langchain/dist/agents/utils.cjs.map

Typescript bindings for langchain

{"version":3,"file":"utils.cjs","names":["StateSchema","AIMessage","AIMessageChunk","Runnable","isBaseChatModel","RunnableBinding","RunnableSequence","isConfigurableModel","MultipleToolsBoundError","SystemMessage","ToolMessage","MiddlewareError"],"sources":["../../src/agents/utils.ts"],"sourcesContent":["import {\n  AIMessage,\n  AIMessageChunk,\n  BaseMessage,\n  BaseMessageLike,\n  SystemMessage,\n  MessageContent,\n  ToolMessage,\n} from \"@langchain/core/messages\";\nimport { isCommand, StateSchema } from \"@langchain/langgraph\";\nimport {\n  type InteropZodObject,\n  interopParse,\n  isInteropZodSchema,\n} from \"@langchain/core/utils/types\";\nimport {\n  BaseChatModel,\n  type BaseChatModelCallOptions,\n} from \"@langchain/core/language_models/chat_models\";\nimport { BaseLanguageModelInput } from \"@langchain/core/language_models/base\";\nimport {\n  Runnable,\n  RunnableLike,\n  RunnableConfig,\n  RunnableSequence,\n  RunnableBinding,\n} from \"@langchain/core/runnables\";\nimport type { ClientTool, ServerTool } from \"@langchain/core/tools\";\n\nimport {\n  isBaseChatModel,\n  isConfigurableModel,\n  type AgentLanguageModelLike as LanguageModelLike,\n} from \"./model.js\";\nimport { MultipleToolsBoundError, MiddlewareError } from \"./errors.js\";\nimport type { AgentBuiltInState } from \"./runtime.js\";\nimport type {\n  ToolCallHandler,\n  AnyAgentMiddleware,\n  ToolCallRequest,\n  WrapToolCallHook,\n} from \"./middleware/types.js\";\n\nconst NAME_PATTERN = /<name>(.*?)<\\/name>/s;\nconst CONTENT_PATTERN = /<content>(.*?)<\\/content>/s;\n\n/**\n * Parse middleware state from the full agent state based on the middleware's stateSchema.\n *\n * Handles two types of state schemas:\n * 1. Zod schemas (v3 or v4) - parsed using interopParse\n * 2. LangGraph StateSchema - extracts only the keys defined in `fields`\n *\n * @param stateSchema - The middleware's state schema (Zod or LangGraph StateSchema)\n * @param state - The full agent state to parse from\n * @returns Parsed state containing only the keys defined in the schema\n */\nfunction parseMiddlewareState(\n  stateSchema: unknown,\n  state: Record<string, unknown>\n): Record<string, unknown> {\n  // Handle LangGraph StateSchema (has `fields` property)\n  if (StateSchema.isInstance(stateSchema)) {\n    const result: Record<string, unknown> = {};\n    for (const key of Object.keys(stateSchema.fields)) {\n      if (key in state) {\n        result[key] = state[key];\n      }\n    }\n    return result;\n  }\n\n  // Handle Zod schemas using interopParse\n  if (isInteropZodSchema(stateSchema)) {\n    return interopParse(stateSchema as InteropZodObject, state);\n  }\n\n  throw new Error(`Invalid state schema type: ${typeof stateSchema}`);\n}\n\nexport type AgentNameMode = \"inline\";\n\n/**\n * Attach formatted agent names to the messages passed to and from a language model.\n *\n * This is useful for making a message history with multiple agents more coherent.\n *\n * NOTE: agent name is consumed from the message.name field.\n * If you're using an agent built with createAgent, name is automatically set.\n * If you're building a custom agent, make sure to set the name on the AI message returned by the LLM.\n *\n * @param message - Message to add agent name formatting to\n * @returns Message with agent name formatting\n *\n * @internal\n */\nexport function _addInlineAgentName<T extends BaseMessageLike>(\n  message: T\n): T | AIMessage {\n  if (!AIMessage.isInstance(message) || AIMessageChunk.isInstance(message)) {\n    return message;\n  }\n\n  if (!message.name) {\n    return message;\n  }\n\n  const { name } = message;\n\n  if (typeof message.content === \"string\") {\n    return new AIMessage({\n      ...message.lc_kwargs,\n      content: `<name>${name}</name><content>${message.content}</content>`,\n      name: undefined,\n    });\n  }\n\n  const updatedContent = [];\n  let textBlockCount = 0;\n\n  for (const contentBlock of message.content) {\n    if (typeof contentBlock === \"string\") {\n      textBlockCount += 1;\n      updatedContent.push(\n        `<name>${name}</name><content>${contentBlock}</content>`\n      );\n    } else if (\n      typeof contentBlock === \"object\" &&\n      \"type\" in contentBlock &&\n      contentBlock.type === \"text\"\n    ) {\n      textBlockCount += 1;\n      updatedContent.push({\n        ...contentBlock,\n        text: `<name>${name}</name><content>${contentBlock.text}</content>`,\n      });\n    } else {\n      updatedContent.push(contentBlock);\n    }\n  }\n\n  if (!textBlockCount) {\n    updatedContent.unshift({\n      type: \"text\",\n      text: `<name>${name}</name><content></content>`,\n    });\n  }\n  return new AIMessage({\n    ...message.lc_kwargs,\n    content: updatedContent as MessageContent,\n    name: undefined,\n  });\n}\n\n/**\n * Remove explicit name and content XML tags from the AI message content.\n *\n * Examples:\n *\n * @example\n * ```typescript\n * removeInlineAgentName(new AIMessage({ content: \"<name>assistant</name><content>Hello</content>\", name: \"assistant\" }))\n * // AIMessage with content: \"Hello\"\n *\n * removeInlineAgentName(new AIMessage({ content: [{type: \"text\", text: \"<name>assistant</name><content>Hello</content>\"}], name: \"assistant\" }))\n * // AIMessage with content: [{type: \"text\", text: \"Hello\"}]\n * ```\n *\n * @internal\n */\nexport function _removeInlineAgentName<T extends BaseMessage>(message: T): T {\n  if (!AIMessage.isInstance(message) || !message.content) {\n    return message;\n  }\n\n  let updatedContent: MessageContent = [];\n  let updatedName: string | undefined;\n\n  if (Array.isArray(message.content)) {\n    updatedContent = message.content\n      .filter((block) => {\n        if (block.type === \"text\" && typeof block.text === \"string\") {\n          const nameMatch = block.text.match(NAME_PATTERN);\n          const contentMatch = block.text.match(CONTENT_PATTERN);\n          // don't include empty content blocks that were added because there was no text block to modify\n          if (nameMatch && (!contentMatch || contentMatch[1] === \"\")) {\n            // capture name from text block\n            updatedName = nameMatch[1];\n            return false;\n          }\n          return true;\n        }\n        return true;\n      })\n      .map((block) => {\n        if (block.type === \"text\" && typeof block.text === \"string\") {\n          const nameMatch = block.text.match(NAME_PATTERN);\n          const contentMatch = block.text.match(CONTENT_PATTERN);\n\n          if (!nameMatch || !contentMatch) {\n            return block;\n          }\n\n          // capture name from text block\n          updatedName = nameMatch[1];\n\n          return {\n            ...block,\n            text: contentMatch[1],\n          };\n        }\n        return block;\n      });\n  } else {\n    const content = message.content as string;\n    const nameMatch = content.match(NAME_PATTERN);\n    const contentMatch = content.match(CONTENT_PATTERN);\n\n    if (!nameMatch || !contentMatch) {\n      return message;\n    }\n\n    updatedName = nameMatch[1];\n    updatedContent = contentMatch[1];\n  }\n\n  return new AIMessage({\n    ...(Object.keys(message.lc_kwargs ?? {}).length > 0\n      ? message.lc_kwargs\n      : message),\n    content: updatedContent,\n    name: updatedName,\n  }) as T;\n}\n\nexport function isClientTool(\n  tool: ClientTool | ServerTool\n): tool is ClientTool {\n  return Runnable.isRunnable(tool);\n}\n\n/**\n * Helper function to check if a language model has a bindTools method.\n * @param llm - The language model to check if it has a bindTools method.\n * @returns True if the language model has a bindTools method, false otherwise.\n */\nfunction _isChatModelWithBindTools(\n  llm: LanguageModelLike\n): llm is BaseChatModel & Required<Pick<BaseChatModel, \"bindTools\">> {\n  if (!isBaseChatModel(llm)) return false;\n  return \"bindTools\" in llm && typeof llm.bindTools === \"function\";\n}\n\n/**\n * Helper function to bind tools to a language model.\n * @param llm - The language model to bind tools to.\n * @param toolClasses - The tools to bind to the language model.\n * @param options - The options to pass to the language model.\n * @returns The language model with the tools bound to it.\n */\nconst _simpleBindTools = (\n  llm: LanguageModelLike,\n  toolClasses: (ClientTool | ServerTool)[],\n  options: Partial<BaseChatModelCallOptions> = {}\n) => {\n  if (_isChatModelWithBindTools(llm)) {\n    return llm.bindTools(toolClasses, options);\n  }\n\n  if (\n    RunnableBinding.isRunnableBinding(llm) &&\n    _isChatModelWithBindTools(llm.bound)\n  ) {\n    const newBound = llm.bound.bindTools(toolClasses, options);\n\n    if (RunnableBinding.isRunnableBinding(newBound)) {\n      return new RunnableBinding({\n        bound: newBound.bound,\n        config: { ...llm.config, ...newBound.config },\n        kwargs: { ...llm.kwargs, ...newBound.kwargs },\n        configFactories: newBound.configFactories ?? llm.configFactories,\n      });\n    }\n\n    return new RunnableBinding({\n      bound: newBound,\n      config: llm.config,\n      kwargs: llm.kwargs,\n      configFactories: llm.configFactories,\n    });\n  }\n\n  return null;\n};\n\n/**\n * Check if the LLM already has bound tools and throw if it does.\n *\n * @param llm - The LLM to check.\n * @returns void\n */\nexport function validateLLMHasNoBoundTools(llm: LanguageModelLike): void {\n  /**\n   * If llm is a function, we can't validate until runtime, so skip\n   */\n  if (typeof llm === \"function\") {\n    return;\n  }\n\n  let model = llm;\n\n  /**\n   * If model is a RunnableSequence, find a RunnableBinding in its steps\n   */\n  if (RunnableSequence.isRunnableSequence(model)) {\n    model =\n      model.steps.find((step: RunnableLike) =>\n        RunnableBinding.isRunnableBinding(step)\n      ) || model;\n  }\n\n  /**\n   * If model is configurable, get the underlying model\n   */\n  if (isConfigurableModel(model)) {\n    /**\n     * Can't validate async model retrieval in constructor\n     */\n    return;\n  }\n\n  /**\n   * Check if model is a RunnableBinding with bound tools\n   */\n  if (RunnableBinding.isRunnableBinding(model)) {\n    const hasToolsInKwargs =\n      model.kwargs != null &&\n      typeof model.kwargs === \"object\" &&\n      \"tools\" in model.kwargs &&\n      Array.isArray(model.kwargs.tools) &&\n      model.kwargs.tools.length > 0;\n\n    const hasToolsInConfig =\n      model.config != null &&\n      typeof model.config === \"object\" &&\n      \"tools\" in model.config &&\n      Array.isArray(model.config.tools) &&\n      model.config.tools.length > 0;\n\n    if (hasToolsInKwargs || hasToolsInConfig) {\n      throw new MultipleToolsBoundError();\n    }\n  }\n\n  /**\n   * Also check if model has tools property directly (e.g., FakeToolCallingModel)\n   */\n  if (\n    \"tools\" in model &&\n    model.tools !== undefined &&\n    Array.isArray(model.tools) &&\n    model.tools.length > 0\n  ) {\n    throw new MultipleToolsBoundError();\n  }\n}\n\n/**\n * Check if the last message in the messages array has tool calls.\n *\n * @param messages - The messages to check.\n * @returns True if the last message has tool calls, false otherwise.\n */\nexport function hasToolCalls(message?: BaseMessage): boolean {\n  return Boolean(\n    AIMessage.isInstance(message) &&\n    message.tool_calls &&\n    message.tool_calls.length > 0\n  );\n}\n\n/**\n * Normalizes a system prompt to a SystemMessage object.\n * If it's already a SystemMessage, returns it as-is.\n * If it's a string, converts it to a SystemMessage.\n * If it's undefined, creates an empty system message so it is easier to append to it later.\n */\nexport function normalizeSystemPrompt(\n  systemPrompt?: string | SystemMessage\n): SystemMessage {\n  if (systemPrompt == null) {\n    return new SystemMessage(\"\");\n  }\n  if (SystemMessage.isInstance(systemPrompt)) {\n    return systemPrompt;\n  }\n  if (typeof systemPrompt === \"string\") {\n    return new SystemMessage({\n      content: [{ type: \"text\", text: systemPrompt }],\n    });\n  }\n  throw new Error(\n    `Invalid systemPrompt type: expected string or SystemMessage, got ${typeof systemPrompt}`\n  );\n}\n\n/**\n * Helper function to bind tools to a language model.\n * @param llm - The language model to bind tools to.\n * @param toolClasses - The tools to bind to the language model.\n * @param options - The options to pass to the language model.\n * @returns The language model with the tools bound to it.\n */\nexport async function bindTools(\n  llm: LanguageModelLike,\n  toolClasses: (ClientTool | ServerTool)[],\n  options: Partial<BaseChatModelCallOptions> = {}\n): Promise<\n  | RunnableSequence<unknown, unknown>\n  | RunnableBinding<unknown, unknown, RunnableConfig<Record<string, unknown>>>\n  | Runnable<BaseLanguageModelInput, AIMessageChunk, BaseChatModelCallOptions>\n> {\n  const model = _simpleBindTools(llm, toolClasses, options);\n  if (model) return model;\n\n  if (isConfigurableModel(llm)) {\n    const model = _simpleBindTools(\n      await llm._getModelInstance(),\n      toolClasses,\n      options\n    );\n    if (model) return model;\n  }\n\n  if (RunnableSequence.isRunnableSequence(llm)) {\n    const modelStep = llm.steps.findIndex(\n      (step) =>\n        RunnableBinding.isRunnableBinding(step) ||\n        isBaseChatModel(step) ||\n        isConfigurableModel(step)\n    );\n\n    if (modelStep >= 0) {\n      const model = _simpleBindTools(\n        llm.steps[modelStep],\n        toolClasses,\n        options\n      );\n      if (model) {\n        const nextSteps: unknown[] = llm.steps.slice();\n        nextSteps.splice(modelStep, 1, model);\n\n        return RunnableSequence.from(\n          nextSteps as [RunnableLike, ...RunnableLike[], RunnableLike]\n        );\n      }\n    }\n  }\n\n  throw new Error(`llm ${llm} must define bindTools method.`);\n}\n\n/**\n * Compose multiple wrapToolCall handlers into a single middleware stack.\n *\n * Composes handlers so the first in the list becomes the outermost layer.\n * Each handler receives a handler callback to execute inner layers.\n *\n * @param handlers - List of handlers. First handler wraps all others.\n * @returns Composed handler, or undefined if handlers array is empty.\n *\n * @example\n * ```typescript\n * // handlers=[auth, retry] means: auth wraps retry\n * // Flow: auth calls retry, retry calls base handler\n * const auth: ToolCallWrapper = async (request, handler) => {\n *   try {\n *     return await handler(request);\n *   } catch (error) {\n *     if (error.message === \"Unauthorized\") {\n *       await refreshToken();\n *       return await handler(request);\n *     }\n *     throw error;\n *   }\n * };\n *\n * const retry: ToolCallWrapper = async (request, handler) => {\n *   for (let attempt = 0; attempt < 3; attempt++) {\n *     try {\n *       return await handler(request);\n *     } catch (error) {\n *       if (attempt === 2) throw error;\n *     }\n *   }\n *   throw new Error(\"Unreachable\");\n * };\n *\n * const composedHandler = chainToolCallHandlers([auth, retry]);\n * ```\n */\nfunction chainToolCallHandlers(\n  handlers: WrapToolCallHook[]\n): WrapToolCallHook | undefined {\n  if (handlers.length === 0) {\n    return undefined;\n  }\n\n  if (handlers.length === 1) {\n    return handlers[0];\n  }\n\n  // Compose two handlers where outer wraps inner\n  // The key is to properly propagate request modifications through the chain\n  function composeTwo(\n    outer: WrapToolCallHook,\n    inner: WrapToolCallHook\n  ): WrapToolCallHook {\n    return async (request, handler) => {\n      // Create a wrapper that calls inner with the base handler\n      // The innerHandler receives the (possibly modified) request from outer\n      // and passes it to inner, which then calls the base handler\n      const innerHandler: ToolCallHandler = async (passedRequest) => {\n        // inner receives the request passed by outer (which may be modified)\n        return inner(passedRequest, handler);\n      };\n\n      // Call outer with the wrapped inner as its handler\n      return outer(request, innerHandler);\n    };\n  }\n\n  // Compose right-to-left: outer(inner(innermost(handler)))\n  let result = handlers[handlers.length - 1];\n  for (let i = handlers.length - 2; i >= 0; i--) {\n    result = composeTwo(handlers[i], result);\n  }\n\n  return result;\n}\n\n/**\n * Wrapping `wrapToolCall` invocation so we can inject middleware name into\n * the error message.\n *\n * @param middleware list of middleware passed to the agent\n * @param state state of the agent\n * @returns single wrap function\n */\nexport function wrapToolCall(middleware: readonly AnyAgentMiddleware[]) {\n  const middlewareWithWrapToolCall = middleware.filter((m) => m.wrapToolCall);\n\n  if (middlewareWithWrapToolCall.length === 0) {\n    return;\n  }\n\n  return chainToolCallHandlers(\n    middlewareWithWrapToolCall.map((m) => {\n      const originalHandler = m.wrapToolCall!;\n      /**\n       * Wrap with error handling and validation\n       */\n      const wrappedHandler: WrapToolCallHook = async (request, handler) => {\n        /**\n         * Capture the original state for this middleware's schema parsing.\n         * This is important because the request may be modified (via override)\n         * as it passes through the middleware chain, but each middleware\n         * should always see the full original state for its schema parsing.\n         */\n        const originalState = request.state;\n\n        /**\n         * Create a handler that preserves state parsing for this middleware\n         * while allowing tool/toolCall/state modifications from inner middleware\n         */\n        const wrappedInnerHandler: ToolCallHandler = async (passedRequest) => {\n          /**\n           * Merge the passed request with the original state for parsing.\n           * This ensures middleware can override tool/toolCall while\n           * maintaining proper state parsing for each middleware in the chain.\n           */\n          const mergedState = {\n            ...originalState,\n            ...passedRequest.state,\n          };\n          return handler({\n            ...passedRequest,\n            state: mergedState,\n          });\n        };\n\n        try {\n          const result = await originalHandler(\n            {\n              ...request,\n              /**\n               * override state with the state from the specific middleware\n               */\n              state: {\n                messages: originalState.messages,\n                ...(m.stateSchema\n                  ? parseMiddlewareState(m.stateSchema, { ...originalState })\n                  : {}),\n              },\n            } as ToolCallRequest<AgentBuiltInState, unknown>,\n            wrappedInnerHandler\n          );\n\n          /**\n           * Validate return type\n           */\n          if (!ToolMessage.isInstance(result) && !isCommand(result)) {\n            throw new Error(\n              `Invalid response from \"wrapToolCall\" in middleware \"${m.name}\": ` +\n                `expected ToolMessage or Command, got ${typeof result}`\n            );\n          }\n\n          return result;\n        } catch (error) {\n          throw MiddlewareError.wrap(error, m.name);\n        }\n      };\n      return wrappedHandler;\n    })\n  );\n}\n\n/**\n * Static LangGraph config keys propagated from ReactAgent defaults onto the\n * compiled inner graph. This ensures values set via `withConfig()` survive\n * LangGraph API loading, which unwraps ReactAgent to `.graph` before execution.\n */\nconst GRAPH_DEFAULT_CONFIG_KEYS = [\n  \"tags\",\n  \"metadata\",\n  \"runName\",\n  \"maxConcurrency\",\n  \"recursionLimit\",\n  \"configurable\",\n] as const satisfies readonly (keyof RunnableConfig)[];\n\nexport function toGraphDefaultConfig(\n  config: RunnableConfig\n): Omit<RunnableConfig, \"store\" | \"writer\" | \"interrupt\"> {\n  const result: Record<string, unknown> = {};\n  for (const key of GRAPH_DEFAULT_CONFIG_KEYS) {\n    const value = config[key];\n    if (value !== undefined) {\n      result[key] = value;\n    }\n  }\n  return result as Omit<RunnableConfig, \"store\" | \"writer\" | 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