87 lines
3.8 KiB
TypeScript
87 lines
3.8 KiB
TypeScript
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
|
|
import type { ToolInterface } from "@langchain/core/tools";
|
|
import { ChatPromptTemplate } from "@langchain/core/prompts";
|
|
import type { AgentStep } from "@langchain/core/agents";
|
|
import { Optional } from "../../types/type-utils.js";
|
|
import { Agent, AgentArgs, OutputParserArgs } from "../agent.js";
|
|
import { AgentInput } from "../types.js";
|
|
import { ChatAgentOutputParser } from "./outputParser.js";
|
|
/**
|
|
* Interface for arguments used to create a chat prompt.
|
|
* @deprecated
|
|
*/
|
|
export interface ChatCreatePromptArgs {
|
|
/** String to put after the list of tools. */
|
|
suffix?: string;
|
|
/** String to put before the list of tools. */
|
|
prefix?: string;
|
|
/** String to use directly as the human message template. */
|
|
humanMessageTemplate?: string;
|
|
/** Formattable string to use as the instructions template. */
|
|
formatInstructions?: string;
|
|
/** List of input variables the final prompt will expect. */
|
|
inputVariables?: string[];
|
|
}
|
|
/**
|
|
* Type for input data for creating a ChatAgent, extending AgentInput with
|
|
* optional 'outputParser'.
|
|
*
|
|
* @deprecated
|
|
*/
|
|
export type ChatAgentInput = Optional<AgentInput, "outputParser">;
|
|
/**
|
|
* Agent for the MRKL chain.
|
|
* @augments Agent
|
|
*
|
|
* @deprecated Use the {@link https://api.js.langchain.com/functions/langchain.agents.createStructuredChatAgent.html | createStructuredChatAgent method instead}.
|
|
*/
|
|
export declare class ChatAgent extends Agent {
|
|
static lc_name(): string;
|
|
lc_namespace: string[];
|
|
ToolType: ToolInterface;
|
|
constructor(input: ChatAgentInput);
|
|
_agentType(): "chat-zero-shot-react-description";
|
|
observationPrefix(): string;
|
|
llmPrefix(): string;
|
|
_stop(): string[];
|
|
/**
|
|
* Validates that all tools have descriptions. Throws an error if a tool
|
|
* without a description is found.
|
|
* @param tools Array of Tool instances to validate.
|
|
* @returns void
|
|
*/
|
|
static validateTools(tools: ToolInterface[]): void;
|
|
/**
|
|
* Returns a default output parser for the ChatAgent.
|
|
* @param _fields Optional OutputParserArgs to customize the output parser.
|
|
* @returns ChatAgentOutputParser instance
|
|
*/
|
|
static getDefaultOutputParser(_fields?: OutputParserArgs): ChatAgentOutputParser;
|
|
/**
|
|
* Constructs the agent's scratchpad, which is a string representation of
|
|
* the agent's previous steps.
|
|
* @param steps Array of AgentStep instances representing the agent's previous steps.
|
|
* @returns Promise resolving to a string representing the agent's scratchpad.
|
|
*/
|
|
constructScratchPad(steps: AgentStep[]): Promise<string>;
|
|
/**
|
|
* Create prompt in the style of the zero shot agent.
|
|
*
|
|
* @param tools - List of tools the agent will have access to, used to format the prompt.
|
|
* @param args - Arguments to create the prompt with.
|
|
* @param args.suffix - String to put after the list of tools.
|
|
* @param args.prefix - String to put before the list of tools.
|
|
* @param args.humanMessageTemplate - String to use directly as the human message template
|
|
* @param args.formatInstructions - Formattable string to use as the instructions template
|
|
*/
|
|
static createPrompt(tools: ToolInterface[], args?: ChatCreatePromptArgs): ChatPromptTemplate<any, any>;
|
|
/**
|
|
* Creates a ChatAgent instance using a language model, tools, and
|
|
* optional arguments.
|
|
* @param llm BaseLanguageModelInterface instance to use in the agent.
|
|
* @param tools Array of Tool instances to include in the agent.
|
|
* @param args Optional arguments to customize the agent and prompt.
|
|
* @returns ChatAgent instance
|
|
*/
|
|
static fromLLMAndTools(llm: BaseLanguageModelInterface, tools: ToolInterface[], args?: ChatCreatePromptArgs & AgentArgs): ChatAgent;
|
|
}
|