99 lines
3.3 KiB
JavaScript
99 lines
3.3 KiB
JavaScript
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import { isBaseMessage } from "@langchain/core/messages";
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import { OutputParserException } from "@langchain/core/output_parsers";
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import { AgentActionOutputParser } from "../types.js";
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/**
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* @example
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* ```typescript
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*
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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 modelWithFunctions = new ChatOpenAI({
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* modelName: "gpt-4",
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* temperature: 0,
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* }).bind({
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* functions: tools.map((tool) => convertToOpenAIFunction(tool)),
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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) => i.input,
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* agent_scratchpad: (i) => formatAgentSteps(i.steps),
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* },
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* prompt,
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* modelWithFunctions,
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* new OpenAIFunctionsAgentOutputParser(),
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* ]);
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*
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* const result = await runnableAgent.invoke({
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* input: "What is the weather in New York?",
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* steps: agentSteps,
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* });
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*
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* ```
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*/
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export class OpenAIFunctionsAgentOutputParser extends AgentActionOutputParser {
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constructor() {
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super(...arguments);
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Object.defineProperty(this, "lc_namespace", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: ["langchain", "agents", "openai"]
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});
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}
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static lc_name() {
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return "OpenAIFunctionsAgentOutputParser";
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}
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async parse(text) {
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throw new Error(`OpenAIFunctionsAgentOutputParser can only parse messages.\nPassed input: ${text}`);
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}
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async parseResult(generations) {
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if ("message" in generations[0] && isBaseMessage(generations[0].message)) {
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return this.parseAIMessage(generations[0].message);
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}
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throw new Error("parseResult on OpenAIFunctionsAgentOutputParser only works on ChatGeneration output");
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}
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/**
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* Parses the output message into a FunctionsAgentAction or AgentFinish
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* object.
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* @param message The BaseMessage to parse.
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* @returns A FunctionsAgentAction or AgentFinish object.
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*/
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parseAIMessage(message) {
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if (message.content && typeof message.content !== "string") {
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throw new Error("This agent cannot parse non-string model responses.");
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}
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if (message.additional_kwargs.function_call) {
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// eslint-disable-next-line prefer-destructuring
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const function_call = message.additional_kwargs.function_call;
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try {
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const toolInput = function_call.arguments
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? JSON.parse(function_call.arguments)
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: {};
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return {
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tool: function_call.name,
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toolInput,
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log: `Invoking "${function_call.name}" with ${function_call.arguments ?? "{}"}\n${message.content}`,
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messageLog: [message],
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};
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}
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catch (error) {
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throw new OutputParserException(`Failed to parse function arguments from chat model response. Text: "${function_call.arguments}". ${error}`);
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}
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}
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else {
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return {
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returnValues: { output: message.content },
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log: message.content,
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};
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}
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}
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getFormatInstructions() {
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throw new Error("getFormatInstructions not implemented inside OpenAIFunctionsAgentOutputParser.");
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}
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}
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