ai/rsc/dist/rsc-server.mjs.map

AI SDK by Vercel - The AI Toolkit for TypeScript and JavaScript

{"version":3,"sources":["../ai-state.tsx","../../util/create-resolvable-promise.ts","../../util/is-function.ts","../provider.tsx","../stream-ui/stream-ui.tsx","../../util/download-error.ts","../../util/download.ts","../../core/util/detect-mimetype.ts","../../core/prompt/data-content.ts","../../core/prompt/invalid-data-content-error.ts","../../core/prompt/invalid-message-role-error.ts","../../core/prompt/split-data-url.ts","../../core/prompt/convert-to-language-model-prompt.ts","../../errors/invalid-argument-error.ts","../../core/prompt/prepare-call-settings.ts","../../util/retry-with-exponential-backoff.ts","../../util/retry-error.ts","../../core/prompt/prepare-retries.ts","../../core/prompt/prepare-tools-and-tool-choice.ts","../../core/util/is-non-empty-object.ts","../../core/prompt/standardize-prompt.ts","../../core/prompt/attachments-to-parts.ts","../../core/prompt/message-conversion-error.ts","../../core/prompt/convert-to-core-messages.ts","../../core/prompt/message.ts","../../core/types/provider-metadata.ts","../../core/types/json-value.ts","../../core/prompt/content-part.ts","../../core/prompt/tool-result-content.ts","../../core/types/usage.ts","../../errors/invalid-tool-arguments-error.ts","../../errors/no-such-tool-error.ts","../../util/is-async-generator.ts","../../util/is-generator.ts","../../util/constants.ts","../streamable-ui/create-suspended-chunk.tsx","../streamable-ui/create-streamable-ui.tsx","../streamable-value/streamable-value.ts","../streamable-value/create-streamable-value.ts"],"sourcesContent":["import * as jsondiffpatch from 'jsondiffpatch';\nimport { AsyncLocalStorage } from 'node:async_hooks';\nimport { createResolvablePromise } from '../util/create-resolvable-promise';\nimport { isFunction } from '../util/is-function';\nimport type {\n  AIProvider,\n  InferAIState,\n  InternalAIStateStorageOptions,\n  MutableAIState,\n  ValueOrUpdater,\n} from './types';\n\n// It is possible that multiple AI requests get in concurrently, for different\n// AI instances. So ALS is necessary here for a simpler API.\nconst asyncAIStateStorage = new AsyncLocalStorage<{\n  currentState: any;\n  originalState: any;\n  sealed: boolean;\n  options: InternalAIStateStorageOptions;\n  mutationDeltaPromise?: Promise<any>;\n  mutationDeltaResolve?: (v: any) => void;\n}>();\n\nfunction getAIStateStoreOrThrow(message: string) {\n  const store = asyncAIStateStorage.getStore();\n  if (!store) {\n    throw new Error(message);\n  }\n  return store;\n}\n\nexport function withAIState<S, T>(\n  { state, options }: { state: S; options: InternalAIStateStorageOptions },\n  fn: () => T,\n): T {\n  return asyncAIStateStorage.run(\n    {\n      currentState: JSON.parse(JSON.stringify(state)), // deep clone object\n      originalState: state,\n      sealed: false,\n      options,\n    },\n    fn,\n  );\n}\n\nexport function getAIStateDeltaPromise() {\n  const store = getAIStateStoreOrThrow('Internal error occurred.');\n  return store.mutationDeltaPromise;\n}\n\n// Internal method. This will be called after the AI Action has been returned\n// and you can no longer call `getMutableAIState()` inside any async callbacks\n// created by that Action.\nexport function sealMutableAIState() {\n  const store = getAIStateStoreOrThrow('Internal error occurred.');\n  store.sealed = true;\n}\n\n/**\n * Get the current AI state.\n * If `key` is provided, it will return the value of the specified key in the\n * AI state, if it's an object. If it's not an object, it will throw an error.\n *\n * @example const state = getAIState() // Get the entire AI state\n * @example const field = getAIState('key') // Get the value of the key\n */\nfunction getAIState<AI extends AIProvider = any>(): Readonly<\n  InferAIState<AI, any>\n>;\nfunction getAIState<AI extends AIProvider = any>(\n  key: keyof InferAIState<AI, any>,\n): Readonly<InferAIState<AI, any>[typeof key]>;\nfunction getAIState<AI extends AIProvider = any>(\n  ...args: [] | [key: keyof InferAIState<AI, any>]\n) {\n  const store = getAIStateStoreOrThrow(\n    '`getAIState` must be called within an AI Action.',\n  );\n\n  if (args.length > 0) {\n    const key = args[0];\n    if (typeof store.currentState !== 'object') {\n      throw new Error(\n        `You can't get the \"${String(\n          key,\n        )}\" field from the AI state because it's not an object.`,\n      );\n    }\n    return store.currentState[key as keyof typeof store.currentState];\n  }\n\n  return store.currentState;\n}\n\n/**\n * Get the mutable AI state. Note that you must call `.done()` when finishing\n * updating the AI state.\n *\n * @example\n * ```tsx\n * const state = getMutableAIState()\n * state.update({ ...state.get(), key: 'value' })\n * state.update((currentState) => ({ ...currentState, key: 'value' }))\n * state.done()\n * ```\n *\n * @example\n * ```tsx\n * const state = getMutableAIState()\n * state.done({ ...state.get(), key: 'value' }) // Done with a new state\n * ```\n */\nfunction getMutableAIState<AI extends AIProvider = any>(): MutableAIState<\n  InferAIState<AI, any>\n>;\nfunction getMutableAIState<AI extends AIProvider = any>(\n  key: keyof InferAIState<AI, any>,\n): MutableAIState<InferAIState<AI, any>[typeof key]>;\nfunction getMutableAIState<AI extends AIProvider = any>(\n  ...args: [] | [key: keyof InferAIState<AI, any>]\n) {\n  type AIState = InferAIState<AI, any>;\n  type AIStateWithKey = typeof args extends [key: keyof AIState]\n    ? AIState[(typeof args)[0]]\n    : AIState;\n  type NewStateOrUpdater = ValueOrUpdater<AIStateWithKey>;\n\n  const store = getAIStateStoreOrThrow(\n    '`getMutableAIState` must be called within an AI Action.',\n  );\n\n  if (store.sealed) {\n    throw new Error(\n      \"`getMutableAIState` must be called before returning from an AI Action. Please move it to the top level of the Action's function body.\",\n    );\n  }\n\n  if (!store.mutationDeltaPromise) {\n    const { promise, resolve } = createResolvablePromise();\n    store.mutationDeltaPromise = promise;\n    store.mutationDeltaResolve = resolve;\n  }\n\n  function doUpdate(newState: NewStateOrUpdater, done: boolean) {\n    if (args.length > 0) {\n      if (typeof store.currentState !== 'object') {\n        const key = args[0];\n        throw new Error(\n          `You can't modify the \"${String(\n            key,\n          )}\" field of the AI state because it's not an object.`,\n        );\n      }\n    }\n\n    if (isFunction(newState)) {\n      if (args.length > 0) {\n        store.currentState[args[0]] = newState(store.currentState[args[0]]);\n      } else {\n        store.currentState = newState(store.currentState);\n      }\n    } else {\n      if (args.length > 0) {\n        store.currentState[args[0]] = newState;\n      } else {\n        store.currentState = newState;\n      }\n    }\n\n    store.options.onSetAIState?.({\n      key: args.length > 0 ? args[0] : undefined,\n      state: store.currentState,\n      done,\n    });\n  }\n\n  const mutableState = {\n    get: () => {\n      if (args.length > 0) {\n        const key = args[0];\n        if (typeof store.currentState !== 'object') {\n          throw new Error(\n            `You can't get the \"${String(\n              key,\n            )}\" field from the AI state because it's not an object.`,\n          );\n        }\n        return store.currentState[key] as Readonly<AIStateWithKey>;\n      }\n\n      return store.currentState as Readonly<AIState>;\n    },\n    update: function update(newAIState: NewStateOrUpdater) {\n      doUpdate(newAIState, false);\n    },\n    done: function done(...doneArgs: [] | [NewStateOrUpdater]) {\n      if (doneArgs.length > 0) {\n        doUpdate(doneArgs[0] as NewStateOrUpdater, true);\n      }\n\n      const delta = jsondiffpatch.diff(store.originalState, store.currentState);\n      store.mutationDeltaResolve!(delta);\n    },\n  };\n\n  return mutableState;\n}\n\nexport { getAIState, getMutableAIState };\n","/**\n * Creates a Promise with externally accessible resolve and reject functions.\n *\n * @template T - The type of the value that the Promise will resolve to.\n * @returns An object containing:\n *   - promise: A Promise that can be resolved or rejected externally.\n *   - resolve: A function to resolve the Promise with a value of type T.\n *   - reject: A function to reject the Promise with an error.\n */\nexport function createResolvablePromise<T = any>(): {\n  promise: Promise<T>;\n  resolve: (value: T) => void;\n  reject: (error: unknown) => void;\n} {\n  let resolve: (value: T) => void;\n  let reject: (error: unknown) => void;\n\n  const promise = new Promise<T>((res, rej) => {\n    resolve = res;\n    reject = rej;\n  });\n\n  return {\n    promise,\n    resolve: resolve!,\n    reject: reject!,\n  };\n}\n","/**\n * Checks if the given value is a function.\n *\n * @param {unknown} value - The value to check.\n * @returns {boolean} True if the value is a function, false otherwise.\n */\nexport const isFunction = (value: unknown): value is Function =>\n  typeof value === 'function';\n","// This file provides the AI context to all AI Actions via AsyncLocalStorage.\n\nimport * as React from 'react';\nimport { InternalAIProvider } from './rsc-shared.mjs';\nimport {\n  withAIState,\n  getAIStateDeltaPromise,\n  sealMutableAIState,\n} from './ai-state';\nimport type {\n  ServerWrappedActions,\n  AIAction,\n  AIActions,\n  AIProvider,\n  InternalAIStateStorageOptions,\n  OnSetAIState,\n  OnGetUIState,\n} from './types';\n\nasync function innerAction<T>(\n  {\n    action,\n    options,\n  }: { action: AIAction; options: InternalAIStateStorageOptions },\n  state: T,\n  ...args: unknown[]\n) {\n  'use server';\n  return await withAIState(\n    {\n      state,\n      options,\n    },\n    async () => {\n      const result = await action(...args);\n      sealMutableAIState();\n      return [getAIStateDeltaPromise() as Promise<T>, result];\n    },\n  );\n}\n\nfunction wrapAction<T = unknown>(\n  action: AIAction,\n  options: InternalAIStateStorageOptions,\n) {\n  return innerAction.bind(null, { action, options }) as AIAction<T>;\n}\n\nexport function createAI<\n  AIState = any,\n  UIState = any,\n  Actions extends AIActions = {},\n>({\n  actions,\n  initialAIState,\n  initialUIState,\n\n  onSetAIState,\n  onGetUIState,\n}: {\n  actions: Actions;\n  initialAIState?: AIState;\n  initialUIState?: UIState;\n\n  /**\n   * This function is called whenever the AI state is updated by an Action.\n   * You can use this to persist the AI state to a database, or to send it to a\n   * logging service.\n   */\n  onSetAIState?: OnSetAIState<AIState>;\n\n  /**\n   * This function is used to retrieve the UI state based on the AI state.\n   * For example, to render the initial UI state based on a given AI state, or\n   * to sync the UI state when the application is already loaded.\n   *\n   * If returning `undefined`, the client side UI state will not be updated.\n   *\n   * This function must be annotated with the `\"use server\"` directive.\n   *\n   * @example\n   * ```tsx\n   * onGetUIState: async () => {\n   *   'use server';\n   *\n   *   const currentAIState = getAIState();\n   *   const externalAIState = await loadAIStateFromDatabase();\n   *\n   *   if (currentAIState === externalAIState) return undefined;\n   *\n   *   // Update current AI state and return the new UI state\n   *   const state = getMutableAIState()\n   *   state.done(externalAIState)\n   *\n   *   return <div>...</div>;\n   * }\n   * ```\n   */\n  onGetUIState?: OnGetUIState<UIState>;\n}) {\n  // Wrap all actions with our HoC.\n  const wrappedActions: ServerWrappedActions = {};\n  for (const name in actions) {\n    wrappedActions[name] = wrapAction(actions[name], {\n      onSetAIState,\n    });\n  }\n\n  const wrappedSyncUIState = onGetUIState\n    ? wrapAction(onGetUIState, {})\n    : undefined;\n\n  const AI: AIProvider<AIState, UIState, Actions> = async props => {\n    if ('useState' in React) {\n      // This file must be running on the React Server layer.\n      // Ideally we should be using `import \"server-only\"` here but we can have a\n      // more customized error message with this implementation.\n      throw new Error(\n        'This component can only be used inside Server Components.',\n      );\n    }\n\n    let uiState = props.initialUIState ?? initialUIState;\n    let aiState = props.initialAIState ?? initialAIState;\n    let aiStateDelta = undefined;\n\n    if (wrappedSyncUIState) {\n      const [newAIStateDelta, newUIState] = await wrappedSyncUIState(aiState);\n      if (newUIState !== undefined) {\n        aiStateDelta = newAIStateDelta;\n        uiState = newUIState;\n      }\n    }\n\n    return (\n      <InternalAIProvider\n        wrappedActions={wrappedActions}\n        wrappedSyncUIState={wrappedSyncUIState}\n        initialUIState={uiState}\n        initialAIState={aiState}\n        initialAIStatePatch={aiStateDelta}\n      >\n        {props.children}\n      </InternalAIProvider>\n    );\n  };\n\n  return AI;\n}\n","import { LanguageModelV1 } from '@ai-sdk/provider';\nimport { safeParseJSON } from '@ai-sdk/provider-utils';\nimport { ReactNode } from 'react';\nimport { z } from 'zod';\nimport { CallSettings } from '../../core/prompt/call-settings';\nimport { convertToLanguageModelPrompt } from '../../core/prompt/convert-to-language-model-prompt';\nimport { prepareCallSettings } from '../../core/prompt/prepare-call-settings';\nimport { prepareRetries } from '../../core/prompt/prepare-retries';\nimport { prepareToolsAndToolChoice } from '../../core/prompt/prepare-tools-and-tool-choice';\nimport { Prompt } from '../../core/prompt/prompt';\nimport { standardizePrompt } from '../../core/prompt/standardize-prompt';\nimport {\n  CallWarning,\n  FinishReason,\n  ProviderMetadata,\n  ToolChoice,\n} from '../../core/types';\nimport { ProviderOptions } from '../../core/types/provider-metadata';\nimport {\n  LanguageModelUsage,\n  calculateLanguageModelUsage,\n} from '../../core/types/usage';\nimport { InvalidToolArgumentsError } from '../../errors/invalid-tool-arguments-error';\nimport { NoSuchToolError } from '../../errors/no-such-tool-error';\nimport { createResolvablePromise } from '../../util/create-resolvable-promise';\nimport { isAsyncGenerator } from '../../util/is-async-generator';\nimport { isGenerator } from '../../util/is-generator';\nimport { createStreamableUI } from '../streamable-ui/create-streamable-ui';\n\ntype Streamable = ReactNode | Promise<ReactNode>;\n\ntype Renderer<T extends Array<any>> = (\n  ...args: T\n) =>\n  | Streamable\n  | Generator<Streamable, Streamable, void>\n  | AsyncGenerator<Streamable, Streamable, void>;\n\ntype RenderTool<PARAMETERS extends z.ZodTypeAny = any> = {\n  description?: string;\n  parameters: PARAMETERS;\n  generate?: Renderer<\n    [\n      z.infer<PARAMETERS>,\n      {\n        toolName: string;\n        toolCallId: string;\n      },\n    ]\n  >;\n};\n\ntype RenderText = Renderer<\n  [\n    {\n      /**\n       * The full text content from the model so far.\n       */\n      content: string;\n\n      /**\n       * The new appended text content from the model since the last `text` call.\n       */\n      delta: string;\n\n      /**\n       * Whether the model is done generating text.\n       * If `true`, the `content` will be the final output and this call will be the last.\n       */\n      done: boolean;\n    },\n  ]\n>;\n\ntype RenderResult = {\n  value: ReactNode;\n} & Awaited<ReturnType<LanguageModelV1['doStream']>>;\n\nconst defaultTextRenderer: RenderText = ({ content }: { content: string }) =>\n  content;\n\n/**\n * `streamUI` is a helper function to create a streamable UI from LLMs.\n */\nexport async function streamUI<\n  TOOLS extends { [name: string]: z.ZodTypeAny } = {},\n>({\n  model,\n  tools,\n  toolChoice,\n  system,\n  prompt,\n  messages,\n  maxRetries,\n  abortSignal,\n  headers,\n  initial,\n  text,\n  experimental_providerMetadata,\n  providerOptions = experimental_providerMetadata,\n  onFinish,\n  ...settings\n}: CallSettings &\n  Prompt & {\n    /**\n     * The language model to use.\n     */\n    model: LanguageModelV1;\n\n    /**\n     * The tools that the model can call. The model needs to support calling tools.\n     */\n    tools?: {\n      [name in keyof TOOLS]: RenderTool<TOOLS[name]>;\n    };\n\n    /**\n     * The tool choice strategy. Default: 'auto'.\n     */\n    toolChoice?: ToolChoice<TOOLS>;\n\n    text?: RenderText;\n    initial?: ReactNode;\n\n    /**\nAdditional provider-specific options. They are passed through\nto the provider from the AI SDK and enable provider-specific\nfunctionality that can be fully encapsulated in the provider.\n */\n    providerOptions?: ProviderOptions;\n\n    /**\n@deprecated Use `providerOptions` instead.\n*/\n    experimental_providerMetadata?: ProviderMetadata;\n\n    /**\n     * Callback that is called when the LLM response and the final object validation are finished.\n     */\n    onFinish?: (event: {\n      /**\n       * The reason why the generation finished.\n       */\n      finishReason: FinishReason;\n      /**\n       * The token usage of the generated response.\n       */\n      usage: LanguageModelUsage;\n      /**\n       * The final ui node that was generated.\n       */\n      value: ReactNode;\n      /**\n       * Warnings from the model provider (e.g. unsupported settings)\n       */\n      warnings?: CallWarning[];\n      /**\n       * Optional raw response data.\n       */\n      rawResponse?: {\n        /**\n         * Response headers.\n         */\n        headers?: Record<string, string>;\n      };\n    }) => Promise<void> | void;\n  }): Promise<RenderResult> {\n  // TODO: Remove these errors after the experimental phase.\n  if (typeof model === 'string') {\n    throw new Error(\n      '`model` cannot be a string in `streamUI`. Use the actual model instance instead.',\n    );\n  }\n  if ('functions' in settings) {\n    throw new Error(\n      '`functions` is not supported in `streamUI`, use `tools` instead.',\n    );\n  }\n  if ('provider' in settings) {\n    throw new Error(\n      '`provider` is no longer needed in `streamUI`. Use `model` instead.',\n    );\n  }\n  if (tools) {\n    for (const [name, tool] of Object.entries(tools)) {\n      if ('render' in tool) {\n        throw new Error(\n          'Tool definition in `streamUI` should not have `render` property. Use `generate` instead. Found in tool: ' +\n            name,\n        );\n      }\n    }\n  }\n\n  const ui = createStreamableUI(initial);\n\n  // The default text renderer just returns the content as string.\n  const textRender = text || defaultTextRenderer;\n\n  let finished: Promise<void> | undefined;\n\n  let finishEvent: {\n    finishReason: FinishReason;\n    usage: LanguageModelUsage;\n    warnings?: CallWarning[];\n    rawResponse?: {\n      headers?: Record<string, string>;\n    };\n  } | null = null;\n\n  async function render({\n    args,\n    renderer,\n    streamableUI,\n    isLastCall = false,\n  }: {\n    renderer: undefined | Renderer<any>;\n    args: [payload: any] | [payload: any, options: any];\n    streamableUI: ReturnType<typeof createStreamableUI>;\n    isLastCall?: boolean;\n  }) {\n    if (!renderer) return;\n\n    // create a promise that will be resolved when the render call is finished.\n    // it is appended to the `finished` promise chain to ensure the render call\n    // is finished before the next render call starts.\n    const renderFinished = createResolvablePromise<void>();\n    finished = finished\n      ? finished.then(() => renderFinished.promise)\n      : renderFinished.promise;\n\n    const rendererResult = renderer(...args);\n\n    if (isAsyncGenerator(rendererResult) || isGenerator(rendererResult)) {\n      while (true) {\n        const { done, value } = await rendererResult.next();\n        const node = await value;\n\n        if (isLastCall && done) {\n          streamableUI.done(node);\n        } else {\n          streamableUI.update(node);\n        }\n\n        if (done) break;\n      }\n    } else {\n      const node = await rendererResult;\n\n      if (isLastCall) {\n        streamableUI.done(node);\n      } else {\n        streamableUI.update(node);\n      }\n    }\n\n    // resolve the promise to signal that the render call is finished\n    renderFinished.resolve(undefined);\n  }\n\n  const { retry } = prepareRetries({ maxRetries });\n\n  const validatedPrompt = standardizePrompt({\n    prompt: { system, prompt, messages },\n    tools: undefined, // streamUI tools don't support multi-modal tool result conversion\n  });\n  const result = await retry(async () =>\n    model.doStream({\n      mode: {\n        type: 'regular',\n        ...prepareToolsAndToolChoice({\n          tools,\n          toolChoice,\n          activeTools: undefined,\n        }),\n      },\n      ...prepareCallSettings(settings),\n      inputFormat: validatedPrompt.type,\n      prompt: await convertToLanguageModelPrompt({\n        prompt: validatedPrompt,\n        modelSupportsImageUrls: model.supportsImageUrls,\n        modelSupportsUrl: model.supportsUrl?.bind(model), // support 'this' context\n      }),\n      providerMetadata: providerOptions,\n      abortSignal,\n      headers,\n    }),\n  );\n\n  // For the stream and consume it asynchronously:\n  const [stream, forkedStream] = result.stream.tee();\n  (async () => {\n    try {\n      let content = '';\n      let hasToolCall = false;\n\n      const reader = forkedStream.getReader();\n      while (true) {\n        const { done, value } = await reader.read();\n        if (done) break;\n\n        switch (value.type) {\n          case 'text-delta': {\n            content += value.textDelta;\n            render({\n              renderer: textRender,\n              args: [{ content, done: false, delta: value.textDelta }],\n              streamableUI: ui,\n            });\n            break;\n          }\n\n          case 'tool-call-delta': {\n            hasToolCall = true;\n            break;\n          }\n\n          case 'tool-call': {\n            const toolName = value.toolName as keyof TOOLS & string;\n\n            if (!tools) {\n              throw new NoSuchToolError({ toolName });\n            }\n\n            const tool = tools[toolName];\n            if (!tool) {\n              throw new NoSuchToolError({\n                toolName,\n                availableTools: Object.keys(tools),\n              });\n            }\n\n            hasToolCall = true;\n            const parseResult = safeParseJSON({\n              text: value.args,\n              schema: tool.parameters,\n            });\n\n            if (parseResult.success === false) {\n              throw new InvalidToolArgumentsError({\n                toolName,\n                toolArgs: value.args,\n                cause: parseResult.error,\n              });\n            }\n\n            render({\n              renderer: tool.generate,\n              args: [\n                parseResult.value,\n                {\n                  toolName,\n                  toolCallId: value.toolCallId,\n                },\n              ],\n              streamableUI: ui,\n              isLastCall: true,\n            });\n\n            break;\n          }\n\n          case 'error': {\n            throw value.error;\n          }\n\n          case 'finish': {\n            finishEvent = {\n              finishReason: value.finishReason,\n              usage: calculateLanguageModelUsage(value.usage),\n              warnings: result.warnings,\n              rawResponse: result.rawResponse,\n            };\n            break;\n          }\n        }\n      }\n\n      if (!hasToolCall) {\n        render({\n          renderer: textRender,\n          args: [{ content, done: true }],\n          streamableUI: ui,\n          isLastCall: true,\n        });\n      }\n\n      await finished;\n\n      if (finishEvent && onFinish) {\n        await onFinish({\n          ...finishEvent,\n          value: ui.value,\n        });\n      }\n    } catch (error) {\n      // During the stream rendering, we don't want to throw the error to the\n      // parent scope but only let the React's error boundary to catch it.\n      ui.error(error);\n    }\n  })();\n\n  return {\n    ...result,\n    stream,\n    value: ui.value,\n  };\n}\n","import { AISDKError } from '@ai-sdk/provider';\n\nconst name = 'AI_DownloadError';\nconst marker = `vercel.ai.error.${name}`;\nconst symbol = Symbol.for(marker);\n\nexport class DownloadError extends AISDKError {\n  private readonly [symbol] = true; // used in isInstance\n\n  readonly url: string;\n  readonly statusCode?: number;\n  readonly statusText?: string;\n\n  constructor({\n    url,\n    statusCode,\n    statusText,\n    cause,\n    message = cause == null\n      ? `Failed to download ${url}: ${statusCode} ${statusText}`\n      : `Failed to download ${url}: ${cause}`,\n  }: {\n    url: string;\n    statusCode?: number;\n    statusText?: string;\n    message?: string;\n    cause?: unknown;\n  }) {\n    super({ name, message, cause });\n\n    this.url = url;\n    this.statusCode = statusCode;\n    this.statusText = statusText;\n  }\n\n  static isInstance(error: unknown): error is DownloadError {\n    return AISDKError.hasMarker(error, marker);\n  }\n}\n","import { DownloadError } from './download-error';\n\nexport async function download({ url }: { url: URL }): Promise<{\n  data: Uint8Array;\n  mimeType: string | undefined;\n}> {\n  const urlText = url.toString();\n  try {\n    const response = await fetch(urlText);\n\n    if (!response.ok) {\n      throw new DownloadError({\n        url: urlText,\n        statusCode: response.status,\n        statusText: response.statusText,\n      });\n    }\n\n    return {\n      data: new Uint8Array(await response.arrayBuffer()),\n      mimeType: response.headers.get('content-type') ?? undefined,\n    };\n  } catch (error) {\n    if (DownloadError.isInstance(error)) {\n      throw error;\n    }\n\n    throw new DownloadError({ url: urlText, cause: error });\n  }\n}\n","import { convertBase64ToUint8Array } from '@ai-sdk/provider-utils';\n\nexport const imageMimeTypeSignatures = [\n  {\n    mimeType: 'image/gif' as const,\n    bytesPrefix: [0x47, 0x49, 0x46],\n    base64Prefix: 'R0lG',\n  },\n  {\n    mimeType: 'image/png' as const,\n    bytesPrefix: [0x89, 0x50, 0x4e, 0x47],\n    base64Prefix: 'iVBORw',\n  },\n  {\n    mimeType: 'image/jpeg' as const,\n    bytesPrefix: [0xff, 0xd8],\n    base64Prefix: '/9j/',\n  },\n  {\n    mimeType: 'image/webp' as const,\n    bytesPrefix: [0x52, 0x49, 0x46, 0x46],\n    base64Prefix: 'UklGRg',\n  },\n  {\n    mimeType: 'image/bmp' as const,\n    bytesPrefix: [0x42, 0x4d],\n    base64Prefix: 'Qk',\n  },\n  {\n    mimeType: 'image/tiff' as const,\n    bytesPrefix: [0x49, 0x49, 0x2a, 0x00],\n    base64Prefix: 'SUkqAA',\n  },\n  {\n    mimeType: 'image/tiff' as const,\n    bytesPrefix: [0x4d, 0x4d, 0x00, 0x2a],\n    base64Prefix: 'TU0AKg',\n  },\n  {\n    mimeType: 'image/avif' as const,\n    bytesPrefix: [\n      0x00, 0x00, 0x00, 0x20, 0x66, 0x74, 0x79, 0x70, 0x61, 0x76, 0x69, 0x66,\n    ],\n    base64Prefix: 'AAAAIGZ0eXBhdmlm',\n  },\n  {\n    mimeType: 'image/heic' as const,\n    bytesPrefix: [\n      0x00, 0x00, 0x00, 0x20, 0x66, 0x74, 0x79, 0x70, 0x68, 0x65, 0x69, 0x63,\n    ],\n    base64Prefix: 'AAAAIGZ0eXBoZWlj',\n  },\n] as const;\n\nexport const audioMimeTypeSignatures = [\n  {\n    mimeType: 'audio/mpeg' as const,\n    bytesPrefix: [0xff, 0xfb],\n    base64Prefix: '//s=',\n  },\n  {\n    mimeType: 'audio/wav' as const,\n    bytesPrefix: [0x52, 0x49, 0x46, 0x46],\n    base64Prefix: 'UklGR',\n  },\n  {\n    mimeType: 'audio/ogg' as const,\n    bytesPrefix: [0x4f, 0x67, 0x67, 0x53],\n    base64Prefix: 'T2dnUw',\n  },\n  {\n    mimeType: 'audio/flac' as const,\n    bytesPrefix: [0x66, 0x4c, 0x61, 0x43],\n    base64Prefix: 'ZkxhQw',\n  },\n  {\n    mimeType: 'audio/aac' as const,\n    bytesPrefix: [0x40, 0x15, 0x00, 0x00],\n    base64Prefix: 'QBUA',\n  },\n  {\n    mimeType: 'audio/mp4' as const,\n    bytesPrefix: [0x66, 0x74, 0x79, 0x70],\n    base64Prefix: 'ZnR5cA',\n  },\n] as const;\n\nconst stripID3 = (data: Uint8Array | string) => {\n  const bytes =\n    typeof data === 'string' ? convertBase64ToUint8Array(data) : data;\n  const id3Size =\n    ((bytes[6] & 0x7f) << 21) |\n    ((bytes[7] & 0x7f) << 14) |\n    ((bytes[8] & 0x7f) << 7) |\n    (bytes[9] & 0x7f);\n\n  // The raw MP3 starts here\n  return bytes.slice(id3Size + 10);\n};\n\nfunction stripID3TagsIfPresent(data: Uint8Array | string): Uint8Array | string {\n  const hasId3 =\n    (typeof data === 'string' && data.startsWith('SUQz')) ||\n    (typeof data !== 'string' &&\n      data.length > 10 &&\n      data[0] === 0x49 && // 'I'\n      data[1] === 0x44 && // 'D'\n      data[2] === 0x33); // '3'\n\n  return hasId3 ? stripID3(data) : data;\n}\n\nexport function detectMimeType({\n  data,\n  signatures,\n}: {\n  data: Uint8Array | string;\n  signatures: typeof audioMimeTypeSignatures | typeof imageMimeTypeSignatures;\n}): (typeof signatures)[number]['mimeType'] | undefined {\n  const processedData = stripID3TagsIfPresent(data);\n\n  for (const signature of signatures) {\n    if (\n      typeof processedData === 'string'\n        ? processedData.startsWith(signature.base64Prefix)\n        : processedData.length >= signature.bytesPrefix.length &&\n          signature.bytesPrefix.every(\n            (byte, index) => processedData[index] === byte,\n          )\n    ) {\n      return signature.mimeType;\n    }\n  }\n\n  return undefined;\n}\n","import {\n  convertBase64ToUint8Array,\n  convertUint8ArrayToBase64,\n} from '@ai-sdk/provider-utils';\nimport { InvalidDataContentError } from './invalid-data-content-error';\nimport { z } from 'zod';\n\n/**\nData content. Can either be a base64-encoded string, a Uint8Array, an ArrayBuffer, or a Buffer.\n */\nexport type DataContent = string | Uint8Array | ArrayBuffer | Buffer;\n\n/**\n@internal\n */\nexport const dataContentSchema: z.ZodType<DataContent> = z.union([\n  z.string(),\n  z.instanceof(Uint8Array),\n  z.instanceof(ArrayBuffer),\n  z.custom(\n    // Buffer might not be available in some environments such as CloudFlare:\n    (value: unknown): value is Buffer =>\n      globalThis.Buffer?.isBuffer(value) ?? false,\n    { message: 'Must be a Buffer' },\n  ),\n]);\n\n/**\nConverts data content to a base64-encoded string.\n\n@param content - Data content to convert.\n@returns Base64-encoded string.\n*/\nexport function convertDataContentToBase64String(content: DataContent): string {\n  if (typeof content === 'string') {\n    return content;\n  }\n\n  if (content instanceof ArrayBuffer) {\n    return convertUint8ArrayToBase64(new Uint8Array(content));\n  }\n\n  return convertUint8ArrayToBase64(content);\n}\n\n/**\nConverts data content to a Uint8Array.\n\n@param content - Data content to convert.\n@returns Uint8Array.\n */\nexport function convertDataContentToUint8Array(\n  content: DataContent,\n): Uint8Array {\n  if (content instanceof Uint8Array) {\n    return content;\n  }\n\n  if (typeof content === 'string') {\n    try {\n      return convertBase64ToUint8Array(content);\n    } catch (error) {\n      throw new InvalidDataContentError({\n        message:\n          'Invalid data content. Content string is not a base64-encoded media.',\n        content,\n        cause: error,\n      });\n    }\n  }\n\n  if (content instanceof ArrayBuffer) {\n    return new Uint8Array(content);\n  }\n\n  throw new InvalidDataContentError({ content });\n}\n\n/**\n * Converts a Uint8Array to a string of text.\n *\n * @param uint8Array - The Uint8Array to convert.\n * @returns The converted string.\n */\nexport function convertUint8ArrayToText(uint8Array: Uint8Array): string {\n  try {\n    return new TextDecoder().decode(uint8Array);\n  } catch (error) {\n    throw new Error('Error decoding Uint8Array to text');\n  }\n}\n","import { AISDKError } from '@ai-sdk/provider';\n\nconst name = 'AI_InvalidDataContentError';\nconst marker = `vercel.ai.error.${name}`;\nconst symbol = Symbol.for(marker);\n\nexport class InvalidDataContentError extends AISDKError {\n  private readonly [symbol] = true; // used in isInstance\n\n  readonly content: unknown;\n\n  constructor({\n    content,\n    cause,\n    message = `Invalid data content. Expected a base64 string, Uint8Array, ArrayBuffer, or Buffer, but got ${typeof content}.`,\n  }: {\n    content: unknown;\n    cause?: unknown;\n    message?: string;\n  }) {\n    super({ name, message, cause });\n\n    this.content = content;\n  }\n\n  static isInstance(error: unknown): error is InvalidDataContentError {\n    return AISDKError.hasMarker(error, marker);\n  }\n}\n","import { AISDKError } from '@ai-sdk/provider';\n\nconst name = 'AI_InvalidMessageRoleError';\nconst marker = `vercel.ai.error.${name}`;\nconst symbol = Symbol.for(marker);\n\nexport class InvalidMessageRoleError extends AISDKError {\n  private readonly [symbol] = true; // used in isInstance\n\n  readonly role: string;\n\n  constructor({\n    role,\n    message = `Invalid message role: '${role}'. Must be one of: \"system\", \"user\", \"assistant\", \"tool\".`,\n  }: {\n    role: string;\n    message?: string;\n  }) {\n    super({ name, message });\n\n    this.role = role;\n  }\n\n  static isInstance(error: unknown): error is InvalidMessageRoleError {\n    return AISDKError.hasMarker(error, marker);\n  }\n}\n","export function splitDataUrl(dataUrl: string): {\n  mimeType: string | undefined;\n  base64Content: string | undefined;\n} {\n  try {\n    const [header, base64Content] = dataUrl.split(',');\n    return {\n      mimeType: header.split(';')[0].split(':')[1],\n      base64Content,\n    };\n  } catch (error) {\n    return {\n      mimeType: undefined,\n      base64Content: undefined,\n    };\n  }\n}\n","import {\n  LanguageModelV1FilePart,\n  LanguageModelV1ImagePart,\n  LanguageModelV1Message,\n  LanguageModelV1Prompt,\n  LanguageModelV1TextPart,\n} from '@ai-sdk/provider';\nimport { download } from '../../util/download';\nimport { CoreMessage } from '../prompt/message';\nimport {\n  detectMimeType,\n  imageMimeTypeSignatures,\n} from '../util/detect-mimetype';\nimport { FilePart, ImagePart, TextPart } from './content-part';\nimport {\n  convertDataContentToBase64String,\n  convertDataContentToUint8Array,\n  DataContent,\n} from './data-content';\nimport { InvalidMessageRoleError } from './invalid-message-role-error';\nimport { splitDataUrl } from './split-data-url';\nimport { StandardizedPrompt } from './standardize-prompt';\n\nexport async function convertToLanguageModelPrompt({\n  prompt,\n  modelSupportsImageUrls = true,\n  modelSupportsUrl = () => false,\n  downloadImplementation = download,\n}: {\n  prompt: StandardizedPrompt;\n  modelSupportsImageUrls: boolean | undefined;\n  modelSupportsUrl: undefined | ((url: URL) => boolean);\n  downloadImplementation?: typeof download;\n}): Promise<LanguageModelV1Prompt> {\n  const downloadedAssets = await downloadAssets(\n    prompt.messages,\n    downloadImplementation,\n    modelSupportsImageUrls,\n    modelSupportsUrl,\n  );\n\n  return [\n    ...(prompt.system != null\n      ? [{ role: 'system' as const, content: prompt.system }]\n      : []),\n    ...prompt.messages.map(message =>\n      convertToLanguageModelMessage(message, downloadedAssets),\n    ),\n  ];\n}\n\n/**\n * Convert a CoreMessage to a LanguageModelV1Message.\n *\n * @param message The CoreMessage to convert.\n * @param downloadedAssets A map of URLs to their downloaded data. Only\n *   available if the model does not support URLs, null otherwise.\n */\nexport function convertToLanguageModelMessage(\n  message: CoreMessage,\n  downloadedAssets: Record<\n    string,\n    { mimeType: string | undefined; data: Uint8Array }\n  >,\n): LanguageModelV1Message {\n  const role = message.role;\n  switch (role) {\n    case 'system': {\n      return {\n        role: 'system',\n        content: message.content,\n        providerMetadata:\n          message.providerOptions ?? message.experimental_providerMetadata,\n      };\n    }\n\n    case 'user': {\n      if (typeof message.content === 'string') {\n        return {\n          role: 'user',\n          content: [{ type: 'text', text: message.content }],\n          providerMetadata:\n            message.providerOptions ?? message.experimental_providerMetadata,\n        };\n      }\n\n      return {\n        role: 'user',\n        content: message.content\n          .map(part => convertPartToLanguageModelPart(part, downloadedAssets))\n          // remove empty text parts:\n          .filter(part => part.type !== 'text' || part.text !== ''),\n        providerMetadata:\n          message.providerOptions ?? message.experimental_providerMetadata,\n      };\n    }\n\n    case 'assistant': {\n      if (typeof message.content === 'string') {\n        return {\n          role: 'assistant',\n          content: [{ type: 'text', text: message.content }],\n          providerMetadata:\n            message.providerOptions ?? message.experimental_providerMetadata,\n        };\n      }\n\n      return {\n        role: 'assistant',\n        content: message.content\n          .filter(\n            // remove empty text parts:\n            part => part.type !== 'text' || part.text !== '',\n          )\n          .map(part => {\n            const providerOptions =\n              part.providerOptions ?? part.experimental_providerMetadata;\n\n            switch (part.type) {\n              case 'file': {\n                return {\n                  type: 'file',\n                  data:\n                    part.data instanceof URL\n                      ? part.data\n                      : convertDataContentToBase64String(part.data),\n                  filename: part.filename,\n                  mimeType: part.mimeType,\n                  providerMetadata: providerOptions,\n                };\n              }\n              case 'reasoning': {\n                return {\n                  type: 'reasoning',\n                  text: part.text,\n                  signature: part.signature,\n                  providerMetadata: providerOptions,\n                };\n              }\n              case 'redacted-reasoning': {\n                return {\n                  type: 'redacted-reasoning',\n                  data: part.data,\n                  providerMetadata: providerOptions,\n                };\n              }\n              case 'text': {\n                return {\n                  type: 'text' as const,\n                  text: part.text,\n                  providerMetadata: providerOptions,\n                };\n              }\n              case 'tool-call': {\n                return {\n                  type: 'tool-call' as const,\n                  toolCallId: part.toolCallId,\n                  toolName: part.toolName,\n                  args: part.args,\n                  providerMetadata: providerOptions,\n                };\n              }\n            }\n          }),\n        providerMetadata:\n          message.providerOptions ?? message.experimental_providerMetadata,\n      };\n    }\n\n    case 'tool': {\n      return {\n        role: 'tool',\n        content: message.content.map(part => ({\n          type: 'tool-result',\n          toolCallId: part.toolCallId,\n          toolName: part.toolName,\n          result: part.result,\n          content: part.experimental_content,\n          isError: part.isError,\n          providerMetadata:\n            part.providerOptions ?? part.experimental_providerMetadata,\n        })),\n        providerMetadata:\n          message.providerOptions ?? message.experimental_providerMetadata,\n      };\n    }\n\n    default: {\n      const _exhaustiveCheck: never = role;\n      throw new InvalidMessageRoleError({ role: _exhaustiveCheck });\n    }\n  }\n}\n\n/**\n * Downloads images and files from URLs in the messages.\n */\nasync function downloadAssets(\n  messages: CoreMessage[],\n  downloadImplementation: typeof download,\n  modelSupportsImageUrls: boolean | undefined,\n  modelSupportsUrl: (url: URL) => boolean,\n): Promise<Record<string, { mimeType: string | undefined; data: Uint8Array }>> {\n  const urls = messages\n    .filter(message => message.role === 'user')\n    .map(message => message.content)\n    .filter((content): content is Array<TextPart | ImagePart | FilePart> =>\n      Array.isArray(content),\n    )\n    .flat()\n    .filter(\n      (part): part is ImagePart | FilePart =>\n        part.type === 'image' || part.type === 'file',\n    )\n    /**\n     * Filter out image parts if the model supports image URLs, before letting it\n     * decide if it supports a particular URL.\n     */\n    .filter(\n      (part): part is ImagePart | FilePart =>\n        !(part.type === 'image' && modelSupportsImageUrls === true),\n    )\n    .map(part => (part.type === 'image' ? part.image : part.data))\n    .map(part =>\n      // support string urls:\n      typeof part === 'string' &&\n      (part.startsWith('http:') || part.startsWith('https:'))\n        ? new URL(part)\n        : part,\n    )\n    .filter((image): image is URL => image instanceof URL)\n    /**\n     * Filter out URLs that the model supports natively, so we don't download them.\n     */\n    .filter(url => !modelSupportsUrl(url));\n\n  // download in parallel:\n  const downloadedImages = await Promise.all(\n    urls.map(async url => ({\n      url,\n      data: await downloadImplementation({ url }),\n    })),\n  );\n\n  return Object.fromEntries(\n    downloadedImages.map(({ url, data }) => [url.toString(), data]),\n  );\n}\n\n/**\n * Convert part of a message to a LanguageModelV1Part.\n * @param part The part to convert.\n * @param downloadedAssets A map of URLs to their downloaded data. Only\n *  available if the model does not support URLs, null otherwise.\n *\n * @returns The converted part.\n */\nfunction convertPartToLanguageModelPart(\n  part: TextPart | ImagePart | FilePart,\n  downloadedAssets: Record<\n    string,\n    { mimeType: string | undefined; data: Uint8Array }\n  >,\n):\n  | LanguageModelV1TextPart\n  | LanguageModelV1ImagePart\n  | LanguageModelV1FilePart {\n  if (part.type === 'text') {\n    return {\n      type: 'text',\n      text: part.text,\n      providerMetadata:\n        part.providerOptions ?? part.experimental_providerMetadata,\n    };\n  }\n\n  let mimeType: string | undefined = part.mimeType;\n  let data: DataContent | URL;\n  let content: URL | ArrayBuffer | string;\n  let normalizedData: Uint8Array | URL;\n\n  const type = part.type;\n  switch (type) {\n    case 'image':\n      data = part.image;\n      break;\n    case 'file':\n      data = part.data;\n      break;\n    default:\n      throw new Error(`Unsupported part type: ${type}`);\n  }\n\n  // Attempt to create a URL from the data. If it fails, we can assume the data\n  // is not a URL and likely some other sort of data.\n  try {\n    content = typeof data === 'string' ? new URL(data) : data;\n  } catch (error) {\n    content = data;\n  }\n\n  // If we successfully created a URL, we can use that to normalize the data\n  // either by passing it through or converting normalizing the base64 content\n  // to a Uint8Array.\n  if (content instanceof URL) {\n    // If the content is a data URL, we want to convert that to a Uint8Array\n    if (content.protocol === 'data:') {\n      const { mimeType: dataUrlMimeType, base64Content } = splitDataUrl(\n        content.toString(),\n      );\n\n      if (dataUrlMimeType == null || base64Content == null) {\n        throw new Error(`Invalid data URL format in part ${type}`);\n      }\n\n      mimeType = dataUrlMimeType;\n      normalizedData = convertDataContentToUint8Array(base64Content);\n    } else {\n      /**\n       * If the content is a URL, we should first see if it was downloaded. And if not,\n       * we can let the model decide if it wants to support the URL. This also allows\n       * for non-HTTP URLs to be passed through (e.g. gs://).\n       */\n      const downloadedFile = downloadedAssets[content.toString()];\n      if (downloadedFile) {\n        normalizedData = downloadedFile.data;\n        mimeType ??= downloadedFile.mimeType;\n      } else {\n        normalizedData = content;\n      }\n    }\n  } else {\n    // Since we know now the content is not a URL, we can attempt to normalize\n    // the data assuming it is some sort of data.\n    normalizedData = convertDataContentToUint8Array(content);\n  }\n\n  // Now that we have the normalized data either as a URL or a Uint8Array,\n  // we can create the LanguageModelV1Part.\n  switch (type) {\n    case 'image': {\n      // When possible, try to detect the mimetype automatically\n      // to deal with incorrect mimetype inputs.\n      // When detection fails, use provided mimetype.\n\n      if (normalizedData instanceof Uint8Array) {\n        mimeType =\n          detectMimeType({\n            data: normalizedData,\n            signatures: imageMimeTypeSignatures,\n          }) ?? mimeType;\n      }\n      return {\n        type: 'image',\n        image: normalizedData,\n        mimeType,\n        providerMetadata:\n          part.providerOptions ?? part.experimental_providerMetadata,\n      };\n    }\n\n    case 'file': {\n      // We should have a mimeType at this point, if not, throw an error.\n      if (mimeType == null) {\n        throw new Error(`Mime type is missing for file part`);\n      }\n\n      return {\n        type: 'file',\n        data:\n          normalizedData instanceof Uint8Array\n            ? convertDataContentToBase64String(normalizedData)\n            : normalizedData,\n        filename: part.filename,\n        mimeType,\n        providerMetadata:\n          part.providerOptions ?? part.experimental_providerMetadata,\n      };\n    }\n  }\n}\n","import { AISDKError } from '@ai-sdk/provider';\n\nconst name = 'AI_InvalidArgumentError';\nconst marker = `vercel.ai.error.${name}`;\nconst symbol = Symbol.for(marker);\n\nexport class InvalidArgumentError extends AISDKError {\n  private readonly [symbol] = true; // used in isInstance\n\n  readonly parameter: string;\n  readonly value: unknown;\n\n  constructor({\n    parameter,\n    value,\n    message,\n  }: {\n    parameter: string;\n    value: unknown;\n    message: string;\n  }) {\n    super({\n      name,\n      message: `Invalid argument for parameter ${parameter}: ${message}`,\n    });\n\n    this.parameter = parameter;\n    this.value = value;\n  }\n\n  static isInstance(error: unknown): error is InvalidArgumentError {\n    return AISDKError.hasMarker(error, marker);\n  }\n}\n","import { InvalidArgumentError } from '../../errors/invalid-argument-error';\nimport { CallSettings } from './call-settings';\n\n/**\n * Validates call settings and sets default values.\n */\nexport function prepareCallSettings({\n  maxTokens,\n  temperature,\n  topP,\n  topK,\n  presencePenalty,\n  frequencyPenalty,\n  stopSequences,\n  seed,\n}: Omit<CallSettings, 'abortSignal' | 'headers' | 'maxRetries'>): Omit<\n  CallSettings,\n  'abortSignal' | 'headers' | 'maxRetries'\n> {\n  if (maxTokens != null) {\n    if (!Number.isInteger(maxTokens)) {\n      throw new InvalidArgumentError({\n        parameter: 'maxTokens',\n        value: maxTokens,\n        message: 'maxTokens must be an integer',\n      });\n    }\n\n    if (maxTokens < 1) {\n      throw new InvalidArgumentError({\n        parameter: 'maxTokens',\n        value: maxTokens,\n        message: 'maxTokens must be >= 1',\n      });\n    }\n  }\n\n  if (temperature != null) {\n    if (typeof temperature !== 'number') {\n      throw new InvalidArgumentError({\n        parameter: 'temperature',\n        value: temperature,\n        message: 'temperature must be a number',\n      });\n    }\n  }\n\n  if (topP != null) {\n    if (typeof topP !== 'number') {\n      throw new InvalidArgumentError({\n        parameter: 'topP',\n        value: topP,\n        message: 'topP must be a number',\n      });\n    }\n  }\n\n  if (topK != null) {\n    if (typeof topK !== 'number') {\n      throw new InvalidArgumentError({\n        parameter: 'topK',\n        value: topK,\n        message: 'topK must be a number',\n      });\n    }\n  }\n\n  if (presencePenalty != null) {\n    if (typeof presencePenalty !== 'number') {\n      throw new InvalidArgumentError({\n        parameter: 'presencePenalty',\n        value: presencePenalty,\n        message: 'presencePenalty must be a number',\n      });\n    }\n  }\n\n  if (frequencyPenalty != null) {\n    if (typeof frequencyPenalty !== 'number') {\n      throw new InvalidArgumentError({\n        parameter: 'frequencyPenalty',\n        value: frequencyPenalty,\n        message: 'frequencyPenalty must be a number',\n      });\n    }\n  }\n\n  if (seed != null) {\n    if (!Number.isInteger(seed)) {\n      throw new InvalidArgumentError({\n        parameter: 'seed',\n        value: seed,\n        message: 'seed must be an integer',\n      });\n    }\n  }\n\n  return {\n    maxTokens,\n    // TODO v5 remove default 0 for temperature\n    temperature: temperature ?? 0,\n    topP,\n    topK,\n    presencePenalty,\n    frequencyPenalty,\n    stopSequences:\n      stopSequences != null && stopSequences.length > 0\n        ? stopSequences\n        : undefined,\n    seed,\n  };\n}\n","import { APICallError } from '@ai-sdk/provider';\nimport { delay, getErrorMessage, isAbortError } from '@ai-sdk/provider-utils';\nimport { RetryError } from './retry-error';\n\nexport type RetryFunction = <OUTPUT>(\n  fn: () => PromiseLike<OUTPUT>,\n) => PromiseLike<OUTPUT>;\n\n/**\nThe `retryWithExponentialBackoff` strategy retries a failed API call with an exponential backoff.\nYou can configure the maximum number of retries, the initial delay, and the backoff factor.\n */\nexport const retryWithExponentialBackoff =\n  ({\n