49 lines
1.9 KiB
TypeScript
49 lines
1.9 KiB
TypeScript
import { AgentAction, AgentFinish } from "@langchain/core/agents";
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import { BaseMessage } from "@langchain/core/messages";
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import { ChatGeneration } from "@langchain/core/outputs";
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import { AgentMultiActionOutputParser } from "../types.js";
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import { ToolsAgentAction, ToolsAgentStep } from "../tool_calling/output_parser.js";
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export type { ToolsAgentAction, ToolsAgentStep };
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/**
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* @example
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* ```typescript
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* const prompt = ChatPromptTemplate.fromMessages([
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* ["ai", "You are a helpful assistant"],
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* ["human", "{input}"],
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* new MessagesPlaceholder("agent_scratchpad"),
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* ]);
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*
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* const runnableAgent = RunnableSequence.from([
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* {
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* input: (i: { input: string; steps: ToolsAgentStep[] }) => i.input,
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* agent_scratchpad: (i: { input: string; steps: ToolsAgentStep[] }) =>
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* formatToOpenAIToolMessages(i.steps),
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* },
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* prompt,
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* new ChatOpenAI({
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* modelName: "gpt-3.5-turbo-1106",
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* temperature: 0,
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* }).bind({ tools: tools.map((tool) => convertToOpenAITool(tool)) }),
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* new OpenAIToolsAgentOutputParser(),
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* ]).withConfig({ runName: "OpenAIToolsAgent" });
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*
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* const result = await runnableAgent.invoke({
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* input:
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* "What is the sum of the current temperature in San Francisco, New York, and Tokyo?",
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* });
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* ```
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*/
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export declare class OpenAIToolsAgentOutputParser extends AgentMultiActionOutputParser {
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lc_namespace: string[];
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static lc_name(): string;
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parse(text: string): Promise<AgentAction[] | AgentFinish>;
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parseResult(generations: ChatGeneration[]): Promise<AgentFinish | ToolsAgentAction[]>;
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/**
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* Parses the output message into a ToolsAgentAction[] or AgentFinish
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* object.
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* @param message The BaseMessage to parse.
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* @returns A ToolsAgentAction[] or AgentFinish object.
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*/
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parseAIMessage(message: BaseMessage): ToolsAgentAction[] | AgentFinish;
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getFormatInstructions(): string;
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}
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