code || undefined\n if (message && code) return `${code}: ${message}`\n return message || code || fallback\n}\n\nconst providerError = (event: OpenAIResponsesEvent, fallback: string) => {\n const code = event.code || event.error?.code || event.response?.error?.code || undefined\n const message = providerErrorMessage(event, fallback)\n return new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({ message, code }),\n })\n}\n\nconst step = (state: ParserState, event: OpenAIResponsesEvent) => {\n if (event.type === \"response.output_text.delta\") return Effect.succeed(onOutputTextDelta(state, event))\n if (event.type === \"response.output_text.done\") return Effect.succeed(onOutputTextDone(state, event))\n if (\n event.type === \"response.reasoning_text.delta\" ||\n event.type === \"response.reasoning_summary.delta\" ||\n event.type === \"response.reasoning_summary_text.delta\"\n )\n return Effect.succeed(onReasoningDelta(state, event))\n if (\n event.type === \"response.reasoning_text.done\" ||\n event.type === \"response.reasoning_summary.done\" ||\n event.type === \"response.reasoning_summary_text.done\"\n )\n return Effect.succeed(onReasoningDone(state, event))\n if (event.type === \"response.reasoning_summary_part.added\")\n return Effect.succeed(onReasoningSummaryPartAdded(state, event))\n if (event.type === \"response.reasoning_summary_part.done\")\n return Effect.succeed(onReasoningSummaryPartDone(state, event))\n if (event.type === \"response.output_item.added\") return Effect.succeed(onOutputItemAdded(state, event))\n if (event.type === \"response.function_call_arguments.delta\") return onFunctionCallArgumentsDelta(state, event)\n if (event.type === \"response.output_item.done\") return onOutputItemDone(state, event)\n if (event.type === \"response.completed\" || event.type === \"response.incomplete\")\n return Effect.succeed(onResponseFinish(state, event))\n if (event.type === \"response.failed\") return providerError(event, \"OpenAI Responses response failed\")\n if (event.type === \"error\") return providerError(event, \"OpenAI Responses stream error\")\n return Effect.succeed<StepResult>([state, NO_EVENTS])\n}\n\n// =============================================================================\n// Protocol And OpenAI Route\n// =============================================================================\n/**\n * The OpenAI Responses protocol — request body construction, body schema, and\n * the streaming-event state machine. Used by native OpenAI and (once\n * registered) Azure OpenAI Responses.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: OpenAIResponsesBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(OpenAIResponsesEvent),\n initial: (request) => ({\n hasFunctionCall: false,\n tools: ToolStream.empty<string>(),\n lifecycle: Lifecycle.initial(),\n reasoningItems: {},\n store: OpenAIOptions.store(request),\n }),\n step,\n terminal: (event) => TERMINAL_TYPES.has(event.type),\n },\n})\n\nconst endpoint = Endpoint.path<OpenAIResponsesBody>(PATH, { baseURL: DEFAULT_BASE_URL })\nconst auth = Auth.none\n\nexport const httpTransport = HttpTransport.sseJson.with<OpenAIResponsesBody>()\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint,\n auth,\n transport: httpTransport,\n defaults: { providerOptions: { openai: { store: false } } },\n})\n\nconst decodeWebSocketMessage = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesWebSocketMessage))\n\nconst webSocketMessage = (body: OpenAIResponsesBody | Record<string, unknown>) =>\n Effect.gen(function* () {\n if (!ProviderShared.isRecord(body))\n return yield* ProviderShared.invalidRequest(\"OpenAI Responses WebSocket body must be a JSON object\")\n const { stream: _stream, ...message } = body\n return yield* decodeWebSocketMessage({ ...message, type: \"response.create\" })\n })\n\nexport const webSocketTransport = WebSocketTransport.jsonTransport.with<\n OpenAIResponsesBody,\n OpenAIResponsesWebSocketMessage\n>({\n toMessage: webSocketMessage,\n encodeMessage: encodeWebSocketMessage,\n})\n\nexport const webSocketRoute = Route.make({\n id: `${ADAPTER}-websocket`,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint,\n auth,\n transport: webSocketTransport,\n defaults: { providerOptions: { openai: { store: false } } },\n})\n\nexport * as OpenAIResponses from \"./openai-responses\"\n" | ||
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| ||
| "debugId": "0AC81B2102696FCF64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
| ], | ||
| "mappings": "", | ||
| "debugId": "7141D32940188BD564756E2164756E21", | ||
| "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 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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$7;\n 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(closed) throw new Error(\"timeline closed\");\n if (writing) throw new Error(\"timeline write already in progress\");\n writing = true;\n try {\n const style = kind === \"pending\" ? undefined : ROWS[kind];\n const marker = kind === \"pending\" ? \".\" : ROWS[kind].marker;\n const connector = style?.connector ? \"│\\n\" : \"\";\n active = new Promise((resolve, reject) => {\n stdout.write(`${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": "F9A263D7E1EAF79864756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "FC6F397A271217B664756E2164756E21", | ||
| "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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| "debugId": "9E1059ECFA917FE964756E2164756E21", | ||
| "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": "182A2235DD73EB1064756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/backend/network.ts", "../simulation/src/backend/openai.ts", "../simulation/src/backend/simulated-provider.ts", "../simulation/src/backend/index.ts"], | ||
| "sourcesContent": [ | ||
| "import { Clock, Effect, Layer, Ref } from \"effect\"\nimport { HttpClient, HttpClientResponse, type HttpMethod } from \"effect/unstable/http\"\nimport { HttpClientError, TransportError } from \"effect/unstable/http/HttpClientError\"\nimport type { HttpClientRequest } from \"effect/unstable/http\"\nimport { SimulationProtocol } from \"../protocol\"\n\n/**\n * Simulated network.\n *\n * Replaces the `HttpClient.HttpClient` platform node in simulation mode. All\n * outbound HTTP resolves against an in-memory route table; unknown\n * destinations fail loudly with a transport error so no simulation run can\n * silently reach the real network. The scripted LLM is one registered route,\n * not a separate mechanism.\n *\n * Each acquired run owns its routes and request log.\n */\n\nexport interface Route {\n /** Return a response effect to claim the request, undefined to pass. */\n readonly match: (\n request: HttpClientRequest.HttpClientRequest,\n url: URL,\n ) => Effect.Effect<HttpClientResponse.HttpClientResponse, HttpClientError> | undefined\n}\n\nexport type LogEntry = SimulationProtocol.Backend.NetworkLogEntry\n\nconst LOG_LIMIT = 1000\n\n/** Static JSON route: exact method + origin/path match answered with a fixed body. */\nexport function json(method: HttpMethod.HttpMethod, url: string, body: unknown): Route {\n return {\n match: (request, requestUrl) => {\n if (request.method !== method) return undefined\n if (requestUrl.origin + requestUrl.pathname !== url) return undefined\n return Effect.sync(() =>\n HttpClientResponse.fromWeb(\n request,\n new Response(JSON.stringify(body), { status: 200, headers: { \"content-type\": \"application/json\" } }),\n ),\n )\n },\n }\n}\n\nexport interface Run {\n readonly client: HttpClient.HttpClient\n readonly log: () => Effect.Effect<readonly LogEntry[]>\n}\n\nexport const make = Effect.fn(\"SimulationNetwork.make\")(function* (routes: readonly Route[] = []) {\n const log = yield* Ref.make<readonly LogEntry[]>([])\n const client = HttpClient.make((request, url) =>\n Effect.gen(function* () {\n let matched: Effect.Effect<HttpClientResponse.HttpClientResponse, HttpClientError> | undefined\n for (const route of routes) {\n matched = route.match(request, url)\n if (matched) break\n }\n const entry = {\n time: yield* Clock.currentTimeMillis,\n method: request.method,\n url: url.toString(),\n matched: matched !== undefined,\n }\n yield* Ref.update(log, (entries) => [...entries, entry].slice(-LOG_LIMIT))\n if (matched) return yield* matched\n return yield* Effect.fail(\n new HttpClientError({\n reason: new TransportError({\n request,\n description: `Simulation denied unregistered network destination: ${request.method} ${url}`,\n }),\n }),\n )\n }),\n )\n return { client, log: () => Ref.get(log) } satisfies Run\n})\n\nexport const layer = (routes: readonly Route[] = []) =>\n Layer.effect(HttpClient.HttpClient, make(routes).pipe(Effect.map((run) => run.client)))\n\nexport * as SimulationNetwork from \"./network\"\n", | ||
| "import { Effect, Schema, Stream } from \"effect\"\nimport { HttpClientResponse } from \"effect/unstable/http\"\nimport { HttpClientError, TransportError } from \"effect/unstable/http/HttpClientError\"\nimport { OpenAIChatEvent, DEFAULT_BASE_URL, PATH } from \"@opencode-ai/ai/protocols/openai-chat\"\nimport { SimulationNetwork } from \"./network\"\nimport { SimulatedProvider } from \"./simulated-provider\"\n\n/**\n * Driver-answered OpenAI endpoint for the simulated network.\n *\n * Claims `POST {DEFAULT_BASE_URL}{PATH}` (the real openai-chat route\n * endpoint), invokes the simulated provider, and streams the driver's events back as\n * an OpenAI Chat SSE response terminated by `[DONE]`. Everything downstream\n * of the response bytes is the real pipeline: SSE framing, the OpenAIChat\n * event schema, the protocol state machine, and Lifecycle grammar.\n */\n\nconst encodeChunk = Schema.encodeUnknownSync(OpenAIChatEvent)\n\nconst encoder = new TextEncoder()\nconst decodeBody = Schema.decodeUnknownEffect(Schema.fromJsonString(Schema.Json))\n\n// The simulated model id is echoed back only in non-schema fields; the\n// protocol event schema ignores unknown fields, so id/object/model are\n// decorative wire realism.\ntype ProviderItem = Exclude<SimulatedProvider.ProviderResponseEvent, { readonly type: \"finish\" }>\ntype FinishReason = Extract<SimulatedProvider.ProviderResponseEvent, { readonly type: \"finish\" }>[\"reason\"]\n\nfunction chunkOf(item: ProviderItem): OpenAIChatEvent | unknown {\n if (item.type === \"textDelta\") return { choices: [{ delta: { content: item.text } }] }\n if (item.type === \"reasoningDelta\") return { choices: [{ delta: { reasoning_content: item.text } }] }\n if (item.type === \"toolCall\")\n return {\n choices: [\n {\n delta: {\n tool_calls: [\n {\n index: item.index,\n id: item.id,\n function: { name: item.name, arguments: JSON.stringify(item.input) },\n },\n ],\n },\n },\n ],\n }\n return item.chunk\n}\n\nconst finishReasonWire: Record<FinishReason, string> = {\n stop: \"stop\",\n \"tool-calls\": \"tool_calls\",\n length: \"length\",\n \"content-filter\": \"content_filter\",\n}\n\nfunction frame(payload: unknown): Uint8Array {\n return encoder.encode(`data: ${JSON.stringify(payload)}\\n\\n`)\n}\n\nfunction sseBody(\n events: Stream.Stream<SimulatedProvider.ProviderResponseEvent, SimulatedProvider.ProviderDisconnectedError>,\n): Stream.Stream<Uint8Array, SimulatedProvider.ProviderDisconnectedError> {\n return events.pipe(\n Stream.map((event) => {\n if (event.type === \"finish\")\n return frame(encodeChunk({ choices: [{ delta: {}, finish_reason: finishReasonWire[event.reason] }] }))\n if (event.type === \"raw\") return frame(event.chunk)\n return frame(encodeChunk(chunkOf(event)))\n }),\n Stream.concat(Stream.make(encoder.encode(\"data: [DONE]\\n\\n\"))),\n )\n}\n\nexport const route = (provider: SimulatedProvider.Interface): SimulationNetwork.Route => ({\n match: (request, url) => {\n if (request.method !== \"POST\") return undefined\n if (url.origin + url.pathname !== DEFAULT_BASE_URL + PATH) return undefined\n return Effect.gen(function* () {\n const body =\n request.body._tag === \"Uint8Array\"\n ? yield* decodeBody(new TextDecoder().decode(request.body.body)).pipe(\n Effect.mapError(\n (cause) =>\n new HttpClientError({\n reason: new TransportError({\n request,\n cause,\n description: \"Simulation received an invalid OpenAI request body\",\n }),\n }),\n ),\n )\n : {}\n return HttpClientResponse.fromWeb(\n request,\n new Response(Stream.toReadableStream(sseBody(provider.stream({ url: url.toString(), body }))), {\n status: 200,\n headers: { \"content-type\": \"text/event-stream\" },\n }),\n )\n })\n },\n})\n\nexport * as SimulationOpenAI from \"./openai\"\n", | ||
| "import { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Cause, Context, Effect, Fiber, FiberSet, Layer, PubSub, Queue, Ref, Schema, Semaphore, Stream } from \"effect\"\nimport { SimulationControlServer } from \"../control-server\"\nimport { SimulationProtocol } from \"../protocol\"\n\nexport interface ProviderRequest {\n readonly url: string\n readonly body: unknown\n}\n\nexport type ProviderResponseEvent =\n | SimulationProtocol.Backend.Item\n | { readonly type: \"finish\"; readonly reason: SimulationProtocol.Backend.FinishReason }\n\nexport class ProviderDisconnectedError extends Schema.TaggedErrorClass<ProviderDisconnectedError>()(\n \"SimulatedProvider.ProviderDisconnectedError\",\n { message: Schema.String },\n) {}\n\nexport interface Interface {\n readonly stream: (request: ProviderRequest) => Stream.Stream<ProviderResponseEvent, ProviderDisconnectedError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/simulation/SimulatedProvider\") {}\n\ninterface ProviderInvocation extends ProviderRequest {\n readonly id: string\n}\n\ninterface PendingInvocation extends ProviderInvocation {\n readonly responses: Queue.Queue<ProviderResponseEvent, ProviderDisconnectedError | Cause.Done>\n}\n\ninterface State {\n readonly counter: number\n readonly pending: ReadonlyMap<string, PendingInvocation>\n}\n\ninterface Driver {\n readonly requests: Stream.Stream<ProviderInvocation>\n readonly push: (\n id: string,\n items: readonly SimulationProtocol.Backend.Item[],\n ) => Effect.Effect<void, InvocationNotFoundError>\n readonly finish: (\n id: string,\n reason: SimulationProtocol.Backend.FinishReason,\n ) => Effect.Effect<void, InvocationNotFoundError>\n readonly disconnect: (id: string) => Effect.Effect<void, InvocationNotFoundError>\n readonly pending: () => Effect.Effect<readonly ProviderInvocation[]>\n}\n\nclass InvocationNotFoundError extends Schema.TaggedErrorClass<InvocationNotFoundError>()(\n \"SimulatedProvider.InvocationNotFoundError\",\n { id: Schema.String, message: Schema.String },\n) {}\n\nclass ControllerDisconnectedError extends Schema.TaggedErrorClass<ControllerDisconnectedError>()(\n \"SimulatedProvider.ControllerDisconnectedError\",\n { message: Schema.String },\n) {}\n\ntype ControlSocket = SimulationControlServer.Socket\n\nexport const layerDrive = (options: { readonly endpoint: string }) =>\n Layer.effect(\n Service,\n Effect.gen(function* () {\n const state = yield* Ref.make<State>({ counter: 0, pending: new Map() })\n const opened = yield* PubSub.unbounded<ProviderInvocation>()\n const lock = yield* Semaphore.make(1)\n\n const close = (invocation: PendingInvocation) =>\n Effect.gen(function* () {\n yield* Queue.shutdown(invocation.responses)\n yield* lock.withPermit(\n Ref.update(state, (current) =>\n current.pending.get(invocation.id) === invocation ? remove(current, invocation.id) : current,\n ),\n )\n })\n\n yield* Effect.addFinalizer(() =>\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n yield* Effect.forEach(current.pending.values(), (invocation) => Queue.shutdown(invocation.responses), {\n discard: true,\n })\n yield* PubSub.shutdown(opened)\n }),\n )\n\n const open = (request: ProviderRequest) =>\n lock.withPermit(\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n const id = `inv_${current.counter + 1}`\n const responses = yield* Queue.bounded<ProviderResponseEvent, ProviderDisconnectedError | Cause.Done>(256)\n const invocation: PendingInvocation = { id, ...request, responses }\n yield* Ref.set(state, {\n counter: current.counter + 1,\n pending: new Map(current.pending).set(id, invocation),\n })\n yield* PubSub.publish(opened, { id, ...request })\n return invocation\n }),\n )\n\n const requireInvocation = (id: string) =>\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n const invocation = current.pending.get(id)\n if (invocation) return invocation\n return yield* Effect.fail(\n new InvocationNotFoundError({\n id,\n message: `Simulated provider invocation not found or already finished: ${id}`,\n }),\n )\n })\n\n const remove = (current: State, id: string) => {\n const pending = new Map(current.pending)\n pending.delete(id)\n return { ...current, pending }\n }\n\n const driver: Driver = {\n requests: Stream.unwrap(\n lock.withPermit(\n Effect.gen(function* () {\n const subscription = yield* PubSub.subscribe(opened)\n const current = yield* Ref.get(state)\n const pending = Array.from(current.pending.values(), ({ id, url, body }) => ({ id, url, body }))\n return Stream.concat(Stream.fromIterable(pending), Stream.fromEffectRepeat(PubSub.take(subscription)))\n }),\n ),\n ),\n push: (id, items) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(requireInvocation(id))\n yield* Queue.offerAll(invocation.responses, items)\n }),\n finish: (id, reason) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(\n Effect.gen(function* () {\n const invocation = yield* requireInvocation(id)\n const current = yield* Ref.get(state)\n yield* Ref.set(state, remove(current, id))\n return invocation\n }),\n )\n yield* Queue.offer(invocation.responses, { type: \"finish\", reason })\n yield* Queue.end(invocation.responses)\n }),\n disconnect: (id) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(\n Effect.gen(function* () {\n const invocation = yield* requireInvocation(id)\n const current = yield* Ref.get(state)\n yield* Ref.set(state, remove(current, id))\n return invocation\n }),\n )\n yield* Queue.fail(\n invocation.responses,\n new ProviderDisconnectedError({ message: \"Simulated model provider disconnected\" }),\n )\n }),\n pending: () =>\n lock.withPermit(\n Ref.get(state).pipe(\n Effect.map((current) => Array.from(current.pending.values(), ({ id, url, body }) => ({ id, url, body }))),\n ),\n ),\n }\n\n const fibers = yield* FiberSet.make<void, unknown>()\n const activeController = yield* Ref.make<Fiber.Fiber<void> | undefined>(undefined)\n const controllerLock = yield* Semaphore.make(1)\n yield* SimulationControlServer.start({\n endpoint: options.endpoint,\n label: \"opencode drive backend websocket\",\n data: () => ({}),\n decode: SimulationProtocol.Backend.decodeRequestEffect,\n handle: (socket, request) => handle(driver, fibers, activeController, controllerLock, socket, request),\n close: (socket) => releaseController(activeController, controllerLock, socket),\n })\n yield* Effect.sync(() => process.stderr.write(`opencode drive backend websocket: ${options.endpoint}\\n`))\n\n return Service.of({\n stream: (request) =>\n Stream.unwrap(\n Effect.acquireRelease(open(request), close).pipe(\n Effect.map((invocation) =>\n Stream.fromQueue(invocation.responses).pipe(Stream.takeUntil((event) => event.type === \"finish\")),\n ),\n ),\n ),\n })\n }),\n )\n\nfunction handle(\n driver: Driver,\n fibers: FiberSet.FiberSet<void, unknown>,\n activeController: Ref.Ref<Fiber.Fiber<void> | undefined>,\n controllerLock: Semaphore.Semaphore,\n socket: ControlSocket,\n request: SimulationProtocol.Backend.Request,\n) {\n switch (request.method) {\n case \"simulation.handshake\":\n return SimulationProtocol.Handshake.dispatch(\n {\n role: \"backend\",\n server: { name: \"opencode\", version: InstallationVersion },\n capabilities: SimulationProtocol.Backend.Capabilities,\n },\n request.params,\n )\n case \"llm.attach\":\n return controllerLock.withPermit(\n Effect.gen(function* () {\n if (socket.data.closed)\n return yield* Effect.fail(\n new ControllerDisconnectedError({ message: \"Drive controller disconnected before attachment\" }),\n )\n const previous = yield* Ref.get(activeController)\n if (previous) yield* Fiber.interrupt(previous)\n const attachment = yield* FiberSet.run(\n fibers,\n driver.requests.pipe(\n Stream.runForEach((invocation) =>\n Effect.sync(() => {\n socket.send(JSON.stringify({ jsonrpc: \"2.0\", method: \"llm.request\", params: invocation }))\n }),\n ),\n ),\n )\n if (socket.data.closed) {\n yield* Fiber.interrupt(attachment)\n return yield* Effect.fail(\n new ControllerDisconnectedError({ message: \"Drive controller disconnected during attachment\" }),\n )\n }\n socket.data.attachment = attachment\n yield* Ref.set(activeController, attachment)\n return { attached: true }\n }),\n )\n case \"llm.chunk\":\n return driver.push(request.params.id, request.params.items).pipe(Effect.as({ ok: true }))\n case \"llm.finish\":\n return driver.finish(request.params.id, request.params.reason).pipe(Effect.as({ ok: true }))\n case \"llm.disconnect\":\n return driver.disconnect(request.params.id).pipe(Effect.as({ ok: true }))\n case \"llm.pending\":\n return driver.pending().pipe(Effect.map((invocations) => ({ invocations })))\n }\n}\n\nfunction releaseController(\n activeController: Ref.Ref<Fiber.Fiber<void> | undefined>,\n controllerLock: Semaphore.Semaphore,\n socket: ControlSocket,\n) {\n return controllerLock.withPermit(\n Effect.gen(function* () {\n const attachment = socket.data.attachment\n if (!attachment) return\n yield* Fiber.interrupt(attachment)\n yield* Ref.update(activeController, (active) => (active === attachment ? undefined : active))\n }),\n )\n}\n\nexport * as SimulatedProvider from \"./simulated-provider\"\n", | ||
| "import { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { httpClient } from \"@opencode-ai/core/effect/app-node-platform\"\nimport { Config, Effect, Layer } from \"effect\"\nimport { HttpClient } from \"effect/unstable/http\"\nimport { DriveManifest } from \"../manifest\"\nimport { SimulationNetwork } from \"./network\"\nimport { SimulationOpenAI } from \"./openai\"\nimport { SimulatedProvider } from \"./simulated-provider\"\n\n/**\n * Layer replacements applied when the server is built in simulation mode.\n *\n * The server merges these into the app node build when `OPENCODE_SIMULATE`\n * is enabled, via a dynamic import so this module is never loaded eagerly.\n *\n * - Network: all outbound HTTP resolves against the simulated route table;\n * unknown destinations are denied. The driver-answered OpenAI endpoint is\n * registered here as the first route.\n *\n */\n\nexport const simulationReplacements = Effect.fn(\"Simulation.replacements\")(function* () {\n // ModelsDev dies when its catalog fetch fails, so simulation answers it with\n // an empty catalog; providers come from seeded config instead.\n const models = SimulationNetwork.json(\"GET\", \"https://models.dev/api.json\", {})\n const drive = yield* Config.string(\"OPENCODE_DRIVE\").pipe(Config.withDefault(undefined))\n if (!drive) return [[httpClient, SimulationNetwork.layer([models])]] satisfies LayerNode.Replacements\n\n const manifest = yield* DriveManifest.resolve()\n const networkLayer = Layer.effect(\n HttpClient.HttpClient,\n Effect.gen(function* () {\n const provider = yield* SimulatedProvider.Service\n const network = yield* SimulationNetwork.make([SimulationOpenAI.route(provider), models])\n return network.client\n }),\n ).pipe(\n Layer.provide(\n SimulatedProvider.layerDrive({\n endpoint: manifest.endpoints.backend,\n }),\n ),\n )\n return [[httpClient, networkLayer]] satisfies LayerNode.Replacements\n})\n\nexport * as Simulation from \"./index\"\n" | ||
| ], | ||
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| ||
| "debugId": "8949052148BB0FE164756E2164756E21", | ||
| "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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| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
| ], | ||
| "mappings": "", | ||
| "debugId": "6366E8E5FC60115964756E2164756E21", | ||
| "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": "E60A31140DF5697C64756E2164756E21", | ||
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| } |
| { | ||
| "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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| } |
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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/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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| } |
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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": "4E82D9423974D14764756E2164756E21", | ||
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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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| "debugId": "AA4E57CBB6119C1464756E2164756E21", | ||
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| { | ||
| "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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Sorry, the diff of this file is too big to display
| { | ||
| "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(\"../../mini\"))\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": "081A8799C4AAAE8D64756E2164756E21", | ||
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| { | ||
| "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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+1
-1
| { | ||
| "name": "@opencode-ai/cli-linux-arm64", | ||
| "version": "0.0.0-next-15793", | ||
| "version": "0.0.0-next-15798", | ||
| "license": "MIT", | ||
@@ -5,0 +5,0 @@ "repository": { |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
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| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/backend/network.ts", "../simulation/src/backend/openai.ts", "../simulation/src/backend/simulated-provider.ts", "../simulation/src/backend/index.ts"], | ||
| "sourcesContent": [ | ||
| "import { Clock, Effect, Layer, Ref } from \"effect\"\nimport { HttpClient, HttpClientResponse, type HttpMethod } from \"effect/unstable/http\"\nimport { HttpClientError, TransportError } from \"effect/unstable/http/HttpClientError\"\nimport type { HttpClientRequest } from \"effect/unstable/http\"\nimport { SimulationProtocol } from \"../protocol\"\n\n/**\n * Simulated network.\n *\n * Replaces the `HttpClient.HttpClient` platform node in simulation mode. All\n * outbound HTTP resolves against an in-memory route table; unknown\n * destinations fail loudly with a transport error so no simulation run can\n * silently reach the real network. The scripted LLM is one registered route,\n * not a separate mechanism.\n *\n * Each acquired run owns its routes and request log.\n */\n\nexport interface Route {\n /** Return a response effect to claim the request, undefined to pass. */\n readonly match: (\n request: HttpClientRequest.HttpClientRequest,\n url: URL,\n ) => Effect.Effect<HttpClientResponse.HttpClientResponse, HttpClientError> | undefined\n}\n\nexport type LogEntry = SimulationProtocol.Backend.NetworkLogEntry\n\nconst LOG_LIMIT = 1000\n\n/** Static JSON route: exact method + origin/path match answered with a fixed body. */\nexport function json(method: HttpMethod.HttpMethod, url: string, body: unknown): Route {\n return {\n match: (request, requestUrl) => {\n if (request.method !== method) return undefined\n if (requestUrl.origin + requestUrl.pathname !== url) return undefined\n return Effect.sync(() =>\n HttpClientResponse.fromWeb(\n request,\n new Response(JSON.stringify(body), { status: 200, headers: { \"content-type\": \"application/json\" } }),\n ),\n )\n },\n }\n}\n\nexport interface Run {\n readonly client: HttpClient.HttpClient\n readonly log: () => Effect.Effect<readonly LogEntry[]>\n}\n\nexport const make = Effect.fn(\"SimulationNetwork.make\")(function* (routes: readonly Route[] = []) {\n const log = yield* Ref.make<readonly LogEntry[]>([])\n const client = HttpClient.make((request, url) =>\n Effect.gen(function* () {\n let matched: Effect.Effect<HttpClientResponse.HttpClientResponse, HttpClientError> | undefined\n for (const route of routes) {\n matched = route.match(request, url)\n if (matched) break\n }\n const entry = {\n time: yield* Clock.currentTimeMillis,\n method: request.method,\n url: url.toString(),\n matched: matched !== undefined,\n }\n yield* Ref.update(log, (entries) => [...entries, entry].slice(-LOG_LIMIT))\n if (matched) return yield* matched\n return yield* Effect.fail(\n new HttpClientError({\n reason: new TransportError({\n request,\n description: `Simulation denied unregistered network destination: ${request.method} ${url}`,\n }),\n }),\n )\n }),\n )\n return { client, log: () => Ref.get(log) } satisfies Run\n})\n\nexport const layer = (routes: readonly Route[] = []) =>\n Layer.effect(HttpClient.HttpClient, make(routes).pipe(Effect.map((run) => run.client)))\n\nexport * as SimulationNetwork from \"./network\"\n", | ||
| "import { Effect, Schema, Stream } from \"effect\"\nimport { HttpClientResponse } from \"effect/unstable/http\"\nimport { HttpClientError, TransportError } from \"effect/unstable/http/HttpClientError\"\nimport { OpenAIChatEvent, DEFAULT_BASE_URL, PATH } from \"@opencode-ai/ai/protocols/openai-chat\"\nimport { SimulationNetwork } from \"./network\"\nimport { SimulatedProvider } from \"./simulated-provider\"\n\n/**\n * Driver-answered OpenAI endpoint for the simulated network.\n *\n * Claims `POST {DEFAULT_BASE_URL}{PATH}` (the real openai-chat route\n * endpoint), invokes the simulated provider, and streams the driver's events back as\n * an OpenAI Chat SSE response terminated by `[DONE]`. Everything downstream\n * of the response bytes is the real pipeline: SSE framing, the OpenAIChat\n * event schema, the protocol state machine, and Lifecycle grammar.\n */\n\nconst encodeChunk = Schema.encodeUnknownSync(OpenAIChatEvent)\n\nconst encoder = new TextEncoder()\nconst decodeBody = Schema.decodeUnknownEffect(Schema.fromJsonString(Schema.Json))\n\n// The simulated model id is echoed back only in non-schema fields; the\n// protocol event schema ignores unknown fields, so id/object/model are\n// decorative wire realism.\ntype ProviderItem = Exclude<SimulatedProvider.ProviderResponseEvent, { readonly type: \"finish\" }>\ntype FinishReason = Extract<SimulatedProvider.ProviderResponseEvent, { readonly type: \"finish\" }>[\"reason\"]\n\nfunction chunkOf(item: ProviderItem): OpenAIChatEvent | unknown {\n if (item.type === \"textDelta\") return { choices: [{ delta: { content: item.text } }] }\n if (item.type === \"reasoningDelta\") return { choices: [{ delta: { reasoning_content: item.text } }] }\n if (item.type === \"toolCall\")\n return {\n choices: [\n {\n delta: {\n tool_calls: [\n {\n index: item.index,\n id: item.id,\n function: { name: item.name, arguments: JSON.stringify(item.input) },\n },\n ],\n },\n },\n ],\n }\n return item.chunk\n}\n\nconst finishReasonWire: Record<FinishReason, string> = {\n stop: \"stop\",\n \"tool-calls\": \"tool_calls\",\n length: \"length\",\n \"content-filter\": \"content_filter\",\n}\n\nfunction frame(payload: unknown): Uint8Array {\n return encoder.encode(`data: ${JSON.stringify(payload)}\\n\\n`)\n}\n\nfunction sseBody(\n events: Stream.Stream<SimulatedProvider.ProviderResponseEvent, SimulatedProvider.ProviderDisconnectedError>,\n): Stream.Stream<Uint8Array, SimulatedProvider.ProviderDisconnectedError> {\n return events.pipe(\n Stream.map((event) => {\n if (event.type === \"finish\")\n return frame(encodeChunk({ choices: [{ delta: {}, finish_reason: finishReasonWire[event.reason] }] }))\n if (event.type === \"raw\") return frame(event.chunk)\n return frame(encodeChunk(chunkOf(event)))\n }),\n Stream.concat(Stream.make(encoder.encode(\"data: [DONE]\\n\\n\"))),\n )\n}\n\nexport const route = (provider: SimulatedProvider.Interface): SimulationNetwork.Route => ({\n match: (request, url) => {\n if (request.method !== \"POST\") return undefined\n if (url.origin + url.pathname !== DEFAULT_BASE_URL + PATH) return undefined\n return Effect.gen(function* () {\n const body =\n request.body._tag === \"Uint8Array\"\n ? yield* decodeBody(new TextDecoder().decode(request.body.body)).pipe(\n Effect.mapError(\n (cause) =>\n new HttpClientError({\n reason: new TransportError({\n request,\n cause,\n description: \"Simulation received an invalid OpenAI request body\",\n }),\n }),\n ),\n )\n : {}\n return HttpClientResponse.fromWeb(\n request,\n new Response(Stream.toReadableStream(sseBody(provider.stream({ url: url.toString(), body }))), {\n status: 200,\n headers: { \"content-type\": \"text/event-stream\" },\n }),\n )\n })\n },\n})\n\nexport * as SimulationOpenAI from \"./openai\"\n", | ||
| "import { InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Cause, Context, Effect, Fiber, FiberSet, Layer, PubSub, Queue, Ref, Schema, Semaphore, Stream } from \"effect\"\nimport { SimulationControlServer } from \"../control-server\"\nimport { SimulationProtocol } from \"../protocol\"\n\nexport interface ProviderRequest {\n readonly url: string\n readonly body: unknown\n}\n\nexport type ProviderResponseEvent =\n | SimulationProtocol.Backend.Item\n | { readonly type: \"finish\"; readonly reason: SimulationProtocol.Backend.FinishReason }\n\nexport class ProviderDisconnectedError extends Schema.TaggedErrorClass<ProviderDisconnectedError>()(\n \"SimulatedProvider.ProviderDisconnectedError\",\n { message: Schema.String },\n) {}\n\nexport interface Interface {\n readonly stream: (request: ProviderRequest) => Stream.Stream<ProviderResponseEvent, ProviderDisconnectedError>\n}\n\nexport class Service extends Context.Service<Service, Interface>()(\"@opencode/simulation/SimulatedProvider\") {}\n\ninterface ProviderInvocation extends ProviderRequest {\n readonly id: string\n}\n\ninterface PendingInvocation extends ProviderInvocation {\n readonly responses: Queue.Queue<ProviderResponseEvent, ProviderDisconnectedError | Cause.Done>\n}\n\ninterface State {\n readonly counter: number\n readonly pending: ReadonlyMap<string, PendingInvocation>\n}\n\ninterface Driver {\n readonly requests: Stream.Stream<ProviderInvocation>\n readonly push: (\n id: string,\n items: readonly SimulationProtocol.Backend.Item[],\n ) => Effect.Effect<void, InvocationNotFoundError>\n readonly finish: (\n id: string,\n reason: SimulationProtocol.Backend.FinishReason,\n ) => Effect.Effect<void, InvocationNotFoundError>\n readonly disconnect: (id: string) => Effect.Effect<void, InvocationNotFoundError>\n readonly pending: () => Effect.Effect<readonly ProviderInvocation[]>\n}\n\nclass InvocationNotFoundError extends Schema.TaggedErrorClass<InvocationNotFoundError>()(\n \"SimulatedProvider.InvocationNotFoundError\",\n { id: Schema.String, message: Schema.String },\n) {}\n\nclass ControllerDisconnectedError extends Schema.TaggedErrorClass<ControllerDisconnectedError>()(\n \"SimulatedProvider.ControllerDisconnectedError\",\n { message: Schema.String },\n) {}\n\ntype ControlSocket = SimulationControlServer.Socket\n\nexport const layerDrive = (options: { readonly endpoint: string }) =>\n Layer.effect(\n Service,\n Effect.gen(function* () {\n const state = yield* Ref.make<State>({ counter: 0, pending: new Map() })\n const opened = yield* PubSub.unbounded<ProviderInvocation>()\n const lock = yield* Semaphore.make(1)\n\n const close = (invocation: PendingInvocation) =>\n Effect.gen(function* () {\n yield* Queue.shutdown(invocation.responses)\n yield* lock.withPermit(\n Ref.update(state, (current) =>\n current.pending.get(invocation.id) === invocation ? remove(current, invocation.id) : current,\n ),\n )\n })\n\n yield* Effect.addFinalizer(() =>\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n yield* Effect.forEach(current.pending.values(), (invocation) => Queue.shutdown(invocation.responses), {\n discard: true,\n })\n yield* PubSub.shutdown(opened)\n }),\n )\n\n const open = (request: ProviderRequest) =>\n lock.withPermit(\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n const id = `inv_${current.counter + 1}`\n const responses = yield* Queue.bounded<ProviderResponseEvent, ProviderDisconnectedError | Cause.Done>(256)\n const invocation: PendingInvocation = { id, ...request, responses }\n yield* Ref.set(state, {\n counter: current.counter + 1,\n pending: new Map(current.pending).set(id, invocation),\n })\n yield* PubSub.publish(opened, { id, ...request })\n return invocation\n }),\n )\n\n const requireInvocation = (id: string) =>\n Effect.gen(function* () {\n const current = yield* Ref.get(state)\n const invocation = current.pending.get(id)\n if (invocation) return invocation\n return yield* Effect.fail(\n new InvocationNotFoundError({\n id,\n message: `Simulated provider invocation not found or already finished: ${id}`,\n }),\n )\n })\n\n const remove = (current: State, id: string) => {\n const pending = new Map(current.pending)\n pending.delete(id)\n return { ...current, pending }\n }\n\n const driver: Driver = {\n requests: Stream.unwrap(\n lock.withPermit(\n Effect.gen(function* () {\n const subscription = yield* PubSub.subscribe(opened)\n const current = yield* Ref.get(state)\n const pending = Array.from(current.pending.values(), ({ id, url, body }) => ({ id, url, body }))\n return Stream.concat(Stream.fromIterable(pending), Stream.fromEffectRepeat(PubSub.take(subscription)))\n }),\n ),\n ),\n push: (id, items) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(requireInvocation(id))\n yield* Queue.offerAll(invocation.responses, items)\n }),\n finish: (id, reason) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(\n Effect.gen(function* () {\n const invocation = yield* requireInvocation(id)\n const current = yield* Ref.get(state)\n yield* Ref.set(state, remove(current, id))\n return invocation\n }),\n )\n yield* Queue.offer(invocation.responses, { type: \"finish\", reason })\n yield* Queue.end(invocation.responses)\n }),\n disconnect: (id) =>\n Effect.gen(function* () {\n const invocation = yield* lock.withPermit(\n Effect.gen(function* () {\n const invocation = yield* requireInvocation(id)\n const current = yield* Ref.get(state)\n yield* Ref.set(state, remove(current, id))\n return invocation\n }),\n )\n yield* Queue.fail(\n invocation.responses,\n new ProviderDisconnectedError({ message: \"Simulated model provider disconnected\" }),\n )\n }),\n pending: () =>\n lock.withPermit(\n Ref.get(state).pipe(\n Effect.map((current) => Array.from(current.pending.values(), ({ id, url, body }) => ({ id, url, body }))),\n ),\n ),\n }\n\n const fibers = yield* FiberSet.make<void, unknown>()\n const activeController = yield* Ref.make<Fiber.Fiber<void> | undefined>(undefined)\n const controllerLock = yield* Semaphore.make(1)\n yield* SimulationControlServer.start({\n endpoint: options.endpoint,\n label: \"opencode drive backend websocket\",\n data: () => ({}),\n decode: SimulationProtocol.Backend.decodeRequestEffect,\n handle: (socket, request) => handle(driver, fibers, activeController, controllerLock, socket, request),\n close: (socket) => releaseController(activeController, controllerLock, socket),\n })\n yield* Effect.sync(() => process.stderr.write(`opencode drive backend websocket: ${options.endpoint}\\n`))\n\n return Service.of({\n stream: (request) =>\n Stream.unwrap(\n Effect.acquireRelease(open(request), close).pipe(\n Effect.map((invocation) =>\n Stream.fromQueue(invocation.responses).pipe(Stream.takeUntil((event) => event.type === \"finish\")),\n ),\n ),\n ),\n })\n }),\n )\n\nfunction handle(\n driver: Driver,\n fibers: FiberSet.FiberSet<void, unknown>,\n activeController: Ref.Ref<Fiber.Fiber<void> | undefined>,\n controllerLock: Semaphore.Semaphore,\n socket: ControlSocket,\n request: SimulationProtocol.Backend.Request,\n) {\n switch (request.method) {\n case \"simulation.handshake\":\n return SimulationProtocol.Handshake.dispatch(\n {\n role: \"backend\",\n server: { name: \"opencode\", version: InstallationVersion },\n capabilities: SimulationProtocol.Backend.Capabilities,\n },\n request.params,\n )\n case \"llm.attach\":\n return controllerLock.withPermit(\n Effect.gen(function* () {\n if (socket.data.closed)\n return yield* Effect.fail(\n new ControllerDisconnectedError({ message: \"Drive controller disconnected before attachment\" }),\n )\n const previous = yield* Ref.get(activeController)\n if (previous) yield* Fiber.interrupt(previous)\n const attachment = yield* FiberSet.run(\n fibers,\n driver.requests.pipe(\n Stream.runForEach((invocation) =>\n Effect.sync(() => {\n socket.send(JSON.stringify({ jsonrpc: \"2.0\", method: \"llm.request\", params: invocation }))\n }),\n ),\n ),\n )\n if (socket.data.closed) {\n yield* Fiber.interrupt(attachment)\n return yield* Effect.fail(\n new ControllerDisconnectedError({ message: \"Drive controller disconnected during attachment\" }),\n )\n }\n socket.data.attachment = attachment\n yield* Ref.set(activeController, attachment)\n return { attached: true }\n }),\n )\n case \"llm.chunk\":\n return driver.push(request.params.id, request.params.items).pipe(Effect.as({ ok: true }))\n case \"llm.finish\":\n return driver.finish(request.params.id, request.params.reason).pipe(Effect.as({ ok: true }))\n case \"llm.disconnect\":\n return driver.disconnect(request.params.id).pipe(Effect.as({ ok: true }))\n case \"llm.pending\":\n return driver.pending().pipe(Effect.map((invocations) => ({ invocations })))\n }\n}\n\nfunction releaseController(\n activeController: Ref.Ref<Fiber.Fiber<void> | undefined>,\n controllerLock: Semaphore.Semaphore,\n socket: ControlSocket,\n) {\n return controllerLock.withPermit(\n Effect.gen(function* () {\n const attachment = socket.data.attachment\n if (!attachment) return\n yield* Fiber.interrupt(attachment)\n yield* Ref.update(activeController, (active) => (active === attachment ? undefined : active))\n }),\n )\n}\n\nexport * as SimulatedProvider from \"./simulated-provider\"\n", | ||
| "import { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { httpClient } from \"@opencode-ai/core/effect/app-node-platform\"\nimport { Config, Effect, Layer } from \"effect\"\nimport { HttpClient } from \"effect/unstable/http\"\nimport { DriveManifest } from \"../manifest\"\nimport { SimulationNetwork } from \"./network\"\nimport { SimulationOpenAI } from \"./openai\"\nimport { SimulatedProvider } from \"./simulated-provider\"\n\n/**\n * Layer replacements applied when the server is built in simulation mode.\n *\n * The server merges these into the app node build when `OPENCODE_SIMULATE`\n * is enabled, via a dynamic import so this module is never loaded eagerly.\n *\n * - Network: all outbound HTTP resolves against the simulated route table;\n * unknown destinations are denied. The driver-answered OpenAI endpoint is\n * registered here as the first route.\n *\n */\n\nexport const simulationReplacements = Effect.fn(\"Simulation.replacements\")(function* () {\n // ModelsDev dies when its catalog fetch fails, so simulation answers it with\n // an empty catalog; providers come from seeded config instead.\n const models = SimulationNetwork.json(\"GET\", \"https://models.dev/api.json\", {})\n const drive = yield* Config.string(\"OPENCODE_DRIVE\").pipe(Config.withDefault(undefined))\n if (!drive) return [[httpClient, SimulationNetwork.layer([models])]] satisfies LayerNode.Replacements\n\n const manifest = yield* DriveManifest.resolve()\n const networkLayer = Layer.effect(\n HttpClient.HttpClient,\n Effect.gen(function* () {\n const provider = yield* SimulatedProvider.Service\n const network = yield* SimulationNetwork.make([SimulationOpenAI.route(provider), models])\n return network.client\n }),\n ).pipe(\n Layer.provide(\n SimulatedProvider.layerDrive({\n endpoint: manifest.endpoints.backend,\n }),\n ),\n )\n return [[httpClient, networkLayer]] satisfies LayerNode.Replacements\n})\n\nexport * as Simulation from \"./index\"\n" | ||
| ], | ||
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| ||
| "debugId": "8949052148BB0FE164756E2164756E21", | ||
| "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(options)\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 ${endpoint.url} did not provide a compatible V2 health response`, { cause })\n}\n\nexport * as ServerConnection from \"./server-connection\"\n" | ||
| ], | ||
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| "debugId": "768779241BF74DD764756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/auth.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport {\n OpenCode,\n type IntegrationAttemptStatus,\n type IntegrationOAuthMethod,\n type OpenCodeClient,\n} from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\nimport { resolveIntegration } from \"./resolve\"\n\nconst location = { directory: process.cwd() }\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.auth,\n Effect.fn(\"cli.mcp.auth\")(function* (input) {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n\n const integration = yield* resolveIntegration(client, input.name, location)\n if (!integration)\n return yield* Effect.fail(new Error(`MCP server \"${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": "19C66A0F9C127B2264756E2164756E21", | ||
| "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": "BC47EB20848E0C7764756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "9B7BE33529ECC63864756E2164756E21", | ||
| "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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| "debugId": "6D896DB21873270764756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/protocols/openai-responses.ts"], | ||
| "sourcesContent": [ | ||
| "import { Effect, Schema } from \"effect\"\nimport { Route } from \"../route/client\"\nimport { Auth } from \"../route/auth\"\nimport { Endpoint } from \"../route/endpoint\"\nimport { HttpTransport, WebSocketTransport } from \"../route/transport\"\nimport { Protocol } from \"../route/protocol\"\nimport {\n LLMError,\n LLMEvent,\n Usage,\n type FinishReason,\n type JsonSchema,\n type LLMRequest,\n type ProviderMetadata,\n type ReasoningPart,\n type TextPart,\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 { 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-responses\"\nexport const DEFAULT_BASE_URL = \"https://api.openai.com/v1\"\nexport const PATH = \"/responses\"\n\n// =============================================================================\n// Request Body Schema\n// =============================================================================\nconst OpenAIResponsesInputText = Schema.Struct({\n type: Schema.tag(\"input_text\"),\n text: Schema.String,\n})\nconst OpenAIResponsesInputImage = Schema.Struct({\n type: Schema.tag(\"input_image\"),\n image_url: Schema.String,\n})\nconst OpenAIResponsesInputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])\ntype OpenAIResponsesInputContent = Schema.Schema.Type<typeof OpenAIResponsesInputContent>\n\nconst OpenAIResponsesOutputText = Schema.Struct({\n type: Schema.tag(\"output_text\"),\n text: Schema.String,\n})\n\nconst OpenAIResponsesReasoningSummaryText = Schema.Struct({\n type: Schema.tag(\"summary_text\"),\n text: Schema.String,\n})\n\nconst OpenAIResponsesReasoningItem = Schema.Struct({\n type: Schema.tag(\"reasoning\"),\n id: Schema.optionalKey(Schema.String),\n summary: Schema.Array(OpenAIResponsesReasoningSummaryText),\n encrypted_content: optionalNull(Schema.String),\n})\n\nconst OpenAIResponsesItemReference = Schema.Struct({\n type: Schema.tag(\"item_reference\"),\n id: Schema.String,\n})\n\n// `function_call_output.output` accepts either a plain string or an ordered\n// array of content items so tools can return images in addition to text.\n// https://platform.openai.com/docs/api-reference/responses/object\nconst OpenAIResponsesFunctionCallOutputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])\n\nconst OpenAIResponsesFunctionCallOutput = Schema.Union([\n Schema.String,\n Schema.Array(OpenAIResponsesFunctionCallOutputContent),\n])\n\nconst OpenAIResponsesInputItem = Schema.Union([\n Schema.Struct({ role: Schema.tag(\"system\"), content: Schema.String }),\n Schema.Struct({ role: Schema.tag(\"user\"), content: Schema.Array(OpenAIResponsesInputContent) }),\n Schema.Struct({ role: Schema.tag(\"assistant\"), content: Schema.Array(OpenAIResponsesOutputText) }),\n OpenAIResponsesReasoningItem,\n OpenAIResponsesItemReference,\n Schema.Struct({\n type: Schema.tag(\"function_call\"),\n call_id: Schema.String,\n name: Schema.String,\n arguments: Schema.String,\n }),\n Schema.Struct({\n type: Schema.tag(\"function_call_output\"),\n call_id: Schema.String,\n output: OpenAIResponsesFunctionCallOutput,\n }),\n])\ntype OpenAIResponsesInputItem = Schema.Schema.Type<typeof OpenAIResponsesInputItem>\n\n// Mutable counterpart of the schema reasoning item so `lowerMessages` can fold\n// multiple streamed summary parts into the same item before flushing.\ntype OpenAIResponsesReasoningInput = {\n type: \"reasoning\"\n id: string\n summary: Array<{ type: \"summary_text\"; text: string }>\n encrypted_content?: string | null\n}\ntype OpenAIResponsesReasoningReplay = Omit<OpenAIResponsesReasoningInput, \"id\">\n\nconst OpenAIResponsesTool = Schema.Struct({\n type: Schema.tag(\"function\"),\n name: Schema.String,\n description: Schema.String,\n parameters: JsonObject,\n strict: Schema.optional(Schema.Boolean),\n})\ntype OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTool>\n\nconst OpenAIResponsesToolChoice = Schema.Union([\n Schema.Literals([\"auto\", \"none\", \"required\"]),\n Schema.Struct({ type: Schema.tag(\"function\"), name: Schema.String }),\n])\n\n// Fields shared between the HTTP body and the WebSocket `response.create`\n// message. The HTTP body adds `stream: true`; the WebSocket message adds\n// `type: \"response.create\"`. Defining the shared shape once keeps the two\n// transports in sync without a destructure-and-strip dance.\nconst OpenAIResponsesCoreFields = {\n model: Schema.String,\n input: Schema.Array(OpenAIResponsesInputItem),\n instructions: Schema.optional(Schema.String),\n tools: optionalArray(OpenAIResponsesTool),\n tool_choice: Schema.optional(OpenAIResponsesToolChoice),\n store: Schema.optional(Schema.Boolean),\n service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),\n prompt_cache_key: Schema.optional(Schema.String),\n include: optionalArray(OpenAIOptions.OpenAIResponseIncludable),\n reasoning: Schema.optional(\n Schema.Struct({\n effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),\n summary: Schema.optional(Schema.Literal(\"auto\")),\n }),\n ),\n text: Schema.optional(\n Schema.Struct({\n verbosity: Schema.optional(OpenAIOptions.OpenAITextVerbosity),\n }),\n ),\n max_output_tokens: Schema.optional(Schema.Number),\n temperature: Schema.optional(Schema.Number),\n top_p: Schema.optional(Schema.Number),\n}\n\nconst OpenAIResponsesBody = Schema.Struct({\n ...OpenAIResponsesCoreFields,\n stream: Schema.Literal(true),\n})\nexport type OpenAIResponsesBody = Schema.Schema.Type<typeof OpenAIResponsesBody>\n\nconst OpenAIResponsesWebSocketMessage = Schema.StructWithRest(\n Schema.Struct({\n type: Schema.tag(\"response.create\"),\n ...OpenAIResponsesCoreFields,\n }),\n [Schema.Record(Schema.String, Schema.Unknown)],\n)\ntype OpenAIResponsesWebSocketMessage = Schema.Schema.Type<typeof OpenAIResponsesWebSocketMessage>\nconst encodeWebSocketMessage = Schema.encodeSync(Schema.fromJsonString(OpenAIResponsesWebSocketMessage))\n\nconst OpenAIResponsesUsage = Schema.Struct({\n input_tokens: Schema.optional(Schema.Number),\n input_tokens_details: optionalNull(Schema.Struct({ cached_tokens: Schema.optional(Schema.Number) })),\n output_tokens: Schema.optional(Schema.Number),\n output_tokens_details: optionalNull(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) })),\n total_tokens: Schema.optional(Schema.Number),\n})\ntype OpenAIResponsesUsage = Schema.Schema.Type<typeof OpenAIResponsesUsage>\n\nconst OpenAIResponsesStreamItem = Schema.Struct({\n type: Schema.String,\n id: Schema.optional(Schema.String),\n call_id: Schema.optional(Schema.String),\n name: Schema.optional(Schema.String),\n arguments: Schema.optional(Schema.String),\n // Hosted (provider-executed) tool fields. Each hosted tool item carries its\n // own subset of these — we capture them generically so we can surface the\n // call's typed input portion and round-trip the full result payload without\n // hand-rolling a per-tool schema.\n status: Schema.optional(Schema.String),\n action: Schema.optional(Schema.Unknown),\n queries: Schema.optional(Schema.Unknown),\n results: Schema.optional(Schema.Unknown),\n code: Schema.optional(Schema.String),\n container_id: Schema.optional(Schema.String),\n outputs: Schema.optional(Schema.Unknown),\n server_label: Schema.optional(Schema.String),\n output: Schema.optional(Schema.Unknown),\n error: Schema.optional(Schema.Unknown),\n encrypted_content: optionalNull(Schema.String),\n})\ntype OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>\n\n// The Responses schema puts streaming error details at the top level and\n// response failures under `response.error`. The official SDK also recognizes\n// an event-level HTTP-style `error` envelope, so accept all three shapes here.\n// https://github.com/openai/openai-openapi/blob/5162af98d3147432c14680df789e8e12d4891e6b/openapi.yaml#L67234-L67382\n// https://github.com/openai/openai-node/blob/61539248cbe04665de68a71e6fd878127ae4db87/src/core/streaming.ts#L58-L85\nconst OpenAIResponsesErrorPayload = Schema.Struct({\n code: optionalNull(Schema.String),\n message: optionalNull(Schema.String),\n param: optionalNull(Schema.String),\n})\n\nconst OpenAIResponsesEvent = Schema.Struct({\n type: Schema.String,\n delta: Schema.optional(Schema.String),\n item_id: Schema.optional(Schema.String),\n summary_index: Schema.optional(Schema.Number),\n item: Schema.optional(OpenAIResponsesStreamItem),\n response: Schema.optional(\n Schema.StructWithRest(\n Schema.Struct({\n id: Schema.optional(Schema.String),\n service_tier: optionalNull(Schema.String),\n incomplete_details: optionalNull(Schema.Struct({ reason: Schema.String })),\n usage: optionalNull(OpenAIResponsesUsage),\n error: optionalNull(OpenAIResponsesErrorPayload),\n }),\n [Schema.Record(Schema.String, Schema.Unknown)],\n ),\n ),\n code: optionalNull(Schema.String),\n message: Schema.optional(Schema.String),\n param: optionalNull(Schema.String),\n error: optionalNull(OpenAIResponsesErrorPayload),\n})\ntype OpenAIResponsesEvent = Schema.Schema.Type<typeof OpenAIResponsesEvent>\n\ninterface ParserState {\n readonly tools: ToolStream.State<string>\n readonly hasFunctionCall: boolean\n readonly lifecycle: Lifecycle.State\n readonly reasoningItems: Readonly<Record<string, ReasoningStreamItem>>\n readonly store: boolean | undefined\n}\n\ntype ReasoningSummaryStatus = \"active\" | \"can-conclude\" | \"concluded\"\n\ninterface ReasoningStreamItem {\n readonly encryptedContent: string | null | undefined\n // Keyed by OpenAI's numeric `summary_index`. JS object keys coerce to\n // strings, but typing the map as `Record<number, ...>` documents intent\n // and matches the wire field.\n readonly summaryParts: Readonly<Record<number, ReasoningSummaryStatus>>\n}\n\nconst invalid = ProviderShared.invalidRequest\n\n// =============================================================================\n// Request Lowering\n// =============================================================================\nconst lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIResponsesTool => ({\n type: \"function\",\n name: tool.name,\n description: tool.description,\n parameters: ToolSchemaProjection.openAI(inputSchema),\n // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.\n strict: false,\n})\n\nconst lowerToolChoice = (toolChoice: NonNullable<LLMRequest[\"toolChoice\"]>) =>\n ProviderShared.matchToolChoice(\"OpenAI Responses\", toolChoice, {\n auto: () => \"auto\" as const,\n none: () => \"none\" as const,\n required: () => \"required\" as const,\n tool: (name) => ({ type: \"function\" as const, name }),\n })\n\nconst lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({\n type: \"function_call\",\n call_id: part.id,\n name: part.name,\n arguments: ProviderShared.encodeJson(part.input),\n})\n\nconst lowerReasoning = (part: ReasoningPart): OpenAIResponsesReasoningInput | undefined => {\n const openai = part.providerMetadata?.openai\n if (!ProviderShared.isRecord(openai) || typeof openai.itemId !== \"string\" || openai.itemId.length === 0)\n return undefined\n const encryptedContent =\n typeof openai.reasoningEncryptedContent === \"string\"\n ? openai.reasoningEncryptedContent\n : openai.reasoningEncryptedContent === null\n ? null\n : undefined\n return {\n type: \"reasoning\",\n id: openai.itemId,\n summary: part.text.length > 0 ? [{ type: \"summary_text\", text: part.text }] : [],\n encrypted_content: encryptedContent,\n }\n}\n\nconst hostedToolItemID = (part: ToolResultPart) => {\n const openai = part.providerMetadata?.openai\n return ProviderShared.isRecord(openai) && typeof openai.itemId === \"string\" && openai.itemId.length > 0\n ? openai.itemId\n : undefined\n}\n\nconst lowerUserContent = Effect.fn(\"OpenAIResponses.lowerUserContent\")(function* (\n part: LLMRequest[\"messages\"][number][\"content\"][number],\n) {\n if (part.type === \"text\") return { type: \"input_text\" as const, text: part.text }\n if (part.type === \"media\") {\n const media = yield* ProviderShared.validateMedia(\n \"OpenAI Responses\",\n part,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return { type: \"input_image\" as const, image_url: media.dataUrl }\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"user\", [\"text\", \"media\"])\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(\"OpenAIResponses.lowerToolResultContentItem\")(function* (\n item: ToolContent,\n) {\n if (item.type === \"text\") return { type: \"input_text\" as const, text: item.text }\n const media = yield* ProviderShared.validateToolFile(\n \"OpenAI Responses\",\n item,\n new Set<string>(ProviderShared.IMAGE_MIMES),\n )\n return { type: \"input_image\" as const, image_url: media.dataUrl }\n})\n\nconst lowerToolResultOutput = Effect.fn(\"OpenAIResponses.lowerToolResultOutput\")(function* (part: ToolResultPart) {\n // Text/json/error results are encoded as a plain string for backward\n // compatibility 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\nconst lowerMessages = Effect.fn(\"OpenAIResponses.lowerMessages\")(function* (request: LLMRequest) {\n const system: OpenAIResponsesInputItem[] =\n request.system.length === 0 ? [] : [{ role: \"system\", content: ProviderShared.joinText(request.system) }]\n const input: OpenAIResponsesInputItem[] = [...system]\n const store = OpenAIOptions.store(request)\n\n for (const message of request.messages) {\n if (message.role === \"system\") {\n const part = yield* ProviderShared.wrappedSystemUpdate(\"OpenAI Responses\", message)\n const previous = input.at(-1)\n if (previous && \"role\" in previous && previous.role === \"user\")\n input[input.length - 1] = {\n role: \"user\",\n content: [...previous.content, { type: \"input_text\", text: part.text }],\n }\n else input.push({ role: \"user\", content: [{ type: \"input_text\", text: part.text }] })\n continue\n }\n\n if (message.role === \"user\") {\n input.push({ role: \"user\", content: yield* Effect.forEach(message.content, lowerUserContent) })\n continue\n }\n\n if (message.role === \"assistant\") {\n const content: TextPart[] = []\n const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}\n const reasoningReferences = new Set<string>()\n const hostedToolReferences = new Set<string>()\n const flushText = () => {\n if (content.length === 0) return\n input.push({ role: \"assistant\", content: content.map((part) => ({ type: \"output_text\", text: part.text })) })\n content.splice(0, content.length)\n }\n for (const part of message.content) {\n if (part.type === \"text\") {\n content.push(part)\n continue\n }\n if (part.type === \"reasoning\") {\n flushText()\n const reasoning = lowerReasoning(part)\n if (!reasoning) continue\n if (store !== false) {\n if (!reasoningReferences.has(reasoning.id)) input.push({ type: \"item_reference\", id: reasoning.id })\n reasoningReferences.add(reasoning.id)\n continue\n }\n const existing = reasoningItems[reasoning.id]\n if (existing) {\n existing.summary.push(...reasoning.summary)\n if (typeof reasoning.encrypted_content === \"string\")\n existing.encrypted_content = reasoning.encrypted_content\n continue\n }\n const replay = {\n type: reasoning.type,\n summary: reasoning.summary,\n encrypted_content: reasoning.encrypted_content,\n }\n reasoningItems[reasoning.id] = replay\n input.push(replay)\n continue\n }\n if (part.type === \"tool-call\") {\n flushText()\n if (part.providerExecuted === true) continue\n input.push(lowerToolCall(part))\n continue\n }\n if (part.type === \"tool-result\" && part.providerExecuted === true) {\n flushText()\n const itemID = hostedToolItemID(part)\n if (store !== false && itemID && !hostedToolReferences.has(itemID))\n input.push({ type: \"item_reference\", id: itemID })\n if (itemID) hostedToolReferences.add(itemID)\n continue\n }\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"assistant\", [\n \"text\",\n \"reasoning\",\n \"tool-call\",\n \"tool-result\",\n ])\n }\n flushText()\n continue\n }\n\n for (const part of message.content) {\n if (!ProviderShared.supportsContent(part, [\"tool-result\"]))\n return yield* ProviderShared.unsupportedContent(\"OpenAI Responses\", \"tool\", [\"tool-result\"])\n input.push({\n type: \"function_call_output\",\n call_id: part.id,\n output: yield* lowerToolResultOutput(part),\n })\n }\n }\n\n // With store:false, OpenAI only accepts previous reasoning items when the\n // complete item has encrypted state. Summary blocks for one item may carry\n // that state only on the last block, so filter after they have been joined.\n return store === false\n ? input.filter(\n (item) => !(\"type\" in item) || item.type !== \"reasoning\" || typeof item.encrypted_content === \"string\",\n )\n : input\n})\n\nconst lowerOptions = Effect.fn(\"OpenAIResponses.lowerOptions\")(function* (request: LLMRequest) {\n const store = OpenAIOptions.store(request)\n const promptCacheKey = OpenAIOptions.promptCacheKey(request)\n const effort = OpenAIOptions.reasoningEffort(request)\n const summary = OpenAIOptions.reasoningSummary(request)\n const include = OpenAIOptions.include(request)\n const verbosity = OpenAIOptions.textVerbosity(request)\n const instructions = OpenAIOptions.instructions(request)\n const serviceTier = OpenAIOptions.serviceTier(request)\n return {\n ...(instructions ? { instructions } : {}),\n ...(store !== undefined ? { store } : {}),\n ...(promptCacheKey ? { prompt_cache_key: promptCacheKey } : {}),\n ...(include ? { include } : {}),\n ...(effort || summary ? { reasoning: { effort, summary } } : {}),\n ...(verbosity ? { text: { verbosity } } : {}),\n ...(serviceTier ? { service_tier: serviceTier } : {}),\n }\n})\n\nconst fromRequest = Effect.fn(\"OpenAIResponses.fromRequest\")(function* (request: LLMRequest) {\n const generation = request.generation\n const options = yield* lowerOptions(request)\n const toolSchemaCompatibility = request.model.compatibility?.toolSchema\n return {\n model: request.model.id,\n input: 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 max_output_tokens: generation?.maxTokens,\n temperature: generation?.temperature,\n top_p: generation?.topP,\n ...options,\n }\n})\n\n// =============================================================================\n// Stream Parsing\n// =============================================================================\n// OpenAI Responses reports `input_tokens` (inclusive total) with a\n// `cached_tokens` subset, and `output_tokens` (inclusive total) with a\n// `reasoning_tokens` subset. Pass the totals through and derive the\n// non-cached breakdown.\nconst mapUsage = (usage: OpenAIResponsesUsage | null | undefined) => {\n if (!usage) return undefined\n const cached = usage.input_tokens_details?.cached_tokens\n const reasoning = usage.output_tokens_details?.reasoning_tokens\n const nonCached = ProviderShared.subtractTokens(usage.input_tokens, cached)\n return new Usage({\n inputTokens: usage.input_tokens,\n outputTokens: usage.output_tokens,\n nonCachedInputTokens: nonCached,\n cacheReadInputTokens: cached,\n reasoningTokens: reasoning,\n totalTokens: ProviderShared.totalTokens(usage.input_tokens, usage.output_tokens, usage.total_tokens),\n providerMetadata: { openai: usage },\n })\n}\n\nconst mapFinishReason = (event: OpenAIResponsesEvent, hasFunctionCall: boolean): FinishReason => {\n const reason = event.response?.incomplete_details?.reason\n if (reason === undefined || reason === null) return hasFunctionCall ? \"tool-calls\" : \"stop\"\n if (reason === \"max_output_tokens\") return \"length\"\n if (reason === \"content_filter\") return \"content-filter\"\n return hasFunctionCall ? \"tool-calls\" : \"unknown\"\n}\n\nconst openaiMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ openai: metadata })\n\n// Hosted tool items (provider-executed) ship their typed input + status +\n// result fields all in one item. We expose them as a `tool-call` +\n// `tool-result` pair so consumers can treat them uniformly with client tools,\n// only differentiated by `providerExecuted: true`.\n//\n// One record per OpenAI Responses item type that represents a hosted\n// (provider-executed) tool call: the common name we surface, plus an `input`\n// extractor that picks the fields the model actually populated for that tool.\n// Falling back to `{}` when an entry isn't fully typed keeps unknown tools\n// observable without rolling a per-tool schema.\nconst HOSTED_TOOLS = {\n web_search_call: { name: \"web_search\", input: (item) => item.action ?? {} },\n web_search_preview_call: { name: \"web_search_preview\", input: (item) => item.action ?? {} },\n file_search_call: { name: \"file_search\", input: (item) => ({ queries: item.queries ?? [] }) },\n code_interpreter_call: {\n name: \"code_interpreter\",\n input: (item) => ({ code: item.code, container_id: item.container_id }),\n },\n computer_use_call: { name: \"computer_use\", input: (item) => item.action ?? {} },\n image_generation_call: { name: \"image_generation\", input: () => ({}) },\n mcp_call: {\n name: \"mcp\",\n input: (item) => ({ server_label: item.server_label, name: item.name, arguments: item.arguments }),\n },\n local_shell_call: { name: \"local_shell\", input: (item) => item.action ?? {} },\n} as const satisfies Record<\n string,\n { readonly name: string; readonly input: (item: OpenAIResponsesStreamItem) => unknown }\n>\n\ntype HostedToolType = keyof typeof HOSTED_TOOLS\n\nconst isHostedToolItem = (\n item: OpenAIResponsesStreamItem,\n): item is OpenAIResponsesStreamItem & { type: HostedToolType; id: string } =>\n item.type in HOSTED_TOOLS && typeof item.id === \"string\" && item.id.length > 0\n\nconst isReasoningItem = (\n item: OpenAIResponsesStreamItem,\n): item is OpenAIResponsesStreamItem & { type: \"reasoning\"; id: string } =>\n item.type === \"reasoning\" && typeof item.id === \"string\" && item.id.length > 0\n\n// Round-trip the full item as the structured result so consumers can extract\n// outputs / sources / status without re-decoding.\nconst hostedToolResult = (item: OpenAIResponsesStreamItem) => {\n const isError = typeof item.error !== \"undefined\" && item.error !== null\n return isError ? { type: \"error\" as const, value: item.error } : { type: \"json\" as const, value: item }\n}\n\nconst hostedToolEvents = (\n item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },\n): ReadonlyArray<LLMEvent> => {\n const tool = HOSTED_TOOLS[item.type]\n const providerMetadata = openaiMetadata({ itemId: item.id })\n return [\n LLMEvent.toolCall({\n id: item.id,\n name: tool.name,\n input: tool.input(item),\n providerExecuted: true,\n providerMetadata,\n }),\n LLMEvent.toolResult({\n id: item.id,\n name: tool.name,\n result: hostedToolResult(item),\n providerExecuted: true,\n providerMetadata,\n }),\n ]\n}\n\ntype StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]\n\nconst NO_EVENTS: StepResult[\"1\"] = []\n\n// `response.completed` / `response.incomplete` are clean finishes that emit a\n// `finish` event; `response.failed` is a hard failure. All three end the stream,\n// so keep this set aligned with `step` and the protocol's terminal predicate.\nconst TERMINAL_TYPES = new Set([\"response.completed\", \"response.incomplete\", \"response.failed\"])\n\nconst onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.delta) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, event.item_id ?? \"text-0\", event.delta) },\n events,\n ]\n}\n\nconst onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const events: LLMEvent[] = []\n return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? \"text-0\") }, events]\n}\n\nconst onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.delta) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n const itemID = event.item_id ?? \"reasoning-0\"\n const id =\n event.summary_index !== undefined || state.reasoningItems[itemID] ? `${itemID}:${event.summary_index ?? 0}` : itemID\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, id, event.delta),\n },\n events,\n ]\n}\n\nconst onReasoningDone = (state: ParserState, _event: OpenAIResponsesEvent): StepResult => [state, NO_EVENTS]\n\nconst reasoningMetadata = (item: OpenAIResponsesStreamItem & { id: string }) =>\n openaiMetadata({ itemId: item.id, reasoningEncryptedContent: item.encrypted_content ?? null })\n\n// OpenAI Responses streams reasoning items in a stable order:\n// `output_item.added` (reasoning) →\n// `reasoning_summary_part.added` (index=0) →\n// `reasoning_summary_text.delta` →\n// `reasoning_summary_part.done` (index=0) →\n// (repeat for index>0) →\n// `output_item.done` (reasoning).\n// The handlers below rely on this ordering: `onOutputItemAdded` seeds the\n// per-item entry, `onReasoningSummaryPartAdded` for `summary_index === 0`\n// short-circuits when the entry already exists, and higher-index handlers\n// fold against the same entry. Behaviour for out-of-order events is\n// best-effort, not guaranteed.\nconst onOutputItemAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const item = event.item\n if (item && isReasoningItem(item)) {\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(state.lifecycle, events, `${item.id}:0`, reasoningMetadata(item)),\n reasoningItems: {\n ...state.reasoningItems,\n [item.id]: { encryptedContent: item.encrypted_content, summaryParts: { 0: \"active\" } },\n },\n },\n events,\n ]\n }\n if (item?.type !== \"function_call\" || !item.id) return [state, NO_EVENTS]\n const providerMetadata = openaiMetadata({ itemId: item.id })\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n return [\n {\n ...state,\n lifecycle,\n hasFunctionCall: state.hasFunctionCall,\n tools: ToolStream.start(state.tools, item.id, {\n id: item.call_id ?? item.id,\n name: item.name ?? \"\",\n input: item.arguments ?? \"\",\n providerMetadata,\n }),\n },\n [...events, LLMEvent.toolInputStart({ id: item.call_id ?? item.id, name: item.name ?? \"\", providerMetadata })],\n ]\n}\n\nconst onReasoningSummaryPartAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]\n const item = state.reasoningItems[event.item_id] ?? { encryptedContent: undefined, summaryParts: {} }\n if (event.summary_index === 0) {\n if (state.reasoningItems[event.item_id]) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(\n state.lifecycle,\n events,\n `${event.item_id}:0`,\n openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: null }),\n ),\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: { ...item, summaryParts: { 0: \"active\" } },\n },\n },\n events,\n ]\n }\n\n const events: LLMEvent[] = []\n const closed = Object.entries(item.summaryParts)\n .filter((entry) => entry[1] === \"can-conclude\")\n .reduce(\n (lifecycle, entry) =>\n Lifecycle.reasoningEnd(\n lifecycle,\n events,\n `${event.item_id}:${entry[0]}`,\n openaiMetadata({ itemId: event.item_id }),\n ),\n state.lifecycle,\n )\n return [\n {\n ...state,\n lifecycle: Lifecycle.reasoningStart(\n closed,\n events,\n `${event.item_id}:${event.summary_index}`,\n openaiMetadata({ itemId: event.item_id, reasoningEncryptedContent: item.encryptedContent ?? null }),\n ),\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: {\n ...item,\n summaryParts: {\n ...Object.fromEntries(\n Object.entries(item.summaryParts).map((entry) =>\n entry[1] === \"can-conclude\" ? [entry[0], \"concluded\" as const] : entry,\n ),\n ),\n [event.summary_index]: \"active\",\n },\n },\n },\n },\n events,\n ]\n}\n\nconst onReasoningSummaryPartDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n if (!event.item_id || event.summary_index === undefined) return [state, NO_EVENTS]\n const item = state.reasoningItems[event.item_id]\n if (!item) return [state, NO_EVENTS]\n const events: LLMEvent[] = []\n return [\n {\n ...state,\n lifecycle:\n state.store !== false\n ? Lifecycle.reasoningEnd(\n state.lifecycle,\n events,\n `${event.item_id}:${event.summary_index}`,\n openaiMetadata({ itemId: event.item_id }),\n )\n : state.lifecycle,\n reasoningItems: {\n ...state.reasoningItems,\n [event.item_id]: {\n ...item,\n summaryParts: {\n ...item.summaryParts,\n [event.summary_index]: state.store !== false ? \"concluded\" : \"can-conclude\",\n },\n },\n },\n },\n events,\n ]\n}\n\nconst onFunctionCallArgumentsDelta = Effect.fn(\"OpenAIResponses.onFunctionCallArgumentsDelta\")(function* (\n state: ParserState,\n event: OpenAIResponsesEvent,\n) {\n if (!event.item_id || !event.delta) return [state, NO_EVENTS] satisfies StepResult\n const result = ToolStream.appendExisting(\n ADAPTER,\n state.tools,\n event.item_id,\n event.delta,\n \"OpenAI Responses 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\nconst onOutputItemDone = Effect.fn(\"OpenAIResponses.onOutputItemDone\")(function* (\n state: ParserState,\n event: OpenAIResponsesEvent,\n) {\n const item = event.item\n if (!item) return [state, NO_EVENTS] satisfies StepResult\n\n if (item.type === \"message\" && item.id) return onOutputTextDone(state, { ...event, item_id: item.id })\n\n if (item.type === \"function_call\") {\n if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult\n const tools = state.tools[item.id]\n ? state.tools\n : ToolStream.start(state.tools, item.id, { id: item.call_id, name: item.name })\n const result =\n item.arguments === undefined\n ? yield* ToolStream.finish(ADAPTER, tools, item.id)\n : yield* ToolStream.finishWithInput(ADAPTER, tools, item.id, item.arguments)\n const events: LLMEvent[] = []\n const resultEvents = result.events ?? []\n const lifecycle = resultEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle\n events.push(...resultEvents)\n return [\n {\n ...state,\n lifecycle,\n hasFunctionCall: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasFunctionCall,\n tools: result.tools,\n },\n events,\n ] satisfies StepResult\n }\n\n if (isHostedToolItem(item)) {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n events.push(...hostedToolEvents(item))\n return [{ ...state, lifecycle }, events] satisfies StepResult\n }\n\n if (isReasoningItem(item)) {\n const events: LLMEvent[] = []\n const providerMetadata = reasoningMetadata(item)\n const reasoningItem = state.reasoningItems[item.id]\n if (reasoningItem) {\n const lifecycle = Object.entries(reasoningItem.summaryParts)\n .filter((entry) => entry[1] === \"active\" || entry[1] === \"can-conclude\")\n .reduce(\n (lifecycle, entry) => Lifecycle.reasoningEnd(lifecycle, events, `${item.id}:${entry[0]}`, providerMetadata),\n state.lifecycle,\n )\n const { [item.id]: _removed, ...reasoningItems } = state.reasoningItems\n return [{ ...state, lifecycle, reasoningItems }, events] satisfies StepResult\n }\n if (!state.lifecycle.reasoning.has(item.id)) {\n const lifecycle = Lifecycle.stepStart(state.lifecycle, events)\n events.push(LLMEvent.reasoningStart({ id: item.id, providerMetadata }))\n events.push(LLMEvent.reasoningEnd({ id: item.id, providerMetadata }))\n return [{ ...state, lifecycle }, events] satisfies StepResult\n }\n return [\n { ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, item.id, providerMetadata) },\n events,\n ] satisfies StepResult\n }\n\n return [state, NO_EVENTS] satisfies StepResult\n})\n\nconst onResponseFinish = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {\n const events: LLMEvent[] = []\n const lifecycle = Lifecycle.finish(state.lifecycle, events, {\n reason: mapFinishReason(event, state.hasFunctionCall),\n usage: mapUsage(event.response?.usage),\n providerMetadata:\n event.response?.id || event.response?.service_tier\n ? openaiMetadata({\n responseId: event.response.id,\n serviceTier: event.response.service_tier,\n })\n : undefined,\n })\n return [{ ...state, lifecycle }, events]\n}\n\n// Build a single human-readable message from whatever the provider supplied.\n// When both code and message are present, prefix the code so consumers see\n// the failure mode (e.g. `rate_limit_exceeded: Slow down`) instead of just\n// the bare message — production rate limits and context-length failures used\n// to be indistinguishable from generic stream drops.\nconst providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): string => {\n const nested = event.error ?? event.response?.error ?? undefined\n const message = event.message || nested?.message || undefined\n const code = event.code || nested?.code || undefined\n if (message && code) return `${code}: ${message}`\n return message || code || fallback\n}\n\nconst providerError = (event: OpenAIResponsesEvent, fallback: string) => {\n const code = event.code || event.error?.code || event.response?.error?.code || undefined\n const message = providerErrorMessage(event, fallback)\n return new LLMError({\n module: ADAPTER,\n method: \"stream\",\n reason: classifyProviderFailure({ message, code }),\n })\n}\n\nconst step = (state: ParserState, event: OpenAIResponsesEvent) => {\n if (event.type === \"response.output_text.delta\") return Effect.succeed(onOutputTextDelta(state, event))\n if (event.type === \"response.output_text.done\") return Effect.succeed(onOutputTextDone(state, event))\n if (\n event.type === \"response.reasoning_text.delta\" ||\n event.type === \"response.reasoning_summary.delta\" ||\n event.type === \"response.reasoning_summary_text.delta\"\n )\n return Effect.succeed(onReasoningDelta(state, event))\n if (\n event.type === \"response.reasoning_text.done\" ||\n event.type === \"response.reasoning_summary.done\" ||\n event.type === \"response.reasoning_summary_text.done\"\n )\n return Effect.succeed(onReasoningDone(state, event))\n if (event.type === \"response.reasoning_summary_part.added\")\n return Effect.succeed(onReasoningSummaryPartAdded(state, event))\n if (event.type === \"response.reasoning_summary_part.done\")\n return Effect.succeed(onReasoningSummaryPartDone(state, event))\n if (event.type === \"response.output_item.added\") return Effect.succeed(onOutputItemAdded(state, event))\n if (event.type === \"response.function_call_arguments.delta\") return onFunctionCallArgumentsDelta(state, event)\n if (event.type === \"response.output_item.done\") return onOutputItemDone(state, event)\n if (event.type === \"response.completed\" || event.type === \"response.incomplete\")\n return Effect.succeed(onResponseFinish(state, event))\n if (event.type === \"response.failed\") return providerError(event, \"OpenAI Responses response failed\")\n if (event.type === \"error\") return providerError(event, \"OpenAI Responses stream error\")\n return Effect.succeed<StepResult>([state, NO_EVENTS])\n}\n\n// =============================================================================\n// Protocol And OpenAI Route\n// =============================================================================\n/**\n * The OpenAI Responses protocol — request body construction, body schema, and\n * the streaming-event state machine. Used by native OpenAI and (once\n * registered) Azure OpenAI Responses.\n */\nexport const protocol = Protocol.make({\n id: ADAPTER,\n body: {\n schema: OpenAIResponsesBody,\n from: fromRequest,\n },\n stream: {\n event: Protocol.jsonEvent(OpenAIResponsesEvent),\n initial: (request) => ({\n hasFunctionCall: false,\n tools: ToolStream.empty<string>(),\n lifecycle: Lifecycle.initial(),\n reasoningItems: {},\n store: OpenAIOptions.store(request),\n }),\n step,\n terminal: (event) => TERMINAL_TYPES.has(event.type),\n },\n})\n\nconst endpoint = Endpoint.path<OpenAIResponsesBody>(PATH, { baseURL: DEFAULT_BASE_URL })\nconst auth = Auth.none\n\nexport const httpTransport = HttpTransport.sseJson.with<OpenAIResponsesBody>()\n\nexport const route = Route.make({\n id: ADAPTER,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint,\n auth,\n transport: httpTransport,\n defaults: { providerOptions: { openai: { store: false } } },\n})\n\nconst decodeWebSocketMessage = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesWebSocketMessage))\n\nconst webSocketMessage = (body: OpenAIResponsesBody | Record<string, unknown>) =>\n Effect.gen(function* () {\n if (!ProviderShared.isRecord(body))\n return yield* ProviderShared.invalidRequest(\"OpenAI Responses WebSocket body must be a JSON object\")\n const { stream: _stream, ...message } = body\n return yield* decodeWebSocketMessage({ ...message, type: \"response.create\" })\n })\n\nexport const webSocketTransport = WebSocketTransport.jsonTransport.with<\n OpenAIResponsesBody,\n OpenAIResponsesWebSocketMessage\n>({\n toMessage: webSocketMessage,\n encodeMessage: encodeWebSocketMessage,\n})\n\nexport const webSocketRoute = Route.make({\n id: `${ADAPTER}-websocket`,\n provider: \"openai\",\n providerMetadataKey: \"openai\",\n protocol,\n endpoint,\n auth,\n transport: webSocketTransport,\n defaults: { providerOptions: { openai: { store: false } } },\n})\n\nexport * as OpenAIResponses from \"./openai-responses\"\n" | ||
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| ||
| "debugId": "0AC81B2102696FCF64756E2164756E21", | ||
| "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": "E6F930650F645B7C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
| ], | ||
| "mappings": "", | ||
| "debugId": "E7F80835EB24065D64756E2164756E21", | ||
| "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": "F9A263D7E1EAF79864756E2164756E21", | ||
| "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": "4E82D9423974D14764756E2164756E21", | ||
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| } |
| { | ||
| "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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| "debugId": "9E1059ECFA917FE964756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": [], | ||
| "sourcesContent": [ | ||
| ], | ||
| "mappings": "", | ||
| "debugId": "70233F245B44841C64756E2164756E21", | ||
| "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": "76422CD8D44AA85464756E2164756E21", | ||
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| } |
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| { | ||
| "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": "CB8F5843882A95E764756E2164756E21", | ||
| "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": "182A2235DD73EB1064756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "C4100C96DB51D19664756E2164756E21", | ||
| "names": [] | ||
| } |
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| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mini.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.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 yield* Effect.promise(() =>\n runMini({\n server,\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 }),\n )\n }),\n)\n" | ||
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| "debugId": "BD71950B14C79B8D64756E2164756E21", | ||
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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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| "debugId": "AA4E57CBB6119C1464756E2164756E21", | ||
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| } |
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| { | ||
| "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": "99EA1FBB0D67A92D64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "FE5E8F30C3B9A1BE64756E2164756E21", | ||
| "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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| "debugId": "5E031B156041ACB864756E2164756E21", | ||
| "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(\"../../mini\"))\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": "081A8799C4AAAE8D64756E2164756E21", | ||
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| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/mini/variant.shared.ts", "src/mini/session.shared.ts", "src/mini/theme.ts"], | ||
| "sourcesContent": [ | ||
| "// Model variant resolution and persistence.\n//\n// Variants are provider-specific reasoning effort levels (e.g., \"high\", \"max\").\n// Resolution priority: CLI --variant flag > saved preference > session history.\n//\n// The saved variant persists across sessions in ~/.local/state/opencode/model.json\n// so your last-used variant sticks. Cycling (ctrl+t) updates both the active\n// variant and the persisted file.\nimport path from \"path\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { Context, Effect, Layer } from \"effect\"\nimport { LayerNode } from \"@opencode-ai/core/effect/layer-node\"\nimport { makeGlobalNode } from \"@opencode-ai/core/effect/app-node\"\nimport { makeRuntime } from \"@opencode-ai/core/effect/runtime\"\nimport { Global } from \"@opencode-ai/core/global\"\nimport { createSession, sessionVariant, type RunSession, type SessionMessages } from \"./session.shared\"\nimport type { RunInput, RunProvider } from \"./types\"\n\nconst MODEL_FILE = path.join(Global.Path.state, \"model.json\")\n\ntype ModelState = Record<string, unknown> & {\n variant?: Record<string, string | undefined>\n}\ntype VariantService = {\n readonly resolveSavedVariant: (model: RunInput[\"model\"]) => Effect.Effect<string | undefined>\n readonly saveVariant: (model: RunInput[\"model\"], variant: string | undefined) => Effect.Effect<void>\n}\ntype VariantRuntime = {\n resolveSavedVariant(model: RunInput[\"model\"]): Promise<string | undefined>\n saveVariant(model: RunInput[\"model\"], variant: string | undefined): Promise<void>\n}\n\nfunction isRecord(value: unknown): value is Record<string, unknown> {\n return !!value && typeof value === \"object\" && !Array.isArray(value)\n}\n\nclass Service extends Context.Service<Service, VariantService>()(\"@opencode/RunVariant\") {}\n\nfunction modelKey(provider: string, model: string): string {\n return `${provider}/${model}`\n}\n\nfunction variantKey(model: NonNullable<RunInput[\"model\"]>): string {\n return modelKey(model.providerID, model.modelID)\n}\n\nexport function modelInfo(providers: RunProvider[] | undefined, model: NonNullable<RunInput[\"model\"]>) {\n const provider = providers?.find((item) => item.id === model.providerID)\n return {\n provider: provider?.name ?? model.providerID,\n model: provider?.models[model.modelID]?.name ?? model.modelID,\n }\n}\n\nexport function formatModelLabel(\n model: NonNullable<RunInput[\"model\"]>,\n variant: string | undefined,\n providers?: RunProvider[],\n): string {\n const names = modelInfo(providers, model)\n const label = variant ? ` · ${variant}` : \"\"\n return `${names.model} · ${names.provider}${label}`\n}\n\nexport function cycleVariant(current: string | undefined, variants: string[]): string | undefined {\n if (variants.length === 0) {\n return undefined\n }\n\n if (!current) {\n return variants[0]\n }\n\n const idx = variants.indexOf(current)\n if (idx === -1 || idx === variants.length - 1) {\n return undefined\n }\n\n return variants[idx + 1]\n}\n\nexport function pickVariant(model: RunInput[\"model\"], input: RunSession | SessionMessages): string | undefined {\n return sessionVariant(Array.isArray(input) ? createSession(input) : input, model)\n}\n\nfunction fitVariant(value: string | undefined, variants: string[]): string | undefined {\n if (!value) {\n return undefined\n }\n\n if (variants.length === 0 || variants.includes(value)) {\n return value\n }\n\n return undefined\n}\n\n// Picks the active variant. CLI flag wins, then saved preference, then session\n// history. fitVariant() checks saved and session values against the available\n// variants list -- if the provider doesn't offer a variant, it drops.\nexport function resolveVariant(\n input: string | undefined,\n session: string | undefined,\n saved: string | undefined,\n variants: string[],\n): string | undefined {\n if (input !== undefined) {\n return input\n }\n\n const fallback = fitVariant(saved, variants)\n const current = fitVariant(session, variants)\n if (current !== undefined) {\n return current\n }\n\n return fallback\n}\n\nfunction state(value: unknown): ModelState {\n if (!isRecord(value)) {\n return {}\n }\n\n const variant = isRecord(value.variant)\n ? Object.fromEntries(\n Object.entries(value.variant).flatMap(([key, item]) => {\n if (typeof item !== \"string\") {\n return []\n }\n\n return [[key, item] as const]\n }),\n )\n : undefined\n\n return {\n ...value,\n variant,\n }\n}\n\nconst layer = Layer.fresh(\n Layer.effect(\n Service,\n Effect.gen(function* () {\n const file = yield* FSUtil.Service\n\n const read = Effect.fn(\"RunVariant.read\")(function* () {\n return yield* file.readJson(MODEL_FILE).pipe(\n Effect.map(state),\n Effect.catchCause(() => Effect.succeed(state(undefined))),\n )\n })\n\n const resolveSavedVariant = Effect.fn(\"RunVariant.resolveSavedVariant\")(function* (model: RunInput[\"model\"]) {\n if (!model) {\n return undefined\n }\n\n return (yield* read()).variant?.[variantKey(model)]\n })\n\n const saveVariant = Effect.fn(\"RunVariant.saveVariant\")(function* (\n model: RunInput[\"model\"],\n variant: string | undefined,\n ) {\n if (!model) {\n return\n }\n\n const current = yield* read()\n const next = {\n ...current.variant,\n }\n const key = variantKey(model)\n if (variant) {\n next[key] = variant\n }\n\n if (!variant) {\n delete next[key]\n }\n\n yield* file\n .writeJson(MODEL_FILE, {\n ...current,\n variant: next,\n })\n .pipe(Effect.orElseSucceed(() => undefined))\n })\n\n return Service.of({\n resolveSavedVariant,\n saveVariant,\n })\n }),\n ),\n)\n\nconst node = makeGlobalNode({ service: Service, layer, deps: [FSUtil.node] })\n\n/** @internal Exported for testing. */\nexport function createVariantRuntime(replacements?: readonly LayerNode.Replacement[]): VariantRuntime {\n const runtime = makeRuntime(Service, LayerNode.compile(node, replacements))\n return {\n resolveSavedVariant: (model) => runtime.runPromise((svc) => svc.resolveSavedVariant(model)).catch(() => undefined),\n saveVariant: (model, variant) => runtime.runPromise((svc) => svc.saveVariant(model, variant)).catch(() => {}),\n }\n}\n\nconst runtime = createVariantRuntime()\n\nexport async function resolveSavedVariant(model: RunInput[\"model\"]): Promise<string | undefined> {\n return runtime.resolveSavedVariant(model)\n}\n\nexport function saveVariant(model: RunInput[\"model\"], variant: string | undefined): void {\n void runtime.saveVariant(model, variant)\n}\n", | ||
| "import type { SessionMessageInfo, SessionMessageUser } from \"@opencode-ai/client/promise\"\nimport { promptCopy, promptSame } from \"./prompt.shared\"\nimport type { RunInput, RunPrompt } from \"./types\"\n\nconst LIMIT = 200\n\nexport type SessionMessages = SessionMessageInfo[]\n\ntype Turn = {\n prompt: RunPrompt\n provider: string | undefined\n model: string | undefined\n variant: string | undefined\n}\n\nexport type RunSession = {\n first: boolean\n turns: Turn[]\n model?: NonNullable<RunInput[\"model\"]>\n variant?: string\n}\n\nfunction messagePrompt(message: SessionMessageUser): RunPrompt {\n return {\n text: message.text,\n parts: [\n ...(message.files ?? []).map((file) => ({\n type: \"file\" as const,\n url: file.source.type === \"uri\" ? file.source.uri : `data:${file.mime};base64,${file.data}`,\n mime: file.mime,\n filename: file.name,\n source: file.mention\n ? {\n type: \"file\",\n path: file.name ?? (file.source.type === \"uri\" ? file.source.uri : \"inline attachment\"),\n text: { start: file.mention.start, end: file.mention.end, value: file.mention.text },\n }\n : undefined,\n })),\n ...(message.agents ?? []).map((agent) => ({\n type: \"agent\" as const,\n name: agent.name,\n source: agent.mention\n ? { start: agent.mention.start, end: agent.mention.end, value: agent.mention.text }\n : undefined,\n })),\n ],\n }\n}\n\nexport function createSession(messages: SessionMessages): RunSession {\n return {\n first: messages.length === 0,\n turns: messages.flatMap((message) =>\n message.type === \"user\"\n ? [{ prompt: messagePrompt(message), provider: undefined, model: undefined, variant: undefined }]\n : [],\n ),\n }\n}\n\nexport async function resolveCurrentSession(\n sdk: RunInput[\"sdk\"],\n sessionID: string,\n limit = LIMIT,\n): Promise<RunSession> {\n const [response, session] = await Promise.all([\n sdk.message.list({ sessionID, limit, order: \"desc\" }),\n sdk.session.get({ sessionID }),\n ])\n const current = createSession(response.data.toReversed())\n return {\n ...current,\n turns: current.turns.map((turn) => ({\n ...turn,\n provider: session.model?.providerID,\n model: session.model?.id,\n variant: session.model?.variant,\n })),\n ...(session.model && {\n model: { providerID: session.model.providerID, modelID: session.model.id },\n variant: session.model.variant,\n }),\n }\n}\n\nexport function sessionHistory(session: RunSession, limit = LIMIT): RunPrompt[] {\n return session.turns\n .map((turn) => turn.prompt)\n .filter((prompt) => prompt.text.trim())\n .filter((prompt, index, prompts) => index === 0 || !promptSame(prompts[index - 1], prompt))\n .map(promptCopy)\n .slice(-limit)\n}\n\nexport function sessionVariant(session: RunSession, model: RunInput[\"model\"]): string | undefined {\n if (!model) return\n if (session.model?.providerID === model.providerID && session.model.modelID === model.modelID) return session.variant\n\n return session.turns.findLast((turn) => turn.provider === model.providerID && turn.model === model.modelID)?.variant\n}\n", | ||
| "// Theme resolution for direct interactive mode.\n//\n// Derives scrollback and footer colors from the terminal's actual palette.\n// resolveRunTheme() queries the renderer for the terminal's palette,\n// detects dark/light mode, builds a small system theme locally, and maps it to\n// the run footer + scrollback color model. Falls back to a hardcoded dark-mode\n// palette if detection fails.\nimport { RGBA, SyntaxStyle, type CliRenderer, type ColorInput, type TerminalColors } from \"@opentui/core\"\nimport type { TuiThemeCurrent } from \"@opencode-ai/plugin/tui\"\nimport type { EntryKind } from \"./types\"\n\ntype Tone = {\n body: ColorInput\n start?: ColorInput\n}\n\nexport type RunEntryTheme = Record<EntryKind, Tone>\n\nexport type RunSplashTheme = {\n left: ColorInput\n right: ColorInput\n leftShadow: ColorInput\n rightShadow: ColorInput\n}\n\nexport type RunFooterTheme = {\n highlight: ColorInput\n selected: ColorInput\n selectedText: ColorInput\n warning: ColorInput\n success: ColorInput\n error: ColorInput\n muted: ColorInput\n text: ColorInput\n status: ColorInput\n statusAccent: ColorInput\n shade: ColorInput\n surface: ColorInput\n pane: ColorInput\n border: ColorInput\n line: ColorInput\n}\n\nexport type RunBlockTheme = {\n highlight: ColorInput\n warning: ColorInput\n text: ColorInput\n muted: ColorInput\n syntax?: SyntaxStyle\n diffAdded: ColorInput\n diffRemoved: ColorInput\n diffAddedBg: ColorInput\n diffRemovedBg: ColorInput\n diffContextBg: ColorInput\n diffHighlightAdded: ColorInput\n diffHighlightRemoved: ColorInput\n diffLineNumber: ColorInput\n diffAddedLineNumberBg: ColorInput\n diffRemovedLineNumberBg: ColorInput\n}\n\nexport type RunTheme = {\n background: ColorInput\n footer: RunFooterTheme\n entry: RunEntryTheme\n splash: RunSplashTheme\n block: RunBlockTheme\n}\n\ntype ThemeColor = Exclude<keyof TuiThemeCurrent, \"thinkingOpacity\">\ntype HexColor = `#${string}`\ntype RefName = string\ntype Variant = {\n dark: HexColor | RefName\n light: HexColor | RefName\n}\ntype ColorValue = HexColor | RefName | Variant | RGBA | number\ntype ThemeJson = {\n defs?: Record<string, HexColor | RefName>\n theme: Omit<Record<ThemeColor, ColorValue>, \"selectedListItemText\" | \"backgroundMenu\"> & {\n selectedListItemText?: ColorValue\n backgroundMenu?: ColorValue\n thinkingOpacity?: number\n }\n}\n\ntype SharedSyntaxTheme = TuiThemeCurrent & {\n _hasSelectedListItemText: boolean\n}\n\nexport const transparent = RGBA.fromValues(0, 0, 0, 0)\n\nfunction alpha(color: RGBA, value: number): RGBA {\n return RGBA.fromValues(color.r, color.g, color.b, Math.max(0, Math.min(1, value)))\n}\n\nfunction rgba(hex: string, value?: number): RGBA {\n const color = RGBA.fromHex(hex)\n return value === undefined ? color : alpha(color, value)\n}\n\nfunction mode(bg: RGBA): \"dark\" | \"light\" {\n return luminance(bg) > 0.5 ? \"light\" : \"dark\"\n}\n\nfunction luminance(color: RGBA): number {\n return 0.299 * color.r + 0.587 * color.g + 0.114 * color.b\n}\n\nfunction fade(color: RGBA, base: RGBA, fallback: number, scale: number, limit: number): RGBA {\n if (color.a === 0) {\n return RGBA.fromValues(color.r, color.g, color.b, Math.max(0, Math.min(1, fallback)))\n }\n\n const target = Math.min(limit, color.a * scale)\n const mix = Math.min(1, target / color.a)\n\n return RGBA.fromValues(\n base.r + (color.r - base.r) * mix,\n base.g + (color.g - base.g) * mix,\n base.b + (color.b - base.b) * mix,\n color.a,\n )\n}\n\nfunction ansiToRgba(code: number): RGBA {\n if (code < 16) {\n const ansi = [\n \"#000000\",\n \"#800000\",\n \"#008000\",\n \"#808000\",\n \"#000080\",\n \"#800080\",\n \"#008080\",\n \"#c0c0c0\",\n \"#808080\",\n \"#ff0000\",\n \"#00ff00\",\n \"#ffff00\",\n \"#0000ff\",\n \"#ff00ff\",\n \"#00ffff\",\n \"#ffffff\",\n ]\n return RGBA.fromHex(ansi[code] ?? \"#000000\")\n }\n\n if (code < 232) {\n const index = code - 16\n const b = index % 6\n const g = Math.floor(index / 6) % 6\n const r = Math.floor(index / 36)\n const value = (x: number) => (x === 0 ? 0 : x * 40 + 55)\n return RGBA.fromInts(value(r), value(g), value(b))\n }\n\n if (code < 256) {\n const gray = (code - 232) * 10 + 8\n return RGBA.fromInts(gray, gray, gray)\n }\n\n return RGBA.fromInts(0, 0, 0)\n}\n\nfunction tint(base: RGBA, overlay: RGBA, value: number): RGBA {\n return RGBA.fromInts(\n Math.round((base.r + (overlay.r - base.r) * value) * 255),\n Math.round((base.g + (overlay.g - base.g) * value) * 255),\n Math.round((base.b + (overlay.b - base.b) * value) * 255),\n )\n}\n\nfunction chroma(color: RGBA) {\n return Math.max(color.r, color.g, color.b) - Math.min(color.r, color.g, color.b)\n}\n\nfunction indexedPalette(colors: TerminalColors, size: number = Math.max(colors.palette.length, 16)): RGBA[] {\n return Array.from({ length: size }, (_, index) => {\n const value = colors.palette[index]\n return RGBA.fromIndex(index, value ? RGBA.fromHex(value) : ansiToRgba(index))\n })\n}\n\nfunction srgbToLinear(value: number): number {\n if (value <= 0.04045) {\n return value / 12.92\n }\n\n return ((value + 0.055) / 1.055) ** 2.4\n}\n\nfunction oklab(color: RGBA) {\n const r = srgbToLinear(color.r)\n const g = srgbToLinear(color.g)\n const b = srgbToLinear(color.b)\n\n const l = Math.cbrt(0.4122214708 * r + 0.5363325363 * g + 0.0514459929 * b)\n const m = Math.cbrt(0.2119034982 * r + 0.6806995451 * g + 0.1073969566 * b)\n const s = Math.cbrt(0.0883024619 * r + 0.2817188376 * g + 0.6299787005 * b)\n\n return {\n l: 0.2104542553 * l + 0.793617785 * m - 0.0040720468 * s,\n a: 1.9779984951 * l - 2.428592205 * m + 0.4505937099 * s,\n b: 0.0259040371 * l + 0.7827717662 * m - 0.808675766 * s,\n }\n}\n\nfunction nearestIndexed(indexed: RGBA[], rgba: RGBA): RGBA {\n const target = oklab(rgba)\n const hit = indexed.reduce(\n (best, item) => {\n const sample = oklab(item)\n const dl = sample.l - target.l\n const da = sample.a - target.a\n const db = sample.b - target.b\n const dist = dl * dl * 2 + da * da + db * db\n if (dist >= best.dist) return best\n return {\n dist,\n item,\n }\n },\n {\n dist: Number.POSITIVE_INFINITY,\n item: indexed[0]!,\n },\n )\n\n return RGBA.clone(hit.item)\n}\n\nfunction paletteColor(colors: TerminalColors, index: number): RGBA {\n const value = colors.palette[index]\n return value ? RGBA.fromHex(value) : ansiToRgba(index)\n}\n\nfunction splashShadow(indexed: RGBA[], base: RGBA, overlay: RGBA, value: number): RGBA {\n const mixed = tint(base, overlay, value)\n return nearestIndexed(indexed, mixed)\n}\n\nexport function resolveTheme(theme: ThemeJson, pick: \"dark\" | \"light\"): TuiThemeCurrent {\n const defs = theme.defs ?? {}\n\n const resolveColor = (value: ColorValue, chain: string[] = []): RGBA => {\n if (value instanceof RGBA) return value\n\n if (typeof value === \"number\") {\n return RGBA.fromIndex(value, ansiToRgba(value))\n }\n\n if (typeof value !== \"string\") {\n return resolveColor(value[pick], chain)\n }\n\n if (value === \"transparent\" || value === \"none\") {\n return RGBA.fromInts(0, 0, 0, 0)\n }\n\n if (value.startsWith(\"#\")) {\n return RGBA.fromHex(value)\n }\n\n if (chain.includes(value)) {\n throw new Error(`Circular color reference: ${[...chain, value].join(\" -> \")}`)\n }\n\n const next = defs[value] ?? theme.theme[value as ThemeColor]\n if (next === undefined) {\n throw new Error(`Color reference \"${value}\" not found in defs or theme`)\n }\n\n return resolveColor(next, [...chain, value])\n }\n\n const resolved = Object.fromEntries(\n Object.entries(theme.theme)\n .filter(([key]) => key !== \"selectedListItemText\" && key !== \"backgroundMenu\" && key !== \"thinkingOpacity\")\n .map(([key, value]) => [key, resolveColor(value as ColorValue)]),\n ) as Partial<Record<ThemeColor, RGBA>>\n\n return {\n ...(resolved as Record<ThemeColor, RGBA>),\n selectedListItemText:\n theme.theme.selectedListItemText === undefined\n ? resolved.background!\n : resolveColor(theme.theme.selectedListItemText),\n backgroundMenu:\n theme.theme.backgroundMenu === undefined ? resolved.backgroundElement! : resolveColor(theme.theme.backgroundMenu),\n thinkingOpacity: theme.theme.thinkingOpacity ?? 0.6,\n }\n}\n\nfunction generateGrayScale(bg: RGBA, isDark: boolean, map: (rgba: RGBA) => RGBA): Record<number, RGBA> {\n const r = bg.r * 255\n const g = bg.g * 255\n const b = bg.b * 255\n const lum = 0.299 * r + 0.587 * g + 0.114 * b\n const cast = 0.25 * (1 - chroma(bg)) ** 2\n\n const gray = (level: number) => {\n const factor = level / 12\n\n if (isDark && lum < 10) {\n const value = Math.floor(factor * 0.4 * 255)\n return map(RGBA.fromInts(value, value, value))\n }\n\n if (!isDark && lum > 245) {\n const value = Math.floor(255 - factor * 0.4 * 255)\n return map(RGBA.fromInts(value, value, value))\n }\n\n const value = isDark ? lum + (255 - lum) * factor * 0.4 : lum * (1 - factor * 0.4)\n const tone = RGBA.fromInts(Math.floor(value), Math.floor(value), Math.floor(value))\n if (cast === 0) return map(tone)\n\n const ratio = lum === 0 ? 0 : value / lum\n return map(\n tint(\n tone,\n RGBA.fromInts(\n Math.floor(Math.max(0, Math.min(r * ratio, 255))),\n Math.floor(Math.max(0, Math.min(g * ratio, 255))),\n Math.floor(Math.max(0, Math.min(b * ratio, 255))),\n ),\n cast,\n ),\n )\n }\n\n return Object.fromEntries(Array.from({ length: 12 }, (_, index) => [index + 1, gray(index + 1)]))\n}\n\nfunction generateMutedTextColor(bg: RGBA, isDark: boolean, map: (rgba: RGBA) => RGBA): RGBA {\n const lum = 0.299 * bg.r * 255 + 0.587 * bg.g * 255 + 0.114 * bg.b * 255\n const gray = isDark\n ? lum < 10\n ? 180\n : Math.min(Math.floor(160 + lum * 0.3), 200)\n : lum > 245\n ? 75\n : Math.max(Math.floor(100 - (255 - lum) * 0.2), 60)\n\n return map(RGBA.fromInts(gray, gray, gray))\n}\n\nexport function generateSystem(colors: TerminalColors, pick: \"dark\" | \"light\"): ThemeJson {\n const bg_snapshot = RGBA.fromHex(colors.defaultBackground ?? colors.palette[0]!)\n const fg_snapshot = RGBA.fromHex(colors.defaultForeground ?? colors.palette[7]!)\n const bg = RGBA.defaultBackground(bg_snapshot)\n const fg = RGBA.defaultForeground(fg_snapshot)\n const isDark = pick === \"dark\"\n\n const color = (index: number) => paletteColor(colors, index)\n\n const grays = generateGrayScale(bg_snapshot, isDark, (rgba) => rgba)\n const textMuted = generateMutedTextColor(bg_snapshot, isDark, (rgba) => rgba)\n\n const ansi = {\n red: color(1),\n green: color(2),\n yellow: color(3),\n blue: color(4),\n magenta: color(5),\n cyan: color(6),\n red_bright: color(9),\n green_bright: color(10),\n }\n\n const diff_alpha = isDark ? 0.22 : 0.14\n const diff_context_bg = grays[2]\n const primary = ansi.cyan\n const secondary = ansi.magenta\n\n return {\n theme: {\n primary,\n secondary,\n accent: primary,\n error: ansi.red,\n warning: ansi.yellow,\n success: ansi.green,\n info: ansi.cyan,\n text: fg,\n textMuted,\n selectedListItemText: bg,\n background: alpha(bg, 0),\n backgroundPanel: grays[2],\n backgroundElement: grays[3],\n backgroundMenu: grays[3],\n borderSubtle: grays[6],\n border: grays[7],\n borderActive: grays[8],\n diffAdded: ansi.green,\n diffRemoved: ansi.red,\n diffContext: grays[7],\n diffHunkHeader: grays[7],\n diffHighlightAdded: ansi.green_bright,\n diffHighlightRemoved: ansi.red_bright,\n diffAddedBg: tint(bg_snapshot, ansi.green, diff_alpha),\n diffRemovedBg: tint(bg_snapshot, ansi.red, diff_alpha),\n diffContextBg: diff_context_bg,\n diffLineNumber: textMuted,\n diffAddedLineNumberBg: tint(diff_context_bg, ansi.green, diff_alpha),\n diffRemovedLineNumberBg: tint(diff_context_bg, ansi.red, diff_alpha),\n markdownText: fg,\n markdownHeading: fg,\n markdownLink: ansi.blue,\n markdownLinkText: ansi.cyan,\n markdownCode: ansi.green,\n markdownBlockQuote: ansi.yellow,\n markdownEmph: ansi.yellow,\n markdownStrong: fg,\n markdownHorizontalRule: grays[7],\n markdownListItem: ansi.blue,\n markdownListEnumeration: ansi.cyan,\n markdownImage: ansi.blue,\n markdownImageText: ansi.cyan,\n markdownCodeBlock: fg,\n syntaxComment: textMuted,\n syntaxKeyword: ansi.magenta,\n syntaxFunction: ansi.blue,\n syntaxVariable: fg,\n syntaxString: ansi.green,\n syntaxNumber: ansi.yellow,\n syntaxType: ansi.cyan,\n syntaxOperator: ansi.cyan,\n syntaxPunctuation: fg,\n },\n }\n}\n\nfunction quantizeColor(indexed: RGBA[], rgba: RGBA): RGBA {\n if (rgba.a === 0 || rgba.intent === \"default\" || rgba.intent === \"indexed\") {\n return RGBA.clone(rgba)\n }\n\n return nearestIndexed(indexed, rgba)\n}\n\nfunction quantizeTheme(theme: TuiThemeCurrent, indexed: RGBA[]): TuiThemeCurrent {\n const resolved = Object.fromEntries(\n Object.entries(theme)\n .filter(([key]) => key !== \"thinkingOpacity\")\n .map(([key, value]) => [key, quantizeColor(indexed, value as RGBA)]),\n ) as Partial<Record<ThemeColor, RGBA>>\n\n return {\n ...(resolved as Record<ThemeColor, RGBA>),\n thinkingOpacity: theme.thinkingOpacity,\n }\n}\n\nfunction splashTheme(theme: TuiThemeCurrent, indexed: RGBA[]): RunSplashTheme {\n const left = nearestIndexed(indexed, theme.textMuted)\n const right = nearestIndexed(indexed, theme.text)\n return {\n left,\n right,\n leftShadow: splashShadow(indexed, theme.background, left, 0.14),\n rightShadow: splashShadow(indexed, theme.background, right, 0.14),\n }\n}\n\nfunction map(\n footerTheme: TuiThemeCurrent,\n scrollbackTheme: TuiThemeCurrent,\n splash: RunSplashTheme,\n syntax?: SyntaxStyle,\n): RunTheme {\n const footerBackground = alpha(footerTheme.background, 1)\n const footerMode = mode(footerBackground)\n const shade = fade(footerTheme.backgroundMenu, footerTheme.background, 0.12, 0.56, 0.72)\n const surface = fade(footerTheme.backgroundMenu, footerTheme.background, 0.18, 0.76, 0.9)\n const line = fade(footerTheme.backgroundMenu, footerTheme.background, 0.24, 0.9, 0.98)\n const statusBase = tint(footerBackground, rgba(\"#000000\"), footerMode === \"dark\" ? 0.12 : 0.06)\n const statusAccentBase =\n footerMode === \"dark\" ? tint(footerBackground, rgba(\"#ffffff\"), 0.06) : tint(statusBase, rgba(\"#000000\"), 0.04)\n const collapsedStatus = footerMode === \"dark\" && luminance(statusBase) <= 0.04\n // Pure-black backgrounds need a slight lift or the row disappears into the terminal background.\n const status = collapsedStatus ? tint(statusBase, statusAccentBase, 0.7) : statusBase\n const statusAccent = collapsedStatus ? tint(status, rgba(\"#ffffff\"), 0.06) : statusAccentBase\n\n return {\n background: footerTheme.background,\n footer: {\n highlight: footerTheme.primary,\n selected: footerTheme.backgroundElement,\n selectedText: footerTheme.selectedListItemText,\n warning: footerTheme.warning,\n success: footerTheme.success,\n error: footerTheme.error,\n muted: footerTheme.textMuted,\n text: footerTheme.text,\n status,\n statusAccent,\n shade,\n surface,\n pane: footerTheme.backgroundMenu,\n border: footerTheme.border,\n line,\n },\n entry: {\n system: {\n body: scrollbackTheme.textMuted,\n },\n user: {\n body: scrollbackTheme.primary,\n },\n assistant: {\n body: scrollbackTheme.text,\n },\n reasoning: {\n body: scrollbackTheme.textMuted,\n },\n tool: {\n body: scrollbackTheme.text,\n start: scrollbackTheme.textMuted,\n },\n error: {\n body: scrollbackTheme.error,\n },\n },\n splash,\n block: {\n highlight: scrollbackTheme.primary,\n warning: scrollbackTheme.warning,\n text: scrollbackTheme.text,\n muted: scrollbackTheme.textMuted,\n syntax,\n diffAdded: scrollbackTheme.diffAdded,\n diffRemoved: scrollbackTheme.diffRemoved,\n diffAddedBg: transparent,\n diffRemovedBg: transparent,\n diffContextBg: transparent,\n diffHighlightAdded: scrollbackTheme.diffHighlightAdded,\n diffHighlightRemoved: scrollbackTheme.diffHighlightRemoved,\n diffLineNumber: scrollbackTheme.diffLineNumber,\n diffAddedLineNumberBg: scrollbackTheme.diffAddedLineNumberBg,\n diffRemovedLineNumberBg: scrollbackTheme.diffRemovedLineNumberBg,\n },\n }\n}\n\nconst seed = {\n highlight: RGBA.fromIndex(6, rgba(\"#38bdf8\")),\n muted: RGBA.fromIndex(8, rgba(\"#64748b\")),\n text: RGBA.defaultForeground(rgba(\"#f8fafc\")),\n panel: rgba(\"#0f172a\"),\n success: RGBA.fromIndex(2, rgba(\"#22c55e\")),\n warning: RGBA.fromIndex(3, rgba(\"#f59e0b\")),\n error: RGBA.fromIndex(1, rgba(\"#ef4444\")),\n}\n\nfunction tone(body: ColorInput, start?: ColorInput): Tone {\n return {\n body,\n start,\n }\n}\n\nconst fallbackSplashIndexed = Array.from({ length: 256 }, (_, index) => RGBA.fromIndex(index))\nconst fallbackSplashLeft = RGBA.fromIndex(67)\nconst fallbackSplashRight = RGBA.fromIndex(110)\n\nexport const RUN_THEME_FALLBACK: RunTheme = {\n background: RGBA.fromValues(0, 0, 0, 0),\n footer: {\n highlight: seed.highlight,\n selected: seed.text,\n selectedText: seed.panel,\n warning: seed.warning,\n success: seed.success,\n error: seed.error,\n muted: seed.muted,\n text: seed.text,\n status: tint(seed.panel, rgba(\"#000000\"), 0.12),\n statusAccent: tint(seed.panel, rgba(\"#ffffff\"), 0.06),\n shade: alpha(seed.panel, 0.68),\n surface: alpha(seed.panel, 0.86),\n pane: seed.panel,\n border: seed.muted,\n line: alpha(seed.panel, 0.96),\n },\n entry: {\n system: tone(seed.muted),\n user: tone(seed.highlight),\n assistant: tone(seed.text),\n reasoning: tone(seed.muted),\n tool: tone(seed.text, seed.muted),\n error: tone(seed.error),\n },\n splash: {\n left: fallbackSplashLeft,\n right: fallbackSplashRight,\n leftShadow: splashShadow(fallbackSplashIndexed, RGBA.fromValues(0, 0, 0, 0), fallbackSplashLeft, 0.14),\n rightShadow: splashShadow(fallbackSplashIndexed, RGBA.fromValues(0, 0, 0, 0), fallbackSplashRight, 0.14),\n },\n block: {\n highlight: seed.highlight,\n warning: seed.warning,\n text: seed.text,\n muted: seed.muted,\n diffAdded: seed.success,\n diffRemoved: seed.error,\n diffAddedBg: alpha(seed.success, 0.18),\n diffRemovedBg: alpha(seed.error, 0.18),\n diffContextBg: alpha(seed.panel, 0.72),\n diffHighlightAdded: seed.success,\n diffHighlightRemoved: seed.error,\n diffLineNumber: seed.muted,\n diffAddedLineNumberBg: alpha(seed.success, 0.12),\n diffRemovedLineNumberBg: alpha(seed.error, 0.12),\n },\n}\n\nexport async function resolveRunTheme(renderer: CliRenderer): Promise<RunTheme> {\n try {\n const colors = await renderer.getPalette({\n size: 256,\n })\n const bg = colors.defaultBackground ?? colors.palette[0]\n if (!bg) {\n return RUN_THEME_FALLBACK\n }\n\n // Palette-only terminal reloads can leave renderer.themeMode stale, but\n // ANSI slot zero is not the terminal background when OSC 11 is absent.\n const pick = colors.defaultBackground\n ? mode(RGBA.fromHex(colors.defaultBackground))\n : (renderer.themeMode ?? mode(RGBA.fromHex(bg)))\n const footerTheme = resolveTheme(generateSystem(colors, pick), pick)\n const indexed = indexedPalette(colors, 256)\n const scrollbackTheme = quantizeTheme(footerTheme, indexed)\n const shared = await import(\"@opencode-ai/tui/context/theme\")\n const syntaxTheme: SharedSyntaxTheme = {\n ...scrollbackTheme,\n _hasSelectedListItemText: true,\n }\n const syntax = shared.generateSyntax(syntaxTheme)\n return map(footerTheme, scrollbackTheme, splashTheme(scrollbackTheme, indexed), syntax)\n } catch {\n return RUN_THEME_FALLBACK\n }\n}\n" | ||
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| ||
| "debugId": "80138DF5DA39BE6764756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../simulation/src/frontend/actions.ts", "../simulation/src/recording.ts", "../simulation/src/frontend/renderer.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 } from \"effect\"\nimport type { SimulationProtocol } from \"../protocol\"\nimport { SimulationRenderer } from \"./renderer\"\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 return renderer.hitTest(x, y) === renderable.num\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 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 yield* Effect.tryPromise(() => harness.mockMouse.click(action.x, action.y))\n break\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 { 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.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 })\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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| "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 }),\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 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}\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 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 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 ? reasoning.map((part) => part.text).join(\"\")\n : openAICompatibleReasoningContent(message.native?.openaiCompatible),\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 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 if (delta?.reasoning_content)\n lifecycle = Lifecycle.reasoningDelta(lifecycle, events, \"reasoning-0\", delta.reasoning_content)\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 // JSON parse failures fail the stream at the boundary rather than at halt.\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 },\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: () => ({ tools: ToolStream.empty<number>(), toolCallEvents: [], lifecycle: Lifecycle.initial() }),\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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| "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}?${query}` : pathname\n}\n" | ||
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| "debugId": "E60A31140DF5697C64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/commands/handlers/mcp/list.ts"], | ||
| "sourcesContent": [ | ||
| "import { EOL } from \"node:os\"\nimport { Effect } from \"effect\"\nimport { OpenCode, type McpServer } from \"@opencode-ai/client\"\nimport { Commands } from \"../../commands\"\nimport { Runtime } from \"../../../framework/runtime\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { ServiceConfig } from \"../../../services/service-config\"\n\nexport default Runtime.handler(\n Commands.commands.mcp.commands.list,\n Effect.fn(\"cli.mcp.list\")(function* () {\n const options = yield* ServiceConfig.options()\n const found = yield* Service.discover(options)\n const endpoint = found ?? (yield* Service.ensure(options))\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const response = yield* Effect.promise(() => client.mcp.list({ location: { directory: process.cwd() } }))\n const servers = response.data.toSorted((a, b) => a.name.localeCompare(b.name))\n if (servers.length === 0) {\n process.stdout.write(\"No MCP servers configured\" + EOL)\n return\n }\n const width = Math.max(...servers.map((server) => server.name.length))\n const lines = servers.map(\n (server) => `${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": "FC6F397A271217B664756E2164756E21", | ||
| "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": "73810C096C678A7764756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "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": "E09E42E2EB97C92E64756E2164756E21", | ||
| "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 ? yield* ServiceConfig.password()\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) => register(address, password, instanceID, serviceOptions.file, shutdown),\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.max([Schedule.spaced(\"100 millis\"), Schedule.recurs(60)])),\n Effect.option,\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": "B74C79EF7C17BEE564756E2164756E21", | ||
| "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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| "debugId": "10DC247A636E749864756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["../ai/src/providers/openai.ts"], | ||
| "sourcesContent": [ | ||
| "import { AuthOptions, type ProviderAuthOption } from \"../route/auth-options\"\nimport type { Route, 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 type { OpenAIOptionsInput, OpenAIResponseIncludable } from \"./openai-options\"\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 }\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, ...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\n return {\n id,\n model: responses,\n responses,\n responsesWebSocket,\n chat,\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\n" | ||
| ], | ||
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| "debugId": "18753B65C0ABDCCA64756E2164756E21", | ||
| "names": [] | ||
| } |
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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": "44C73C366C68F65D64756E2164756E21", | ||
| "names": [] | ||
| } |
Sorry, the diff of this file is too big to display
| { | ||
| "version": 3, | ||
| "sources": ["src/util/io.ts", "src/mini/mini.ts", "src/mini/run.ts", "src/mini/noninteractive.ts", "src/mini/ui.ts"], | ||
| "sourcesContent": [ | ||
| "import { text } from \"node:stream/consumers\"\n\nexport function readStdin() {\n return text(process.stdin)\n}\n", | ||
| "import { Service } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { waitForCatalogReady } from \"./catalog.shared\"\nimport { INTERACTIVE_INPUT_ERROR, resolveInteractiveStdin } from \"./runtime.stdin\"\nimport type { RunInput, RunTuiConfig } from \"./types\"\nimport { readStdin } from \"../util/io\"\nimport { setTimeout } from \"node:timers/promises\"\n\nexport type MiniCommandInput = {\n server: ServerConnection.Resolved\n continue?: boolean\n session?: string\n fork?: boolean\n model?: string\n agent?: string\n prompt?: string\n replay?: boolean\n replayLimit?: number\n demo?: boolean\n tuiConfig?: RunTuiConfig | Promise<RunTuiConfig>\n}\n\ntype Session = Awaited<ReturnType<OpenCodeClient[\"session\"][\"get\"]>>\nexport async function runMini(input: MiniCommandInput) {\n validate(input)\n const initialInput = mergeInput(process.stdin.isTTY ? undefined : await readStdin(), input.prompt)\n const runtimeTask = import(\"./runtime\")\n const directory = localDirectory()\n\n try {\n const sdk = OpenCode.make({\n baseUrl: input.server.endpoint.url,\n headers: Service.headers(input.server.endpoint),\n })\n const model = parseModel(input.model)\n let agentTask: Promise<string | undefined> | undefined\n const resolveAgent = () => {\n agentTask ??= validateAgent(sdk, directory, input.agent)\n return agentTask\n }\n const resolveSession = async () => {\n const [agent, selected] = await Promise.all([resolveAgent(), selectSession(sdk, directory, input)])\n const readyModel =\n model ?? (selected?.model ? { providerID: selected.model.providerID, modelID: selected.model.id } : undefined)\n if (readyModel) await waitForCatalogReady({ sdk, directory, model: readyModel })\n const session = selected ?? (await createSession(sdk, directory, agent, model))\n return { id: session.id, title: session.title, resume: selected !== undefined }\n }\n const create = (\n _sdk: OpenCodeClient,\n next: { agent: string | undefined; model: RunInput[\"model\"]; variant: string | undefined },\n ) => createSession(sdk, directory, next.agent, next.model, next.variant)\n const runtime = await runtimeTask\n await runtime.runInteractiveDeferredMode({\n sdk,\n directory,\n resolveAgent,\n session: resolveSession,\n createSession: create,\n agent: input.agent,\n model,\n variant: undefined,\n files: [],\n initialInput,\n thinking: true,\n replay: input.replay ?? true,\n replayLimit: input.replayLimit,\n demo: input.demo,\n tuiConfig: input.tuiConfig,\n })\n } catch (error) {\n if (error instanceof Error && error.message === INTERACTIVE_INPUT_ERROR) fail(error.message)\n throw error\n }\n}\n\nexport function validateMiniTerminal() {\n if (!process.stdout.isTTY) fail(\"opencode mini requires a TTY stdout\")\n}\n\n/** @internal Exported for testing. */\nexport function mergeInput(piped: string | undefined, prompt: string | undefined) {\n if (!prompt) return piped || undefined\n if (!piped) return prompt\n return piped + \"\\n\" + prompt\n}\n\nfunction validate(input: MiniCommandInput) {\n validateMiniTerminal()\n if (input.replayLimit !== undefined && (!Number.isInteger(input.replayLimit) || input.replayLimit <= 0)) {\n fail(\"--replay-limit must be a positive integer\")\n }\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n resolveInteractiveStdin().cleanup?.()\n}\n\nfunction localDirectory(): string {\n const root = process.env.PWD ?? process.cwd()\n try {\n process.chdir(root)\n return process.cwd()\n } catch {\n fail(`Failed to change directory to ${root}`)\n }\n}\n\nfunction parseModel(value?: string): RunInput[\"model\"] {\n if (!value) return\n const [providerID, ...rest] = value.split(\"/\")\n const modelID = rest.join(\"/\")\n if (!providerID || !modelID) fail(\"--model must use the format provider/model\")\n return { providerID, modelID }\n}\n\nasync function validateAgent(sdk: OpenCodeClient, directory: string, name?: string) {\n if (!name) return\n const deadline = Date.now() + 5_000\n let agents: Awaited<ReturnType<OpenCodeClient[\"agent\"][\"list\"]>> | undefined\n while (Date.now() < deadline) {\n agents = await sdk.agent.list({ location: { directory } }).catch(() => undefined)\n const agent = agents?.data.find((item) => item.id === name)\n if (agent?.mode === \"subagent\") {\n warning(`agent \"${name}\" is a subagent, not a primary agent. Falling back to default agent`)\n return\n }\n if (agent) return name\n await setTimeout(25)\n }\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n warning(`agent \"${name}\" not found. Falling back to default agent`)\n}\n\nasync function selectSession(sdk: OpenCodeClient, directory: string, input: MiniCommandInput, preselected?: Session) {\n const selected =\n preselected ??\n (input.session\n ? await sdk.session.get({ sessionID: input.session }).catch(() => undefined)\n : input.continue\n ? await sdk.session\n .list({ directory, parentID: null, limit: 1, order: \"desc\" })\n .then((result) => result.data[0])\n : undefined)\n if (input.session && !selected) fail(\"Session not found\")\n if (!selected) return\n if (!input.fork) return selected\n return sdk.session.fork({ sessionID: selected.id })\n}\n\nasync function createSession(\n sdk: OpenCodeClient,\n directory: string,\n agent: string | undefined,\n model: RunInput[\"model\"],\n variant?: string,\n): Promise<Session> {\n if (model) await waitForCatalogReady({ sdk, directory, model })\n return sdk.session.create({\n agent,\n model: model ? { providerID: model.providerID, id: model.modelID, variant } : undefined,\n location: { directory },\n })\n}\n\nfunction warning(message: string) {\n process.stderr.write(`\\x1b[93m\\x1b[1m!\\x1b[0m ${message}\\n`)\n}\n\nfunction fail(message: string): never {\n process.stderr.write(`\\x1b[91m\\x1b[1mError: \\x1b[0m${message}\\n`)\n process.exit(1)\n}\n", | ||
| "import { Service, type Endpoint } from \"@opencode-ai/client/effect/service\"\nimport { OpenCode, type OpenCodeClient } from \"@opencode-ai/client/promise\"\nimport { FSUtil } from \"@opencode-ai/core/fs-util\"\nimport { Model } from \"@opencode-ai/schema/model\"\nimport { open } from \"node:fs/promises\"\nimport path from \"node:path\"\nimport { readStdin } from \"../util/io\"\nimport { ServerConnection } from \"../services/server-connection\"\nimport { loadRunAgents, waitForCatalogReady } from \"./catalog.shared\"\nimport { runNonInteractivePrompt } from \"./noninteractive\"\nimport { toolInlineInfo } from \"./tool\"\nimport type { MiniToolPart } from \"./types\"\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\nconst ATTACH_FILE_MAX_BYTES = 10 * 1024 * 1024\n\nexport function runNonInteractive(input: RunCommandInput) {\n return run(input).catch((error) => reportError(input, error instanceof Error ? error.message : String(error)))\n}\n\nasync function run(input: RunCommandInput) {\n if (input.fork && !input.continue && !input.session) fail(\"--fork requires --continue or --session\")\n const root = process.env.PWD ?? process.cwd()\n const directory = localDirectory(root)\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)))\n const prepared = { directory, message, files }\n return execute(input, prepared, input.server.endpoint)\n}\n\nasync function execute(input: RunCommandInput, prepared: Prepared, endpoint: Endpoint) {\n const client = OpenCode.make({ baseUrl: endpoint.url, headers: Service.headers(endpoint) })\n const requestedDirectory = prepared.directory ?? (await client.location.get()).directory\n if (!requestedDirectory) fail(\"Failed to resolve server directory\")\n const session = await selectSession(client, requestedDirectory, input)\n const cwd = session?.location.directory ?? requestedDirectory\n const workspace = session?.location.workspaceID\n const explicit = parseRunModel(input.model)\n const explicitModel = explicit?.model\n const variant = explicit?.variant\n const sessionModel = session?.model ? { providerID: session.model.providerID, modelID: session.model.id } : undefined\n const defaultModel =\n !explicitModel && !sessionModel\n ? await client.model\n .default({ location: { directory: cwd, workspace } })\n .then((result) => (result.data ? { providerID: result.data.providerID, modelID: result.data.id } : undefined))\n : undefined\n const model = pickRunModel(explicitModel, variant, sessionModel, defaultModel)\n if (variant && !model) return reportError(input, \"Cannot select a variant before selecting a model\", session?.id)\n if (model) {\n await waitForCatalogReady({ sdk: client, directory: cwd, workspace, model })\n const available = await client.model.list({ location: { directory: cwd, workspace } })\n if (!available.data.some((item) => item.providerID === model.providerID && item.id === model.modelID))\n return reportError(input, `Model unavailable: ${model.providerID}/${model.modelID}`, session?.id)\n }\n const agent = await validateAgent(client, cwd, input.agent)\n const selected =\n session ??\n (await client.session.create({\n agent,\n model: model ? { providerID: model.providerID, id: model.modelID, variant } : undefined,\n location: { directory: cwd },\n }))\n if (!session && input.title !== undefined) {\n await client.session.rename({\n sessionID: selected.id,\n title: input.title || prepared.message.slice(0, 50) + (prepared.message.length > 50 ? \"...\" : \"\"),\n })\n }\n\n await runNonInteractivePrompt({\n client,\n sessionID: selected.id,\n message: prepared.message,\n files: prepared.files,\n agent,\n model,\n variant,\n thinking: input.thinking ?? false,\n format: input.format,\n auto: input.auto ?? false,\n attached: true,\n renderTool,\n renderToolError,\n }).catch((error) => reportError(input, error instanceof Error ? error.message : String(error), selected.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\nexport function pickRunModel(\n explicit: { providerID: string; modelID: string } | undefined,\n variant: string | undefined,\n session: { providerID: string; modelID: string } | undefined,\n fallback: { providerID: string; modelID: string } | undefined,\n) {\n if (explicit) return explicit\n if (!variant) return\n return session ?? fallback\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 ${root}`)\n }\n}\n\nexport function parseRunModel(value?: string) {\n if (!value) return\n const ref = Model.Ref.parse(value)\n return {\n model: { providerID: ref.providerID, modelID: ref.id },\n variant: ref.variant,\n }\n}\n\nasync function validateAgent(client: OpenCodeClient, directory: string, name?: string) {\n if (!name) return\n const agents = await loadRunAgents(client, directory).catch(() => undefined)\n if (!agents) {\n warning(\"failed to list agents. Falling back to default agent\")\n return\n }\n const agent = agents.find((item) => item.id === name)\n if (!agent) {\n warning(`agent \"${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 selectSession(client: OpenCodeClient, directory: string, input: RunCommandInput) {\n const selected = input.session\n ? await client.session.get({ sessionID: input.session }).catch(() => undefined)\n : input.continue\n ? await client.session\n .list({ directory, parentID: null, limit: 1, order: \"desc\" })\n .then((result) => result.data[0])\n : undefined\n if (input.session && !selected) fail(\"Session not found\")\n if (!selected || !input.fork) return selected\n return client.session.fork({ sessionID: selected.id })\n}\n\nasync function prepareFile(input: string, directory: string): 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 (!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,${bytes.toString(\"base64\")}`,\n filename: path.basename(file),\n mime,\n }\n } finally {\n await handle.close()\n }\n}\n\nfunction isBinaryContent(bytes: Uint8Array) {\n if (bytes.length === 0) return false\n if (bytes.includes(0)) return true\n return bytes.reduce((count, byte) => count + Number(byte < 9 || (byte > 13 && byte < 32)), 0) / bytes.length > 0.3\n}\n\nasync function renderTool(part: MiniToolPart) {\n const info = toolInlineInfo(part)\n if (info.mode === \"block\") {\n UI.empty()\n UI.println(UI.Style.TEXT_NORMAL + info.icon, UI.Style.TEXT_NORMAL + info.title)\n if (info.body?.trim()) UI.println(info.body)\n UI.empty()\n return\n }\n UI.println(\n UI.Style.TEXT_NORMAL + info.icon,\n UI.Style.TEXT_NORMAL + info.title,\n info.description ? UI.Style.TEXT_DIM + info.description + UI.Style.TEXT_NORMAL : \"\",\n )\n}\n\nasync function renderToolError(part: MiniToolPart) {\n const info = toolInlineInfo(part)\n UI.println(UI.Style.TEXT_NORMAL + \"✗\", UI.Style.TEXT_NORMAL + `${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 reportError(input: RunCommandInput, 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 { EventSubscribeOutput, OpenCodeClient } 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 { UI } from \"./ui\"\nimport type { MiniToolPart } from \"./types\"\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 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 renderTool: (part: MiniToolPart) => Promise<void>\n renderToolError: (part: MiniToolPart) => 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, unknown>\n raw?: string\n provider?: unknown\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 questionRejected = false\n let permissionRejected = false\n let formCancelled = false\n let interrupted = false\n let admission: AbortController | 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 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 rejectQuestion = async (request: { id: string }) => {\n questionRejected = true\n await input.client.question.reject({ sessionID: input.sessionID, requestID: request.id }).catch(() => {})\n }\n\n const cancelForm = async (request: Pick<FormRequest, \"id\" | \"sessionID\">) => {\n formCancelled = true\n await input.client.form.cancel({ sessionID: request.sessionID, formID: request.id }).catch(() => {})\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 (event.type === \"question.v2.asked\" && submitted && event.data.sessionID === input.sessionID) {\n await rejectQuestion(event.data)\n continue\n }\n if (\n event.type === \"form.created\" &&\n submitted &&\n (event.data.form.sessionID === input.sessionID ||\n (!input.attached && event.data.form.sessionID === GLOBAL_FORM_SESSION_ID))\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 || questionRejected || 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 (!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 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 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 tools.set(event.data.callID, {\n id: partID(event.id),\n timestamp: time,\n assistantMessageID: event.data.assistantMessageID,\n tool: event.data.name,\n input: {},\n })\n continue\n }\n if (event.type === \"session.tool.input.ended\") {\n const current = tools.get(event.data.callID)\n if (current) current.raw = event.data.text\n continue\n }\n if (event.type === \"session.tool.called\") {\n const current = tools.get(event.data.callID)\n tools.set(event.data.callID, {\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 })\n continue\n }\n if (event.type === \"session.tool.success\") {\n const current = tools.get(event.data.callID) ?? fallbackTool(event)\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: event.data.content\n .filter((item) => item.type === \"text\")\n .map((item) => item.text)\n .join(\"\\n\"),\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(event.data.callID)\n if (!emit(\"tool_use\", time, { part })) await input.renderTool(part)\n continue\n }\n if (event.type === \"session.tool.failed\") {\n const current = tools.get(event.data.callID) ?? fallbackTool(event)\n const error = event.data.error.message\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(event.data.callID)\n if (!emit(\"tool_use\", time, { part })) {\n await input.renderToolError(part)\n UI.error(error)\n }\n continue\n }\n\n if (event.type === \"session.step.ended\") {\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 (interrupted || permissionRejected || questionRejected || formCancelled) continue\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 (!emittedError && !questionRejected && !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 (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, questions, forms] = await Promise.all([\n input.client.permission.list({ sessionID: input.sessionID }).catch(() => undefined),\n input.client.question.list({ sessionID: input.sessionID }).catch(() => undefined),\n Promise.all(\n (input.attached ? [input.sessionID] : [input.sessionID, GLOBAL_FORM_SESSION_ID]).map((sessionID) =>\n input.client.form.list({ sessionID }).catch(() => undefined),\n ),\n ),\n ])\n await Promise.all([\n ...(permissions ?? []).map(replyPermission),\n ...(questions ?? []).map(rejectQuestion),\n ...forms.flatMap((response) => response ?? []).map(cancelForm),\n ])\n await completed\n } finally {\n process.off(\"SIGINT\", interrupt)\n controller.abort()\n await stream.return?.(undefined).catch(() => {})\n }\n}\n\nfunction partID(eventID: string) {\n return `prt_${eventID.replace(/^evt_/, \"\")}`\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 }\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, mime: file.mime, 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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| ||
| "debugId": "05C71445390B310E64756E2164756E21", | ||
| "names": [] | ||
| } |
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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}${EOL}`,\n )\n }),\n)\n" | ||
| ], | ||
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| "debugId": "87E9EE8B3B69F0AA64756E2164756E21", | ||
| "names": [] | ||
| } |
| { | ||
| "version": 3, | ||
| "sources": ["src/services/service-config.ts", "src/util/process.ts"], | ||
| "sourcesContent": [ | ||
| "import { Global } from \"@opencode-ai/core/global\"\nimport { InstallationChannel, InstallationVersion } from \"@opencode-ai/core/installation/version\"\nimport { Hash } from \"@opencode-ai/core/util/hash\"\nimport { Service } from \"@opencode-ai/client/effect/service\"\nimport { Effect, FileSystem, Option, Schema } from \"effect\"\nimport { randomBytes } from \"crypto\"\nimport path from \"path\"\nimport { selfCommand } from \"../util/process\"\n\n// The CLI's service configuration file, plus the Service.EnsureOptions binding that\n// points the client package's service operations at this CLI: which\n// registration file (by channel), which version, and how to spawn opencode.\n\nexport const Info = Schema.Struct({\n hostname: Schema.optional(Schema.String),\n port: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1), Schema.isLessThanOrEqualTo(65_535))),\n password: Schema.optional(Schema.String),\n})\nexport type Info = typeof Info.Type\n\nconst keys = [\"hostname\", \"port\", \"password\"] as const\ntype Key = (typeof keys)[number]\n\nconst decodeInfo = Schema.decodeUnknownEffect(Schema.fromJsonString(Info))\nconst decodeRegistration = Schema.decodeUnknownEffect(Schema.fromJsonString(Service.Info))\n\nexport function filename(channel = InstallationChannel) {\n if (channel === \"latest\") return \"service.json\"\n if (channel === \"local\") return \"service-local.json\"\n return `service-${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": "896BBDE1B75FD21364756E2164756E21", | ||
| "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": "58C4FFFF967DE5CF64756E2164756E21", | ||
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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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