@ai-sdk/open-responses/dist/index.mjs.map

The **[Open Responses provider](https://ai-sdk.dev/providers/ai-sdk-providers/open-responses)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for [Open Responses](https://www.openresponses.org/) compatible APIs.

{"version":3,"sources":["../src/version.ts","../src/open-responses-provider.ts","../src/responses/open-responses-language-model.ts","../src/responses/convert-to-open-responses-input.ts","../src/responses/open-responses-api.ts","../src/responses/map-open-responses-finish-reason.ts","../src/responses/open-responses-options.ts"],"sourcesContent":["// 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    : '0.0.0-test';\n","import {\n  LanguageModelV3,\n  NoSuchModelError,\n  ProviderV3,\n} from '@ai-sdk/provider';\nimport {\n  FetchFunction,\n  generateId,\n  loadApiKey,\n  withUserAgentSuffix,\n} from '@ai-sdk/provider-utils';\nimport { OpenResponsesLanguageModel } from './responses/open-responses-language-model';\nimport { VERSION } from './version';\n\nexport interface OpenResponsesProvider extends ProviderV3 {\n  (modelId: string): LanguageModelV3;\n}\n\nexport interface OpenResponsesProviderSettings {\n  /**\n   * URL for the Open Responses API POST endpoint.\n   */\n  url: string;\n\n  /**\n   * Provider name. Used as key for provider options and metadata.\n   */\n  name: string;\n\n  /**\n   * API key for authenticating requests.\n   */\n  apiKey?: string;\n\n  /**\n   * Custom headers to include in the requests.\n   */\n  headers?: Record<string, string>;\n\n  /**\n   * Custom fetch implementation. You can use it as a middleware to intercept requests,\n   * or to provide a custom fetch implementation for e.g. testing.\n   */\n  fetch?: FetchFunction;\n}\n\nexport function createOpenResponses(\n  options: OpenResponsesProviderSettings,\n): OpenResponsesProvider {\n  const providerName = options.name;\n\n  const getHeaders = () =>\n    withUserAgentSuffix(\n      {\n        ...(options.apiKey\n          ? {\n              Authorization: `Bearer ${options.apiKey}`,\n            }\n          : {}),\n        ...options.headers,\n      },\n      `ai-sdk/open-responses/${VERSION}`,\n    );\n\n  const createResponsesModel = (modelId: string) => {\n    return new OpenResponsesLanguageModel(modelId, {\n      provider: `${providerName}.responses`,\n      providerOptionsName: providerName,\n      headers: getHeaders,\n      url: options.url,\n      fetch: options.fetch,\n      generateId: () => generateId(),\n    });\n  };\n\n  const createLanguageModel = (modelId: string) => {\n    if (new.target) {\n      throw new Error(\n        'The OpenAI model function cannot be called with the new keyword.',\n      );\n    }\n\n    return createResponsesModel(modelId);\n  };\n\n  const provider = function (modelId: string) {\n    return createLanguageModel(modelId);\n  };\n\n  provider.specificationVersion = 'v3' as const;\n  provider.languageModel = createLanguageModel;\n\n  provider.embeddingModel = (modelId: string) => {\n    throw new NoSuchModelError({ modelId, modelType: 'embeddingModel' });\n  };\n  provider.imageModel = (modelId: string) => {\n    throw new NoSuchModelError({ modelId, modelType: 'imageModel' });\n  };\n\n  return provider as OpenResponsesProvider;\n}\n","import {\n  LanguageModelV3,\n  LanguageModelV3CallOptions,\n  LanguageModelV3Content,\n  LanguageModelV3FinishReason,\n  LanguageModelV3GenerateResult,\n  LanguageModelV3StreamPart,\n  LanguageModelV3StreamResult,\n  LanguageModelV3Usage,\n  SharedV3Warning,\n} from '@ai-sdk/provider';\nimport {\n  combineHeaders,\n  createEventSourceResponseHandler,\n  createJsonErrorResponseHandler,\n  createJsonResponseHandler,\n  jsonSchema,\n  parseProviderOptions,\n  ParseResult,\n  postJsonToApi,\n} from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { convertToOpenResponsesInput } from './convert-to-open-responses-input';\nimport {\n  FunctionToolParam,\n  OpenResponsesRequestBody,\n  OpenResponsesResponseBody,\n  OpenResponsesChunk,\n  openResponsesErrorSchema,\n  ToolChoiceParam,\n} from './open-responses-api';\nimport { mapOpenResponsesFinishReason } from './map-open-responses-finish-reason';\nimport { OpenResponsesConfig } from './open-responses-config';\nimport { openResponsesOptionsSchema } from './open-responses-options';\n\nexport class OpenResponsesLanguageModel implements LanguageModelV3 {\n  readonly specificationVersion = 'v3';\n\n  readonly modelId: string;\n\n  private readonly config: OpenResponsesConfig;\n\n  constructor(modelId: string, config: OpenResponsesConfig) {\n    this.modelId = modelId;\n    this.config = config;\n  }\n\n  readonly supportedUrls: Record<string, RegExp[]> = {\n    'image/*': [/^https?:\\/\\/.*$/],\n  };\n\n  get provider(): string {\n    return this.config.provider;\n  }\n\n  private async getArgs({\n    maxOutputTokens,\n    temperature,\n    stopSequences,\n    topP,\n    topK,\n    presencePenalty,\n    frequencyPenalty,\n    seed,\n    prompt,\n    providerOptions,\n    tools,\n    toolChoice,\n    responseFormat,\n  }: LanguageModelV3CallOptions): Promise<{\n    body: Omit<OpenResponsesRequestBody, 'stream' | 'stream_options'>;\n    warnings: SharedV3Warning[];\n  }> {\n    const warnings: SharedV3Warning[] = [];\n\n    if (stopSequences != null) {\n      warnings.push({ type: 'unsupported', feature: 'stopSequences' });\n    }\n\n    if (topK != null) {\n      warnings.push({ type: 'unsupported', feature: 'topK' });\n    }\n\n    if (seed != null) {\n      warnings.push({ type: 'unsupported', feature: 'seed' });\n    }\n\n    const {\n      input,\n      instructions,\n      warnings: inputWarnings,\n    } = await convertToOpenResponsesInput({\n      prompt,\n    });\n\n    warnings.push(...inputWarnings);\n\n    // Convert function tools to the Open Responses format\n    const functionTools: FunctionToolParam[] | undefined = tools\n      ?.filter(tool => tool.type === 'function')\n      .map(tool => ({\n        type: 'function' as const,\n        name: tool.name,\n        description: tool.description,\n        parameters: tool.inputSchema,\n        ...(tool.strict != null ? { strict: tool.strict } : {}),\n      }));\n\n    // Convert tool choice to the Open Responses format\n    const convertedToolChoice: ToolChoiceParam | undefined =\n      toolChoice == null\n        ? undefined\n        : toolChoice.type === 'tool'\n          ? { type: 'function', name: toolChoice.toolName }\n          : toolChoice.type; // 'auto' | 'none' | 'required'\n\n    const textFormat =\n      responseFormat?.type === 'json'\n        ? {\n            type: 'json_schema' as const,\n            ...(responseFormat.schema != null\n              ? {\n                  name: responseFormat.name ?? 'response',\n                  description: responseFormat.description,\n                  schema: responseFormat.schema,\n                  strict: true,\n                }\n              : {}),\n          }\n        : undefined;\n\n    const openResponsesOptions = await parseProviderOptions({\n      provider: this.config.providerOptionsName,\n      providerOptions,\n      schema: openResponsesOptionsSchema,\n    });\n\n    return {\n      body: {\n        model: this.modelId,\n        input,\n        instructions,\n        max_output_tokens: maxOutputTokens,\n        temperature,\n        top_p: topP,\n        presence_penalty: presencePenalty,\n        frequency_penalty: frequencyPenalty,\n        reasoning:\n          openResponsesOptions?.reasoningEffort != null ||\n          openResponsesOptions?.reasoningSummary != null\n            ? {\n                ...(openResponsesOptions?.reasoningEffort != null && {\n                  effort: openResponsesOptions.reasoningEffort,\n                }),\n                ...(openResponsesOptions?.reasoningSummary != null && {\n                  summary: openResponsesOptions.reasoningSummary,\n                }),\n              }\n            : undefined,\n        tools: functionTools?.length ? functionTools : undefined,\n        tool_choice: convertedToolChoice,\n        ...(textFormat != null && { text: { format: textFormat } }),\n      },\n      warnings,\n    };\n  }\n\n  async doGenerate(\n    options: LanguageModelV3CallOptions,\n  ): Promise<LanguageModelV3GenerateResult> {\n    const { body, warnings } = await this.getArgs(options);\n\n    const {\n      responseHeaders,\n      value: response,\n      rawValue: rawResponse,\n    } = await postJsonToApi({\n      url: this.config.url,\n      headers: combineHeaders(this.config.headers(), options.headers),\n      body,\n      failedResponseHandler: createJsonErrorResponseHandler({\n        errorSchema: openResponsesErrorSchema,\n        errorToMessage: error => error.error.message,\n      }),\n      successfulResponseHandler: createJsonResponseHandler(\n        // do not validate the response body, only apply types to the response body\n        jsonSchema<OpenResponsesResponseBody>(() => {\n          throw new Error('json schema not implemented');\n        }),\n      ),\n      abortSignal: options.abortSignal,\n      fetch: this.config.fetch,\n    });\n\n    const content: Array<LanguageModelV3Content> = [];\n    let hasToolCalls = false;\n\n    for (const part of response.output!) {\n      switch (part.type) {\n        // TODO AI SDK 7 adjust reasoning in the specification to better support the reasoning structure from open responses.\n        case 'reasoning': {\n          for (const contentPart of part.content ?? []) {\n            content.push({\n              type: 'reasoning',\n              text: contentPart.text,\n            });\n          }\n          break;\n        }\n\n        case 'message': {\n          for (const contentPart of part.content) {\n            content.push({\n              type: 'text',\n              text: contentPart.text,\n            });\n          }\n\n          break;\n        }\n\n        case 'function_call': {\n          hasToolCalls = true;\n          content.push({\n            type: 'tool-call',\n            toolCallId: part.call_id,\n            toolName: part.name,\n            input: part.arguments,\n          });\n          break;\n        }\n      }\n    }\n\n    const usage = response.usage;\n    const inputTokens = usage?.input_tokens;\n    const cachedInputTokens = usage?.input_tokens_details?.cached_tokens;\n    const outputTokens = usage?.output_tokens;\n    const reasoningTokens = usage?.output_tokens_details?.reasoning_tokens;\n\n    return {\n      content,\n      finishReason: {\n        unified: mapOpenResponsesFinishReason({\n          finishReason: response.incomplete_details?.reason,\n          hasToolCalls,\n        }),\n        raw: response.incomplete_details?.reason ?? undefined,\n      },\n      usage: {\n        inputTokens: {\n          total: inputTokens,\n          noCache: (inputTokens ?? 0) - (cachedInputTokens ?? 0),\n          cacheRead: cachedInputTokens,\n          cacheWrite: undefined,\n        },\n        outputTokens: {\n          total: outputTokens,\n          text: (outputTokens ?? 0) - (reasoningTokens ?? 0),\n          reasoning: reasoningTokens,\n        },\n        raw: response.usage,\n      },\n      request: { body },\n      response: {\n        id: response.id,\n        timestamp: new Date(response.created_at! * 1000),\n        modelId: response.model,\n        headers: responseHeaders,\n        body: rawResponse,\n      },\n      providerMetadata: undefined,\n      warnings,\n    };\n  }\n\n  async doStream(\n    options: LanguageModelV3CallOptions,\n  ): Promise<LanguageModelV3StreamResult> {\n    const { body, warnings } = await this.getArgs(options);\n\n    const { responseHeaders, value: response } = await postJsonToApi({\n      url: this.config.url,\n      headers: combineHeaders(this.config.headers(), options.headers),\n      body: {\n        ...body,\n        stream: true,\n      } satisfies OpenResponsesRequestBody,\n      failedResponseHandler: createJsonErrorResponseHandler({\n        errorSchema: openResponsesErrorSchema,\n        errorToMessage: error => error.error.message,\n      }),\n      // TODO consider validation\n      successfulResponseHandler: createEventSourceResponseHandler(z.any()),\n      abortSignal: options.abortSignal,\n      fetch: this.config.fetch,\n    });\n\n    const usage: LanguageModelV3Usage = {\n      inputTokens: {\n        total: undefined,\n        noCache: undefined,\n        cacheRead: undefined,\n        cacheWrite: undefined,\n      },\n      outputTokens: {\n        total: undefined,\n        text: undefined,\n        reasoning: undefined,\n      },\n    };\n\n    const updateUsage = (\n      responseUsage?: OpenResponsesResponseBody['usage'],\n    ) => {\n      if (!responseUsage) {\n        return;\n      }\n\n      const inputTokens = responseUsage.input_tokens;\n      const cachedInputTokens =\n        responseUsage.input_tokens_details?.cached_tokens;\n      const outputTokens = responseUsage.output_tokens;\n      const reasoningTokens =\n        responseUsage.output_tokens_details?.reasoning_tokens;\n\n      usage.inputTokens = {\n        total: inputTokens,\n        noCache: (inputTokens ?? 0) - (cachedInputTokens ?? 0),\n        cacheRead: cachedInputTokens,\n        cacheWrite: undefined,\n      };\n      usage.outputTokens = {\n        total: outputTokens,\n        text: (outputTokens ?? 0) - (reasoningTokens ?? 0),\n        reasoning: reasoningTokens,\n      };\n      usage.raw = responseUsage;\n    };\n\n    let isActiveReasoning = false;\n    let hasToolCalls = false;\n    let finishReason: LanguageModelV3FinishReason = {\n      unified: 'other',\n      raw: undefined,\n    };\n    const toolCallsByItemId: Record<\n      string,\n      { toolName?: string; toolCallId?: string; arguments?: string }\n    > = {};\n\n    return {\n      stream: response.pipeThrough(\n        new TransformStream<\n          ParseResult<OpenResponsesChunk>,\n          LanguageModelV3StreamPart\n        >({\n          start(controller) {\n            controller.enqueue({ type: 'stream-start', warnings });\n          },\n\n          transform(parseResult, controller) {\n            if (options.includeRawChunks) {\n              controller.enqueue({\n                type: 'raw',\n                rawValue: parseResult.rawValue,\n              });\n            }\n\n            if (!parseResult.success) {\n              controller.enqueue({ type: 'error', error: parseResult.error });\n              return;\n            }\n\n            const chunk = parseResult.value;\n\n            // Tool call events (single-shot tool-call when complete)\n            if (\n              chunk.type === 'response.output_item.added' &&\n              chunk.item.type === 'function_call'\n            ) {\n              toolCallsByItemId[chunk.item.id] = {\n                toolName: chunk.item.name,\n                toolCallId: chunk.item.call_id,\n                arguments: chunk.item.arguments,\n              };\n            } else if (\n              (chunk as { type: string }).type ===\n              'response.function_call_arguments.delta'\n            ) {\n              const functionCallChunk = chunk as {\n                item_id: string;\n                delta: string;\n              };\n              const toolCall =\n                toolCallsByItemId[functionCallChunk.item_id] ??\n                (toolCallsByItemId[functionCallChunk.item_id] = {});\n              toolCall.arguments =\n                (toolCall.arguments ?? '') + functionCallChunk.delta;\n            } else if (\n              (chunk as { type: string }).type ===\n              'response.function_call_arguments.done'\n            ) {\n              const functionCallChunk = chunk as {\n                item_id: string;\n                arguments: string;\n              };\n              const toolCall =\n                toolCallsByItemId[functionCallChunk.item_id] ??\n                (toolCallsByItemId[functionCallChunk.item_id] = {});\n              toolCall.arguments = functionCallChunk.arguments;\n            } else if (\n              chunk.type === 'response.output_item.done' &&\n              chunk.item.type === 'function_call'\n            ) {\n              const toolCall = toolCallsByItemId[chunk.item.id];\n              const toolName = toolCall?.toolName ?? chunk.item.name;\n              const toolCallId = toolCall?.toolCallId ?? chunk.item.call_id;\n              const input = toolCall?.arguments ?? chunk.item.arguments ?? '';\n\n              controller.enqueue({\n                type: 'tool-call',\n                toolCallId,\n                toolName,\n                input,\n              });\n              hasToolCalls = true;\n\n              delete toolCallsByItemId[chunk.item.id];\n            }\n\n            // Reasoning events (note: response.reasoning_text.delta is an LM Studio extension, not in official spec)\n            else if (\n              chunk.type === 'response.output_item.added' &&\n              chunk.item.type === 'reasoning'\n            ) {\n              controller.enqueue({\n                type: 'reasoning-start',\n                id: chunk.item.id,\n              });\n              isActiveReasoning = true;\n            } else if (\n              (chunk as { type: string }).type ===\n              'response.reasoning_text.delta'\n            ) {\n              const reasoningChunk = chunk as {\n                item_id: string;\n                delta: string;\n              };\n              controller.enqueue({\n                type: 'reasoning-delta',\n                id: reasoningChunk.item_id,\n                delta: reasoningChunk.delta,\n              });\n            } else if (\n              chunk.type === 'response.output_item.done' &&\n              chunk.item.type === 'reasoning'\n            ) {\n              controller.enqueue({ type: 'reasoning-end', id: chunk.item.id });\n              isActiveReasoning = false;\n            }\n\n            // Text events\n            else if (\n              chunk.type === 'response.output_item.added' &&\n              chunk.item.type === 'message'\n            ) {\n              controller.enqueue({ type: 'text-start', id: chunk.item.id });\n            } else if (chunk.type === 'response.output_text.delta') {\n              controller.enqueue({\n                type: 'text-delta',\n                id: chunk.item_id,\n                delta: chunk.delta,\n              });\n            } else if (\n              chunk.type === 'response.output_item.done' &&\n              chunk.item.type === 'message'\n            ) {\n              controller.enqueue({ type: 'text-end', id: chunk.item.id });\n            } else if (\n              chunk.type === 'response.completed' ||\n              chunk.type === 'response.incomplete'\n            ) {\n              const reason = chunk.response.incomplete_details?.reason;\n              finishReason = {\n                unified: mapOpenResponsesFinishReason({\n                  finishReason: reason,\n                  hasToolCalls,\n                }),\n                raw: reason ?? undefined,\n              };\n              updateUsage(chunk.response.usage);\n            } else if (chunk.type === 'response.failed') {\n              finishReason = {\n                unified: 'error',\n                raw: chunk.response.error?.code ?? chunk.response.status,\n              };\n              updateUsage(chunk.response.usage);\n            }\n          },\n\n          flush(controller) {\n            if (isActiveReasoning) {\n              controller.enqueue({ type: 'reasoning-end', id: 'reasoning-0' });\n            }\n\n            controller.enqueue({\n              type: 'finish',\n              finishReason,\n              usage,\n              providerMetadata: undefined,\n            });\n          },\n        }),\n      ),\n      request: { body },\n      response: { headers: responseHeaders },\n    };\n  }\n}\n","import { LanguageModelV3Prompt, SharedV3Warning } from '@ai-sdk/provider';\nimport { convertToBase64 } from '@ai-sdk/provider-utils';\nimport {\n  FunctionCallItemParam,\n  FunctionCallOutputItemParam,\n  InputFileContentParam,\n  InputImageContentParam,\n  InputTextContentParam,\n  OpenResponsesRequestBody,\n  OutputTextContentParam,\n  RefusalContentParam,\n} from './open-responses-api';\n\nexport async function convertToOpenResponsesInput({\n  prompt,\n}: {\n  prompt: LanguageModelV3Prompt;\n}): Promise<{\n  input: OpenResponsesRequestBody['input'];\n  instructions: string | undefined;\n  warnings: Array<SharedV3Warning>;\n}> {\n  const input: OpenResponsesRequestBody['input'] = [];\n  const warnings: Array<SharedV3Warning> = [];\n  const systemMessages: string[] = [];\n\n  for (const { role, content } of prompt) {\n    switch (role) {\n      case 'system': {\n        systemMessages.push(content);\n        break;\n      }\n\n      case 'user': {\n        const userContent: Array<\n          InputTextContentParam | InputImageContentParam | InputFileContentParam\n        > = [];\n\n        for (const part of content) {\n          switch (part.type) {\n            case 'text': {\n              userContent.push({ type: 'input_text', text: part.text });\n              break;\n            }\n            case 'file': {\n              if (!part.mediaType.startsWith('image/')) {\n                warnings.push({\n                  type: 'other',\n                  message: `unsupported file content type: ${part.mediaType}`,\n                });\n                break;\n              }\n\n              const mediaType =\n                part.mediaType === 'image/*' ? 'image/jpeg' : part.mediaType;\n\n              userContent.push({\n                type: 'input_image',\n                ...(part.data instanceof URL\n                  ? { image_url: part.data.toString() }\n                  : {\n                      image_url: `data:${mediaType};base64,${convertToBase64(part.data)}`,\n                    }),\n              });\n              break;\n            }\n          }\n        }\n\n        input.push({ type: 'message', role: 'user', content: userContent });\n        break;\n      }\n\n      case 'assistant': {\n        const assistantContent: Array<\n          OutputTextContentParam | RefusalContentParam\n        > = [];\n        const toolCalls: Array<FunctionCallItemParam> = [];\n\n        for (const part of content) {\n          switch (part.type) {\n            case 'text': {\n              assistantContent.push({ type: 'output_text', text: part.text });\n              break;\n            }\n            case 'tool-call': {\n              const argumentsValue =\n                typeof part.input === 'string'\n                  ? part.input\n                  : JSON.stringify(part.input);\n              toolCalls.push({\n                type: 'function_call',\n                call_id: part.toolCallId,\n                name: part.toolName,\n                arguments: argumentsValue,\n              });\n              break;\n            }\n          }\n        }\n\n        // Push assistant message with text content if any\n        if (assistantContent.length > 0) {\n          input.push({\n            type: 'message',\n            role: 'assistant',\n            content: assistantContent,\n          });\n        }\n\n        // Push function calls as separate items\n        for (const toolCall of toolCalls) {\n          input.push(toolCall);\n        }\n\n        break;\n      }\n\n      case 'tool': {\n        for (const part of content) {\n          if (part.type === 'tool-result') {\n            const output = part.output;\n            let contentValue: FunctionCallOutputItemParam['output'];\n\n            switch (output.type) {\n              case 'text':\n              case 'error-text':\n                contentValue = output.value;\n                break;\n              case 'execution-denied':\n                contentValue = output.reason ?? 'Tool execution denied.';\n                break;\n              case 'json':\n              case 'error-json':\n                contentValue = JSON.stringify(output.value);\n                break;\n              case 'content': {\n                const contentParts: Array<\n                  | InputTextContentParam\n                  | InputImageContentParam\n                  | InputFileContentParam\n                > = [];\n                for (const item of output.value) {\n                  switch (item.type) {\n                    case 'text': {\n                      contentParts.push({\n                        type: 'input_text',\n                        text: item.text,\n                      });\n                      break;\n                    }\n                    case 'image-data': {\n                      contentParts.push({\n                        type: 'input_image',\n                        image_url: `data:${item.mediaType};base64,${item.data}`,\n                      });\n                      break;\n                    }\n                    case 'image-url': {\n                      contentParts.push({\n                        type: 'input_image',\n                        image_url: item.url,\n                      });\n                      break;\n                    }\n                    case 'file-data': {\n                      contentParts.push({\n                        type: 'input_file',\n                        filename: item.filename ?? 'data',\n                        file_data: `data:${item.mediaType};base64,${item.data}`,\n                      });\n                      break;\n                    }\n                    default: {\n                      warnings.push({\n                        type: 'other',\n                        message: `unsupported tool content part type: ${(item as { type: string }).type}`,\n                      });\n                      break;\n                    }\n                  }\n                }\n                contentValue = contentParts;\n                break;\n              }\n            }\n\n            input.push({\n              type: 'function_call_output',\n              call_id: part.toolCallId,\n              output: contentValue,\n            });\n          }\n        }\n        break;\n      }\n    }\n  }\n\n  return {\n    input,\n    instructions:\n      systemMessages.length > 0 ? systemMessages.join('\\n') : undefined,\n    warnings,\n  };\n}\n","import { JSONSchema7 } from '@ai-sdk/provider';\nimport { lazySchema } from '@ai-sdk/provider-utils';\nimport { z } from 'zod/v4';\nimport { zodSchema } from '@ai-sdk/provider-utils';\n\nexport const openResponsesErrorSchema = lazySchema(() =>\n  zodSchema(\n    z.object({\n      error: z.object({\n        message: z.string(),\n        type: z.string(),\n        param: z.string(),\n        code: z.string(),\n      }),\n    }),\n  ),\n);\n\n// ============================================================================\n// Enums\n// ============================================================================\n\n/**\n * The status of a function call or message item.\n */\nexport type FunctionCallStatus = 'in_progress' | 'completed' | 'incomplete';\n\n/**\n * Image detail level for input images.\n */\nexport type ImageDetail = 'low' | 'high' | 'auto';\n\n/**\n * Reasoning effort level.\n */\nexport type ReasoningEffortEnum = 'none' | 'low' | 'medium' | 'high' | 'xhigh';\n\n/**\n * Reasoning summary level.\n */\nexport type ReasoningSummaryEnum = 'concise' | 'detailed' | 'auto';\n\n/**\n * Tool choice value enum.\n */\nexport type ToolChoiceValueEnum = 'none' | 'auto' | 'required';\n\n/**\n * Verbosity level for text output.\n */\nexport type VerbosityEnum = 'low' | 'medium' | 'high';\n\n// ============================================================================\n// Content Types\n// ============================================================================\n\n/**\n * A text input to the model.\n */\nexport type InputTextContentParam = {\n  type: 'input_text';\n  text: string;\n};\n\n/**\n * An image input to the model.\n */\nexport type InputImageContentParam = {\n  type: 'input_image';\n  image_url?: string;\n  detail?: ImageDetail;\n};\n\n/**\n * A file input to the model.\n */\nexport type InputFileContentParam = {\n  type: 'input_file';\n  filename?: string;\n  file_data?: string;\n  file_url?: string;\n};\n\n/**\n * A video input to the model.\n */\nexport type InputVideoContent = {\n  type: 'input_video';\n  video_url: string;\n};\n\n/**\n * A text output from the model.\n */\nexport type OutputTextContentParam = {\n  type: 'output_text';\n  text: string;\n  annotations?: UrlCitationParam[];\n};\n\n/**\n * A refusal from the model.\n */\nexport type RefusalContentParam = {\n  type: 'refusal';\n  refusal: string;\n};\n\n/**\n * A URL citation annotation.\n */\nexport type UrlCitationParam = {\n  type: 'url_citation';\n  start_index: number;\n  end_index: number;\n  url: string;\n  title: string;\n};\n\n/**\n * Reasoning summary content.\n */\nexport type ReasoningSummaryContentParam = {\n  type: 'summary_text';\n  text: string;\n};\n\n// ============================================================================\n// Message Item Types\n// ============================================================================\n\n/**\n * An internal identifier for an item to reference.\n */\nexport type ItemReferenceParam = {\n  type?: 'item_reference';\n  id: string;\n};\n\n/**\n * A reasoning item.\n */\nexport type ReasoningItemParam = {\n  id?: string;\n  type: 'reasoning';\n  summary: ReasoningSummaryContentParam[];\n  content?: unknown;\n  encrypted_content?: string;\n};\n\n/**\n * A user message item.\n */\nexport type UserMessageItemParam = {\n  id?: string;\n  type: 'message';\n  role: 'user';\n  content:\n    | string\n    | Array<\n        InputTextContentParam | InputImageContentParam | InputFileContentParam\n      >;\n  status?: string;\n};\n\n/**\n * A system message item.\n */\nexport type SystemMessageItemParam = {\n  id?: string;\n  type: 'message';\n  role: 'system';\n  content: string | InputTextContentParam[];\n  status?: string;\n};\n\n/**\n * A developer message item.\n */\nexport type DeveloperMessageItemParam = {\n  id?: string;\n  type: 'message';\n  role: 'developer';\n  content: string | InputTextContentParam[];\n  status?: string;\n};\n\n/**\n * An assistant message item.\n */\nexport type AssistantMessageItemParam = {\n  id?: string;\n  type: 'message';\n  role: 'assistant';\n  content: string | Array<OutputTextContentParam | RefusalContentParam>;\n  status?: string;\n};\n\n/**\n * A function call item.\n */\nexport type FunctionCallItemParam = {\n  id?: string;\n  call_id: string;\n  type: 'function_call';\n  name: string;\n  arguments: string;\n  status?: FunctionCallStatus;\n};\n\n/**\n * A function call output item.\n */\nexport type FunctionCallOutputItemParam = {\n  id?: string;\n  call_id: string;\n  type: 'function_call_output';\n  output:\n    | string\n    | Array<\n        | InputTextContentParam\n        | InputImageContentParam\n        | InputFileContentParam\n        | InputVideoContent\n      >;\n  status?: FunctionCallStatus;\n};\n\n// ============================================================================\n// Tool Types\n// ============================================================================\n\n/**\n * A function tool parameter.\n */\nexport type FunctionToolParam = {\n  name: string;\n  description?: string;\n  parameters?: JSONSchema7;\n  strict?: boolean;\n  type: 'function';\n};\n\n/**\n * A specific function tool choice.\n */\nexport type SpecificFunctionParam = {\n  type: 'function';\n  name: string;\n};\n\n/**\n * Allowed tools parameter.\n */\nexport type AllowedToolsParam = {\n  type: 'allowed_tools';\n  tools: SpecificFunctionParam[];\n  mode?: ToolChoiceValueEnum;\n};\n\n/**\n * Controls which tool the model should use, if any.\n */\nexport type ToolChoiceParam =\n  | ToolChoiceValueEnum\n  | SpecificFunctionParam\n  | AllowedToolsParam;\n\n// ============================================================================\n// Configuration Types\n// ============================================================================\n\n/**\n * Set of 16 key-value pairs that can be attached to an object.\n */\nexport type MetadataParam = Record<string, string>;\n\n/**\n * Text response format (plain text).\n */\nexport type TextResponseFormat = {\n  type: 'text';\n};\n\n/**\n * JSON schema response format.\n */\nexport type JsonSchemaResponseFormatParam = {\n  type: 'json_schema';\n  description?: string;\n  name?: string;\n  schema?: JSONSchema7;\n  strict?: boolean;\n};\n\n/**\n * Configuration options for text output.\n */\nexport type TextParam = {\n  format?: TextResponseFormat | JsonSchemaResponseFormatParam;\n  verbosity?: VerbosityEnum;\n};\n\n/**\n * Options that control streamed response behavior.\n */\nexport type StreamOptionsParam = {\n  include_obfuscation?: boolean;\n};\n\n/**\n * Configuration options for reasoning behavior.\n */\nexport type ReasoningParam = {\n  effort?: ReasoningEffortEnum;\n  summary?: ReasoningSummaryEnum;\n};\n\n// ============================================================================\n// Response-Specific Types\n// ============================================================================\n\n/**\n * The status of a message item in the response.\n */\nexport type MessageStatus = 'in_progress' | 'completed' | 'incomplete';\n\n/**\n * Truncation enum for responses.\n */\nexport type TruncationEnum = 'auto' | 'disabled';\n\n/**\n * Service tier enum.\n */\nexport type ServiceTierEnum = 'auto' | 'default' | 'flex' | 'priority';\n\n/**\n * A top log probability of a token.\n */\nexport type TopLogProb = {\n  token: string;\n  logprob: number;\n  bytes: number[];\n};\n\n/**\n * The log probability of a token.\n */\nexport type LogProb = {\n  token: string;\n  logprob: number;\n  bytes: number[];\n  top_logprobs: TopLogProb[];\n};\n\n/**\n * A URL citation annotation in a response.\n */\nexport type UrlCitationBody = {\n  type: 'url_citation';\n  url: string;\n  start_index: number;\n  end_index: number;\n  title: string;\n};\n\n/**\n * An annotation that applies to a span of output text.\n */\nexport type Annotation = UrlCitationBody;\n\n/**\n * A text input content in a response.\n */\nexport type InputTextContent = {\n  type: 'input_text';\n  text: string;\n};\n\n/**\n * A text output from the model in a response.\n */\nexport type OutputTextContent = {\n  type: 'output_text';\n  text: string;\n  annotations: Annotation[];\n  logprobs: LogProb[];\n};\n\n/**\n * A refusal from the model in a response.\n */\nexport type RefusalContent = {\n  type: 'refusal';\n  refusal: string;\n};\n\n/**\n * Reasoning text from the model.\n */\nexport type ReasoningTextContent = {\n  type: 'reasoning_text';\n  text: string;\n};\n\n/**\n * A summary text from the model.\n */\nexport type SummaryTextContent = {\n  type: 'summary_text';\n  text: string;\n};\n\n/**\n * An image input content in a response.\n */\nexport type InputImageContent = {\n  type: 'input_image';\n  image_url?: string;\n  detail: ImageDetail;\n};\n\n/**\n * A file input content in a response.\n */\nexport type InputFileContent = {\n  type: 'input_file';\n  filename?: string;\n  file_url?: string;\n};\n\n/**\n * A message in the response.\n */\nexport type Message = {\n  type: 'message';\n  id: string;\n  status: MessageStatus;\n  role: 'user' | 'assistant' | 'system' | 'developer';\n  content: InputTextContent[];\n};\n\n/**\n * A function tool call that was generated by the model.\n */\nexport type FunctionCall = {\n  type: 'function_call';\n  id: string;\n  call_id: string;\n  name: string;\n  arguments: string;\n  status: FunctionCallStatus;\n};\n\n/**\n * A function tool call output that was returned.\n */\nexport type FunctionCallOutput = {\n  type: 'function_call_output';\n  id: string;\n  call_id: string;\n  output:\n    | string\n    | Array<InputTextContent | InputImageContent | InputFileContent>;\n  status: FunctionCallStatus;\n};\n\n/**\n * A reasoning item that was generated by the model.\n */\nexport type ReasoningBody = {\n  type: 'reasoning';\n  id: string;\n  content?: InputTextContent[];\n  summary: InputTextContent[];\n  encrypted_content?: string;\n};\n\n/**\n * Output item field union type.\n */\nexport type OutputItem =\n  | FunctionCall\n  | FunctionCallOutput\n  | Message\n  | ReasoningBody;\n\n/**\n * Details about why the response was incomplete.\n */\nexport type IncompleteDetails = {\n  reason: string;\n};\n\n/**\n * An error that occurred while generating the response.\n */\nexport type ResponseError = {\n  code: string;\n  message: string;\n};\n\n/**\n * A function tool in a response.\n */\nexport type FunctionTool = {\n  type: 'function';\n  name: string;\n  description?: string;\n  parameters?: JSONSchema7;\n  strict?: boolean;\n};\n\n/**\n * Function tool choice in a response.\n */\nexport type FunctionToolChoice = {\n  type: 'function';\n  name?: string;\n};\n\n/**\n * Allowed tool choice in a response.\n */\nexport type AllowedToolChoice = {\n  type: 'allowed_tools';\n  tools: FunctionToolChoice[];\n  mode: ToolChoiceValueEnum;\n};\n\n/**\n * Tool choice in a response.\n */\nexport type ResponseToolChoice =\n  | ToolChoiceValueEnum\n  | FunctionToolChoice\n  | AllowedToolChoice;\n\n/**\n * JSON object response format.\n */\nexport type JsonObjectResponseFormat = {\n  type: 'json_object';\n};\n\n/**\n * JSON schema response format in a response.\n */\nexport type JsonSchemaResponseFormat = {\n  type: 'json_schema';\n  name: string;\n  description?: string;\n  schema: unknown;\n  strict: boolean;\n};\n\n/**\n * Text field in a response.\n */\nexport type TextField = {\n  format?:\n    | TextResponseFormat\n    | JsonObjectResponseFormat\n    | JsonSchemaResponseFormat;\n  verbosity?: VerbosityEnum;\n};\n\n/**\n * A breakdown of input token usage that was recorded.\n */\nexport type InputTokensDetails = {\n  cached_tokens: number;\n};\n\n/**\n * A breakdown of output token usage that was recorded.\n */\nexport type OutputTokensDetails = {\n  reasoning_tokens: number;\n};\n\n/**\n * Token usage statistics that were recorded for the response.\n */\nexport type Usage = {\n  input_tokens: number;\n  output_tokens: number;\n  total_tokens: number;\n  input_tokens_details: InputTokensDetails;\n  output_tokens_details: OutputTokensDetails;\n};\n\n/**\n * Reasoning configuration and outputs that were produced for this response.\n */\nexport type Reasoning = {\n  effort?: ReasoningEffortEnum;\n  summary?: ReasoningSummaryEnum;\n};\n\n// ============================================================================\n// Request Body\n// ============================================================================\n\n/**\n * Body that is sent to the Open Responses API.\n */\nexport type OpenResponsesRequestBody = {\n  /**\n   * The model to use for this request, e.g. 'gpt-5.4'.\n   */\n  model: string;\n\n  /**\n   * Context for the model: either a string (interpreted as a user message),\n   * or an array of structured message items.\n   */\n  input:\n    | string\n    | Array<\n        | ItemReferenceParam\n        | ReasoningItemParam\n        | UserMessageItemParam\n        | SystemMessageItemParam\n        | DeveloperMessageItemParam\n        | AssistantMessageItemParam\n        | FunctionCallItemParam\n        | FunctionCallOutputItemParam\n      >;\n\n  /**\n   * The ID of the response to use as the prior turn for this request.\n   */\n  previous_response_id?: string;\n\n  /**\n   * Options specifying extra values to include in the response.\n   */\n  include?: Array<\n    'reasoning.encrypted_content' | 'message.output_text.logprobs'\n  >;\n\n  /**\n   * A list of tools that the model may call while generating the response.\n   */\n  tools?: FunctionToolParam[];\n\n  /**\n   * Controls which tool the model should use, if any.\n   */\n  tool_choice?: ToolChoiceParam;\n\n  /**\n   * Structured metadata as up to 16 key-value pairs.\n   */\n  metadata?: MetadataParam;\n\n  /**\n   * Configuration options for text output.\n   */\n  text?: TextParam;\n\n  /**\n   * Sampling temperature to use, between 0 and 2.\n   */\n  temperature?: number;\n\n  /**\n   * Nucleus sampling parameter, between 0 and 1.\n   */\n  top_p?: number;\n\n  /**\n   * Penalizes new tokens based on whether they appear in the text so far.\n   */\n  presence_penalty?: number;\n\n  /**\n   * Penalizes new tokens based on their frequency in the text so far.\n   */\n  frequency_penalty?: number;\n\n  /**\n   * Whether the model may call multiple tools in parallel.\n   */\n  parallel_tool_calls?: boolean;\n\n  /**\n   * Whether to stream response events as server-sent events.\n   */\n  stream?: boolean;\n\n  /**\n   * Options that control streamed response behavior.\n   */\n  stream_options?: StreamOptionsParam;\n\n  /**\n   * Whether to run the request in the background and return immediately.\n   */\n  background?: boolean;\n\n  /**\n   * Maximum number of tokens the model may generate.\n   */\n  max_output_tokens?: number;\n\n  /**\n   * Maximum number of tool calls the model may make while generating the response.\n   */\n  max_tool_calls?: number;\n\n  /**\n   * Configuration options for reasoning behavior.\n   */\n  reasoning?: ReasoningParam;\n\n  /**\n   * A stable identifier used for safety monitoring and abuse detection.\n   */\n  safety_identifier?: string;\n\n  /**\n   * A key to use when reading/writing to the prompt cache.\n   */\n  prompt_cache_key?: string;\n\n  /**\n   * Controls how input is truncated if it exceeds the model's context window.\n   * - 'auto': Let the service decide how to truncate.\n   * - 'disabled': Disable truncation. Context overflow yields 400 error.\n   */\n  truncation?: 'auto' | 'disabled';\n\n  /**\n   * Additional instructions to guide the model for this request.\n   */\n  instructions?: string;\n\n  /**\n   * Whether to store the response so it can be retrieved later.\n   */\n  store?: boolean;\n\n  /**\n   * The service tier to use for this request.\n   * - 'auto' | 'default' | 'flex' | 'priority'\n   */\n  service_tier?: 'auto' | 'default' | 'flex' | 'priority';\n\n  /**\n   * Number of most likely tokens to return at each position, with logprobs.\n   */\n  top_logprobs?: number;\n};\n\n// ============================================================================\n// Response Body\n// ============================================================================\n\n/**\n * Response body from the Open Responses API.\n */\nexport type OpenResponsesResponseBody = {\n  /**\n   * The unique ID of the response that was created.\n   */\n  id: string;\n\n  /**\n   * The object type, which is always 'response'.\n   */\n  object: 'response';\n\n  /**\n   * The Unix timestamp (in seconds) for when the response was created.\n   */\n  created_at: number;\n\n  /**\n   * The Unix timestamp (in seconds) for when the response was completed, if it was completed.\n   */\n  completed_at?: number;\n\n  /**\n   * The status that was set for the response.\n   */\n  status: string;\n\n  /**\n   * Details about why the response was incomplete, if applicable.\n   */\n  incomplete_details?: IncompleteDetails;\n\n  /**\n   * The model that generated this response.\n   */\n  model: string;\n\n  /**\n   * The ID of the previous response in the chain that was referenced, if any.\n   */\n  previous_response_id?: string;\n\n  /**\n   * Additional instructions that were used to guide the model for this response.\n   */\n  instructions?: string;\n\n  /**\n   * The output items that were generated by the model.\n   */\n  output: OutputItem[];\n\n  /**\n   * The error that occurred, if the response failed.\n   */\n  error?: ResponseError;\n\n  /**\n   * The tools that were available to the model during response generation.\n   */\n  tools?: FunctionTool[];\n\n  /**\n   * The tool choice configuration that was used.\n   */\n  tool_choice?: ResponseToolChoice;\n\n  /**\n   * How the input was truncated by the service when it exceeded the model context window.\n   */\n  truncation?: TruncationEnum;\n\n  /**\n   * Whether the model was allowed to call multiple tools in parallel.\n   */\n  parallel_tool_calls?: boolean;\n\n  /**\n   * Configuration options for text output that were used.\n   */\n  text?: TextField;\n\n  /**\n   * The nucleus sampling parameter that was used for this response.\n   */\n  top_p?: number;\n\n  /**\n   * The presence penalty that was used.\n   */\n  presence_penalty?: number;\n\n  /**\n   * The frequency penalty that was used.\n   */\n  frequency_penalty?: number;\n\n  /**\n   * The number of most likely tokens that were returned at each position.\n   */\n  top_logprobs?: number;\n\n  /**\n   * The sampling temperature that was used for this response.\n   */\n  temperature?: number;\n\n  /**\n   * Reasoning configuration and outputs that were produced for this response.\n   */\n  reasoning?: Reasoning;\n\n  /**\n   * Token usage statistics that were recorded for the response, if available.\n   */\n  usage?: Usage;\n\n  /**\n   * The maximum number of tokens the model was allowed to generate for this response.\n   */\n  max_output_tokens?: number;\n\n  /**\n   * The maximum number of tool calls the model was allowed to make.\n   */\n  max_tool_calls?: number;\n\n  /**\n   * Whether this response was stored so it can be retrieved later.\n   */\n  store?: boolean;\n\n  /**\n   * Whether this request was run in the background.\n   */\n  background?: boolean;\n\n  /**\n   * The service tier that was used for this response.\n   */\n  service_tier?: string;\n\n  /**\n   * Developer-defined metadata that was associated with the response.\n   */\n  metadata?: unknown;\n\n  /**\n   * A stable identifier that was used for safety monitoring and abuse detection.\n   */\n  safety_identifier?: string;\n\n  /**\n   * A key that was used to read from or write to the prompt cache.\n   */\n  prompt_cache_key?: string;\n};\n\n// ============================================================================\n// Streaming Chunk Types\n// ============================================================================\n\n/**\n * Content part for streaming - output text.\n */\nexport type OutputTextContentPart = {\n  type: 'output_text';\n  text: string;\n  annotations: Annotation[];\n};\n\n/**\n * Content part for streaming - refusal.\n */\nexport type RefusalContentPart = {\n  type: 'refusal';\n  refusal: string;\n};\n\n/**\n * Union of content parts that can appear in streaming.\n */\nexport type ContentPart = OutputTextContentPart | RefusalContentPart;\n\n// ----------------------------------------------------------------------------\n// State Machine Events\n// ----------------------------------------------------------------------------\n\n/**\n * Emitted when a response is created.\n */\nexport type ResponseCreatedEvent = {\n  type: 'response.created';\n  sequence_number: number;\n  response: OpenResponsesResponseBody;\n};\n\n/**\n * Emitted when a response transitions to in_progress status.\n */\nexport type ResponseInProgressEvent = {\n  type: 'response.in_progress';\n  sequence_number: number;\n  response: OpenResponsesResponseBody;\n};\n\n/**\n * Emitted when a response completes successfully.\n */\nexport type ResponseCompletedEvent = {\n  type: 'response.completed';\n  sequence_number: number;\n  response: OpenResponsesResponseBody;\n};\n\n/**\n * Emitted when a response fails.\n */\nexport type ResponseFailedEvent = {\n  type: 'response.failed';\n  sequence_number: number;\n  response: OpenResponsesResponseBody;\n};\n\n/**\n * Emitted when a response is incomplete (e.g., token budget exhausted).\n */\nexport type ResponseIncompleteEvent = {\n  type: 'response.incomplete';\n  sequence_number: number;\n  response: OpenResponsesResponseBody;\n};\n\n// ----------------------------------------------------------------------------\n// Delta Events - Output Items\n// ----------------------------------------------------------------------------\n\n/**\n * Emitted when a new output item is added to the response.\n */\nexport type ResponseOutputItemAddedEvent = {\n  type: 'response.output_item.added';\n  sequence_number: number;\n  output_index: number;\n  item: OutputItem;\n};\n\n/**\n * Emitted when an output item is completed.\n */\nexport type ResponseOutputItemDoneEvent = {\n  type: 'response.output_item.done';\n  sequence_number: number;\n  output_index: number;\n  item: OutputItem;\n};\n\n// ----------------------------------------------------------------------------\n// Delta Events - Content Parts\n// ----------------------------------------------------------------------------\n\n/**\n * Emitted when a new content part is added to an item.\n */\nexport type ResponseContentPartAddedEvent = {\n  type: 'response.content_part.added';\n  sequence_number: number;\n  item_id: string;\n  output_index: number;\n  content_index: number;\n  part: ContentPart;\n};\n\n/**\n * Emitted when a content part is completed.\n */\nexport type ResponseContentPartDoneEvent = {\n  type: 'response.content_part.done';\n  sequence_number: number;\n  item_id: string;\n  output_index: number;\n  content_index: number;\n  part: ContentPart;\n};\n\n// ----------------------------------------------------------------------------\n// Delta Events - Text Output\n// ----------------------------------------------------------------------------\n\n/**\n * Emitted when text is appended to an output.\n */\nexport type ResponseOutputTextDeltaEvent = {\n  type: 'response.output_text.delta';\n  sequence_number: number;\n  item_id: string;\n  output_index: number;\n  content_index: number;\n  delta: string;\n  logprobs?: LogProb[];\n};\n\n/**\n * Emitted when text output is complete.\n */\nexport type ResponseOutputTextDoneEvent = {\n  type: 'response.output_text.done';\n  sequence