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@ai-sdk/groq
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@ai-sdk/groq - npm Package Compare versions
+6
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| # @ai-sdk/groq | ||
| ## 2.0.47 | ||
| ### Patch Changes | ||
| - 3fbb9cc: Support plain-text responses from Groq transcription models when `responseFormat` is set to `text`. | ||
| ## 2.0.46 | ||
@@ -4,0 +10,0 @@ |
+16
-5
@@ -809,2 +809,3 @@ "use strict"; | ||
| formData, | ||
| responseFormat: groqOptions == null ? void 0 : groqOptions.responseFormat, | ||
| warnings | ||
@@ -816,3 +817,4 @@ }; | ||
| const currentDate = (_c = (_b = (_a = this.config._internal) == null ? void 0 : _a.currentDate) == null ? void 0 : _b.call(_a)) != null ? _c : /* @__PURE__ */ new Date(); | ||
| const { formData, warnings } = await this.getArgs(options); | ||
| const { formData, responseFormat, warnings } = await this.getArgs(options); | ||
| const successfulResponseHandler = responseFormat === "text" ? groqTextTranscriptionResponseHandler : (0, import_provider_utils4.createJsonResponseHandler)(groqTranscriptionResponseSchema); | ||
| const { | ||
@@ -830,5 +832,3 @@ value: response, | ||
| failedResponseHandler: groqFailedResponseHandler, | ||
| successfulResponseHandler: (0, import_provider_utils4.createJsonResponseHandler)( | ||
| groqTranscriptionResponseSchema | ||
| ), | ||
| successfulResponseHandler, | ||
| abortSignal: options.abortSignal, | ||
@@ -880,2 +880,13 @@ fetch: this.config.fetch | ||
| }); | ||
| var binaryResponseHandler = (0, import_provider_utils4.createBinaryResponseHandler)(); | ||
| var textDecoder = new TextDecoder(); | ||
| var groqTextTranscriptionResponseHandler = async (options) => { | ||
| const { value, responseHeaders } = await binaryResponseHandler(options); | ||
| const text = textDecoder.decode(value); | ||
| return { | ||
| value: { text }, | ||
| rawValue: text, | ||
| responseHeaders | ||
| }; | ||
| }; | ||
@@ -897,3 +908,3 @@ // src/tool/browser-search.ts | ||
| // src/version.ts | ||
| var VERSION = true ? "2.0.46" : "0.0.0-test"; | ||
| var VERSION = true ? "2.0.47" : "0.0.0-test"; | ||
@@ -900,0 +911,0 @@ // src/groq-provider.ts |
@@ -1,1 +0,1 @@ | ||
| {"version":3,"sources":["../src/index.ts","../src/groq-provider.ts","../src/groq-chat-language-model.ts","../src/convert-to-groq-chat-messages.ts","../src/get-response-metadata.ts","../src/groq-chat-options.ts","../src/groq-error.ts","../src/groq-prepare-tools.ts","../src/groq-browser-search-models.ts","../src/map-groq-finish-reason.ts","../src/groq-transcription-model.ts","../src/tool/browser-search.ts","../src/groq-tools.ts","../src/version.ts"],"sourcesContent":["export { createGroq, groq } from './groq-provider';\nexport type { GroqProvider, GroqProviderSettings } from './groq-provider';\nexport type { GroqProviderOptions } from './groq-chat-options';\nexport { browserSearch } from './tool/browser-search';\nexport { VERSION } from './version';\n","import {\n type LanguageModelV2,\n type ProviderV2,\n type TranscriptionModelV2,\n NoSuchModelError,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n loadApiKey,\n withoutTrailingSlash,\n withUserAgentSuffix,\n} from '@ai-sdk/provider-utils';\nimport { GroqChatLanguageModel } from './groq-chat-language-model';\nimport type { GroqChatModelId } from './groq-chat-options';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport { GroqTranscriptionModel } from './groq-transcription-model';\n\nimport { groqTools } from './groq-tools';\nimport { VERSION } from './version';\nexport interface GroqProvider extends ProviderV2 {\n /**\nCreates a model for text generation.\n*/\n (modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates an Groq chat model for text generation.\n */\n languageModel(modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates a model for transcription.\n */\n transcription(modelId: GroqTranscriptionModelId): TranscriptionModelV2;\n\n /**\n * Tools provided by Groq.\n */\n tools: typeof groqTools;\n}\n\nexport interface GroqProviderSettings {\n /**\nBase URL for the Groq API calls.\n */\n baseURL?: string;\n\n /**\nAPI key for authenticating requests.\n */\n apiKey?: string;\n\n /**\nCustom headers to include in the requests.\n */\n headers?: Record<string, string>;\n\n /**\nCustom fetch implementation. You can use it as a middleware to intercept requests,\nor to provide a custom fetch implementation for e.g. testing.\n */\n fetch?: FetchFunction;\n}\n\n/**\nCreate an Groq provider instance.\n */\nexport function createGroq(options: GroqProviderSettings = {}): GroqProvider {\n const baseURL =\n withoutTrailingSlash(options.baseURL) ?? 'https://api.groq.com/openai/v1';\n\n const getHeaders = () =>\n withUserAgentSuffix(\n {\n Authorization: `Bearer ${loadApiKey({\n apiKey: options.apiKey,\n environmentVariableName: 'GROQ_API_KEY',\n description: 'Groq',\n })}`,\n ...options.headers,\n },\n `ai-sdk/groq/${VERSION}`,\n );\n\n const createChatModel = (modelId: GroqChatModelId) =>\n new GroqChatLanguageModel(modelId, {\n provider: 'groq.chat',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n\n const createLanguageModel = (modelId: GroqChatModelId) => {\n if (new.target) {\n throw new Error(\n 'The Groq model function cannot be called with the new keyword.',\n );\n }\n\n return createChatModel(modelId);\n };\n\n const createTranscriptionModel = (modelId: GroqTranscriptionModelId) => {\n return new GroqTranscriptionModel(modelId, {\n provider: 'groq.transcription',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n };\n\n const provider = function (modelId: GroqChatModelId) {\n return createLanguageModel(modelId);\n };\n\n provider.languageModel = createLanguageModel;\n provider.chat = createChatModel;\n\n provider.textEmbeddingModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'textEmbeddingModel' });\n };\n provider.imageModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'imageModel' });\n };\n provider.transcription = createTranscriptionModel;\n provider.transcriptionModel = createTranscriptionModel;\n\n provider.tools = groqTools;\n\n return provider;\n}\n\n/**\nDefault Groq provider instance.\n */\nexport const groq = createGroq();\n","import {\n type LanguageModelV2,\n type LanguageModelV2CallWarning,\n type LanguageModelV2Content,\n type LanguageModelV2FinishReason,\n type LanguageModelV2StreamPart,\n type LanguageModelV2Usage,\n type SharedV2ProviderMetadata,\n InvalidResponseDataError,\n LanguageModelV2Prompt,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n type ParseResult,\n combineHeaders,\n createEventSourceResponseHandler,\n createJsonResponseHandler,\n generateId,\n isParsableJson,\n parseProviderOptions,\n postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { convertToGroqChatMessages } from './convert-to-groq-chat-messages';\nimport { getResponseMetadata } from './get-response-metadata';\nimport { type GroqChatModelId, groqProviderOptions } from './groq-chat-options';\nimport { groqErrorDataSchema, groqFailedResponseHandler } from './groq-error';\nimport { prepareTools } from './groq-prepare-tools';\nimport { mapGroqFinishReason } from './map-groq-finish-reason';\n\ntype GroqChatConfig = {\n provider: string;\n headers: () => Record<string, string | undefined>;\n url: (options: { modelId: string; path: string }) => string;\n fetch?: FetchFunction;\n};\n\nexport class GroqChatLanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2';\n\n readonly modelId: GroqChatModelId;\n\n readonly supportedUrls = {\n 'image/*': [/^https?:\\/\\/.*$/],\n };\n\n private readonly config: GroqChatConfig;\n\n constructor(modelId: GroqChatModelId, config: GroqChatConfig) {\n this.modelId = modelId;\n this.config = config;\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n private async getArgs({\n prompt,\n maxOutputTokens,\n temperature,\n topP,\n topK,\n frequencyPenalty,\n presencePenalty,\n stopSequences,\n responseFormat,\n seed,\n stream,\n tools,\n toolChoice,\n providerOptions,\n }: Parameters<LanguageModelV2['doGenerate']>[0] & {\n stream: boolean;\n }) {\n const warnings: LanguageModelV2CallWarning[] = [];\n\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptions,\n });\n\n const structuredOutputs = groqOptions?.structuredOutputs ?? true;\n\n if (topK != null) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'topK',\n });\n }\n\n if (\n responseFormat?.type === 'json' &&\n responseFormat.schema != null &&\n !structuredOutputs\n ) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'responseFormat',\n details:\n 'JSON response format schema is only supported with structuredOutputs',\n });\n }\n\n const {\n tools: groqTools,\n toolChoice: groqToolChoice,\n toolWarnings,\n } = prepareTools({ tools, toolChoice, modelId: this.modelId });\n\n return {\n args: {\n // model id:\n model: this.modelId,\n\n // model specific settings:\n user: groqOptions?.user,\n parallel_tool_calls: groqOptions?.parallelToolCalls,\n\n // standardized settings:\n max_tokens: maxOutputTokens,\n temperature,\n top_p: topP,\n frequency_penalty: frequencyPenalty,\n presence_penalty: presencePenalty,\n stop: stopSequences,\n seed,\n\n // response format:\n response_format:\n responseFormat?.type === 'json'\n ? structuredOutputs && responseFormat.schema != null\n ? {\n type: 'json_schema',\n json_schema: {\n schema: responseFormat.schema,\n name: responseFormat.name ?? 'response',\n description: responseFormat.description,\n },\n }\n : { type: 'json_object' }\n : undefined,\n\n // provider options:\n reasoning_format: groqOptions?.reasoningFormat,\n reasoning_effort: groqOptions?.reasoningEffort,\n service_tier: groqOptions?.serviceTier,\n\n // messages:\n messages: convertToGroqChatMessages(prompt),\n\n // tools:\n tools: groqTools,\n tool_choice: groqToolChoice,\n },\n warnings: [...warnings, ...toolWarnings],\n };\n }\n\n async doGenerate(\n options: Parameters<LanguageModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {\n const { args, warnings } = await this.getArgs({\n ...options,\n stream: false,\n });\n\n const body = JSON.stringify(args);\n\n const {\n responseHeaders,\n value: response,\n rawValue: rawResponse,\n } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: args,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqChatResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const choice = response.choices[0];\n const content: Array<LanguageModelV2Content> = [];\n\n // text content:\n const text = choice.message.content;\n if (text != null && text.length > 0) {\n content.push({ type: 'text', text: text });\n }\n\n // reasoning:\n const reasoning = choice.message.reasoning;\n if (reasoning != null && reasoning.length > 0) {\n content.push({\n type: 'reasoning',\n text: reasoning,\n });\n }\n\n // tool calls:\n if (choice.message.tool_calls != null) {\n for (const toolCall of choice.message.tool_calls) {\n content.push({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments!,\n });\n }\n }\n\n return {\n content,\n finishReason: mapGroqFinishReason(choice.finish_reason),\n usage: {\n inputTokens: response.usage?.prompt_tokens ?? undefined,\n outputTokens: response.usage?.completion_tokens ?? undefined,\n totalTokens: response.usage?.total_tokens ?? undefined,\n cachedInputTokens:\n response.usage?.prompt_tokens_details?.cached_tokens ?? undefined,\n },\n response: {\n ...getResponseMetadata(response),\n headers: responseHeaders,\n body: rawResponse,\n },\n warnings,\n request: { body },\n };\n }\n\n async doStream(\n options: Parameters<LanguageModelV2['doStream']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {\n const { args, warnings } = await this.getArgs({ ...options, stream: true });\n\n const body = JSON.stringify({ ...args, stream: true });\n\n const { responseHeaders, value: response } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: {\n ...args,\n stream: true,\n },\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler:\n createEventSourceResponseHandler(groqChatChunkSchema),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: {\n name: string;\n arguments: string;\n };\n hasFinished: boolean;\n }> = [];\n\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n const usage: LanguageModelV2Usage = {\n inputTokens: undefined,\n outputTokens: undefined,\n totalTokens: undefined,\n cachedInputTokens: undefined,\n };\n let isFirstChunk = true;\n let isActiveText = false;\n let isActiveReasoning = false;\n\n let providerMetadata: SharedV2ProviderMetadata | undefined;\n return {\n stream: response.pipeThrough(\n new TransformStream<\n ParseResult<z.infer<typeof groqChatChunkSchema>>,\n LanguageModelV2StreamPart\n >({\n start(controller) {\n controller.enqueue({ type: 'stream-start', warnings });\n },\n\n transform(chunk, controller) {\n // Emit raw chunk if requested (before anything else)\n if (options.includeRawChunks) {\n controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });\n }\n\n // handle failed chunk parsing / validation:\n if (!chunk.success) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: chunk.error });\n return;\n }\n\n const value = chunk.value;\n\n // handle error chunks:\n if ('error' in value) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: value.error });\n return;\n }\n\n if (isFirstChunk) {\n isFirstChunk = false;\n\n controller.enqueue({\n type: 'response-metadata',\n ...getResponseMetadata(value),\n });\n }\n\n if (value.x_groq?.usage != null) {\n usage.inputTokens = value.x_groq.usage.prompt_tokens ?? undefined;\n usage.outputTokens =\n value.x_groq.usage.completion_tokens ?? undefined;\n usage.totalTokens = value.x_groq.usage.total_tokens ?? undefined;\n usage.cachedInputTokens =\n value.x_groq.usage.prompt_tokens_details?.cached_tokens ??\n undefined;\n }\n\n const choice = value.choices[0];\n\n if (choice?.finish_reason != null) {\n finishReason = mapGroqFinishReason(choice.finish_reason);\n }\n\n if (choice?.delta == null) {\n return;\n }\n\n const delta = choice.delta;\n\n if (delta.reasoning != null && delta.reasoning.length > 0) {\n if (!isActiveReasoning) {\n controller.enqueue({\n type: 'reasoning-start',\n id: 'reasoning-0',\n });\n isActiveReasoning = true;\n }\n\n controller.enqueue({\n type: 'reasoning-delta',\n id: 'reasoning-0',\n delta: delta.reasoning,\n });\n }\n\n if (delta.content != null && delta.content.length > 0) {\n if (!isActiveText) {\n controller.enqueue({ type: 'text-start', id: 'txt-0' });\n isActiveText = true;\n }\n\n controller.enqueue({\n type: 'text-delta',\n id: 'txt-0',\n delta: delta.content,\n });\n }\n\n if (delta.tool_calls != null) {\n for (const toolCallDelta of delta.tool_calls) {\n const index = toolCallDelta.index;\n\n if (toolCalls[index] == null) {\n if (toolCallDelta.type !== 'function') {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function' type.`,\n });\n }\n\n if (toolCallDelta.id == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'id' to be a string.`,\n });\n }\n\n if (toolCallDelta.function?.name == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function.name' to be a string.`,\n });\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: toolCallDelta.id,\n toolName: toolCallDelta.function.name,\n });\n\n toolCalls[index] = {\n id: toolCallDelta.id,\n type: 'function',\n function: {\n name: toolCallDelta.function.name,\n arguments: toolCallDelta.function.arguments ?? '',\n },\n hasFinished: false,\n };\n\n const toolCall = toolCalls[index];\n\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null\n ) {\n // send delta if the argument text has already started:\n if (toolCall.function.arguments.length > 0) {\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCall.function.arguments,\n });\n }\n\n // check if tool call is complete\n // (some providers send the full tool call in one chunk):\n if (isParsableJson(toolCall.function.arguments)) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n\n continue;\n }\n\n // existing tool call, merge if not finished\n const toolCall = toolCalls[index];\n\n if (toolCall.hasFinished) {\n continue;\n }\n\n if (toolCallDelta.function?.arguments != null) {\n toolCall.function!.arguments +=\n toolCallDelta.function?.arguments ?? '';\n }\n\n // send delta\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCallDelta.function.arguments ?? '',\n });\n\n // check if tool call is complete\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null &&\n isParsableJson(toolCall.function.arguments)\n ) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n }\n },\n\n flush(controller) {\n if (isActiveReasoning) {\n controller.enqueue({ type: 'reasoning-end', id: 'reasoning-0' });\n }\n\n if (isActiveText) {\n controller.enqueue({ type: 'text-end', id: 'txt-0' });\n }\n\n controller.enqueue({\n type: 'finish',\n finishReason,\n usage,\n ...(providerMetadata != null ? { providerMetadata } : {}),\n });\n },\n }),\n ),\n request: { body },\n response: { headers: responseHeaders },\n };\n }\n}\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatResponseSchema = z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n message: z.object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n id: z.string().nullish(),\n type: z.literal('function'),\n function: z.object({\n name: z.string(),\n arguments: z.string(),\n }),\n }),\n )\n .nullish(),\n }),\n index: z.number(),\n finish_reason: z.string().nullish(),\n }),\n ),\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n});\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatChunkSchema = z.union([\n z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n delta: z\n .object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n index: z.number(),\n id: z.string().nullish(),\n type: z.literal('function').optional(),\n function: z.object({\n name: z.string().nullish(),\n arguments: z.string().nullish(),\n }),\n }),\n )\n .nullish(),\n })\n .nullish(),\n finish_reason: z.string().nullable().optional(),\n index: z.number(),\n }),\n ),\n x_groq: z\n .object({\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n })\n .nullish(),\n }),\n groqErrorDataSchema,\n]);\n","import {\n type LanguageModelV2Prompt,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport type { GroqChatPrompt } from './groq-api-types';\nimport { convertToBase64 } from '@ai-sdk/provider-utils';\n\nexport function convertToGroqChatMessages(\n prompt: LanguageModelV2Prompt,\n): GroqChatPrompt {\n const messages: GroqChatPrompt = [];\n\n for (const { role, content } of prompt) {\n switch (role) {\n case 'system': {\n messages.push({ role: 'system', content });\n break;\n }\n\n case 'user': {\n if (content.length === 1 && content[0].type === 'text') {\n messages.push({ role: 'user', content: content[0].text });\n break;\n }\n\n messages.push({\n role: 'user',\n content: content.map(part => {\n switch (part.type) {\n case 'text': {\n return { type: 'text', text: part.text };\n }\n case 'file': {\n if (!part.mediaType.startsWith('image/')) {\n throw new UnsupportedFunctionalityError({\n functionality: 'Non-image file content parts',\n });\n }\n\n const mediaType =\n part.mediaType === 'image/*' ? 'image/jpeg' : part.mediaType;\n\n return {\n type: 'image_url',\n image_url: {\n url:\n part.data instanceof URL\n ? part.data.toString()\n : `data:${mediaType};base64,${convertToBase64(part.data)}`,\n },\n };\n }\n }\n }),\n });\n\n break;\n }\n\n case 'assistant': {\n let text = '';\n let reasoning = '';\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: { name: string; arguments: string };\n }> = [];\n\n for (const part of content) {\n switch (part.type) {\n // groq supports reasoning for tool-calls in multi-turn conversations\n // https://github.com/vercel/ai/issues/7860\n case 'reasoning': {\n reasoning += part.text;\n break;\n }\n\n case 'text': {\n text += part.text;\n break;\n }\n\n case 'tool-call': {\n toolCalls.push({\n id: part.toolCallId,\n type: 'function',\n function: {\n name: part.toolName,\n arguments: JSON.stringify(part.input),\n },\n });\n break;\n }\n }\n }\n\n messages.push({\n role: 'assistant',\n content: text,\n ...(reasoning.length > 0 ? { reasoning } : null),\n ...(toolCalls.length > 0 ? { tool_calls: toolCalls } : null),\n });\n\n break;\n }\n\n case 'tool': {\n for (const toolResponse of content) {\n const output = toolResponse.output;\n\n let contentValue: string;\n switch (output.type) {\n case 'text':\n case 'error-text':\n contentValue = output.value;\n break;\n case 'content':\n case 'json':\n case 'error-json':\n contentValue = JSON.stringify(output.value);\n break;\n }\n\n messages.push({\n role: 'tool',\n tool_call_id: toolResponse.toolCallId,\n content: contentValue,\n });\n }\n break;\n }\n\n default: {\n const _exhaustiveCheck: never = role;\n throw new Error(`Unsupported role: ${_exhaustiveCheck}`);\n }\n }\n }\n\n return messages;\n}\n","export function getResponseMetadata({\n id,\n model,\n created,\n}: {\n id?: string | undefined | null;\n created?: number | undefined | null;\n model?: string | undefined | null;\n}) {\n return {\n id: id ?? undefined,\n modelId: model ?? undefined,\n timestamp: created != null ? new Date(created * 1000) : undefined,\n };\n}\n","import { z } from 'zod/v4';\n\n// https://console.groq.com/docs/models\nexport type GroqChatModelId =\n // production models\n | 'gemma2-9b-it'\n | 'llama-3.1-8b-instant'\n | 'llama-3.3-70b-versatile'\n | 'meta-llama/llama-guard-4-12b'\n | 'openai/gpt-oss-120b'\n | 'openai/gpt-oss-20b'\n // preview models (selection)\n | 'deepseek-r1-distill-llama-70b'\n | 'meta-llama/llama-4-maverick-17b-128e-instruct'\n | 'meta-llama/llama-4-scout-17b-16e-instruct'\n | 'meta-llama/llama-prompt-guard-2-22m'\n | 'meta-llama/llama-prompt-guard-2-86m'\n | 'moonshotai/kimi-k2-instruct-0905'\n | 'qwen/qwen3-32b'\n | 'llama-guard-3-8b'\n | 'llama3-70b-8192'\n | 'llama3-8b-8192'\n | 'mixtral-8x7b-32768'\n | 'qwen-qwq-32b'\n | 'qwen-2.5-32b'\n | 'deepseek-r1-distill-qwen-32b'\n | (string & {});\n\nexport const groqProviderOptions = z.object({\n reasoningFormat: z.enum(['parsed', 'raw', 'hidden']).optional(),\n\n /**\n * Specifies the reasoning effort level for model inference.\n * @see https://console.groq.com/docs/reasoning#reasoning-effort\n */\n reasoningEffort: z\n .enum(['none', 'default', 'low', 'medium', 'high'])\n .optional(),\n\n /**\n * Whether to enable parallel function calling during tool use. Default to true.\n */\n parallelToolCalls: z.boolean().optional(),\n\n /**\n * A unique identifier representing your end-user, which can help OpenAI to\n * monitor and detect abuse. Learn more.\n */\n user: z.string().optional(),\n\n /**\n * Whether to use structured outputs.\n *\n * @default true\n */\n structuredOutputs: z.boolean().optional(),\n\n /**\n * Service tier for the request.\n * - 'on_demand': Default tier with consistent performance and fairness\n * - 'flex': Higher throughput tier optimized for workloads that can handle occasional request failures\n * - 'auto': Uses on_demand rate limits, then falls back to flex tier if exceeded\n *\n * @default 'on_demand'\n */\n serviceTier: z.enum(['on_demand', 'flex', 'auto']).optional(),\n});\n\nexport type GroqProviderOptions = z.infer<typeof groqProviderOptions>;\n","import { z } from 'zod/v4';\nimport { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\n\nexport const groqErrorDataSchema = z.object({\n error: z.object({\n message: z.string(),\n type: z.string(),\n }),\n});\n\nexport type GroqErrorData = z.infer<typeof groqErrorDataSchema>;\n\nexport const groqFailedResponseHandler = createJsonErrorResponseHandler({\n errorSchema: groqErrorDataSchema,\n errorToMessage: data => data.error.message,\n});\n","import {\n type LanguageModelV2CallOptions,\n type LanguageModelV2CallWarning,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport {\n getSupportedModelsString,\n isBrowserSearchSupportedModel,\n} from './groq-browser-search-models';\nimport type { GroqChatModelId } from './groq-chat-options';\n\nexport function prepareTools({\n tools,\n toolChoice,\n modelId,\n}: {\n tools: LanguageModelV2CallOptions['tools'];\n toolChoice?: LanguageModelV2CallOptions['toolChoice'];\n modelId: GroqChatModelId;\n}): {\n tools:\n | undefined\n | Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n >;\n toolChoice:\n | { type: 'function'; function: { name: string } }\n | 'auto'\n | 'none'\n | 'required'\n | undefined;\n toolWarnings: LanguageModelV2CallWarning[];\n} {\n // when the tools array is empty, change it to undefined to prevent errors:\n tools = tools?.length ? tools : undefined;\n\n const toolWarnings: LanguageModelV2CallWarning[] = [];\n\n if (tools == null) {\n return { tools: undefined, toolChoice: undefined, toolWarnings };\n }\n\n const groqTools: Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n > = [];\n\n for (const tool of tools) {\n if (tool.type === 'provider-defined') {\n if (tool.id === 'groq.browser_search') {\n if (!isBrowserSearchSupportedModel(modelId)) {\n toolWarnings.push({\n type: 'unsupported-tool',\n tool,\n details: `Browser search is only supported on the following models: ${getSupportedModelsString()}. Current model: ${modelId}`,\n });\n } else {\n groqTools.push({\n type: 'browser_search',\n });\n }\n } else {\n toolWarnings.push({ type: 'unsupported-tool', tool });\n }\n } else {\n groqTools.push({\n type: 'function',\n function: {\n name: tool.name,\n description: tool.description,\n parameters: tool.inputSchema,\n },\n });\n }\n }\n\n if (toolChoice == null) {\n return { tools: groqTools, toolChoice: undefined, toolWarnings };\n }\n\n const type = toolChoice.type;\n\n switch (type) {\n case 'auto':\n case 'none':\n case 'required':\n return { tools: groqTools, toolChoice: type, toolWarnings };\n case 'tool':\n return {\n tools: groqTools,\n toolChoice: {\n type: 'function',\n function: {\n name: toolChoice.toolName,\n },\n },\n toolWarnings,\n };\n default: {\n const _exhaustiveCheck: never = type;\n throw new UnsupportedFunctionalityError({\n functionality: `tool choice type: ${_exhaustiveCheck}`,\n });\n }\n }\n}\n","import type { GroqChatModelId } from './groq-chat-options';\n\n/**\n * Models that support browser search functionality.\n * Based on: https://console.groq.com/docs/browser-search\n */\nexport const BROWSER_SEARCH_SUPPORTED_MODELS: readonly GroqChatModelId[] = [\n 'openai/gpt-oss-20b',\n 'openai/gpt-oss-120b',\n] as const;\n\n/**\n * Check if a model supports browser search functionality.\n */\nexport function isBrowserSearchSupportedModel(\n modelId: GroqChatModelId,\n): boolean {\n return BROWSER_SEARCH_SUPPORTED_MODELS.includes(modelId);\n}\n\n/**\n * Get a formatted list of supported models for error messages.\n */\nexport function getSupportedModelsString(): string {\n return BROWSER_SEARCH_SUPPORTED_MODELS.join(', ');\n}\n","import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';\n\nexport function mapGroqFinishReason(\n finishReason: string | null | undefined,\n): LanguageModelV2FinishReason {\n switch (finishReason) {\n case 'stop':\n return 'stop';\n case 'length':\n return 'length';\n case 'content_filter':\n return 'content-filter';\n case 'function_call':\n case 'tool_calls':\n return 'tool-calls';\n default:\n return 'unknown';\n }\n}\n","import type {\n TranscriptionModelV2,\n TranscriptionModelV2CallWarning,\n} from '@ai-sdk/provider';\nimport {\n combineHeaders,\n convertBase64ToUint8Array,\n createJsonResponseHandler,\n mediaTypeToExtension,\n parseProviderOptions,\n postFormDataToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport type { GroqConfig } from './groq-config';\nimport { groqFailedResponseHandler } from './groq-error';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport type { GroqTranscriptionAPITypes } from './groq-api-types';\n\n// https://console.groq.com/docs/speech-to-text\nconst groqProviderOptionsSchema = z.object({\n language: z.string().nullish(),\n prompt: z.string().nullish(),\n responseFormat: z.string().nullish(),\n temperature: z.number().min(0).max(1).nullish(),\n timestampGranularities: z.array(z.string()).nullish(),\n});\n\nexport type GroqTranscriptionCallOptions = z.infer<\n typeof groqProviderOptionsSchema\n>;\n\ninterface GroqTranscriptionModelConfig extends GroqConfig {\n _internal?: {\n currentDate?: () => Date;\n };\n}\n\nexport class GroqTranscriptionModel implements TranscriptionModelV2 {\n readonly specificationVersion = 'v2';\n\n get provider(): string {\n return this.config.provider;\n }\n\n constructor(\n readonly modelId: GroqTranscriptionModelId,\n private readonly config: GroqTranscriptionModelConfig,\n ) {}\n\n private async getArgs({\n audio,\n mediaType,\n providerOptions,\n }: Parameters<TranscriptionModelV2['doGenerate']>[0]) {\n const warnings: TranscriptionModelV2CallWarning[] = [];\n\n // Parse provider options\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptionsSchema,\n });\n\n // Create form data with base fields\n const formData = new FormData();\n const blob =\n audio instanceof Uint8Array\n ? new Blob([audio])\n : new Blob([convertBase64ToUint8Array(audio)]);\n\n formData.append('model', this.modelId);\n const fileExtension = mediaTypeToExtension(mediaType);\n formData.append(\n 'file',\n new File([blob], 'audio', { type: mediaType }),\n `audio.${fileExtension}`,\n );\n\n // Add provider-specific options\n if (groqOptions) {\n const transcriptionModelOptions: Omit<\n GroqTranscriptionAPITypes,\n 'model'\n > = {\n language: groqOptions.language ?? undefined,\n prompt: groqOptions.prompt ?? undefined,\n response_format: groqOptions.responseFormat ?? undefined,\n temperature: groqOptions.temperature ?? undefined,\n timestamp_granularities:\n groqOptions.timestampGranularities ?? undefined,\n };\n\n for (const key in transcriptionModelOptions) {\n const value =\n transcriptionModelOptions[\n key as keyof Omit<GroqTranscriptionAPITypes, 'model'>\n ];\n if (value !== undefined) {\n formData.append(key, String(value));\n }\n }\n }\n\n return {\n formData,\n warnings,\n };\n }\n\n async doGenerate(\n options: Parameters<TranscriptionModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<TranscriptionModelV2['doGenerate']>>> {\n const currentDate = this.config._internal?.currentDate?.() ?? new Date();\n const { formData, warnings } = await this.getArgs(options);\n\n const {\n value: response,\n responseHeaders,\n rawValue: rawResponse,\n } = await postFormDataToApi({\n url: this.config.url({\n path: '/audio/transcriptions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n formData,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqTranscriptionResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n return {\n text: response.text,\n segments:\n response.segments?.map(segment => ({\n text: segment.text,\n startSecond: segment.start,\n endSecond: segment.end,\n })) ?? [],\n language: response.language ?? undefined,\n durationInSeconds: response.duration ?? undefined,\n warnings,\n response: {\n timestamp: currentDate,\n modelId: this.modelId,\n headers: responseHeaders,\n body: rawResponse,\n },\n };\n }\n}\n\nconst groqTranscriptionResponseSchema = z.object({\n text: z.string(),\n x_groq: z.object({\n id: z.string(),\n }),\n // additional properties are returned when `response_format: 'verbose_json'` is\n task: z.string().nullish(),\n language: z.string().nullish(),\n duration: z.number().nullish(),\n segments: z\n .array(\n z.object({\n id: z.number(),\n seek: z.number(),\n start: z.number(),\n end: z.number(),\n text: z.string(),\n tokens: z.array(z.number()),\n temperature: z.number(),\n avg_logprob: z.number(),\n compression_ratio: z.number(),\n no_speech_prob: z.number(),\n }),\n )\n .nullish(),\n});\n","import { createProviderDefinedToolFactory } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\n/**\n * Browser search tool for Groq models.\n *\n * Provides interactive browser search capabilities that go beyond traditional web search\n * by navigating websites interactively and providing more detailed results.\n *\n * Currently supported on:\n * - openai/gpt-oss-20b\n * - openai/gpt-oss-120b\n *\n * @see https://console.groq.com/docs/browser-search\n */\nexport const browserSearch = createProviderDefinedToolFactory<\n {\n // Browser search doesn't take input parameters - it's controlled by the prompt\n // The tool is activated automatically when included in the tools array\n },\n {\n // No configuration options needed - the tool works automatically\n // when included in the tools array for supported models\n }\n>({\n id: 'groq.browser_search',\n name: 'browser_search',\n inputSchema: z.object({}),\n});\n","import { browserSearch } from './tool/browser-search';\n\nexport const groqTools = {\n browserSearch,\n};\n","// Version string of this package injected at build time.\ndeclare const __PACKAGE_VERSION__: string | undefined;\nexport const VERSION: string =\n typeof __PACKAGE_VERSION__ !== 'undefined'\n ? __PACKAGE_VERSION__\n : 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| ||
| {"version":3,"sources":["../src/index.ts","../src/groq-provider.ts","../src/groq-chat-language-model.ts","../src/convert-to-groq-chat-messages.ts","../src/get-response-metadata.ts","../src/groq-chat-options.ts","../src/groq-error.ts","../src/groq-prepare-tools.ts","../src/groq-browser-search-models.ts","../src/map-groq-finish-reason.ts","../src/groq-transcription-model.ts","../src/tool/browser-search.ts","../src/groq-tools.ts","../src/version.ts"],"sourcesContent":["export { createGroq, groq } from './groq-provider';\nexport type { GroqProvider, GroqProviderSettings } from './groq-provider';\nexport type { GroqProviderOptions } from './groq-chat-options';\nexport { browserSearch } from './tool/browser-search';\nexport { VERSION } from './version';\n","import {\n type LanguageModelV2,\n type ProviderV2,\n type TranscriptionModelV2,\n NoSuchModelError,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n loadApiKey,\n withoutTrailingSlash,\n withUserAgentSuffix,\n} from '@ai-sdk/provider-utils';\nimport { GroqChatLanguageModel } from './groq-chat-language-model';\nimport type { GroqChatModelId } from './groq-chat-options';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport { GroqTranscriptionModel } from './groq-transcription-model';\n\nimport { groqTools } from './groq-tools';\nimport { VERSION } from './version';\nexport interface GroqProvider extends ProviderV2 {\n /**\nCreates a model for text generation.\n*/\n (modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates an Groq chat model for text generation.\n */\n languageModel(modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates a model for transcription.\n */\n transcription(modelId: GroqTranscriptionModelId): TranscriptionModelV2;\n\n /**\n * Tools provided by Groq.\n */\n tools: typeof groqTools;\n}\n\nexport interface GroqProviderSettings {\n /**\nBase URL for the Groq API calls.\n */\n baseURL?: string;\n\n /**\nAPI key for authenticating requests.\n */\n apiKey?: string;\n\n /**\nCustom headers to include in the requests.\n */\n headers?: Record<string, string>;\n\n /**\nCustom fetch implementation. 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'https://api.groq.com/openai/v1';\n\n const getHeaders = () =>\n withUserAgentSuffix(\n {\n Authorization: `Bearer ${loadApiKey({\n apiKey: options.apiKey,\n environmentVariableName: 'GROQ_API_KEY',\n description: 'Groq',\n })}`,\n ...options.headers,\n },\n `ai-sdk/groq/${VERSION}`,\n );\n\n const createChatModel = (modelId: GroqChatModelId) =>\n new GroqChatLanguageModel(modelId, {\n provider: 'groq.chat',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n\n const createLanguageModel = (modelId: GroqChatModelId) => {\n if (new.target) {\n throw new Error(\n 'The Groq model function cannot be called with the new keyword.',\n );\n }\n\n return createChatModel(modelId);\n };\n\n const createTranscriptionModel = (modelId: GroqTranscriptionModelId) => {\n return new GroqTranscriptionModel(modelId, {\n provider: 'groq.transcription',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n };\n\n const provider = function (modelId: GroqChatModelId) {\n return createLanguageModel(modelId);\n };\n\n provider.languageModel = createLanguageModel;\n provider.chat = createChatModel;\n\n provider.textEmbeddingModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'textEmbeddingModel' });\n };\n provider.imageModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'imageModel' });\n };\n provider.transcription = createTranscriptionModel;\n provider.transcriptionModel = createTranscriptionModel;\n\n provider.tools = groqTools;\n\n return provider;\n}\n\n/**\nDefault Groq provider instance.\n */\nexport const groq = createGroq();\n","import {\n type LanguageModelV2,\n type LanguageModelV2CallWarning,\n type LanguageModelV2Content,\n type LanguageModelV2FinishReason,\n type LanguageModelV2StreamPart,\n type LanguageModelV2Usage,\n type SharedV2ProviderMetadata,\n InvalidResponseDataError,\n LanguageModelV2Prompt,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n type ParseResult,\n combineHeaders,\n createEventSourceResponseHandler,\n createJsonResponseHandler,\n generateId,\n isParsableJson,\n parseProviderOptions,\n postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { convertToGroqChatMessages } from './convert-to-groq-chat-messages';\nimport { getResponseMetadata } from './get-response-metadata';\nimport { type GroqChatModelId, groqProviderOptions } from './groq-chat-options';\nimport { groqErrorDataSchema, groqFailedResponseHandler } from './groq-error';\nimport { prepareTools } from './groq-prepare-tools';\nimport { mapGroqFinishReason } from './map-groq-finish-reason';\n\ntype GroqChatConfig = {\n provider: string;\n headers: () => Record<string, string | undefined>;\n url: (options: { modelId: string; path: string }) => string;\n fetch?: FetchFunction;\n};\n\nexport class GroqChatLanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2';\n\n readonly modelId: GroqChatModelId;\n\n readonly supportedUrls = {\n 'image/*': [/^https?:\\/\\/.*$/],\n };\n\n private readonly config: GroqChatConfig;\n\n constructor(modelId: GroqChatModelId, config: GroqChatConfig) {\n this.modelId = modelId;\n this.config = config;\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n private async getArgs({\n prompt,\n maxOutputTokens,\n temperature,\n topP,\n topK,\n frequencyPenalty,\n presencePenalty,\n stopSequences,\n responseFormat,\n seed,\n stream,\n tools,\n toolChoice,\n providerOptions,\n }: Parameters<LanguageModelV2['doGenerate']>[0] & {\n stream: boolean;\n }) {\n const warnings: LanguageModelV2CallWarning[] = [];\n\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptions,\n });\n\n const structuredOutputs = groqOptions?.structuredOutputs ?? true;\n\n if (topK != null) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'topK',\n });\n }\n\n if (\n responseFormat?.type === 'json' &&\n responseFormat.schema != null &&\n !structuredOutputs\n ) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'responseFormat',\n details:\n 'JSON response format schema is only supported with structuredOutputs',\n });\n }\n\n const {\n tools: groqTools,\n toolChoice: groqToolChoice,\n toolWarnings,\n } = prepareTools({ tools, toolChoice, modelId: this.modelId });\n\n return {\n args: {\n // model id:\n model: this.modelId,\n\n // model specific settings:\n user: groqOptions?.user,\n parallel_tool_calls: groqOptions?.parallelToolCalls,\n\n // standardized settings:\n max_tokens: maxOutputTokens,\n temperature,\n top_p: topP,\n frequency_penalty: frequencyPenalty,\n presence_penalty: presencePenalty,\n stop: stopSequences,\n seed,\n\n // response format:\n response_format:\n responseFormat?.type === 'json'\n ? structuredOutputs && responseFormat.schema != null\n ? {\n type: 'json_schema',\n json_schema: {\n schema: responseFormat.schema,\n name: responseFormat.name ?? 'response',\n description: responseFormat.description,\n },\n }\n : { type: 'json_object' }\n : undefined,\n\n // provider options:\n reasoning_format: groqOptions?.reasoningFormat,\n reasoning_effort: groqOptions?.reasoningEffort,\n service_tier: groqOptions?.serviceTier,\n\n // messages:\n messages: convertToGroqChatMessages(prompt),\n\n // tools:\n tools: groqTools,\n tool_choice: groqToolChoice,\n },\n warnings: [...warnings, ...toolWarnings],\n };\n }\n\n async doGenerate(\n options: Parameters<LanguageModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {\n const { args, warnings } = await this.getArgs({\n ...options,\n stream: false,\n });\n\n const body = JSON.stringify(args);\n\n const {\n responseHeaders,\n value: response,\n rawValue: rawResponse,\n } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: args,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqChatResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const choice = response.choices[0];\n const content: Array<LanguageModelV2Content> = [];\n\n // text content:\n const text = choice.message.content;\n if (text != null && text.length > 0) {\n content.push({ type: 'text', text: text });\n }\n\n // reasoning:\n const reasoning = choice.message.reasoning;\n if (reasoning != null && reasoning.length > 0) {\n content.push({\n type: 'reasoning',\n text: reasoning,\n });\n }\n\n // tool calls:\n if (choice.message.tool_calls != null) {\n for (const toolCall of choice.message.tool_calls) {\n content.push({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments!,\n });\n }\n }\n\n return {\n content,\n finishReason: mapGroqFinishReason(choice.finish_reason),\n usage: {\n inputTokens: response.usage?.prompt_tokens ?? undefined,\n outputTokens: response.usage?.completion_tokens ?? undefined,\n totalTokens: response.usage?.total_tokens ?? undefined,\n cachedInputTokens:\n response.usage?.prompt_tokens_details?.cached_tokens ?? undefined,\n },\n response: {\n ...getResponseMetadata(response),\n headers: responseHeaders,\n body: rawResponse,\n },\n warnings,\n request: { body },\n };\n }\n\n async doStream(\n options: Parameters<LanguageModelV2['doStream']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {\n const { args, warnings } = await this.getArgs({ ...options, stream: true });\n\n const body = JSON.stringify({ ...args, stream: true });\n\n const { responseHeaders, value: response } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: {\n ...args,\n stream: true,\n },\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler:\n createEventSourceResponseHandler(groqChatChunkSchema),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: {\n name: string;\n arguments: string;\n };\n hasFinished: boolean;\n }> = [];\n\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n const usage: LanguageModelV2Usage = {\n inputTokens: undefined,\n outputTokens: undefined,\n totalTokens: undefined,\n cachedInputTokens: undefined,\n };\n let isFirstChunk = true;\n let isActiveText = false;\n let isActiveReasoning = false;\n\n let providerMetadata: SharedV2ProviderMetadata | undefined;\n return {\n stream: response.pipeThrough(\n new TransformStream<\n ParseResult<z.infer<typeof groqChatChunkSchema>>,\n LanguageModelV2StreamPart\n >({\n start(controller) {\n controller.enqueue({ type: 'stream-start', warnings });\n },\n\n transform(chunk, controller) {\n // Emit raw chunk if requested (before anything else)\n if (options.includeRawChunks) {\n controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });\n }\n\n // handle failed chunk parsing / validation:\n if (!chunk.success) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: chunk.error });\n return;\n }\n\n const value = chunk.value;\n\n // handle error chunks:\n if ('error' in value) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: value.error });\n return;\n }\n\n if (isFirstChunk) {\n isFirstChunk = false;\n\n controller.enqueue({\n type: 'response-metadata',\n ...getResponseMetadata(value),\n });\n }\n\n if (value.x_groq?.usage != null) {\n usage.inputTokens = value.x_groq.usage.prompt_tokens ?? undefined;\n usage.outputTokens =\n value.x_groq.usage.completion_tokens ?? undefined;\n usage.totalTokens = value.x_groq.usage.total_tokens ?? undefined;\n usage.cachedInputTokens =\n value.x_groq.usage.prompt_tokens_details?.cached_tokens ??\n undefined;\n }\n\n const choice = value.choices[0];\n\n if (choice?.finish_reason != null) {\n finishReason = mapGroqFinishReason(choice.finish_reason);\n }\n\n if (choice?.delta == null) {\n return;\n }\n\n const delta = choice.delta;\n\n if (delta.reasoning != null && delta.reasoning.length > 0) {\n if (!isActiveReasoning) {\n controller.enqueue({\n type: 'reasoning-start',\n id: 'reasoning-0',\n });\n isActiveReasoning = true;\n }\n\n controller.enqueue({\n type: 'reasoning-delta',\n id: 'reasoning-0',\n delta: delta.reasoning,\n });\n }\n\n if (delta.content != null && delta.content.length > 0) {\n if (!isActiveText) {\n controller.enqueue({ type: 'text-start', id: 'txt-0' });\n isActiveText = true;\n }\n\n controller.enqueue({\n type: 'text-delta',\n id: 'txt-0',\n delta: delta.content,\n });\n }\n\n if (delta.tool_calls != null) {\n for (const toolCallDelta of delta.tool_calls) {\n const index = toolCallDelta.index;\n\n if (toolCalls[index] == null) {\n if (toolCallDelta.type !== 'function') {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function' type.`,\n });\n }\n\n if (toolCallDelta.id == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'id' to be a string.`,\n });\n }\n\n if (toolCallDelta.function?.name == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function.name' to be a string.`,\n });\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: toolCallDelta.id,\n toolName: toolCallDelta.function.name,\n });\n\n toolCalls[index] = {\n id: toolCallDelta.id,\n type: 'function',\n function: {\n name: toolCallDelta.function.name,\n arguments: toolCallDelta.function.arguments ?? '',\n },\n hasFinished: false,\n };\n\n const toolCall = toolCalls[index];\n\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null\n ) {\n // send delta if the argument text has already started:\n if (toolCall.function.arguments.length > 0) {\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCall.function.arguments,\n });\n }\n\n // check if tool call is complete\n // (some providers send the full tool call in one chunk):\n if (isParsableJson(toolCall.function.arguments)) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n\n continue;\n }\n\n // existing tool call, merge if not finished\n const toolCall = toolCalls[index];\n\n if (toolCall.hasFinished) {\n continue;\n }\n\n if (toolCallDelta.function?.arguments != null) {\n toolCall.function!.arguments +=\n toolCallDelta.function?.arguments ?? '';\n }\n\n // send delta\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCallDelta.function.arguments ?? '',\n });\n\n // check if tool call is complete\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null &&\n isParsableJson(toolCall.function.arguments)\n ) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n }\n },\n\n flush(controller) {\n if (isActiveReasoning) {\n controller.enqueue({ type: 'reasoning-end', id: 'reasoning-0' });\n }\n\n if (isActiveText) {\n controller.enqueue({ type: 'text-end', id: 'txt-0' });\n }\n\n controller.enqueue({\n type: 'finish',\n finishReason,\n usage,\n ...(providerMetadata != null ? { providerMetadata } : {}),\n });\n },\n }),\n ),\n request: { body },\n response: { headers: responseHeaders },\n };\n }\n}\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatResponseSchema = z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n message: z.object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n id: z.string().nullish(),\n type: z.literal('function'),\n function: z.object({\n name: z.string(),\n arguments: z.string(),\n }),\n }),\n )\n .nullish(),\n }),\n index: z.number(),\n finish_reason: z.string().nullish(),\n }),\n ),\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n});\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatChunkSchema = z.union([\n z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n delta: z\n .object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n index: z.number(),\n id: z.string().nullish(),\n type: z.literal('function').optional(),\n function: z.object({\n name: z.string().nullish(),\n arguments: z.string().nullish(),\n }),\n }),\n )\n .nullish(),\n })\n .nullish(),\n finish_reason: z.string().nullable().optional(),\n index: z.number(),\n }),\n ),\n x_groq: z\n .object({\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n })\n .nullish(),\n }),\n groqErrorDataSchema,\n]);\n","import {\n type LanguageModelV2Prompt,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport type { GroqChatPrompt } from './groq-api-types';\nimport { convertToBase64 } from '@ai-sdk/provider-utils';\n\nexport function convertToGroqChatMessages(\n prompt: LanguageModelV2Prompt,\n): GroqChatPrompt {\n const messages: GroqChatPrompt = [];\n\n for (const { role, content } of prompt) {\n switch (role) {\n case 'system': {\n messages.push({ role: 'system', content });\n break;\n }\n\n case 'user': {\n if (content.length === 1 && content[0].type === 'text') {\n messages.push({ role: 'user', content: content[0].text });\n break;\n }\n\n messages.push({\n role: 'user',\n content: content.map(part => {\n switch (part.type) {\n case 'text': {\n return { type: 'text', text: part.text };\n }\n case 'file': {\n if (!part.mediaType.startsWith('image/')) {\n throw new UnsupportedFunctionalityError({\n functionality: 'Non-image file content parts',\n });\n }\n\n const mediaType =\n part.mediaType === 'image/*' ? 'image/jpeg' : part.mediaType;\n\n return {\n type: 'image_url',\n image_url: {\n url:\n part.data instanceof URL\n ? part.data.toString()\n : `data:${mediaType};base64,${convertToBase64(part.data)}`,\n },\n };\n }\n }\n }),\n });\n\n break;\n }\n\n case 'assistant': {\n let text = '';\n let reasoning = '';\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: { name: string; arguments: string };\n }> = [];\n\n for (const part of content) {\n switch (part.type) {\n // groq supports reasoning for tool-calls in multi-turn conversations\n // https://github.com/vercel/ai/issues/7860\n case 'reasoning': {\n reasoning += part.text;\n break;\n }\n\n case 'text': {\n text += part.text;\n break;\n }\n\n case 'tool-call': {\n toolCalls.push({\n id: part.toolCallId,\n type: 'function',\n function: {\n name: part.toolName,\n arguments: JSON.stringify(part.input),\n },\n });\n break;\n }\n }\n }\n\n messages.push({\n role: 'assistant',\n content: text,\n ...(reasoning.length > 0 ? { reasoning } : null),\n ...(toolCalls.length > 0 ? { tool_calls: toolCalls } : null),\n });\n\n break;\n }\n\n case 'tool': {\n for (const toolResponse of content) {\n const output = toolResponse.output;\n\n let contentValue: string;\n switch (output.type) {\n case 'text':\n case 'error-text':\n contentValue = output.value;\n break;\n case 'content':\n case 'json':\n case 'error-json':\n contentValue = JSON.stringify(output.value);\n break;\n }\n\n messages.push({\n role: 'tool',\n tool_call_id: toolResponse.toolCallId,\n content: contentValue,\n });\n }\n break;\n }\n\n default: {\n const _exhaustiveCheck: never = role;\n throw new Error(`Unsupported role: ${_exhaustiveCheck}`);\n }\n }\n }\n\n return messages;\n}\n","export function getResponseMetadata({\n id,\n model,\n created,\n}: {\n id?: string | undefined | null;\n created?: number | undefined | null;\n model?: string | undefined | null;\n}) {\n return {\n id: id ?? undefined,\n modelId: model ?? undefined,\n timestamp: created != null ? new Date(created * 1000) : undefined,\n };\n}\n","import { z } from 'zod/v4';\n\n// https://console.groq.com/docs/models\nexport type GroqChatModelId =\n // production models\n | 'gemma2-9b-it'\n | 'llama-3.1-8b-instant'\n | 'llama-3.3-70b-versatile'\n | 'meta-llama/llama-guard-4-12b'\n | 'openai/gpt-oss-120b'\n | 'openai/gpt-oss-20b'\n // preview models (selection)\n | 'deepseek-r1-distill-llama-70b'\n | 'meta-llama/llama-4-maverick-17b-128e-instruct'\n | 'meta-llama/llama-4-scout-17b-16e-instruct'\n | 'meta-llama/llama-prompt-guard-2-22m'\n | 'meta-llama/llama-prompt-guard-2-86m'\n | 'moonshotai/kimi-k2-instruct-0905'\n | 'qwen/qwen3-32b'\n | 'llama-guard-3-8b'\n | 'llama3-70b-8192'\n | 'llama3-8b-8192'\n | 'mixtral-8x7b-32768'\n | 'qwen-qwq-32b'\n | 'qwen-2.5-32b'\n | 'deepseek-r1-distill-qwen-32b'\n | (string & {});\n\nexport const groqProviderOptions = z.object({\n reasoningFormat: z.enum(['parsed', 'raw', 'hidden']).optional(),\n\n /**\n * Specifies the reasoning effort level for model inference.\n * @see https://console.groq.com/docs/reasoning#reasoning-effort\n */\n reasoningEffort: z\n .enum(['none', 'default', 'low', 'medium', 'high'])\n .optional(),\n\n /**\n * Whether to enable parallel function calling during tool use. Default to true.\n */\n parallelToolCalls: z.boolean().optional(),\n\n /**\n * A unique identifier representing your end-user, which can help OpenAI to\n * monitor and detect abuse. Learn more.\n */\n user: z.string().optional(),\n\n /**\n * Whether to use structured outputs.\n *\n * @default true\n */\n structuredOutputs: z.boolean().optional(),\n\n /**\n * Service tier for the request.\n * - 'on_demand': Default tier with consistent performance and fairness\n * - 'flex': Higher throughput tier optimized for workloads that can handle occasional request failures\n * - 'auto': Uses on_demand rate limits, then falls back to flex tier if exceeded\n *\n * @default 'on_demand'\n */\n serviceTier: z.enum(['on_demand', 'flex', 'auto']).optional(),\n});\n\nexport type GroqProviderOptions = z.infer<typeof groqProviderOptions>;\n","import { z } from 'zod/v4';\nimport { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\n\nexport const groqErrorDataSchema = z.object({\n error: z.object({\n message: z.string(),\n type: z.string(),\n }),\n});\n\nexport type GroqErrorData = z.infer<typeof groqErrorDataSchema>;\n\nexport const groqFailedResponseHandler = createJsonErrorResponseHandler({\n errorSchema: groqErrorDataSchema,\n errorToMessage: data => data.error.message,\n});\n","import {\n type LanguageModelV2CallOptions,\n type LanguageModelV2CallWarning,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport {\n getSupportedModelsString,\n isBrowserSearchSupportedModel,\n} from './groq-browser-search-models';\nimport type { GroqChatModelId } from './groq-chat-options';\n\nexport function prepareTools({\n tools,\n toolChoice,\n modelId,\n}: {\n tools: LanguageModelV2CallOptions['tools'];\n toolChoice?: LanguageModelV2CallOptions['toolChoice'];\n modelId: GroqChatModelId;\n}): {\n tools:\n | undefined\n | Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n >;\n toolChoice:\n | { type: 'function'; function: { name: string } }\n | 'auto'\n | 'none'\n | 'required'\n | undefined;\n toolWarnings: LanguageModelV2CallWarning[];\n} {\n // when the tools array is empty, change it to undefined to prevent errors:\n tools = tools?.length ? tools : undefined;\n\n const toolWarnings: LanguageModelV2CallWarning[] = [];\n\n if (tools == null) {\n return { tools: undefined, toolChoice: undefined, toolWarnings };\n }\n\n const groqTools: Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n > = [];\n\n for (const tool of tools) {\n if (tool.type === 'provider-defined') {\n if (tool.id === 'groq.browser_search') {\n if (!isBrowserSearchSupportedModel(modelId)) {\n toolWarnings.push({\n type: 'unsupported-tool',\n tool,\n details: `Browser search is only supported on the following models: ${getSupportedModelsString()}. Current model: ${modelId}`,\n });\n } else {\n groqTools.push({\n type: 'browser_search',\n });\n }\n } else {\n toolWarnings.push({ type: 'unsupported-tool', tool });\n }\n } else {\n groqTools.push({\n type: 'function',\n function: {\n name: tool.name,\n description: tool.description,\n parameters: tool.inputSchema,\n },\n });\n }\n }\n\n if (toolChoice == null) {\n return { tools: groqTools, toolChoice: undefined, toolWarnings };\n }\n\n const type = toolChoice.type;\n\n switch (type) {\n case 'auto':\n case 'none':\n case 'required':\n return { tools: groqTools, toolChoice: type, toolWarnings };\n case 'tool':\n return {\n tools: groqTools,\n toolChoice: {\n type: 'function',\n function: {\n name: toolChoice.toolName,\n },\n },\n toolWarnings,\n };\n default: {\n const _exhaustiveCheck: never = type;\n throw new UnsupportedFunctionalityError({\n functionality: `tool choice type: ${_exhaustiveCheck}`,\n });\n }\n }\n}\n","import type { GroqChatModelId } from './groq-chat-options';\n\n/**\n * Models that support browser search functionality.\n * Based on: https://console.groq.com/docs/browser-search\n */\nexport const BROWSER_SEARCH_SUPPORTED_MODELS: readonly GroqChatModelId[] = [\n 'openai/gpt-oss-20b',\n 'openai/gpt-oss-120b',\n] as const;\n\n/**\n * Check if a model supports browser search functionality.\n */\nexport function isBrowserSearchSupportedModel(\n modelId: GroqChatModelId,\n): boolean {\n return BROWSER_SEARCH_SUPPORTED_MODELS.includes(modelId);\n}\n\n/**\n * Get a formatted list of supported models for error messages.\n */\nexport function getSupportedModelsString(): string {\n return BROWSER_SEARCH_SUPPORTED_MODELS.join(', ');\n}\n","import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';\n\nexport function mapGroqFinishReason(\n finishReason: string | null | undefined,\n): LanguageModelV2FinishReason {\n switch (finishReason) {\n case 'stop':\n return 'stop';\n case 'length':\n return 'length';\n case 'content_filter':\n return 'content-filter';\n case 'function_call':\n case 'tool_calls':\n return 'tool-calls';\n default:\n return 'unknown';\n }\n}\n","import type {\n TranscriptionModelV2,\n TranscriptionModelV2CallWarning,\n} from '@ai-sdk/provider';\nimport {\n combineHeaders,\n convertBase64ToUint8Array,\n createBinaryResponseHandler,\n createJsonResponseHandler,\n mediaTypeToExtension,\n parseProviderOptions,\n postFormDataToApi,\n type ResponseHandler,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport type { GroqConfig } from './groq-config';\nimport { groqFailedResponseHandler } from './groq-error';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport type { GroqTranscriptionAPITypes } from './groq-api-types';\n\n// https://console.groq.com/docs/speech-to-text\nconst groqProviderOptionsSchema = z.object({\n language: z.string().nullish(),\n prompt: z.string().nullish(),\n responseFormat: z.string().nullish(),\n temperature: z.number().min(0).max(1).nullish(),\n timestampGranularities: z.array(z.string()).nullish(),\n});\n\nexport type GroqTranscriptionCallOptions = z.infer<\n typeof groqProviderOptionsSchema\n>;\n\ninterface GroqTranscriptionModelConfig extends GroqConfig {\n _internal?: {\n currentDate?: () => Date;\n };\n}\n\nexport class GroqTranscriptionModel implements TranscriptionModelV2 {\n readonly specificationVersion = 'v2';\n\n get provider(): string {\n return this.config.provider;\n }\n\n constructor(\n readonly modelId: GroqTranscriptionModelId,\n private readonly config: GroqTranscriptionModelConfig,\n ) {}\n\n private async getArgs({\n audio,\n mediaType,\n providerOptions,\n }: Parameters<TranscriptionModelV2['doGenerate']>[0]) {\n const warnings: TranscriptionModelV2CallWarning[] = [];\n\n // Parse provider options\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptionsSchema,\n });\n\n // Create form data with base fields\n const formData = new FormData();\n const blob =\n audio instanceof Uint8Array\n ? new Blob([audio])\n : new Blob([convertBase64ToUint8Array(audio)]);\n\n formData.append('model', this.modelId);\n const fileExtension = mediaTypeToExtension(mediaType);\n formData.append(\n 'file',\n new File([blob], 'audio', { type: mediaType }),\n `audio.${fileExtension}`,\n );\n\n // Add provider-specific options\n if (groqOptions) {\n const transcriptionModelOptions: Omit<\n GroqTranscriptionAPITypes,\n 'model'\n > = {\n language: groqOptions.language ?? undefined,\n prompt: groqOptions.prompt ?? undefined,\n response_format: groqOptions.responseFormat ?? undefined,\n temperature: groqOptions.temperature ?? undefined,\n timestamp_granularities:\n groqOptions.timestampGranularities ?? undefined,\n };\n\n for (const key in transcriptionModelOptions) {\n const value =\n transcriptionModelOptions[\n key as keyof Omit<GroqTranscriptionAPITypes, 'model'>\n ];\n if (value !== undefined) {\n formData.append(key, String(value));\n }\n }\n }\n\n return {\n formData,\n responseFormat: groqOptions?.responseFormat,\n warnings,\n };\n }\n\n async doGenerate(\n options: Parameters<TranscriptionModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<TranscriptionModelV2['doGenerate']>>> {\n const currentDate = this.config._internal?.currentDate?.() ?? new Date();\n const { formData, responseFormat, warnings } = await this.getArgs(options);\n\n const successfulResponseHandler: ResponseHandler<GroqTranscriptionResponse> =\n responseFormat === 'text'\n ? groqTextTranscriptionResponseHandler\n : createJsonResponseHandler(groqTranscriptionResponseSchema);\n\n const {\n value: response,\n responseHeaders,\n rawValue: rawResponse,\n } = await postFormDataToApi({\n url: this.config.url({\n path: '/audio/transcriptions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n formData,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler,\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n return {\n text: response.text,\n segments:\n response.segments?.map(segment => ({\n text: segment.text,\n startSecond: segment.start,\n endSecond: segment.end,\n })) ?? [],\n language: response.language ?? undefined,\n durationInSeconds: response.duration ?? undefined,\n warnings,\n response: {\n timestamp: currentDate,\n modelId: this.modelId,\n headers: responseHeaders,\n body: rawResponse,\n },\n };\n }\n}\n\nconst groqTranscriptionResponseSchema = z.object({\n text: z.string(),\n x_groq: z.object({\n id: z.string(),\n }),\n // additional properties are returned when `response_format: 'verbose_json'` is\n task: z.string().nullish(),\n language: z.string().nullish(),\n duration: z.number().nullish(),\n segments: z\n .array(\n z.object({\n id: z.number(),\n seek: z.number(),\n start: z.number(),\n end: z.number(),\n text: z.string(),\n tokens: z.array(z.number()),\n temperature: z.number(),\n avg_logprob: z.number(),\n compression_ratio: z.number(),\n no_speech_prob: z.number(),\n }),\n )\n .nullish(),\n});\n\ntype GroqTranscriptionResponse = Partial<\n Omit<z.infer<typeof groqTranscriptionResponseSchema>, 'text'>\n> & {\n text: string;\n};\n\nconst binaryResponseHandler = createBinaryResponseHandler();\nconst textDecoder = new TextDecoder();\n\nconst groqTextTranscriptionResponseHandler: ResponseHandler<\n GroqTranscriptionResponse\n> = async options => {\n const { value, responseHeaders } = await binaryResponseHandler(options);\n const text = textDecoder.decode(value);\n\n return {\n value: { text },\n rawValue: text,\n responseHeaders,\n };\n};\n","import { createProviderDefinedToolFactory } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\n/**\n * Browser search tool for Groq models.\n *\n * Provides interactive browser search capabilities that go beyond traditional web search\n * by navigating websites interactively and providing more detailed results.\n *\n * Currently supported on:\n * - openai/gpt-oss-20b\n * - openai/gpt-oss-120b\n *\n * @see https://console.groq.com/docs/browser-search\n */\nexport const browserSearch = createProviderDefinedToolFactory<\n {\n // Browser search doesn't take input parameters - it's controlled by the prompt\n // The tool is activated automatically when included in the tools array\n },\n {\n // No configuration options needed - the tool works automatically\n // when included in the tools array for supported models\n }\n>({\n id: 'groq.browser_search',\n name: 'browser_search',\n inputSchema: z.object({}),\n});\n","import { browserSearch } from './tool/browser-search';\n\nexport const groqTools = {\n browserSearch,\n};\n","// Version string of this package injected at build time.\ndeclare const __PACKAGE_VERSION__: string | undefined;\nexport const VERSION: string =\n typeof __PACKAGE_VERSION__ !== 'undefined'\n ? __PACKAGE_VERSION__\n : 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|
+17
-5
@@ -747,2 +747,3 @@ // src/groq-provider.ts | ||
| convertBase64ToUint8Array, | ||
| createBinaryResponseHandler, | ||
| createJsonResponseHandler as createJsonResponseHandler2, | ||
@@ -808,2 +809,3 @@ mediaTypeToExtension, | ||
| formData, | ||
| responseFormat: groqOptions == null ? void 0 : groqOptions.responseFormat, | ||
| warnings | ||
@@ -815,3 +817,4 @@ }; | ||
| const currentDate = (_c = (_b = (_a = this.config._internal) == null ? void 0 : _a.currentDate) == null ? void 0 : _b.call(_a)) != null ? _c : /* @__PURE__ */ new Date(); | ||
| const { formData, warnings } = await this.getArgs(options); | ||
| const { formData, responseFormat, warnings } = await this.getArgs(options); | ||
| const successfulResponseHandler = responseFormat === "text" ? groqTextTranscriptionResponseHandler : createJsonResponseHandler2(groqTranscriptionResponseSchema); | ||
| const { | ||
@@ -829,5 +832,3 @@ value: response, | ||
| failedResponseHandler: groqFailedResponseHandler, | ||
| successfulResponseHandler: createJsonResponseHandler2( | ||
| groqTranscriptionResponseSchema | ||
| ), | ||
| successfulResponseHandler, | ||
| abortSignal: options.abortSignal, | ||
@@ -879,2 +880,13 @@ fetch: this.config.fetch | ||
| }); | ||
| var binaryResponseHandler = createBinaryResponseHandler(); | ||
| var textDecoder = new TextDecoder(); | ||
| var groqTextTranscriptionResponseHandler = async (options) => { | ||
| const { value, responseHeaders } = await binaryResponseHandler(options); | ||
| const text = textDecoder.decode(value); | ||
| return { | ||
| value: { text }, | ||
| rawValue: text, | ||
| responseHeaders | ||
| }; | ||
| }; | ||
@@ -896,3 +908,3 @@ // src/tool/browser-search.ts | ||
| // src/version.ts | ||
| var VERSION = true ? "2.0.46" : "0.0.0-test"; | ||
| var VERSION = true ? "2.0.47" : "0.0.0-test"; | ||
@@ -899,0 +911,0 @@ // src/groq-provider.ts |
@@ -1,1 +0,1 @@ | ||
| {"version":3,"sources":["../src/groq-provider.ts","../src/groq-chat-language-model.ts","../src/convert-to-groq-chat-messages.ts","../src/get-response-metadata.ts","../src/groq-chat-options.ts","../src/groq-error.ts","../src/groq-prepare-tools.ts","../src/groq-browser-search-models.ts","../src/map-groq-finish-reason.ts","../src/groq-transcription-model.ts","../src/tool/browser-search.ts","../src/groq-tools.ts","../src/version.ts"],"sourcesContent":["import {\n type LanguageModelV2,\n type ProviderV2,\n type TranscriptionModelV2,\n NoSuchModelError,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n loadApiKey,\n withoutTrailingSlash,\n withUserAgentSuffix,\n} from '@ai-sdk/provider-utils';\nimport { GroqChatLanguageModel } from './groq-chat-language-model';\nimport type { GroqChatModelId } from './groq-chat-options';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport { GroqTranscriptionModel } from './groq-transcription-model';\n\nimport { groqTools } from './groq-tools';\nimport { VERSION } from './version';\nexport interface GroqProvider extends ProviderV2 {\n /**\nCreates a model for text generation.\n*/\n (modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates an Groq chat model for text generation.\n */\n languageModel(modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates a model for transcription.\n */\n transcription(modelId: GroqTranscriptionModelId): TranscriptionModelV2;\n\n /**\n * Tools provided by Groq.\n */\n tools: typeof groqTools;\n}\n\nexport interface GroqProviderSettings {\n /**\nBase URL for the Groq API calls.\n */\n baseURL?: string;\n\n /**\nAPI key for authenticating requests.\n */\n apiKey?: string;\n\n /**\nCustom headers to include in the requests.\n */\n headers?: Record<string, string>;\n\n /**\nCustom fetch implementation. You can use it as a middleware to intercept requests,\nor to provide a custom fetch implementation for e.g. testing.\n */\n fetch?: FetchFunction;\n}\n\n/**\nCreate an Groq provider instance.\n */\nexport function createGroq(options: GroqProviderSettings = {}): GroqProvider {\n const baseURL =\n withoutTrailingSlash(options.baseURL) ?? 'https://api.groq.com/openai/v1';\n\n const getHeaders = () =>\n withUserAgentSuffix(\n {\n Authorization: `Bearer ${loadApiKey({\n apiKey: options.apiKey,\n environmentVariableName: 'GROQ_API_KEY',\n description: 'Groq',\n })}`,\n ...options.headers,\n },\n `ai-sdk/groq/${VERSION}`,\n );\n\n const createChatModel = (modelId: GroqChatModelId) =>\n new GroqChatLanguageModel(modelId, {\n provider: 'groq.chat',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n\n const createLanguageModel = (modelId: GroqChatModelId) => {\n if (new.target) {\n throw new Error(\n 'The Groq model function cannot be called with the new keyword.',\n );\n }\n\n return createChatModel(modelId);\n };\n\n const createTranscriptionModel = (modelId: GroqTranscriptionModelId) => {\n return new GroqTranscriptionModel(modelId, {\n provider: 'groq.transcription',\n url: ({ path }) => `${baseURL}${path}`,\n headers: getHeaders,\n fetch: options.fetch,\n });\n };\n\n const provider = function (modelId: GroqChatModelId) {\n return createLanguageModel(modelId);\n };\n\n provider.languageModel = createLanguageModel;\n provider.chat = createChatModel;\n\n provider.textEmbeddingModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'textEmbeddingModel' });\n };\n provider.imageModel = (modelId: string) => {\n throw new NoSuchModelError({ modelId, modelType: 'imageModel' });\n };\n provider.transcription = createTranscriptionModel;\n provider.transcriptionModel = createTranscriptionModel;\n\n provider.tools = groqTools;\n\n return provider;\n}\n\n/**\nDefault Groq provider instance.\n */\nexport const groq = createGroq();\n","import {\n type LanguageModelV2,\n type LanguageModelV2CallWarning,\n type LanguageModelV2Content,\n type LanguageModelV2FinishReason,\n type LanguageModelV2StreamPart,\n type LanguageModelV2Usage,\n type SharedV2ProviderMetadata,\n InvalidResponseDataError,\n LanguageModelV2Prompt,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n type ParseResult,\n combineHeaders,\n createEventSourceResponseHandler,\n createJsonResponseHandler,\n generateId,\n isParsableJson,\n parseProviderOptions,\n postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { convertToGroqChatMessages } from './convert-to-groq-chat-messages';\nimport { getResponseMetadata } from './get-response-metadata';\nimport { type GroqChatModelId, groqProviderOptions } from './groq-chat-options';\nimport { groqErrorDataSchema, groqFailedResponseHandler } from './groq-error';\nimport { prepareTools } from './groq-prepare-tools';\nimport { mapGroqFinishReason } from './map-groq-finish-reason';\n\ntype GroqChatConfig = {\n provider: string;\n headers: () => Record<string, string | undefined>;\n url: (options: { modelId: string; path: string }) => string;\n fetch?: FetchFunction;\n};\n\nexport class GroqChatLanguageModel implements LanguageModelV2 {\n readonly specificationVersion = 'v2';\n\n readonly modelId: GroqChatModelId;\n\n readonly supportedUrls = {\n 'image/*': [/^https?:\\/\\/.*$/],\n };\n\n private readonly config: GroqChatConfig;\n\n constructor(modelId: GroqChatModelId, config: GroqChatConfig) {\n this.modelId = modelId;\n this.config = config;\n }\n\n get provider(): string {\n return this.config.provider;\n }\n\n private async getArgs({\n prompt,\n maxOutputTokens,\n temperature,\n topP,\n topK,\n frequencyPenalty,\n presencePenalty,\n stopSequences,\n responseFormat,\n seed,\n stream,\n tools,\n toolChoice,\n providerOptions,\n }: Parameters<LanguageModelV2['doGenerate']>[0] & {\n stream: boolean;\n }) {\n const warnings: LanguageModelV2CallWarning[] = [];\n\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptions,\n });\n\n const structuredOutputs = groqOptions?.structuredOutputs ?? true;\n\n if (topK != null) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'topK',\n });\n }\n\n if (\n responseFormat?.type === 'json' &&\n responseFormat.schema != null &&\n !structuredOutputs\n ) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'responseFormat',\n details:\n 'JSON response format schema is only supported with structuredOutputs',\n });\n }\n\n const {\n tools: groqTools,\n toolChoice: groqToolChoice,\n toolWarnings,\n } = prepareTools({ tools, toolChoice, modelId: this.modelId });\n\n return {\n args: {\n // model id:\n model: this.modelId,\n\n // model specific settings:\n user: groqOptions?.user,\n parallel_tool_calls: groqOptions?.parallelToolCalls,\n\n // standardized settings:\n max_tokens: maxOutputTokens,\n temperature,\n top_p: topP,\n frequency_penalty: frequencyPenalty,\n presence_penalty: presencePenalty,\n stop: stopSequences,\n seed,\n\n // response format:\n response_format:\n responseFormat?.type === 'json'\n ? structuredOutputs && responseFormat.schema != null\n ? {\n type: 'json_schema',\n json_schema: {\n schema: responseFormat.schema,\n name: responseFormat.name ?? 'response',\n description: responseFormat.description,\n },\n }\n : { type: 'json_object' }\n : undefined,\n\n // provider options:\n reasoning_format: groqOptions?.reasoningFormat,\n reasoning_effort: groqOptions?.reasoningEffort,\n service_tier: groqOptions?.serviceTier,\n\n // messages:\n messages: convertToGroqChatMessages(prompt),\n\n // tools:\n tools: groqTools,\n tool_choice: groqToolChoice,\n },\n warnings: [...warnings, ...toolWarnings],\n };\n }\n\n async doGenerate(\n options: Parameters<LanguageModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {\n const { args, warnings } = await this.getArgs({\n ...options,\n stream: false,\n });\n\n const body = JSON.stringify(args);\n\n const {\n responseHeaders,\n value: response,\n rawValue: rawResponse,\n } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: args,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqChatResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const choice = response.choices[0];\n const content: Array<LanguageModelV2Content> = [];\n\n // text content:\n const text = choice.message.content;\n if (text != null && text.length > 0) {\n content.push({ type: 'text', text: text });\n }\n\n // reasoning:\n const reasoning = choice.message.reasoning;\n if (reasoning != null && reasoning.length > 0) {\n content.push({\n type: 'reasoning',\n text: reasoning,\n });\n }\n\n // tool calls:\n if (choice.message.tool_calls != null) {\n for (const toolCall of choice.message.tool_calls) {\n content.push({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments!,\n });\n }\n }\n\n return {\n content,\n finishReason: mapGroqFinishReason(choice.finish_reason),\n usage: {\n inputTokens: response.usage?.prompt_tokens ?? undefined,\n outputTokens: response.usage?.completion_tokens ?? undefined,\n totalTokens: response.usage?.total_tokens ?? undefined,\n cachedInputTokens:\n response.usage?.prompt_tokens_details?.cached_tokens ?? undefined,\n },\n response: {\n ...getResponseMetadata(response),\n headers: responseHeaders,\n body: rawResponse,\n },\n warnings,\n request: { body },\n };\n }\n\n async doStream(\n options: Parameters<LanguageModelV2['doStream']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {\n const { args, warnings } = await this.getArgs({ ...options, stream: true });\n\n const body = JSON.stringify({ ...args, stream: true });\n\n const { responseHeaders, value: response } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: {\n ...args,\n stream: true,\n },\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler:\n createEventSourceResponseHandler(groqChatChunkSchema),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: {\n name: string;\n arguments: string;\n };\n hasFinished: boolean;\n }> = [];\n\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n const usage: LanguageModelV2Usage = {\n inputTokens: undefined,\n outputTokens: undefined,\n totalTokens: undefined,\n cachedInputTokens: undefined,\n };\n let isFirstChunk = true;\n let isActiveText = false;\n let isActiveReasoning = false;\n\n let providerMetadata: SharedV2ProviderMetadata | undefined;\n return {\n stream: response.pipeThrough(\n new TransformStream<\n ParseResult<z.infer<typeof groqChatChunkSchema>>,\n LanguageModelV2StreamPart\n >({\n start(controller) {\n controller.enqueue({ type: 'stream-start', warnings });\n },\n\n transform(chunk, controller) {\n // Emit raw chunk if requested (before anything else)\n if (options.includeRawChunks) {\n controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });\n }\n\n // handle failed chunk parsing / validation:\n if (!chunk.success) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: chunk.error });\n return;\n }\n\n const value = chunk.value;\n\n // handle error chunks:\n if ('error' in value) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: value.error });\n return;\n }\n\n if (isFirstChunk) {\n isFirstChunk = false;\n\n controller.enqueue({\n type: 'response-metadata',\n ...getResponseMetadata(value),\n });\n }\n\n if (value.x_groq?.usage != null) {\n usage.inputTokens = value.x_groq.usage.prompt_tokens ?? undefined;\n usage.outputTokens =\n value.x_groq.usage.completion_tokens ?? undefined;\n usage.totalTokens = value.x_groq.usage.total_tokens ?? undefined;\n usage.cachedInputTokens =\n value.x_groq.usage.prompt_tokens_details?.cached_tokens ??\n undefined;\n }\n\n const choice = value.choices[0];\n\n if (choice?.finish_reason != null) {\n finishReason = mapGroqFinishReason(choice.finish_reason);\n }\n\n if (choice?.delta == null) {\n return;\n }\n\n const delta = choice.delta;\n\n if (delta.reasoning != null && delta.reasoning.length > 0) {\n if (!isActiveReasoning) {\n controller.enqueue({\n type: 'reasoning-start',\n id: 'reasoning-0',\n });\n isActiveReasoning = true;\n }\n\n controller.enqueue({\n type: 'reasoning-delta',\n id: 'reasoning-0',\n delta: delta.reasoning,\n });\n }\n\n if (delta.content != null && delta.content.length > 0) {\n if (!isActiveText) {\n controller.enqueue({ type: 'text-start', id: 'txt-0' });\n isActiveText = true;\n }\n\n controller.enqueue({\n type: 'text-delta',\n id: 'txt-0',\n delta: delta.content,\n });\n }\n\n if (delta.tool_calls != null) {\n for (const toolCallDelta of delta.tool_calls) {\n const index = toolCallDelta.index;\n\n if (toolCalls[index] == null) {\n if (toolCallDelta.type !== 'function') {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function' type.`,\n });\n }\n\n if (toolCallDelta.id == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'id' to be a string.`,\n });\n }\n\n if (toolCallDelta.function?.name == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function.name' to be a string.`,\n });\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: toolCallDelta.id,\n toolName: toolCallDelta.function.name,\n });\n\n toolCalls[index] = {\n id: toolCallDelta.id,\n type: 'function',\n function: {\n name: toolCallDelta.function.name,\n arguments: toolCallDelta.function.arguments ?? '',\n },\n hasFinished: false,\n };\n\n const toolCall = toolCalls[index];\n\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null\n ) {\n // send delta if the argument text has already started:\n if (toolCall.function.arguments.length > 0) {\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCall.function.arguments,\n });\n }\n\n // check if tool call is complete\n // (some providers send the full tool call in one chunk):\n if (isParsableJson(toolCall.function.arguments)) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n\n continue;\n }\n\n // existing tool call, merge if not finished\n const toolCall = toolCalls[index];\n\n if (toolCall.hasFinished) {\n continue;\n }\n\n if (toolCallDelta.function?.arguments != null) {\n toolCall.function!.arguments +=\n toolCallDelta.function?.arguments ?? '';\n }\n\n // send delta\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCallDelta.function.arguments ?? '',\n });\n\n // check if tool call is complete\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null &&\n isParsableJson(toolCall.function.arguments)\n ) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n }\n },\n\n flush(controller) {\n if (isActiveReasoning) {\n controller.enqueue({ type: 'reasoning-end', id: 'reasoning-0' });\n }\n\n if (isActiveText) {\n controller.enqueue({ type: 'text-end', id: 'txt-0' });\n }\n\n controller.enqueue({\n type: 'finish',\n finishReason,\n usage,\n ...(providerMetadata != null ? { providerMetadata } : {}),\n });\n },\n }),\n ),\n request: { body },\n response: { headers: responseHeaders },\n };\n }\n}\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatResponseSchema = z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n message: z.object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n id: z.string().nullish(),\n type: z.literal('function'),\n function: z.object({\n name: z.string(),\n arguments: z.string(),\n }),\n }),\n )\n .nullish(),\n }),\n index: z.number(),\n finish_reason: z.string().nullish(),\n }),\n ),\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n});\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatChunkSchema = z.union([\n z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n delta: z\n .object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n index: z.number(),\n id: z.string().nullish(),\n type: z.literal('function').optional(),\n function: z.object({\n name: z.string().nullish(),\n arguments: z.string().nullish(),\n }),\n }),\n )\n .nullish(),\n })\n .nullish(),\n finish_reason: z.string().nullable().optional(),\n index: z.number(),\n }),\n ),\n x_groq: z\n .object({\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n })\n .nullish(),\n }),\n groqErrorDataSchema,\n]);\n","import {\n type LanguageModelV2Prompt,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport type { GroqChatPrompt } from './groq-api-types';\nimport { convertToBase64 } from '@ai-sdk/provider-utils';\n\nexport function convertToGroqChatMessages(\n prompt: LanguageModelV2Prompt,\n): GroqChatPrompt {\n const messages: GroqChatPrompt = [];\n\n for (const { role, content } of prompt) {\n switch (role) {\n case 'system': {\n messages.push({ role: 'system', content });\n break;\n }\n\n case 'user': {\n if (content.length === 1 && content[0].type === 'text') {\n messages.push({ role: 'user', content: content[0].text });\n break;\n }\n\n messages.push({\n role: 'user',\n content: content.map(part => {\n switch (part.type) {\n case 'text': {\n return { type: 'text', text: part.text };\n }\n case 'file': {\n if (!part.mediaType.startsWith('image/')) {\n throw new UnsupportedFunctionalityError({\n functionality: 'Non-image file content parts',\n });\n }\n\n const mediaType =\n part.mediaType === 'image/*' ? 'image/jpeg' : part.mediaType;\n\n return {\n type: 'image_url',\n image_url: {\n url:\n part.data instanceof URL\n ? part.data.toString()\n : `data:${mediaType};base64,${convertToBase64(part.data)}`,\n },\n };\n }\n }\n }),\n });\n\n break;\n }\n\n case 'assistant': {\n let text = '';\n let reasoning = '';\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: { name: string; arguments: string };\n }> = [];\n\n for (const part of content) {\n switch (part.type) {\n // groq supports reasoning for tool-calls in multi-turn conversations\n // https://github.com/vercel/ai/issues/7860\n case 'reasoning': {\n reasoning += part.text;\n break;\n }\n\n case 'text': {\n text += part.text;\n break;\n }\n\n case 'tool-call': {\n toolCalls.push({\n id: part.toolCallId,\n type: 'function',\n function: {\n name: part.toolName,\n arguments: JSON.stringify(part.input),\n },\n });\n break;\n }\n }\n }\n\n messages.push({\n role: 'assistant',\n content: text,\n ...(reasoning.length > 0 ? { reasoning } : null),\n ...(toolCalls.length > 0 ? { tool_calls: toolCalls } : null),\n });\n\n break;\n }\n\n case 'tool': {\n for (const toolResponse of content) {\n const output = toolResponse.output;\n\n let contentValue: string;\n switch (output.type) {\n case 'text':\n case 'error-text':\n contentValue = output.value;\n break;\n case 'content':\n case 'json':\n case 'error-json':\n contentValue = JSON.stringify(output.value);\n break;\n }\n\n messages.push({\n role: 'tool',\n tool_call_id: toolResponse.toolCallId,\n content: contentValue,\n });\n }\n break;\n }\n\n default: {\n const _exhaustiveCheck: never = role;\n throw new Error(`Unsupported role: ${_exhaustiveCheck}`);\n }\n }\n }\n\n return messages;\n}\n","export function getResponseMetadata({\n id,\n model,\n created,\n}: {\n id?: string | undefined | null;\n created?: number | undefined | null;\n model?: string | undefined | null;\n}) {\n return {\n id: id ?? undefined,\n modelId: model ?? undefined,\n timestamp: created != null ? new Date(created * 1000) : undefined,\n };\n}\n","import { z } from 'zod/v4';\n\n// https://console.groq.com/docs/models\nexport type GroqChatModelId =\n // production models\n | 'gemma2-9b-it'\n | 'llama-3.1-8b-instant'\n | 'llama-3.3-70b-versatile'\n | 'meta-llama/llama-guard-4-12b'\n | 'openai/gpt-oss-120b'\n | 'openai/gpt-oss-20b'\n // preview models (selection)\n | 'deepseek-r1-distill-llama-70b'\n | 'meta-llama/llama-4-maverick-17b-128e-instruct'\n | 'meta-llama/llama-4-scout-17b-16e-instruct'\n | 'meta-llama/llama-prompt-guard-2-22m'\n | 'meta-llama/llama-prompt-guard-2-86m'\n | 'moonshotai/kimi-k2-instruct-0905'\n | 'qwen/qwen3-32b'\n | 'llama-guard-3-8b'\n | 'llama3-70b-8192'\n | 'llama3-8b-8192'\n | 'mixtral-8x7b-32768'\n | 'qwen-qwq-32b'\n | 'qwen-2.5-32b'\n | 'deepseek-r1-distill-qwen-32b'\n | (string & {});\n\nexport const groqProviderOptions = z.object({\n reasoningFormat: z.enum(['parsed', 'raw', 'hidden']).optional(),\n\n /**\n * Specifies the reasoning effort level for model inference.\n * @see https://console.groq.com/docs/reasoning#reasoning-effort\n */\n reasoningEffort: z\n .enum(['none', 'default', 'low', 'medium', 'high'])\n .optional(),\n\n /**\n * Whether to enable parallel function calling during tool use. Default to true.\n */\n parallelToolCalls: z.boolean().optional(),\n\n /**\n * A unique identifier representing your end-user, which can help OpenAI to\n * monitor and detect abuse. Learn more.\n */\n user: z.string().optional(),\n\n /**\n * Whether to use structured outputs.\n *\n * @default true\n */\n structuredOutputs: z.boolean().optional(),\n\n /**\n * Service tier for the request.\n * - 'on_demand': Default tier with consistent performance and fairness\n * - 'flex': Higher throughput tier optimized for workloads that can handle occasional request failures\n * - 'auto': Uses on_demand rate limits, then falls back to flex tier if exceeded\n *\n * @default 'on_demand'\n */\n serviceTier: z.enum(['on_demand', 'flex', 'auto']).optional(),\n});\n\nexport type GroqProviderOptions = z.infer<typeof groqProviderOptions>;\n","import { z } from 'zod/v4';\nimport { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\n\nexport const groqErrorDataSchema = z.object({\n error: z.object({\n message: z.string(),\n type: z.string(),\n }),\n});\n\nexport type GroqErrorData = z.infer<typeof groqErrorDataSchema>;\n\nexport const groqFailedResponseHandler = createJsonErrorResponseHandler({\n errorSchema: groqErrorDataSchema,\n errorToMessage: data => data.error.message,\n});\n","import {\n type LanguageModelV2CallOptions,\n type LanguageModelV2CallWarning,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport {\n getSupportedModelsString,\n isBrowserSearchSupportedModel,\n} from './groq-browser-search-models';\nimport type { GroqChatModelId } from './groq-chat-options';\n\nexport function prepareTools({\n tools,\n toolChoice,\n modelId,\n}: {\n tools: LanguageModelV2CallOptions['tools'];\n toolChoice?: LanguageModelV2CallOptions['toolChoice'];\n modelId: GroqChatModelId;\n}): {\n tools:\n | undefined\n | Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n >;\n toolChoice:\n | { type: 'function'; function: { name: string } }\n | 'auto'\n | 'none'\n | 'required'\n | undefined;\n toolWarnings: LanguageModelV2CallWarning[];\n} {\n // when the tools array is empty, change it to undefined to prevent errors:\n tools = tools?.length ? tools : undefined;\n\n const toolWarnings: LanguageModelV2CallWarning[] = [];\n\n if (tools == null) {\n return { tools: undefined, toolChoice: undefined, toolWarnings };\n }\n\n const groqTools: Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n > = [];\n\n for (const tool of tools) {\n if (tool.type === 'provider-defined') {\n if (tool.id === 'groq.browser_search') {\n if (!isBrowserSearchSupportedModel(modelId)) {\n toolWarnings.push({\n type: 'unsupported-tool',\n tool,\n details: `Browser search is only supported on the following models: ${getSupportedModelsString()}. Current model: ${modelId}`,\n });\n } else {\n groqTools.push({\n type: 'browser_search',\n });\n }\n } else {\n toolWarnings.push({ type: 'unsupported-tool', tool });\n }\n } else {\n groqTools.push({\n type: 'function',\n function: {\n name: tool.name,\n description: tool.description,\n parameters: tool.inputSchema,\n },\n });\n }\n }\n\n if (toolChoice == null) {\n return { tools: groqTools, toolChoice: undefined, toolWarnings };\n }\n\n const type = toolChoice.type;\n\n switch (type) {\n case 'auto':\n case 'none':\n case 'required':\n return { tools: groqTools, toolChoice: type, toolWarnings };\n case 'tool':\n return {\n tools: groqTools,\n toolChoice: {\n type: 'function',\n function: {\n name: toolChoice.toolName,\n },\n },\n toolWarnings,\n };\n default: {\n const _exhaustiveCheck: never = type;\n throw new UnsupportedFunctionalityError({\n functionality: `tool choice type: ${_exhaustiveCheck}`,\n });\n }\n }\n}\n","import type { GroqChatModelId } from './groq-chat-options';\n\n/**\n * Models that support browser search functionality.\n * Based on: https://console.groq.com/docs/browser-search\n */\nexport const BROWSER_SEARCH_SUPPORTED_MODELS: readonly GroqChatModelId[] = [\n 'openai/gpt-oss-20b',\n 'openai/gpt-oss-120b',\n] as const;\n\n/**\n * Check if a model supports browser search functionality.\n */\nexport function isBrowserSearchSupportedModel(\n modelId: GroqChatModelId,\n): boolean {\n return BROWSER_SEARCH_SUPPORTED_MODELS.includes(modelId);\n}\n\n/**\n * Get a formatted list of supported models for error messages.\n */\nexport function getSupportedModelsString(): string {\n return BROWSER_SEARCH_SUPPORTED_MODELS.join(', ');\n}\n","import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';\n\nexport function mapGroqFinishReason(\n finishReason: string | null | undefined,\n): LanguageModelV2FinishReason {\n switch (finishReason) {\n case 'stop':\n return 'stop';\n case 'length':\n return 'length';\n case 'content_filter':\n return 'content-filter';\n case 'function_call':\n case 'tool_calls':\n return 'tool-calls';\n default:\n return 'unknown';\n }\n}\n","import type {\n TranscriptionModelV2,\n TranscriptionModelV2CallWarning,\n} from '@ai-sdk/provider';\nimport {\n combineHeaders,\n convertBase64ToUint8Array,\n createJsonResponseHandler,\n mediaTypeToExtension,\n parseProviderOptions,\n postFormDataToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport type { GroqConfig } from './groq-config';\nimport { groqFailedResponseHandler } from './groq-error';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport type { GroqTranscriptionAPITypes } from './groq-api-types';\n\n// https://console.groq.com/docs/speech-to-text\nconst groqProviderOptionsSchema = z.object({\n language: z.string().nullish(),\n prompt: z.string().nullish(),\n responseFormat: z.string().nullish(),\n temperature: z.number().min(0).max(1).nullish(),\n timestampGranularities: z.array(z.string()).nullish(),\n});\n\nexport type GroqTranscriptionCallOptions = z.infer<\n typeof groqProviderOptionsSchema\n>;\n\ninterface GroqTranscriptionModelConfig extends GroqConfig {\n _internal?: {\n currentDate?: () => Date;\n };\n}\n\nexport class GroqTranscriptionModel implements TranscriptionModelV2 {\n readonly specificationVersion = 'v2';\n\n get provider(): string {\n return this.config.provider;\n }\n\n constructor(\n readonly modelId: GroqTranscriptionModelId,\n private readonly config: GroqTranscriptionModelConfig,\n ) {}\n\n private async getArgs({\n audio,\n mediaType,\n providerOptions,\n }: Parameters<TranscriptionModelV2['doGenerate']>[0]) {\n const warnings: TranscriptionModelV2CallWarning[] = [];\n\n // Parse provider options\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptionsSchema,\n });\n\n // Create form data with base fields\n const formData = new FormData();\n const blob =\n audio instanceof Uint8Array\n ? new Blob([audio])\n : new Blob([convertBase64ToUint8Array(audio)]);\n\n formData.append('model', this.modelId);\n const fileExtension = mediaTypeToExtension(mediaType);\n formData.append(\n 'file',\n new File([blob], 'audio', { type: mediaType }),\n `audio.${fileExtension}`,\n );\n\n // Add provider-specific options\n if (groqOptions) {\n const transcriptionModelOptions: Omit<\n GroqTranscriptionAPITypes,\n 'model'\n > = {\n language: groqOptions.language ?? undefined,\n prompt: groqOptions.prompt ?? undefined,\n response_format: groqOptions.responseFormat ?? undefined,\n temperature: groqOptions.temperature ?? undefined,\n timestamp_granularities:\n groqOptions.timestampGranularities ?? undefined,\n };\n\n for (const key in transcriptionModelOptions) {\n const value =\n transcriptionModelOptions[\n key as keyof Omit<GroqTranscriptionAPITypes, 'model'>\n ];\n if (value !== undefined) {\n formData.append(key, String(value));\n }\n }\n }\n\n return {\n formData,\n warnings,\n };\n }\n\n async doGenerate(\n options: Parameters<TranscriptionModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<TranscriptionModelV2['doGenerate']>>> {\n const currentDate = this.config._internal?.currentDate?.() ?? new Date();\n const { formData, warnings } = await this.getArgs(options);\n\n const {\n value: response,\n responseHeaders,\n rawValue: rawResponse,\n } = await postFormDataToApi({\n url: this.config.url({\n path: '/audio/transcriptions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n formData,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqTranscriptionResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n return {\n text: response.text,\n segments:\n response.segments?.map(segment => ({\n text: segment.text,\n startSecond: segment.start,\n endSecond: segment.end,\n })) ?? [],\n language: response.language ?? undefined,\n durationInSeconds: response.duration ?? undefined,\n warnings,\n response: {\n timestamp: currentDate,\n modelId: this.modelId,\n headers: responseHeaders,\n body: rawResponse,\n },\n };\n }\n}\n\nconst groqTranscriptionResponseSchema = z.object({\n text: z.string(),\n x_groq: z.object({\n id: z.string(),\n }),\n // additional properties are returned when `response_format: 'verbose_json'` is\n task: z.string().nullish(),\n language: z.string().nullish(),\n duration: z.number().nullish(),\n segments: z\n .array(\n z.object({\n id: z.number(),\n seek: z.number(),\n start: z.number(),\n end: z.number(),\n text: z.string(),\n tokens: z.array(z.number()),\n temperature: z.number(),\n avg_logprob: z.number(),\n compression_ratio: z.number(),\n no_speech_prob: z.number(),\n }),\n )\n .nullish(),\n});\n","import { createProviderDefinedToolFactory } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\n/**\n * Browser search tool for Groq models.\n *\n * Provides interactive browser search capabilities that go beyond traditional web search\n * by navigating websites interactively and providing more detailed results.\n *\n * Currently supported on:\n * - openai/gpt-oss-20b\n * - openai/gpt-oss-120b\n *\n * @see https://console.groq.com/docs/browser-search\n */\nexport const browserSearch = createProviderDefinedToolFactory<\n {\n // Browser search doesn't take input parameters - it's controlled by the prompt\n // The tool is activated automatically when included in the tools array\n },\n {\n // No configuration options needed - the tool works automatically\n // when included in the tools array for supported models\n }\n>({\n id: 'groq.browser_search',\n name: 'browser_search',\n inputSchema: z.object({}),\n});\n","import { browserSearch } from './tool/browser-search';\n\nexport const groqTools = {\n browserSearch,\n};\n","// Version string of this package injected at build time.\ndeclare const __PACKAGE_VERSION__: string | undefined;\nexport const VERSION: string =\n typeof __PACKAGE_VERSION__ !== 'undefined'\n ? __PACKAGE_VERSION__\n : 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| {"version":3,"sources":["../src/groq-provider.ts","../src/groq-chat-language-model.ts","../src/convert-to-groq-chat-messages.ts","../src/get-response-metadata.ts","../src/groq-chat-options.ts","../src/groq-error.ts","../src/groq-prepare-tools.ts","../src/groq-browser-search-models.ts","../src/map-groq-finish-reason.ts","../src/groq-transcription-model.ts","../src/tool/browser-search.ts","../src/groq-tools.ts","../src/version.ts"],"sourcesContent":["import {\n type LanguageModelV2,\n type ProviderV2,\n type TranscriptionModelV2,\n NoSuchModelError,\n} from '@ai-sdk/provider';\nimport {\n type FetchFunction,\n loadApiKey,\n withoutTrailingSlash,\n withUserAgentSuffix,\n} from '@ai-sdk/provider-utils';\nimport { GroqChatLanguageModel } from './groq-chat-language-model';\nimport type { GroqChatModelId } from './groq-chat-options';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport { GroqTranscriptionModel } from './groq-transcription-model';\n\nimport { groqTools } from './groq-tools';\nimport { VERSION } from './version';\nexport interface GroqProvider extends ProviderV2 {\n /**\nCreates a model for text generation.\n*/\n (modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates an Groq chat model for text generation.\n */\n languageModel(modelId: GroqChatModelId): LanguageModelV2;\n\n /**\nCreates a model for transcription.\n */\n transcription(modelId: GroqTranscriptionModelId): TranscriptionModelV2;\n\n /**\n * Tools provided by Groq.\n */\n tools: typeof groqTools;\n}\n\nexport interface GroqProviderSettings {\n /**\nBase URL for the Groq API calls.\n */\n baseURL?: string;\n\n /**\nAPI key for authenticating requests.\n */\n apiKey?: string;\n\n /**\nCustom headers to include in the requests.\n */\n headers?: Record<string, string>;\n\n /**\nCustom fetch implementation. 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true;\n\n if (topK != null) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'topK',\n });\n }\n\n if (\n responseFormat?.type === 'json' &&\n responseFormat.schema != null &&\n !structuredOutputs\n ) {\n warnings.push({\n type: 'unsupported-setting',\n setting: 'responseFormat',\n details:\n 'JSON response format schema is only supported with structuredOutputs',\n });\n }\n\n const {\n tools: groqTools,\n toolChoice: groqToolChoice,\n toolWarnings,\n } = prepareTools({ tools, toolChoice, modelId: this.modelId });\n\n return {\n args: {\n // model id:\n model: this.modelId,\n\n // model specific settings:\n user: groqOptions?.user,\n parallel_tool_calls: groqOptions?.parallelToolCalls,\n\n // standardized settings:\n max_tokens: maxOutputTokens,\n temperature,\n top_p: topP,\n frequency_penalty: frequencyPenalty,\n presence_penalty: presencePenalty,\n stop: stopSequences,\n seed,\n\n // response format:\n response_format:\n responseFormat?.type === 'json'\n ? structuredOutputs && responseFormat.schema != null\n ? {\n type: 'json_schema',\n json_schema: {\n schema: responseFormat.schema,\n name: responseFormat.name ?? 'response',\n description: responseFormat.description,\n },\n }\n : { type: 'json_object' }\n : undefined,\n\n // provider options:\n reasoning_format: groqOptions?.reasoningFormat,\n reasoning_effort: groqOptions?.reasoningEffort,\n service_tier: groqOptions?.serviceTier,\n\n // messages:\n messages: convertToGroqChatMessages(prompt),\n\n // tools:\n tools: groqTools,\n tool_choice: groqToolChoice,\n },\n warnings: [...warnings, ...toolWarnings],\n };\n }\n\n async doGenerate(\n options: Parameters<LanguageModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {\n const { args, warnings } = await this.getArgs({\n ...options,\n stream: false,\n });\n\n const body = JSON.stringify(args);\n\n const {\n responseHeaders,\n value: response,\n rawValue: rawResponse,\n } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: args,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler: createJsonResponseHandler(\n groqChatResponseSchema,\n ),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const choice = response.choices[0];\n const content: Array<LanguageModelV2Content> = [];\n\n // text content:\n const text = choice.message.content;\n if (text != null && text.length > 0) {\n content.push({ type: 'text', text: text });\n }\n\n // reasoning:\n const reasoning = choice.message.reasoning;\n if (reasoning != null && reasoning.length > 0) {\n content.push({\n type: 'reasoning',\n text: reasoning,\n });\n }\n\n // tool calls:\n if (choice.message.tool_calls != null) {\n for (const toolCall of choice.message.tool_calls) {\n content.push({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments!,\n });\n }\n }\n\n return {\n content,\n finishReason: mapGroqFinishReason(choice.finish_reason),\n usage: {\n inputTokens: response.usage?.prompt_tokens ?? undefined,\n outputTokens: response.usage?.completion_tokens ?? undefined,\n totalTokens: response.usage?.total_tokens ?? undefined,\n cachedInputTokens:\n response.usage?.prompt_tokens_details?.cached_tokens ?? undefined,\n },\n response: {\n ...getResponseMetadata(response),\n headers: responseHeaders,\n body: rawResponse,\n },\n warnings,\n request: { body },\n };\n }\n\n async doStream(\n options: Parameters<LanguageModelV2['doStream']>[0],\n ): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {\n const { args, warnings } = await this.getArgs({ ...options, stream: true });\n\n const body = JSON.stringify({ ...args, stream: true });\n\n const { responseHeaders, value: response } = await postJsonToApi({\n url: this.config.url({\n path: '/chat/completions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n body: {\n ...args,\n stream: true,\n },\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler:\n createEventSourceResponseHandler(groqChatChunkSchema),\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: {\n name: string;\n arguments: string;\n };\n hasFinished: boolean;\n }> = [];\n\n let finishReason: LanguageModelV2FinishReason = 'unknown';\n const usage: LanguageModelV2Usage = {\n inputTokens: undefined,\n outputTokens: undefined,\n totalTokens: undefined,\n cachedInputTokens: undefined,\n };\n let isFirstChunk = true;\n let isActiveText = false;\n let isActiveReasoning = false;\n\n let providerMetadata: SharedV2ProviderMetadata | undefined;\n return {\n stream: response.pipeThrough(\n new TransformStream<\n ParseResult<z.infer<typeof groqChatChunkSchema>>,\n LanguageModelV2StreamPart\n >({\n start(controller) {\n controller.enqueue({ type: 'stream-start', warnings });\n },\n\n transform(chunk, controller) {\n // Emit raw chunk if requested (before anything else)\n if (options.includeRawChunks) {\n controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });\n }\n\n // handle failed chunk parsing / validation:\n if (!chunk.success) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: chunk.error });\n return;\n }\n\n const value = chunk.value;\n\n // handle error chunks:\n if ('error' in value) {\n finishReason = 'error';\n controller.enqueue({ type: 'error', error: value.error });\n return;\n }\n\n if (isFirstChunk) {\n isFirstChunk = false;\n\n controller.enqueue({\n type: 'response-metadata',\n ...getResponseMetadata(value),\n });\n }\n\n if (value.x_groq?.usage != null) {\n usage.inputTokens = value.x_groq.usage.prompt_tokens ?? undefined;\n usage.outputTokens =\n value.x_groq.usage.completion_tokens ?? undefined;\n usage.totalTokens = value.x_groq.usage.total_tokens ?? undefined;\n usage.cachedInputTokens =\n value.x_groq.usage.prompt_tokens_details?.cached_tokens ??\n undefined;\n }\n\n const choice = value.choices[0];\n\n if (choice?.finish_reason != null) {\n finishReason = mapGroqFinishReason(choice.finish_reason);\n }\n\n if (choice?.delta == null) {\n return;\n }\n\n const delta = choice.delta;\n\n if (delta.reasoning != null && delta.reasoning.length > 0) {\n if (!isActiveReasoning) {\n controller.enqueue({\n type: 'reasoning-start',\n id: 'reasoning-0',\n });\n isActiveReasoning = true;\n }\n\n controller.enqueue({\n type: 'reasoning-delta',\n id: 'reasoning-0',\n delta: delta.reasoning,\n });\n }\n\n if (delta.content != null && delta.content.length > 0) {\n if (!isActiveText) {\n controller.enqueue({ type: 'text-start', id: 'txt-0' });\n isActiveText = true;\n }\n\n controller.enqueue({\n type: 'text-delta',\n id: 'txt-0',\n delta: delta.content,\n });\n }\n\n if (delta.tool_calls != null) {\n for (const toolCallDelta of delta.tool_calls) {\n const index = toolCallDelta.index;\n\n if (toolCalls[index] == null) {\n if (toolCallDelta.type !== 'function') {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function' type.`,\n });\n }\n\n if (toolCallDelta.id == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'id' to be a string.`,\n });\n }\n\n if (toolCallDelta.function?.name == null) {\n throw new InvalidResponseDataError({\n data: toolCallDelta,\n message: `Expected 'function.name' to be a string.`,\n });\n }\n\n controller.enqueue({\n type: 'tool-input-start',\n id: toolCallDelta.id,\n toolName: toolCallDelta.function.name,\n });\n\n toolCalls[index] = {\n id: toolCallDelta.id,\n type: 'function',\n function: {\n name: toolCallDelta.function.name,\n arguments: toolCallDelta.function.arguments ?? '',\n },\n hasFinished: false,\n };\n\n const toolCall = toolCalls[index];\n\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null\n ) {\n // send delta if the argument text has already started:\n if (toolCall.function.arguments.length > 0) {\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCall.function.arguments,\n });\n }\n\n // check if tool call is complete\n // (some providers send the full tool call in one chunk):\n if (isParsableJson(toolCall.function.arguments)) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n\n continue;\n }\n\n // existing tool call, merge if not finished\n const toolCall = toolCalls[index];\n\n if (toolCall.hasFinished) {\n continue;\n }\n\n if (toolCallDelta.function?.arguments != null) {\n toolCall.function!.arguments +=\n toolCallDelta.function?.arguments ?? '';\n }\n\n // send delta\n controller.enqueue({\n type: 'tool-input-delta',\n id: toolCall.id,\n delta: toolCallDelta.function.arguments ?? '',\n });\n\n // check if tool call is complete\n if (\n toolCall.function?.name != null &&\n toolCall.function?.arguments != null &&\n isParsableJson(toolCall.function.arguments)\n ) {\n controller.enqueue({\n type: 'tool-input-end',\n id: toolCall.id,\n });\n\n controller.enqueue({\n type: 'tool-call',\n toolCallId: toolCall.id ?? generateId(),\n toolName: toolCall.function.name,\n input: toolCall.function.arguments,\n });\n toolCall.hasFinished = true;\n }\n }\n }\n },\n\n flush(controller) {\n if (isActiveReasoning) {\n controller.enqueue({ type: 'reasoning-end', id: 'reasoning-0' });\n }\n\n if (isActiveText) {\n controller.enqueue({ type: 'text-end', id: 'txt-0' });\n }\n\n controller.enqueue({\n type: 'finish',\n finishReason,\n usage,\n ...(providerMetadata != null ? { providerMetadata } : {}),\n });\n },\n }),\n ),\n request: { body },\n response: { headers: responseHeaders },\n };\n }\n}\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatResponseSchema = z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n message: z.object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n id: z.string().nullish(),\n type: z.literal('function'),\n function: z.object({\n name: z.string(),\n arguments: z.string(),\n }),\n }),\n )\n .nullish(),\n }),\n index: z.number(),\n finish_reason: z.string().nullish(),\n }),\n ),\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n});\n\n// limited version of the schema, focussed on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst groqChatChunkSchema = z.union([\n z.object({\n id: z.string().nullish(),\n created: z.number().nullish(),\n model: z.string().nullish(),\n choices: z.array(\n z.object({\n delta: z\n .object({\n content: z.string().nullish(),\n reasoning: z.string().nullish(),\n tool_calls: z\n .array(\n z.object({\n index: z.number(),\n id: z.string().nullish(),\n type: z.literal('function').optional(),\n function: z.object({\n name: z.string().nullish(),\n arguments: z.string().nullish(),\n }),\n }),\n )\n .nullish(),\n })\n .nullish(),\n finish_reason: z.string().nullable().optional(),\n index: z.number(),\n }),\n ),\n x_groq: z\n .object({\n usage: z\n .object({\n prompt_tokens: z.number().nullish(),\n completion_tokens: z.number().nullish(),\n total_tokens: z.number().nullish(),\n prompt_tokens_details: z\n .object({\n cached_tokens: z.number().nullish(),\n })\n .nullish(),\n })\n .nullish(),\n })\n .nullish(),\n }),\n groqErrorDataSchema,\n]);\n","import {\n type LanguageModelV2Prompt,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport type { GroqChatPrompt } from './groq-api-types';\nimport { convertToBase64 } from '@ai-sdk/provider-utils';\n\nexport function convertToGroqChatMessages(\n prompt: LanguageModelV2Prompt,\n): GroqChatPrompt {\n const messages: GroqChatPrompt = [];\n\n for (const { role, content } of prompt) {\n switch (role) {\n case 'system': {\n messages.push({ role: 'system', content });\n break;\n }\n\n case 'user': {\n if (content.length === 1 && content[0].type === 'text') {\n messages.push({ role: 'user', content: content[0].text });\n break;\n }\n\n messages.push({\n role: 'user',\n content: content.map(part => {\n switch (part.type) {\n case 'text': {\n return { type: 'text', text: part.text };\n }\n case 'file': {\n if (!part.mediaType.startsWith('image/')) {\n throw new UnsupportedFunctionalityError({\n functionality: 'Non-image file content parts',\n });\n }\n\n const mediaType =\n part.mediaType === 'image/*' ? 'image/jpeg' : part.mediaType;\n\n return {\n type: 'image_url',\n image_url: {\n url:\n part.data instanceof URL\n ? part.data.toString()\n : `data:${mediaType};base64,${convertToBase64(part.data)}`,\n },\n };\n }\n }\n }),\n });\n\n break;\n }\n\n case 'assistant': {\n let text = '';\n let reasoning = '';\n const toolCalls: Array<{\n id: string;\n type: 'function';\n function: { name: string; arguments: string };\n }> = [];\n\n for (const part of content) {\n switch (part.type) {\n // groq supports reasoning for tool-calls in multi-turn conversations\n // https://github.com/vercel/ai/issues/7860\n case 'reasoning': {\n reasoning += part.text;\n break;\n }\n\n case 'text': {\n text += part.text;\n break;\n }\n\n case 'tool-call': {\n toolCalls.push({\n id: part.toolCallId,\n type: 'function',\n function: {\n name: part.toolName,\n arguments: JSON.stringify(part.input),\n },\n });\n break;\n }\n }\n }\n\n messages.push({\n role: 'assistant',\n content: text,\n ...(reasoning.length > 0 ? { reasoning } : null),\n ...(toolCalls.length > 0 ? { tool_calls: toolCalls } : null),\n });\n\n break;\n }\n\n case 'tool': {\n for (const toolResponse of content) {\n const output = toolResponse.output;\n\n let contentValue: string;\n switch (output.type) {\n case 'text':\n case 'error-text':\n contentValue = output.value;\n break;\n case 'content':\n case 'json':\n case 'error-json':\n contentValue = JSON.stringify(output.value);\n break;\n }\n\n messages.push({\n role: 'tool',\n tool_call_id: toolResponse.toolCallId,\n content: contentValue,\n });\n }\n break;\n }\n\n default: {\n const _exhaustiveCheck: never = role;\n throw new Error(`Unsupported role: ${_exhaustiveCheck}`);\n }\n }\n }\n\n return messages;\n}\n","export function getResponseMetadata({\n id,\n model,\n created,\n}: {\n id?: string | undefined | null;\n created?: number | undefined | null;\n model?: string | undefined | null;\n}) {\n return {\n id: id ?? undefined,\n modelId: model ?? undefined,\n timestamp: created != null ? new Date(created * 1000) : undefined,\n };\n}\n","import { z } from 'zod/v4';\n\n// https://console.groq.com/docs/models\nexport type GroqChatModelId =\n // production models\n | 'gemma2-9b-it'\n | 'llama-3.1-8b-instant'\n | 'llama-3.3-70b-versatile'\n | 'meta-llama/llama-guard-4-12b'\n | 'openai/gpt-oss-120b'\n | 'openai/gpt-oss-20b'\n // preview models (selection)\n | 'deepseek-r1-distill-llama-70b'\n | 'meta-llama/llama-4-maverick-17b-128e-instruct'\n | 'meta-llama/llama-4-scout-17b-16e-instruct'\n | 'meta-llama/llama-prompt-guard-2-22m'\n | 'meta-llama/llama-prompt-guard-2-86m'\n | 'moonshotai/kimi-k2-instruct-0905'\n | 'qwen/qwen3-32b'\n | 'llama-guard-3-8b'\n | 'llama3-70b-8192'\n | 'llama3-8b-8192'\n | 'mixtral-8x7b-32768'\n | 'qwen-qwq-32b'\n | 'qwen-2.5-32b'\n | 'deepseek-r1-distill-qwen-32b'\n | (string & {});\n\nexport const groqProviderOptions = z.object({\n reasoningFormat: z.enum(['parsed', 'raw', 'hidden']).optional(),\n\n /**\n * Specifies the reasoning effort level for model inference.\n * @see https://console.groq.com/docs/reasoning#reasoning-effort\n */\n reasoningEffort: z\n .enum(['none', 'default', 'low', 'medium', 'high'])\n .optional(),\n\n /**\n * Whether to enable parallel function calling during tool use. Default to true.\n */\n parallelToolCalls: z.boolean().optional(),\n\n /**\n * A unique identifier representing your end-user, which can help OpenAI to\n * monitor and detect abuse. Learn more.\n */\n user: z.string().optional(),\n\n /**\n * Whether to use structured outputs.\n *\n * @default true\n */\n structuredOutputs: z.boolean().optional(),\n\n /**\n * Service tier for the request.\n * - 'on_demand': Default tier with consistent performance and fairness\n * - 'flex': Higher throughput tier optimized for workloads that can handle occasional request failures\n * - 'auto': Uses on_demand rate limits, then falls back to flex tier if exceeded\n *\n * @default 'on_demand'\n */\n serviceTier: z.enum(['on_demand', 'flex', 'auto']).optional(),\n});\n\nexport type GroqProviderOptions = z.infer<typeof groqProviderOptions>;\n","import { z } from 'zod/v4';\nimport { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\n\nexport const groqErrorDataSchema = z.object({\n error: z.object({\n message: z.string(),\n type: z.string(),\n }),\n});\n\nexport type GroqErrorData = z.infer<typeof groqErrorDataSchema>;\n\nexport const groqFailedResponseHandler = createJsonErrorResponseHandler({\n errorSchema: groqErrorDataSchema,\n errorToMessage: data => data.error.message,\n});\n","import {\n type LanguageModelV2CallOptions,\n type LanguageModelV2CallWarning,\n UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport {\n getSupportedModelsString,\n isBrowserSearchSupportedModel,\n} from './groq-browser-search-models';\nimport type { GroqChatModelId } from './groq-chat-options';\n\nexport function prepareTools({\n tools,\n toolChoice,\n modelId,\n}: {\n tools: LanguageModelV2CallOptions['tools'];\n toolChoice?: LanguageModelV2CallOptions['toolChoice'];\n modelId: GroqChatModelId;\n}): {\n tools:\n | undefined\n | Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n >;\n toolChoice:\n | { type: 'function'; function: { name: string } }\n | 'auto'\n | 'none'\n | 'required'\n | undefined;\n toolWarnings: LanguageModelV2CallWarning[];\n} {\n // when the tools array is empty, change it to undefined to prevent errors:\n tools = tools?.length ? tools : undefined;\n\n const toolWarnings: LanguageModelV2CallWarning[] = [];\n\n if (tools == null) {\n return { tools: undefined, toolChoice: undefined, toolWarnings };\n }\n\n const groqTools: Array<\n | {\n type: 'function';\n function: {\n name: string;\n description: string | undefined;\n parameters: unknown;\n };\n }\n | {\n type: 'browser_search';\n }\n > = [];\n\n for (const tool of tools) {\n if (tool.type === 'provider-defined') {\n if (tool.id === 'groq.browser_search') {\n if (!isBrowserSearchSupportedModel(modelId)) {\n toolWarnings.push({\n type: 'unsupported-tool',\n tool,\n details: `Browser search is only supported on the following models: ${getSupportedModelsString()}. Current model: ${modelId}`,\n });\n } else {\n groqTools.push({\n type: 'browser_search',\n });\n }\n } else {\n toolWarnings.push({ type: 'unsupported-tool', tool });\n }\n } else {\n groqTools.push({\n type: 'function',\n function: {\n name: tool.name,\n description: tool.description,\n parameters: tool.inputSchema,\n },\n });\n }\n }\n\n if (toolChoice == null) {\n return { tools: groqTools, toolChoice: undefined, toolWarnings };\n }\n\n const type = toolChoice.type;\n\n switch (type) {\n case 'auto':\n case 'none':\n case 'required':\n return { tools: groqTools, toolChoice: type, toolWarnings };\n case 'tool':\n return {\n tools: groqTools,\n toolChoice: {\n type: 'function',\n function: {\n name: toolChoice.toolName,\n },\n },\n toolWarnings,\n };\n default: {\n const _exhaustiveCheck: never = type;\n throw new UnsupportedFunctionalityError({\n functionality: `tool choice type: ${_exhaustiveCheck}`,\n });\n }\n }\n}\n","import type { GroqChatModelId } from './groq-chat-options';\n\n/**\n * Models that support browser search functionality.\n * Based on: https://console.groq.com/docs/browser-search\n */\nexport const BROWSER_SEARCH_SUPPORTED_MODELS: readonly GroqChatModelId[] = [\n 'openai/gpt-oss-20b',\n 'openai/gpt-oss-120b',\n] as const;\n\n/**\n * Check if a model supports browser search functionality.\n */\nexport function isBrowserSearchSupportedModel(\n modelId: GroqChatModelId,\n): boolean {\n return BROWSER_SEARCH_SUPPORTED_MODELS.includes(modelId);\n}\n\n/**\n * Get a formatted list of supported models for error messages.\n */\nexport function getSupportedModelsString(): string {\n return BROWSER_SEARCH_SUPPORTED_MODELS.join(', ');\n}\n","import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';\n\nexport function mapGroqFinishReason(\n finishReason: string | null | undefined,\n): LanguageModelV2FinishReason {\n switch (finishReason) {\n case 'stop':\n return 'stop';\n case 'length':\n return 'length';\n case 'content_filter':\n return 'content-filter';\n case 'function_call':\n case 'tool_calls':\n return 'tool-calls';\n default:\n return 'unknown';\n }\n}\n","import type {\n TranscriptionModelV2,\n TranscriptionModelV2CallWarning,\n} from '@ai-sdk/provider';\nimport {\n combineHeaders,\n convertBase64ToUint8Array,\n createBinaryResponseHandler,\n createJsonResponseHandler,\n mediaTypeToExtension,\n parseProviderOptions,\n postFormDataToApi,\n type ResponseHandler,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport type { GroqConfig } from './groq-config';\nimport { groqFailedResponseHandler } from './groq-error';\nimport type { GroqTranscriptionModelId } from './groq-transcription-options';\nimport type { GroqTranscriptionAPITypes } from './groq-api-types';\n\n// https://console.groq.com/docs/speech-to-text\nconst groqProviderOptionsSchema = z.object({\n language: z.string().nullish(),\n prompt: z.string().nullish(),\n responseFormat: z.string().nullish(),\n temperature: z.number().min(0).max(1).nullish(),\n timestampGranularities: z.array(z.string()).nullish(),\n});\n\nexport type GroqTranscriptionCallOptions = z.infer<\n typeof groqProviderOptionsSchema\n>;\n\ninterface GroqTranscriptionModelConfig extends GroqConfig {\n _internal?: {\n currentDate?: () => Date;\n };\n}\n\nexport class GroqTranscriptionModel implements TranscriptionModelV2 {\n readonly specificationVersion = 'v2';\n\n get provider(): string {\n return this.config.provider;\n }\n\n constructor(\n readonly modelId: GroqTranscriptionModelId,\n private readonly config: GroqTranscriptionModelConfig,\n ) {}\n\n private async getArgs({\n audio,\n mediaType,\n providerOptions,\n }: Parameters<TranscriptionModelV2['doGenerate']>[0]) {\n const warnings: TranscriptionModelV2CallWarning[] = [];\n\n // Parse provider options\n const groqOptions = await parseProviderOptions({\n provider: 'groq',\n providerOptions,\n schema: groqProviderOptionsSchema,\n });\n\n // Create form data with base fields\n const formData = new FormData();\n const blob =\n audio instanceof Uint8Array\n ? new Blob([audio])\n : new Blob([convertBase64ToUint8Array(audio)]);\n\n formData.append('model', this.modelId);\n const fileExtension = mediaTypeToExtension(mediaType);\n formData.append(\n 'file',\n new File([blob], 'audio', { type: mediaType }),\n `audio.${fileExtension}`,\n );\n\n // Add provider-specific options\n if (groqOptions) {\n const transcriptionModelOptions: Omit<\n GroqTranscriptionAPITypes,\n 'model'\n > = {\n language: groqOptions.language ?? undefined,\n prompt: groqOptions.prompt ?? undefined,\n response_format: groqOptions.responseFormat ?? undefined,\n temperature: groqOptions.temperature ?? undefined,\n timestamp_granularities:\n groqOptions.timestampGranularities ?? undefined,\n };\n\n for (const key in transcriptionModelOptions) {\n const value =\n transcriptionModelOptions[\n key as keyof Omit<GroqTranscriptionAPITypes, 'model'>\n ];\n if (value !== undefined) {\n formData.append(key, String(value));\n }\n }\n }\n\n return {\n formData,\n responseFormat: groqOptions?.responseFormat,\n warnings,\n };\n }\n\n async doGenerate(\n options: Parameters<TranscriptionModelV2['doGenerate']>[0],\n ): Promise<Awaited<ReturnType<TranscriptionModelV2['doGenerate']>>> {\n const currentDate = this.config._internal?.currentDate?.() ?? new Date();\n const { formData, responseFormat, warnings } = await this.getArgs(options);\n\n const successfulResponseHandler: ResponseHandler<GroqTranscriptionResponse> =\n responseFormat === 'text'\n ? groqTextTranscriptionResponseHandler\n : createJsonResponseHandler(groqTranscriptionResponseSchema);\n\n const {\n value: response,\n responseHeaders,\n rawValue: rawResponse,\n } = await postFormDataToApi({\n url: this.config.url({\n path: '/audio/transcriptions',\n modelId: this.modelId,\n }),\n headers: combineHeaders(this.config.headers(), options.headers),\n formData,\n failedResponseHandler: groqFailedResponseHandler,\n successfulResponseHandler,\n abortSignal: options.abortSignal,\n fetch: this.config.fetch,\n });\n\n return {\n text: response.text,\n segments:\n response.segments?.map(segment => ({\n text: segment.text,\n startSecond: segment.start,\n endSecond: segment.end,\n })) ?? [],\n language: response.language ?? undefined,\n durationInSeconds: response.duration ?? undefined,\n warnings,\n response: {\n timestamp: currentDate,\n modelId: this.modelId,\n headers: responseHeaders,\n body: rawResponse,\n },\n };\n }\n}\n\nconst groqTranscriptionResponseSchema = z.object({\n text: z.string(),\n x_groq: z.object({\n id: z.string(),\n }),\n // additional properties are returned when `response_format: 'verbose_json'` is\n task: z.string().nullish(),\n language: z.string().nullish(),\n duration: z.number().nullish(),\n segments: z\n .array(\n z.object({\n id: z.number(),\n seek: z.number(),\n start: z.number(),\n end: z.number(),\n text: z.string(),\n tokens: z.array(z.number()),\n temperature: z.number(),\n avg_logprob: z.number(),\n compression_ratio: z.number(),\n no_speech_prob: z.number(),\n }),\n )\n .nullish(),\n});\n\ntype GroqTranscriptionResponse = Partial<\n Omit<z.infer<typeof groqTranscriptionResponseSchema>, 'text'>\n> & {\n text: string;\n};\n\nconst binaryResponseHandler = createBinaryResponseHandler();\nconst textDecoder = new TextDecoder();\n\nconst groqTextTranscriptionResponseHandler: ResponseHandler<\n GroqTranscriptionResponse\n> = async options => {\n const { value, responseHeaders } = await binaryResponseHandler(options);\n const text = textDecoder.decode(value);\n\n return {\n value: { text },\n rawValue: text,\n responseHeaders,\n };\n};\n","import { createProviderDefinedToolFactory } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\n/**\n * Browser search tool for Groq models.\n *\n * Provides interactive browser search capabilities that go beyond traditional web search\n * by navigating websites interactively and providing more detailed results.\n *\n * Currently supported on:\n * - openai/gpt-oss-20b\n * - openai/gpt-oss-120b\n *\n * @see https://console.groq.com/docs/browser-search\n */\nexport const browserSearch = createProviderDefinedToolFactory<\n {\n // Browser search doesn't take input parameters - it's controlled by the prompt\n // The tool is activated automatically when included in the tools array\n },\n {\n // No configuration options needed - the tool works automatically\n // when included in the tools array for supported models\n }\n>({\n id: 'groq.browser_search',\n name: 'browser_search',\n inputSchema: z.object({}),\n});\n","import { browserSearch } from './tool/browser-search';\n\nexport const groqTools = {\n browserSearch,\n};\n","// Version string of this package injected at build time.\ndeclare const __PACKAGE_VERSION__: string | undefined;\nexport const VERSION: string =\n typeof __PACKAGE_VERSION__ !== 'undefined'\n ? __PACKAGE_VERSION__\n : 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|
+1
-1
| { | ||
| "name": "@ai-sdk/groq", | ||
| "version": "2.0.46", | ||
| "version": "2.0.47", | ||
| "license": "Apache-2.0", | ||
@@ -5,0 +5,0 @@ "sideEffects": false, |
No alert changes
Improved metrics
- Total package byte prevSize
224302
1.62%- Lines of code
1992
1.17%No dependency changes