@langchain/langgraph
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LangGraph
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{"version":3,"file":"tool_node.d.ts","names":["BaseMessage","ToolMessage","RunnableConfig","RunnableToolLike","DynamicTool","StructuredToolInterface","ToolCall","RunnableCallable","MessagesAnnotation","END","Command","ToolNodeOptions","ToolNode","T","Promise","toolsCondition","State"],"sources":["../../src/prebuilt/tool_node.d.ts"],"sourcesContent":["import { BaseMessage, ToolMessage } from \"@langchain/core/messages\";\nimport { RunnableConfig, RunnableToolLike } from \"@langchain/core/runnables\";\nimport { DynamicTool, StructuredToolInterface } from \"@langchain/core/tools\";\nimport type { ToolCall } from \"@langchain/core/messages/tool\";\nimport { RunnableCallable } from \"../utils.js\";\nimport { MessagesAnnotation } from \"../graph/messages_annotation.js\";\nimport { END, Command } from \"../constants.js\";\nexport type ToolNodeOptions = {\n name?: string;\n tags?: string[];\n handleToolErrors?: boolean;\n};\n/**\n * @deprecated `ToolNode` has been moved to {@link https://www.npmjs.com/package/langchain langchain} package.\n * Update your import to `import { ToolNode } from \"langchain\";`\n *\n * A node that runs the tools requested in the last AIMessage. It can be used\n * either in StateGraph with a \"messages\" key or in MessageGraph. If multiple\n * tool calls are requested, they will be run in parallel. The output will be\n * a list of ToolMessages, one for each tool call.\n *\n * @example\n * ```ts\n * import { ToolNode } from \"@langchain/langgraph/prebuilt\";\n * import { tool } from \"@langchain/core/tools\";\n * import { z } from \"zod\";\n * import { AIMessage } from \"@langchain/core/messages\";\n *\n * const getWeather = tool((input) => {\n * if ([\"sf\", \"san francisco\"].includes(input.location.toLowerCase())) {\n * return \"It's 60 degrees and foggy.\";\n * } else {\n * return \"It's 90 degrees and sunny.\";\n * }\n * }, {\n * name: \"get_weather\",\n * description: \"Call to get the current weather.\",\n * schema: z.object({\n * location: z.string().describe(\"Location to get the weather for.\"),\n * }),\n * });\n *\n * const tools = [getWeather];\n * const toolNode = new ToolNode(tools);\n *\n * const messageWithSingleToolCall = new AIMessage({\n * content: \"\",\n * tool_calls: [\n * {\n * name: \"get_weather\",\n * args: { location: \"sf\" },\n * id: \"tool_call_id\",\n * type: \"tool_call\",\n * }\n * ]\n * })\n *\n * await toolNode.invoke({ messages: [messageWithSingleToolCall] });\n * // Returns tool invocation responses as:\n * // { messages: ToolMessage[] }\n * ```\n *\n * @example\n * ```ts\n * import {\n * StateGraph,\n * MessagesAnnotation,\n * } from \"@langchain/langgraph\";\n * import { ToolNode } from \"@langchain/langgraph/prebuilt\";\n * import { tool } from \"@langchain/core/tools\";\n * import { z } from \"zod\";\n * import { ChatAnthropic } from \"@langchain/anthropic\";\n *\n * const getWeather = tool((input) => {\n * if ([\"sf\", \"san francisco\"].includes(input.location.toLowerCase())) {\n * return \"It's 60 degrees and foggy.\";\n * } else {\n * return \"It's 90 degrees and sunny.\";\n * }\n * }, {\n * name: \"get_weather\",\n * description: \"Call to get the current weather.\",\n * schema: z.object({\n * location: z.string().describe(\"Location to get the weather for.\"),\n * }),\n * });\n *\n * const tools = [getWeather];\n * const modelWithTools = new ChatAnthropic({\n * model: \"claude-3-haiku-20240307\",\n * temperature: 0\n * }).bindTools(tools);\n *\n * const toolNodeForGraph = new ToolNode(tools)\n *\n * const shouldContinue = (state: typeof MessagesAnnotation.State) => {\n * const { messages } = state;\n * const lastMessage = messages[messages.length - 1];\n * if (\"tool_calls\" in lastMessage && Array.isArray(lastMessage.tool_calls) && lastMessage.tool_calls?.length) {\n * return \"tools\";\n * }\n * return \"__end__\";\n * }\n *\n * const callModel = async (state: typeof MessagesAnnotation.State) => {\n * const { messages } = state;\n * const response = await modelWithTools.invoke(messages);\n * return { messages: response };\n * }\n *\n * const graph = new StateGraph(MessagesAnnotation)\n * .addNode(\"agent\", callModel)\n * .addNode(\"tools\", toolNodeForGraph)\n * .addEdge(\"__start__\", \"agent\")\n * .addConditionalEdges(\"agent\", shouldContinue)\n * .addEdge(\"tools\", \"agent\")\n * .compile();\n *\n * const inputs = {\n * messages: [{ role: \"user\", content: \"what is the weather in SF?\" }],\n * };\n *\n * const stream = await graph.stream(inputs, {\n * streamMode: \"values\",\n * });\n *\n * for await (const { messages } of stream) {\n * console.log(messages);\n * }\n * // Returns the messages in the state at each step of execution\n * ```\n */\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport declare class ToolNode<T = any> extends RunnableCallable<T, T> {\n tools: (StructuredToolInterface | DynamicTool | RunnableToolLike)[];\n handleToolErrors: boolean;\n trace: boolean;\n constructor(tools: (StructuredToolInterface | DynamicTool | RunnableToolLike)[], options?: ToolNodeOptions);\n protected runTool(call: ToolCall, config: RunnableConfig): Promise<ToolMessage | Command>;\n // eslint-disable-next-line @typescript-eslint/no-explicit-any\n protected run(input: unknown, config: RunnableConfig): Promise<T>;\n}\n/**\n * @deprecated Use new `ToolNode` from {@link https://www.npmjs.com/package/langchain langchain} package instead.\n */\nexport declare function toolsCondition(state: BaseMessage[] | typeof MessagesAnnotation.State): \"tools\" | typeof END;\n"],"mappings":";;;;;;;;;KAOYW,eAAAA;;EAAAA,IAAAA,CAAAA,EAAAA,MAAAA,EAAAA;EA8HSC,gBAAQ,CAAA,EAAA,OAAA;CAAA;;;;;;;;;;;;;;;;;;;;AAY7B;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;cAZqBA,0BAA0BL,iBAAiBM,GAAGA;UACvDR,0BAA0BD,cAAcD;;;sBAG5BE,0BAA0BD,cAAcD,+BAA+BQ;0BACnEL,kBAAkBJ,iBAAiBY,QAAQb,cAAcS;;wCAE3CR,iBAAiBY,QAAQD;;;;;iBAK3CE,cAAAA,QAAsBf,uBAAuBQ,kBAAAA,CAAmBQ,yBAAyBP"}