90 lines
3.3 KiB
TypeScript
90 lines
3.3 KiB
TypeScript
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import type { StructuredToolInterface } from "@langchain/core/tools";
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import type { BaseChatModel, BaseChatModelCallOptions } from "@langchain/core/language_models/chat_models";
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import { ChatPromptTemplate } from "@langchain/core/prompts";
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import { OpenAIClient } from "@langchain/openai";
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import { ToolDefinition } from "@langchain/core/language_models/base";
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import { OpenAIToolsAgentOutputParser, type ToolsAgentStep } from "./output_parser.js";
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import { AgentRunnableSequence } from "../agent.js";
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export { OpenAIToolsAgentOutputParser, type ToolsAgentStep };
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/**
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* Params used by the createOpenAIToolsAgent function.
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*/
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export type CreateOpenAIToolsAgentParams = {
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/**
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* LLM to use as the agent. Should work with OpenAI tool calling,
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* so must either be an OpenAI model that supports that or a wrapper of
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* a different model that adds in equivalent support.
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*/
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llm: BaseChatModel<BaseChatModelCallOptions & {
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tools?: StructuredToolInterface[] | OpenAIClient.ChatCompletionTool[] | any[];
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}>;
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/** Tools this agent has access to. */
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tools: StructuredToolInterface[] | ToolDefinition[];
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/** The prompt to use, must have an input key of `agent_scratchpad`. */
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prompt: ChatPromptTemplate;
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/**
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* Whether to invoke the underlying model in streaming mode,
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* allowing streaming of intermediate steps. Defaults to true.
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*/
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streamRunnable?: boolean;
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};
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/**
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* Create an agent that uses OpenAI-style tool calling.
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* @param params Params required to create the agent. Includes an LLM, tools, and prompt.
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* @returns A runnable sequence representing an agent. It takes as input all the same input
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* variables as the prompt passed in does. It returns as output either an
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* AgentAction or AgentFinish.
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*
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* @example
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* ```typescript
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* import { AgentExecutor, createOpenAIToolsAgent } from "langchain/agents";
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* import { pull } from "langchain/hub";
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* import type { ChatPromptTemplate } from "@langchain/core/prompts";
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* import { AIMessage, HumanMessage } from "@langchain/core/messages";
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*
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* import { ChatOpenAI } from "@langchain/openai";
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*
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* // Define the tools the agent will have access to.
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* const tools = [...];
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*
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* // Get the prompt to use - you can modify this!
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* // If you want to see the prompt in full, you can at:
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* // https://smith.langchain.com/hub/hwchase17/openai-tools-agent
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* const prompt = await pull<ChatPromptTemplate>(
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* "hwchase17/openai-tools-agent"
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* );
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*
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* const llm = new ChatOpenAI({
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* temperature: 0,
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* modelName: "gpt-3.5-turbo-1106",
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* });
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*
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* const agent = await createOpenAIToolsAgent({
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* llm,
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* tools,
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* prompt,
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* });
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*
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* const agentExecutor = new AgentExecutor({
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* agent,
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* tools,
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* });
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*
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* const result = await agentExecutor.invoke({
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* input: "what is LangChain?",
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* });
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*
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* // With chat history
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* const result2 = await agentExecutor.invoke({
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* input: "what's my name?",
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* chat_history: [
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* new HumanMessage("hi! my name is cob"),
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* new AIMessage("Hello Cob! How can I assist you today?"),
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* ],
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* });
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* ```
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*/
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export declare function createOpenAIToolsAgent({ llm, tools, prompt, streamRunnable, }: CreateOpenAIToolsAgentParams): Promise<AgentRunnableSequence<{
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steps: ToolsAgentStep[];
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}, import("@langchain/core/agents").AgentFinish | import("@langchain/core/agents").AgentAction[]>>;
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