@ai-sdk/anthropic/dist/index.mjs.map

The **[Anthropic provider](https://ai-sdk.dev/providers/ai-sdk-providers/anthropic)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Anthropic Messages API](https://docs.anthropic.com/claude/reference/messages_post).

{"version":3,"sources":["../src/anthropic-provider.ts","../src/anthropic-messages-language-model.ts","../src/anthropic-error.ts","../src/anthropic-messages-options.ts","../src/anthropic-prepare-tools.ts","../src/get-cache-control.ts","../src/tool/web-search_20250305.ts","../src/convert-to-anthropic-messages-prompt.ts","../src/map-anthropic-stop-reason.ts","../src/tool/bash_20241022.ts","../src/tool/bash_20250124.ts","../src/tool/computer_20241022.ts","../src/tool/computer_20250124.ts","../src/tool/text-editor_20241022.ts","../src/tool/text-editor_20250124.ts","../src/tool/text-editor_20250429.ts","../src/anthropic-tools.ts"],"sourcesContent":["import {\n  LanguageModelV2,\n  NoSuchModelError,\n  ProviderV2,\n} from '@ai-sdk/provider';\nimport {\n  FetchFunction,\n  generateId,\n  loadApiKey,\n  withoutTrailingSlash,\n} from '@ai-sdk/provider-utils';\nimport { AnthropicMessagesLanguageModel } from './anthropic-messages-language-model';\nimport { AnthropicMessagesModelId } from './anthropic-messages-options';\nimport { anthropicTools } from './anthropic-tools';\n\nexport interface AnthropicProvider extends ProviderV2 {\n  /**\nCreates a model for text generation.\n*/\n  (modelId: AnthropicMessagesModelId): LanguageModelV2;\n\n  /**\nCreates a model for text generation.\n*/\n  languageModel(modelId: AnthropicMessagesModelId): LanguageModelV2;\n\n  chat(modelId: AnthropicMessagesModelId): LanguageModelV2;\n\n  messages(modelId: AnthropicMessagesModelId): LanguageModelV2;\n\n  /**\nAnthropic-specific computer use tool.\n   */\n  tools: typeof anthropicTools;\n}\n\nexport interface AnthropicProviderSettings {\n  /**\nUse a different URL prefix for API calls, e.g. to use proxy servers.\nThe default prefix is `https://api.anthropic.com/v1`.\n   */\n  baseURL?: string;\n\n  /**\nAPI key that is being send using the `x-api-key` header.\nIt defaults to the `ANTHROPIC_API_KEY` environment variable.\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  generateId?: () => string;\n}\n\n/**\nCreate an Anthropic provider instance.\n */\nexport function createAnthropic(\n  options: AnthropicProviderSettings = {},\n): AnthropicProvider {\n  const baseURL =\n    withoutTrailingSlash(options.baseURL) ?? 'https://api.anthropic.com/v1';\n\n  const getHeaders = () => ({\n    'anthropic-version': '2023-06-01',\n    'x-api-key': loadApiKey({\n      apiKey: options.apiKey,\n      environmentVariableName: 'ANTHROPIC_API_KEY',\n      description: 'Anthropic',\n    }),\n    ...options.headers,\n  });\n\n  const createChatModel = (modelId: AnthropicMessagesModelId) =>\n    new AnthropicMessagesLanguageModel(modelId, {\n      provider: 'anthropic.messages',\n      baseURL,\n      headers: getHeaders,\n      fetch: options.fetch,\n      generateId: options.generateId ?? generateId,\n      supportedUrls: () => ({\n        'image/*': [/^https?:\\/\\/.*$/],\n      }),\n    });\n\n  const provider = function (modelId: AnthropicMessagesModelId) {\n    if (new.target) {\n      throw new Error(\n        'The Anthropic model function cannot be called with the new keyword.',\n      );\n    }\n\n    return createChatModel(modelId);\n  };\n\n  provider.languageModel = createChatModel;\n  provider.chat = createChatModel;\n  provider.messages = 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\n  provider.tools = anthropicTools;\n\n  return provider;\n}\n\n/**\nDefault Anthropic provider instance.\n */\nexport const anthropic = createAnthropic();\n","import {\n  JSONObject,\n  JSONValue,\n  LanguageModelV2,\n  LanguageModelV2CallWarning,\n  LanguageModelV2Content,\n  LanguageModelV2FinishReason,\n  LanguageModelV2FunctionTool,\n  LanguageModelV2Prompt,\n  LanguageModelV2StreamPart,\n  LanguageModelV2Usage,\n  SharedV2ProviderMetadata,\n  UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport {\n  FetchFunction,\n  ParseResult,\n  Resolvable,\n  combineHeaders,\n  createEventSourceResponseHandler,\n  createJsonResponseHandler,\n  generateId,\n  parseProviderOptions,\n  postJsonToApi,\n  resolve,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { anthropicFailedResponseHandler } from './anthropic-error';\nimport {\n  AnthropicMessagesModelId,\n  anthropicProviderOptions,\n} from './anthropic-messages-options';\nimport { prepareTools } from './anthropic-prepare-tools';\nimport { convertToAnthropicMessagesPrompt } from './convert-to-anthropic-messages-prompt';\nimport { mapAnthropicStopReason } from './map-anthropic-stop-reason';\n\nconst citationSchemas = {\n  webSearchResult: z.object({\n    type: z.literal('web_search_result_location'),\n    cited_text: z.string(),\n    url: z.string(),\n    title: z.string(),\n    encrypted_index: z.string(),\n  }),\n  pageLocation: z.object({\n    type: z.literal('page_location'),\n    cited_text: z.string(),\n    document_index: z.number(),\n    document_title: z.string().nullable(),\n    start_page_number: z.number(),\n    end_page_number: z.number(),\n  }),\n  charLocation: z.object({\n    type: z.literal('char_location'),\n    cited_text: z.string(),\n    document_index: z.number(),\n    document_title: z.string().nullable(),\n    start_char_index: z.number(),\n    end_char_index: z.number(),\n  }),\n};\n\nconst citationSchema = z.discriminatedUnion('type', [\n  citationSchemas.webSearchResult,\n  citationSchemas.pageLocation,\n  citationSchemas.charLocation,\n]);\n\nconst documentCitationSchema = z.discriminatedUnion('type', [\n  citationSchemas.pageLocation,\n  citationSchemas.charLocation,\n]);\n\ntype Citation = z.infer<typeof citationSchema>;\nexport type DocumentCitation = z.infer<typeof documentCitationSchema>;\nexport type AnthropicProviderMetadata = SharedV2ProviderMetadata & {\n  usage?: Record<string, JSONValue>;\n};\n\nfunction processCitation(\n  citation: Citation,\n  citationDocuments: Array<{\n    title: string;\n    filename?: string;\n    mediaType: string;\n  }>,\n  generateId: () => string,\n  onSource: (source: any) => void,\n) {\n  if (citation.type === 'page_location' || citation.type === 'char_location') {\n    const source = createCitationSource(\n      citation,\n      citationDocuments,\n      generateId,\n    );\n    if (source) {\n      onSource(source);\n    }\n  }\n}\n\nfunction createCitationSource(\n  citation: DocumentCitation,\n  citationDocuments: Array<{\n    title: string;\n    filename?: string;\n    mediaType: string;\n  }>,\n  generateId: () => string,\n) {\n  const documentInfo = citationDocuments[citation.document_index];\n  if (!documentInfo) {\n    return null;\n  }\n\n  const providerMetadata =\n    citation.type === 'page_location'\n      ? {\n          citedText: citation.cited_text,\n          startPageNumber: citation.start_page_number,\n          endPageNumber: citation.end_page_number,\n        }\n      : {\n          citedText: citation.cited_text,\n          startCharIndex: citation.start_char_index,\n          endCharIndex: citation.end_char_index,\n        };\n\n  return {\n    type: 'source' as const,\n    sourceType: 'document' as const,\n    id: generateId(),\n    mediaType: documentInfo.mediaType,\n    title: citation.document_title ?? documentInfo.title,\n    filename: documentInfo.filename,\n    providerMetadata: {\n      anthropic: providerMetadata,\n    },\n  };\n}\n\ntype AnthropicMessagesConfig = {\n  provider: string;\n  baseURL: string;\n  headers: Resolvable<Record<string, string | undefined>>;\n  fetch?: FetchFunction;\n  buildRequestUrl?: (baseURL: string, isStreaming: boolean) => string;\n  transformRequestBody?: (args: Record<string, any>) => Record<string, any>;\n  supportedUrls?: () => LanguageModelV2['supportedUrls'];\n  generateId?: () => string;\n};\n\nexport class AnthropicMessagesLanguageModel implements LanguageModelV2 {\n  readonly specificationVersion = 'v2';\n\n  readonly modelId: AnthropicMessagesModelId;\n\n  private readonly config: AnthropicMessagesConfig;\n  private readonly generateId: () => string;\n\n  constructor(\n    modelId: AnthropicMessagesModelId,\n    config: AnthropicMessagesConfig,\n  ) {\n    this.modelId = modelId;\n    this.config = config;\n    this.generateId = config.generateId ?? generateId;\n  }\n\n  supportsUrl(url: URL): boolean {\n    return url.protocol === 'https:';\n  }\n\n  get provider(): string {\n    return this.config.provider;\n  }\n\n  get supportedUrls() {\n    return this.config.supportedUrls?.() ?? {};\n  }\n\n  private async getArgs({\n    prompt,\n    maxOutputTokens = 4096, // 4096: max model output tokens TODO update default in v5\n    temperature,\n    topP,\n    topK,\n    frequencyPenalty,\n    presencePenalty,\n    stopSequences,\n    responseFormat,\n    seed,\n    tools,\n    toolChoice,\n    providerOptions,\n  }: Parameters<LanguageModelV2['doGenerate']>[0]) {\n    const warnings: LanguageModelV2CallWarning[] = [];\n\n    if (frequencyPenalty != null) {\n      warnings.push({\n        type: 'unsupported-setting',\n        setting: 'frequencyPenalty',\n      });\n    }\n\n    if (presencePenalty != null) {\n      warnings.push({\n        type: 'unsupported-setting',\n        setting: 'presencePenalty',\n      });\n    }\n\n    if (seed != null) {\n      warnings.push({\n        type: 'unsupported-setting',\n        setting: 'seed',\n      });\n    }\n\n    if (responseFormat?.type === 'json') {\n      if (responseFormat.schema == null) {\n        warnings.push({\n          type: 'unsupported-setting',\n          setting: 'responseFormat',\n          details:\n            'JSON response format requires a schema. ' +\n            'The response format is ignored.',\n        });\n      } else if (tools != null) {\n        warnings.push({\n          type: 'unsupported-setting',\n          setting: 'tools',\n          details:\n            'JSON response format does not support tools. ' +\n            'The provided tools are ignored.',\n        });\n      }\n    }\n\n    const jsonResponseTool: LanguageModelV2FunctionTool | undefined =\n      responseFormat?.type === 'json' && responseFormat.schema != null\n        ? {\n            type: 'function',\n            name: 'json',\n            description: 'Respond with a JSON object.',\n            inputSchema: responseFormat.schema,\n          }\n        : undefined;\n\n    const anthropicOptions = await parseProviderOptions({\n      provider: 'anthropic',\n      providerOptions,\n      schema: anthropicProviderOptions,\n    });\n\n    const { prompt: messagesPrompt, betas: messagesBetas } =\n      await convertToAnthropicMessagesPrompt({\n        prompt,\n        sendReasoning: anthropicOptions?.sendReasoning ?? true,\n        warnings,\n      });\n\n    const isThinking = anthropicOptions?.thinking?.type === 'enabled';\n    const thinkingBudget = anthropicOptions?.thinking?.budgetTokens;\n\n    const baseArgs = {\n      // model id:\n      model: this.modelId,\n\n      // standardized settings:\n      max_tokens: maxOutputTokens,\n      temperature,\n      top_k: topK,\n      top_p: topP,\n      stop_sequences: stopSequences,\n\n      // provider specific settings:\n      ...(isThinking && {\n        thinking: { type: 'enabled', budget_tokens: thinkingBudget },\n      }),\n\n      // prompt:\n      system: messagesPrompt.system,\n      messages: messagesPrompt.messages,\n    };\n\n    if (isThinking) {\n      if (thinkingBudget == null) {\n        throw new UnsupportedFunctionalityError({\n          functionality: 'thinking requires a budget',\n        });\n      }\n\n      if (baseArgs.temperature != null) {\n        baseArgs.temperature = undefined;\n        warnings.push({\n          type: 'unsupported-setting',\n          setting: 'temperature',\n          details: 'temperature is not supported when thinking is enabled',\n        });\n      }\n\n      if (topK != null) {\n        baseArgs.top_k = undefined;\n        warnings.push({\n          type: 'unsupported-setting',\n          setting: 'topK',\n          details: 'topK is not supported when thinking is enabled',\n        });\n      }\n\n      if (topP != null) {\n        baseArgs.top_p = undefined;\n        warnings.push({\n          type: 'unsupported-setting',\n          setting: 'topP',\n          details: 'topP is not supported when thinking is enabled',\n        });\n      }\n\n      // adjust max tokens to account for thinking:\n      baseArgs.max_tokens = maxOutputTokens + thinkingBudget;\n    }\n\n    const {\n      tools: anthropicTools,\n      toolChoice: anthropicToolChoice,\n      toolWarnings,\n      betas: toolsBetas,\n    } = prepareTools(\n      jsonResponseTool != null\n        ? {\n            tools: [jsonResponseTool],\n            toolChoice: { type: 'tool', toolName: jsonResponseTool.name },\n            disableParallelToolUse: anthropicOptions?.disableParallelToolUse,\n          }\n        : {\n            tools: tools ?? [],\n            toolChoice,\n            disableParallelToolUse: anthropicOptions?.disableParallelToolUse,\n          },\n    );\n\n    return {\n      args: {\n        ...baseArgs,\n        tools: anthropicTools,\n        tool_choice: anthropicToolChoice,\n      },\n      warnings: [...warnings, ...toolWarnings],\n      betas: new Set([...messagesBetas, ...toolsBetas]),\n      usesJsonResponseTool: jsonResponseTool != null,\n    };\n  }\n\n  private async getHeaders({\n    betas,\n    headers,\n  }: {\n    betas: Set<string>;\n    headers: Record<string, string | undefined> | undefined;\n  }) {\n    return combineHeaders(\n      await resolve(this.config.headers),\n      betas.size > 0 ? { 'anthropic-beta': Array.from(betas).join(',') } : {},\n      headers,\n    );\n  }\n\n  private buildRequestUrl(isStreaming: boolean): string {\n    return (\n      this.config.buildRequestUrl?.(this.config.baseURL, isStreaming) ??\n      `${this.config.baseURL}/messages`\n    );\n  }\n\n  private transformRequestBody(args: Record<string, any>): Record<string, any> {\n    return this.config.transformRequestBody?.(args) ?? args;\n  }\n\n  private extractCitationDocuments(prompt: LanguageModelV2Prompt): Array<{\n    title: string;\n    filename?: string;\n    mediaType: string;\n  }> {\n    const isCitationPart = (part: {\n      type: string;\n      mediaType?: string;\n      providerOptions?: { anthropic?: { citations?: { enabled?: boolean } } };\n    }) => {\n      if (part.type !== 'file') {\n        return false;\n      }\n\n      if (\n        part.mediaType !== 'application/pdf' &&\n        part.mediaType !== 'text/plain'\n      ) {\n        return false;\n      }\n\n      const anthropic = part.providerOptions?.anthropic;\n      const citationsConfig = anthropic?.citations as\n        | { enabled?: boolean }\n        | undefined;\n      return citationsConfig?.enabled ?? false;\n    };\n\n    return prompt\n      .filter(message => message.role === 'user')\n      .flatMap(message => message.content)\n      .filter(isCitationPart)\n      .map(part => {\n        // TypeScript knows this is a file part due to our filter\n        const filePart = part as Extract<typeof part, { type: 'file' }>;\n        return {\n          title: filePart.filename ?? 'Untitled Document',\n          filename: filePart.filename,\n          mediaType: filePart.mediaType,\n        };\n      });\n  }\n\n  async doGenerate(\n    options: Parameters<LanguageModelV2['doGenerate']>[0],\n  ): Promise<Awaited<ReturnType<LanguageModelV2['doGenerate']>>> {\n    const { args, warnings, betas, usesJsonResponseTool } =\n      await this.getArgs(options);\n\n    // Extract citation documents for response processing\n    const citationDocuments = this.extractCitationDocuments(options.prompt);\n\n    const {\n      responseHeaders,\n      value: response,\n      rawValue: rawResponse,\n    } = await postJsonToApi({\n      url: this.buildRequestUrl(false),\n      headers: await this.getHeaders({ betas, headers: options.headers }),\n      body: this.transformRequestBody(args),\n      failedResponseHandler: anthropicFailedResponseHandler,\n      successfulResponseHandler: createJsonResponseHandler(\n        anthropicMessagesResponseSchema,\n      ),\n      abortSignal: options.abortSignal,\n      fetch: this.config.fetch,\n    });\n\n    const content: Array<LanguageModelV2Content> = [];\n\n    // map response content to content array\n    for (const part of response.content) {\n      switch (part.type) {\n        case 'text': {\n          // when a json response tool is used, the tool call is returned as text,\n          // so we ignore the text content:\n          if (!usesJsonResponseTool) {\n            content.push({ type: 'text', text: part.text });\n\n            // Process citations if present\n            if (part.citations) {\n              for (const citation of part.citations) {\n                processCitation(\n                  citation,\n                  citationDocuments,\n                  this.generateId,\n                  source => content.push(source),\n                );\n              }\n            }\n          }\n          break;\n        }\n        case 'thinking': {\n          content.push({\n            type: 'reasoning',\n            text: part.thinking,\n            providerMetadata: {\n              anthropic: {\n                signature: part.signature,\n              } satisfies AnthropicReasoningMetadata,\n            },\n          });\n          break;\n        }\n        case 'redacted_thinking': {\n          content.push({\n            type: 'reasoning',\n            text: '',\n            providerMetadata: {\n              anthropic: {\n                redactedData: part.data,\n              } satisfies AnthropicReasoningMetadata,\n            },\n          });\n          break;\n        }\n        case 'tool_use': {\n          content.push(\n            // when a json response tool is used, the tool call becomes the text:\n            usesJsonResponseTool\n              ? {\n                  type: 'text',\n                  text: JSON.stringify(part.input),\n                }\n              : {\n                  type: 'tool-call',\n                  toolCallId: part.id,\n                  toolName: part.name,\n                  input: JSON.stringify(part.input),\n                },\n          );\n\n          break;\n        }\n        case 'server_tool_use': {\n          if (part.name === 'web_search') {\n            content.push({\n              type: 'tool-call',\n              toolCallId: part.id,\n              toolName: part.name,\n              input: JSON.stringify(part.input),\n              providerExecuted: true,\n            });\n          }\n\n          break;\n        }\n        case 'web_search_tool_result': {\n          if (Array.isArray(part.content)) {\n            content.push({\n              type: 'tool-result',\n              toolCallId: part.tool_use_id,\n              toolName: 'web_search',\n              result: part.content.map(result => ({\n                url: result.url,\n                title: result.title,\n                pageAge: result.page_age ?? null,\n                encryptedContent: result.encrypted_content,\n                type: result.type,\n              })),\n              providerExecuted: true,\n            });\n\n            for (const result of part.content) {\n              content.push({\n                type: 'source',\n                sourceType: 'url',\n                id: this.generateId(),\n                url: result.url,\n                title: result.title,\n                providerMetadata: {\n                  anthropic: {\n                    pageAge: result.page_age ?? null,\n                  },\n                },\n              });\n            }\n          } else {\n            content.push({\n              type: 'tool-result',\n              toolCallId: part.tool_use_id,\n              toolName: 'web_search',\n              isError: true,\n              result: {\n                type: 'web_search_tool_result_error',\n                errorCode: part.content.error_code,\n              },\n              providerExecuted: true,\n            });\n          }\n          break;\n        }\n      }\n    }\n\n    return {\n      content,\n      finishReason: mapAnthropicStopReason({\n        finishReason: response.stop_reason,\n        isJsonResponseFromTool: usesJsonResponseTool,\n      }),\n      usage: {\n        inputTokens: response.usage.input_tokens,\n        outputTokens: response.usage.output_tokens,\n        totalTokens: response.usage.input_tokens + response.usage.output_tokens,\n        cachedInputTokens: response.usage.cache_read_input_tokens ?? undefined,\n      },\n      request: { body: args },\n      response: {\n        id: response.id ?? undefined,\n        modelId: response.model ?? undefined,\n        headers: responseHeaders,\n        body: rawResponse,\n      },\n      warnings,\n      providerMetadata: {\n        anthropic: {\n          usage: response.usage as JSONObject,\n          cacheCreationInputTokens:\n            response.usage.cache_creation_input_tokens ?? null,\n        },\n      },\n    };\n  }\n\n  async doStream(\n    options: Parameters<LanguageModelV2['doStream']>[0],\n  ): Promise<Awaited<ReturnType<LanguageModelV2['doStream']>>> {\n    const { args, warnings, betas, usesJsonResponseTool } =\n      await this.getArgs(options);\n\n    // Extract citation documents for response processing\n    const citationDocuments = this.extractCitationDocuments(options.prompt);\n\n    const body = { ...args, stream: true };\n\n    const { responseHeaders, value: response } = await postJsonToApi({\n      url: this.buildRequestUrl(true),\n      headers: await this.getHeaders({ betas, headers: options.headers }),\n      body: this.transformRequestBody(body),\n      failedResponseHandler: anthropicFailedResponseHandler,\n      successfulResponseHandler: createEventSourceResponseHandler(\n        anthropicMessagesChunkSchema,\n      ),\n      abortSignal: options.abortSignal,\n      fetch: this.config.fetch,\n    });\n\n    let finishReason: LanguageModelV2FinishReason = 'unknown';\n    const usage: LanguageModelV2Usage = {\n      inputTokens: undefined,\n      outputTokens: undefined,\n      totalTokens: undefined,\n    };\n\n    const contentBlocks: Record<\n      number,\n      | {\n          type: 'tool-call';\n          toolCallId: string;\n          toolName: string;\n          input: string;\n          providerExecuted?: boolean;\n        }\n      | { type: 'text' | 'reasoning' }\n    > = {};\n\n    let providerMetadata: AnthropicProviderMetadata | undefined = undefined;\n\n    let blockType:\n      | 'text'\n      | 'thinking'\n      | 'tool_use'\n      | 'redacted_thinking'\n      | 'server_tool_use'\n      | 'web_search_tool_result'\n      | undefined = undefined;\n\n    const generateId = this.generateId;\n\n    return {\n      stream: response.pipeThrough(\n        new TransformStream<\n          ParseResult<z.infer<typeof anthropicMessagesChunkSchema>>,\n          LanguageModelV2StreamPart\n        >({\n          start(controller) {\n            controller.enqueue({ type: 'stream-start', warnings });\n          },\n\n          transform(chunk, controller) {\n            if (options.includeRawChunks) {\n              controller.enqueue({ type: 'raw', rawValue: chunk.rawValue });\n            }\n\n            if (!chunk.success) {\n              controller.enqueue({ type: 'error', error: chunk.error });\n              return;\n            }\n\n            const value = chunk.value;\n\n            switch (value.type) {\n              case 'ping': {\n                return; // ignored\n              }\n\n              case 'content_block_start': {\n                const contentBlockType = value.content_block.type;\n\n                blockType = contentBlockType;\n\n                switch (contentBlockType) {\n                  case 'text': {\n                    contentBlocks[value.index] = { type: 'text' };\n                    controller.enqueue({\n                      type: 'text-start',\n                      id: String(value.index),\n                    });\n                    return;\n                  }\n\n                  case 'thinking': {\n                    contentBlocks[value.index] = { type: 'reasoning' };\n                    controller.enqueue({\n                      type: 'reasoning-start',\n                      id: String(value.index),\n                    });\n                    return;\n                  }\n\n                  case 'redacted_thinking': {\n                    contentBlocks[value.index] = { type: 'reasoning' };\n                    controller.enqueue({\n                      type: 'reasoning-start',\n                      id: String(value.index),\n                      providerMetadata: {\n                        anthropic: {\n                          redactedData: value.content_block.data,\n                        } satisfies AnthropicReasoningMetadata,\n                      },\n                    });\n                    return;\n                  }\n\n                  case 'tool_use': {\n                    contentBlocks[value.index] = usesJsonResponseTool\n                      ? { type: 'text' }\n                      : {\n                          type: 'tool-call',\n                          toolCallId: value.content_block.id,\n                          toolName: value.content_block.name,\n                          input: '',\n                        };\n\n                    controller.enqueue(\n                      usesJsonResponseTool\n                        ? { type: 'text-start', id: String(value.index) }\n                        : {\n                            type: 'tool-input-start',\n                            id: value.content_block.id,\n                            toolName: value.content_block.name,\n                          },\n                    );\n                    return;\n                  }\n\n                  case 'server_tool_use': {\n                    if (value.content_block.name === 'web_search') {\n                      contentBlocks[value.index] = {\n                        type: 'tool-call',\n                        toolCallId: value.content_block.id,\n                        toolName: value.content_block.name,\n                        input: '',\n                        providerExecuted: true,\n                      };\n                      controller.enqueue({\n                        type: 'tool-input-start',\n                        id: value.content_block.id,\n                        toolName: value.content_block.name,\n                        providerExecuted: true,\n                      });\n                    }\n\n                    return;\n                  }\n\n                  case 'web_search_tool_result': {\n                    const part = value.content_block;\n\n                    if (Array.isArray(part.content)) {\n                      controller.enqueue({\n                        type: 'tool-result',\n                        toolCallId: part.tool_use_id,\n                        toolName: 'web_search',\n                        result: part.content.map(result => ({\n                          url: result.url,\n                          title: result.title,\n                          pageAge: result.page_age ?? null,\n                          encryptedContent: result.encrypted_content,\n                          type: result.type,\n                        })),\n                        providerExecuted: true,\n                      });\n\n                      for (const result of part.content) {\n                        controller.enqueue({\n                          type: 'source',\n                          sourceType: 'url',\n                          id: generateId(),\n                          url: result.url,\n                          title: result.title,\n                          providerMetadata: {\n                            anthropic: {\n                              pageAge: result.page_age ?? null,\n                            },\n                          },\n                        });\n                      }\n                    } else {\n                      controller.enqueue({\n                        type: 'tool-result',\n                        toolCallId: part.tool_use_id,\n                        toolName: 'web_search',\n                        isError: true,\n                        result: {\n                          type: 'web_search_tool_result_error',\n                          errorCode: part.content.error_code,\n                        },\n                        providerExecuted: true,\n                      });\n                    }\n                    return;\n                  }\n\n                  default: {\n                    const _exhaustiveCheck: never = contentBlockType;\n                    throw new Error(\n                      `Unsupported content block type: ${_exhaustiveCheck}`,\n                    );\n                  }\n                }\n              }\n\n              case 'content_block_stop': {\n                // when finishing a tool call block, send the full tool call:\n                if (contentBlocks[value.index] != null) {\n                  const contentBlock = contentBlocks[value.index];\n\n                  switch (contentBlock.type) {\n                    case 'text': {\n                      controller.enqueue({\n                        type: 'text-end',\n                        id: String(value.index),\n                      });\n                      break;\n                    }\n\n                    case 'reasoning': {\n                      controller.enqueue({\n                        type: 'reasoning-end',\n                        id: String(value.index),\n                      });\n                      break;\n                    }\n\n                    case 'tool-call':\n                      // when a json response tool is used, the tool call is returned as text,\n                      // so we ignore the tool call content:\n                      if (!usesJsonResponseTool) {\n                        controller.enqueue({\n                          type: 'tool-input-end',\n                          id: contentBlock.toolCallId,\n                        });\n                        controller.enqueue(contentBlock);\n                      }\n                      break;\n                  }\n\n                  delete contentBlocks[value.index];\n                }\n\n                blockType = undefined; // reset block type\n\n                return;\n              }\n\n              case 'content_block_delta': {\n                const deltaType = value.delta.type;\n                switch (deltaType) {\n                  case 'text_delta': {\n                    // when a json response tool is used, the tool call is returned as text,\n                    // so we ignore the text content:\n                    if (usesJsonResponseTool) {\n                      return;\n                    }\n\n                    controller.enqueue({\n                      type: 'text-delta',\n                      id: String(value.index),\n                      delta: value.delta.text,\n                    });\n\n                    return;\n                  }\n\n                  case 'thinking_delta': {\n                    controller.enqueue({\n                      type: 'reasoning-delta',\n                      id: String(value.index),\n                      delta: value.delta.thinking,\n                    });\n\n                    return;\n                  }\n\n                  case 'signature_delta': {\n                    // signature are only supported on thinking blocks:\n                    if (blockType === 'thinking') {\n                      controller.enqueue({\n                        type: 'reasoning-delta',\n                        id: String(value.index),\n                        delta: '',\n                        providerMetadata: {\n                          anthropic: {\n                            signature: value.delta.signature,\n                          } satisfies AnthropicReasoningMetadata,\n                        },\n                      });\n                    }\n\n                    return;\n                  }\n\n                  case 'input_json_delta': {\n                    const contentBlock = contentBlocks[value.index];\n                    const delta = value.delta.partial_json;\n\n                    if (usesJsonResponseTool) {\n                      if (contentBlock?.type !== 'text') {\n                        return;\n                      }\n\n                      controller.enqueue({\n                        type: 'text-delta',\n                        id: String(value.index),\n                        delta,\n                      });\n                    } else {\n                      if (contentBlock?.type !== 'tool-call') {\n                        return;\n                      }\n\n                      controller.enqueue({\n                        type: 'tool-input-delta',\n                        id: contentBlock.toolCallId,\n                        delta,\n                      });\n\n                      contentBlock.input += delta;\n                    }\n\n                    return;\n                  }\n\n                  case 'citations_delta': {\n                    const citation = value.delta.citation;\n\n                    processCitation(\n                      citation,\n                      citationDocuments,\n                      generateId,\n                      source => controller.enqueue(source),\n                    );\n                    // Web search citations are handled in web_search_tool_result content block\n                    return;\n                  }\n\n                  default: {\n                    const _exhaustiveCheck: never = deltaType;\n                    throw new Error(\n                      `Unsupported delta type: ${_exhaustiveCheck}`,\n                    );\n                  }\n                }\n              }\n\n              case 'message_start': {\n                usage.inputTokens = value.message.usage.input_tokens;\n                usage.cachedInputTokens =\n                  value.message.usage.cache_read_input_tokens ?? undefined;\n\n                providerMetadata = {\n                  anthropic: {\n                    usage: value.message.usage as JSONObject,\n                    cacheCreationInputTokens:\n                      value.message.usage.cache_creation_input_tokens ?? null,\n                  },\n                };\n\n                controller.enqueue({\n                  type: 'response-metadata',\n                  id: value.message.id ?? undefined,\n                  modelId: value.message.model ?? undefined,\n                });\n\n                return;\n              }\n\n              case 'message_delta': {\n                usage.outputTokens = value.usage.output_tokens;\n                usage.totalTokens =\n                  (usage.inputTokens ?? 0) + (value.usage.output_tokens ?? 0);\n\n                finishReason = mapAnthropicStopReason({\n                  finishReason: value.delta.stop_reason,\n                  isJsonResponseFromTool: usesJsonResponseTool,\n                });\n                return;\n              }\n\n              case 'message_stop': {\n                controller.enqueue({\n                  type: 'finish',\n                  finishReason,\n                  usage,\n                  providerMetadata,\n                });\n                return;\n              }\n\n              case 'error': {\n                controller.enqueue({ type: 'error', error: value.error });\n                return;\n              }\n\n              default: {\n                const _exhaustiveCheck: never = value;\n                throw new Error(`Unsupported chunk type: ${_exhaustiveCheck}`);\n              }\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 anthropicMessagesResponseSchema = z.object({\n  type: z.literal('message'),\n  id: z.string().nullish(),\n  model: z.string().nullish(),\n  content: z.array(\n    z.discriminatedUnion('type', [\n      z.object({\n        type: z.literal('text'),\n        text: z.string(),\n        citations: z.array(citationSchema).optional(),\n      }),\n      z.object({\n        type: z.literal('thinking'),\n        thinking: z.string(),\n        signature: z.string(),\n      }),\n      z.object({\n        type: z.literal('redacted_thinking'),\n        data: z.string(),\n      }),\n      z.object({\n        type: z.literal('tool_use'),\n        id: z.string(),\n        name: z.string(),\n        input: z.unknown(),\n      }),\n      z.object({\n        type: z.literal('server_tool_use'),\n        id: z.string(),\n        name: z.string(),\n        input: z.record(z.string(), z.unknown()).nullish(),\n      }),\n      z.object({\n        type: z.literal('web_search_tool_result'),\n        tool_use_id: z.string(),\n        content: z.union([\n          z.array(\n            z.object({\n              type: z.literal('web_search_result'),\n              url: z.string(),\n              title: z.string(),\n              encrypted_content: z.string(),\n              page_age: z.string().nullish(),\n            }),\n          ),\n          z.object({\n            type: z.literal('web_search_tool_result_error'),\n            error_code: z.string(),\n          }),\n        ]),\n      }),\n    ]),\n  ),\n  stop_reason: z.string().nullish(),\n  usage: z.looseObject({\n    input_tokens: z.number(),\n    output_tokens: z.number(),\n    cache_creation_input_tokens: z.number().nullish(),\n    cache_read_input_tokens: z.number().nullish(),\n  }),\n});\n\n// limited version of the schema, focused on what is needed for the implementation\n// this approach limits breakages when the API changes and increases efficiency\nconst anthropicMessagesChunkSchema = z.discriminatedUnion('type', [\n  z.object({\n    type: z.literal('message_start'),\n    message: z.object({\n      id: z.string().nullish(),\n      model: z.string().nullish(),\n      usage: z.looseObject({\n        input_tokens: z.number(),\n        output_tokens: z.number(),\n        cache_creation_input_tokens: z.number().nullish(),\n        cache_read_input_tokens: z.number().nullish(),\n      }),\n    }),\n  }),\n  z.object({\n    type: z.literal('content_block_start'),\n    index: z.number(),\n    content_block: z.discriminatedUnion('type', [\n      z.object({\n        type: z.literal('text'),\n        text: z.string(),\n      }),\n      z.object({\n        type: z.literal('thinking'),\n        thinking: z.string(),\n      }),\n      z.object({\n        type: z.literal('tool_use'),\n        id: z.string(),\n        name: z.string(),\n      }),\n      z.object({\n        type: z.literal('redacted_thinking'),\n        data: z.string(),\n      }),\n      z.object({\n        type: z.literal('server_tool_use'),\n        id: z.string(),\n        name: z.string(),\n        input: z.record(z.string(), z.unknown()).nullish(),\n      }),\n      z.object({\n        type: z.literal('web_search_tool_result'),\n        tool_use_id: z.string(),\n        content: z.union([\n          z.array(\n            z.object({\n              type: z.literal('web_search_result'),\n              url: z.string(),\n              title: z.string(),\n              encrypted_content: z.string(),\n              page_age: z.string().nullish(),\n            }),\n          ),\n          z.object({\n            type: z.literal('web_search_tool_result_error'),\n            error_code: z.string(),\n          }),\n        ]),\n      }),\n    ]),\n  }),\n  z.object({\n    type: z.literal('content_block_delta'),\n    index: z.number(),\n    delta: z.discriminatedUnion('type', [\n      z.object({\n        type: z.literal('input_json_delta'),\n        partial_json: z.string(),\n      }),\n      z.object({\n        type: z.literal('text_delta'),\n        text: z.string(),\n      }),\n      z.object({\n        type: z.literal('thinking_delta'),\n        thinking: z.string(),\n      }),\n      z.object({\n        type: z.literal('signature_delta'),\n        signature: z.string(),\n      }),\n      z.object({\n        type: z.literal('citations_delta'),\n        citation: citationSchema,\n      }),\n    ]),\n  }),\n  z.object({\n    type: z.literal('content_block_stop'),\n    index: z.number(),\n  }),\n  z.object({\n    type: z.literal('error'),\n    error: z.object({\n      type: z.string(),\n      message: z.string(),\n    }),\n  }),\n  z.object({\n    type: z.literal('message_delta'),\n    delta: z.object({ stop_reason: z.string().nullish() }),\n    usage: z.object({ output_tokens: z.number() }),\n  }),\n  z.object({\n    type: z.literal('message_stop'),\n  }),\n  z.object({\n    type: z.literal('ping'),\n  }),\n]);\n\nexport const anthropicReasoningMetadataSchema = z.object({\n  signature: z.string().optional(),\n  redactedData: z.string().optional(),\n});\n\nexport type AnthropicReasoningMetadata = z.infer<\n  typeof anthropicReasoningMetadataSchema\n>;\n","import { createJsonErrorResponseHandler } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\n\nexport const anthropicErrorDataSchema = z.object({\n  type: z.literal('error'),\n  error: z.object({\n    type: z.string(),\n    message: z.string(),\n  }),\n});\n\nexport type AnthropicErrorData = z.infer<typeof anthropicErrorDataSchema>;\n\nexport const anthropicFailedResponseHandler = createJsonErrorResponseHandler({\n  errorSchema: anthropicErrorDataSchema,\n  errorToMessage: data => data.error.message,\n});\n","import { z } from 'zod/v4';\n\n// https://docs.anthropic.com/claude/docs/models-overview\nexport type AnthropicMessagesModelId =\n  | 'claude-opus-4-20250514'\n  | 'claude-sonnet-4-20250514'\n  | 'claude-3-7-sonnet-20250219'\n  | 'claude-3-5-sonnet-latest'\n  | 'claude-3-5-sonnet-20241022'\n  | 'claude-3-5-sonnet-20240620'\n  | 'claude-3-5-haiku-latest'\n  | 'claude-3-5-haiku-20241022'\n  | 'claude-3-opus-latest'\n  | 'claude-3-opus-20240229'\n  | 'claude-3-sonnet-20240229'\n  | 'claude-3-haiku-20240307'\n  | (string & {});\n\n/**\n * Anthropic file part provider options for document-specific features.\n * These options apply to individual file parts (documents).\n */\nexport const anthropicFilePartProviderOptions = z.object({\n  /**\n   * Citation configuration for this document.\n   * When enabled, this document will generate citations in the response.\n   */\n  citations: z\n    .object({\n      /**\n       * Enable citations for this document\n       */\n      enabled: z.boolean(),\n    })\n    .optional(),\n\n  /**\n   * Custom title for the document.\n   * If not provided, the filename will be used.\n   */\n  title: z.string().optional(),\n\n  /**\n   * Context about the document that will be passed to the model\n   * but not used towards cited content.\n   * Useful for storing document metadata as text or stringified JSON.\n   */\n  context: z.string().optional(),\n});\n\nexport type AnthropicFilePartProviderOptions = z.infer<\n  typeof anthropicFilePartProviderOptions\n>;\n\nexport const anthropicProviderOptions = z.object({\n  sendReasoning: z.boolean().optional(),\n\n  thinking: z\n    .object({\n      type: z.union([z.literal('enabled'), z.literal('disabled')]),\n      budgetTokens: z.number().optional(),\n    })\n    .optional(),\n\n  /**\n   * Whether to disable parallel function calling during tool use. Default is false.\n   * When set to true, Claude will use at most one tool per response.\n   */\n  disableParallelToolUse: z.boolean().optional(),\n});\n\nexport type AnthropicProviderOptions = z.infer<typeof anthropicProviderOptions>;\n","import {\n  LanguageModelV2CallOptions,\n  LanguageModelV2CallWarning,\n  UnsupportedFunctionalityError,\n} from '@ai-sdk/provider';\nimport { AnthropicTool, AnthropicToolChoice } from './anthropic-api-types';\nimport { getCacheControl } from './get-cache-control';\nimport { webSearch_20250305ArgsSchema } from './tool/web-search_20250305';\n\nfunction isWebSearchTool(\n  tool: unknown,\n): tool is Extract<AnthropicTool, { type: 'web_search_20250305' }> {\n  return (\n    typeof tool === 'object' &&\n    tool !== null &&\n    'type' in tool &&\n    tool.type === 'web_search_20250305'\n  );\n}\n\nexport function prepareTools({\n  tools,\n  toolChoice,\n  disableParallelToolUse,\n}: {\n  tools: LanguageModelV2CallOptions['tools'];\n  toolChoice?: LanguageModelV2CallOptions['toolChoice'];\n  disableParallelToolUse?: boolean;\n}): {\n  tools: Array<AnthropicTool> | undefined;\n  toolChoice: AnthropicToolChoice | undefined;\n  toolWarnings: LanguageModelV2CallWarning[];\n  betas: Set<string>;\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  const betas = new Set<string>();\n\n  if (tools == null) {\n    return { tools: undefined, toolChoice: undefined, toolWarnings, betas };\n  }\n\n  const anthropicTools: AnthropicTool[] = [];\n\n  for (const tool of tools) {\n    // handle direct web search tool objects passed from provider options\n    if (isWebSearchTool(tool)) {\n      anthropicTools.push(tool);\n      continue;\n    }\n\n    switch (tool.type) {\n      case 'function':\n        const cacheControl = getCacheControl(tool.providerOptions);\n\n        anthropicTools.push({\n          name: tool.name,\n          description: tool.description,\n          input_schema: tool.inputSchema,\n          cache_control: cacheControl,\n        });\n        break;\n      case 'provider-defined':\n        switch (tool.id) {\n          case 'anthropic.computer_20250124':\n            betas.add('computer-use-2025-01-24');\n            anthropicTools.push({\n              name: 'computer',\n              type: 'computer_20250124',\n              display_width_px: tool.args.displayWidthPx as number,\n              display_height_px: tool.args.displayHeightPx as number,\n              display_number: tool.args.displayNumber as number,\n            });\n            break;\n          case 'anthropic.computer_20241022':\n            betas.add('computer-use-2024-10-22');\n            anthropicTools.push({\n              name: 'computer',\n              type: 'computer_20241022',\n              display_width_px: tool.args.displayWidthPx as number,\n              display_height_px: tool.args.displayHeightPx as number,\n              display_number: tool.args.displayNumber as number,\n            });\n            break;\n          case 'anthropic.text_editor_20250124':\n            betas.add('computer-use-2025-01-24');\n            anthropicTools.push({\n              name: 'str_replace_editor',\n              type: 'text_editor_20250124',\n            });\n            break;\n          case 'anthropic.text_editor_20241022':\n            betas.add('computer-use-2024-10-22');\n            anthropicTools.push({\n              name: 'str_replace_editor',\n              type: 'text_editor_20241022',\n            });\n            break;\n          case 'anthropic.text_editor_20250429':\n            betas.add('computer-use-2025-01-24');\n            anthropicTools.push({\n              name: 'str_replace_based_edit_tool',\n              type: 'text_editor_20250429',\n            });\n            break;\n          case 'anthropic.bash_20250124':\n            betas.add('computer-use-2025-01-24');\n            anthropicTools.push({\n              name: 'bash',\n              type: 'bash_20250124',\n            });\n            break;\n          case 'anthropic.bash_20241022':\n            betas.add('computer-use-2024-10-22');\n            anthropicTools.push({\n              name: 'bash',\n              type: 'bash_20241022',\n            });\n            break;\n          case 'anthropic.web_search_20250305': {\n            const args = webSearch_20250305ArgsSchema.parse(tool.args);\n            anthropicTools.push({\n              type: 'web_search_20250305',\n              name: 'web_search',\n              max_uses: args.maxUses,\n              allowed_domains: args.allowedDomains,\n              blocked_domains: args.blockedDomains,\n              user_location: args.userLocation,\n            });\n            break;\n          }\n          default:\n            toolWarnings.push({ type: 'unsupported-tool', tool });\n            break;\n        }\n        break;\n      default:\n        toolWarnings.push({ type: 'unsupported-tool', tool });\n        break;\n    }\n  }\n\n  if (toolChoice == null) {\n    return {\n      tools: anthropicTools,\n      toolChoice: disableParallelToolUse\n        ? { type: 'auto', disable_parallel_tool_use: disableParallelToolUse }\n        : undefined,\n      toolWarnings,\n      betas,\n    };\n  }\n\n  const type = toolChoice.type;\n\n  switch (type) {\n    case 'auto':\n      return {\n        tools: anthropicTools,\n        toolChoice: {\n          type: 'auto',\n          disable_parallel_tool_use: disableParallelToolUse,\n        },\n        toolWarnings,\n