146 lines
4.9 KiB
JavaScript
146 lines
4.9 KiB
JavaScript
"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.createStructuredOutputRunnable = exports.createOpenAIFnRunnable = void 0;
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const zod_to_json_schema_1 = require("zod-to-json-schema");
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const openai_functions_js_1 = require("../../output_parsers/openai_functions.cjs");
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/**
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* Creates a runnable sequence that calls OpenAI functions.
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* @param config - The parameters required to create the runnable.
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* @returns A runnable sequence that will pass the given functions to the model when run.
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*
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* @example
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* ```typescript
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* const openAIFunction = {
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* name: "get_person_details",
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* description: "Get details about a person",
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* parameters: {
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* title: "Person",
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* description: "Identifying information about a person.",
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* type: "object",
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* properties: {
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* name: { title: "Name", description: "The person's name", type: "string" },
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* age: { title: "Age", description: "The person's age", type: "integer" },
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* fav_food: {
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* title: "Fav Food",
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* description: "The person's favorite food",
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* type: "string",
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* },
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* },
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* required: ["name", "age"],
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* },
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* };
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*
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* const model = new ChatOpenAI();
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* const prompt = ChatPromptTemplate.fromMessages([
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* ["human", "Human description: {description}"],
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* ]);
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* const outputParser = new JsonOutputFunctionsParser();
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*
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* const runnable = createOpenAIFnRunnable({
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* functions: [openAIFunction],
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* llm: model,
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* prompt,
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* enforceSingleFunctionUsage: true, // Default is true
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* outputParser
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* });
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* const response = await runnable.invoke({
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* description:
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* "My name's John Doe and I'm 30 years old. My favorite kind of food are chocolate chip cookies.",
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* });
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*
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* console.log(response);
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*
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* // { name: 'John Doe', age: 30, fav_food: 'chocolate chip cookies' }
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* ```
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*/
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function createOpenAIFnRunnable(config) {
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const { functions, llm, prompt, enforceSingleFunctionUsage = true, outputParser = new openai_functions_js_1.JsonOutputFunctionsParser(), } = config;
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const llmKwargs = {
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functions,
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};
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if (functions.length === 1 && enforceSingleFunctionUsage) {
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llmKwargs.function_call = {
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name: functions[0].name,
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};
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}
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const llmWithKwargs = llm.bind(llmKwargs);
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return prompt.pipe(llmWithKwargs).pipe(outputParser);
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}
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exports.createOpenAIFnRunnable = createOpenAIFnRunnable;
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function isZodSchema(schema) {
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return typeof schema.safeParse === "function";
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}
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/**
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* @deprecated Prefer the `.withStructuredOutput` method on chat model classes.
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*
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* Create a runnable that uses an OpenAI function to get a structured output.
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* @param config Params required to create the runnable.
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* @returns A runnable sequence that will pass the given function to the model when run.
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*
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* @example
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* ```typescript
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* import { createStructuredOutputRunnable } from "langchain/chains/openai_functions";
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* import { ChatOpenAI } from "@langchain/openai";
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* import { ChatPromptTemplate } from "@langchain/core/prompts";
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* import { JsonOutputFunctionsParser } from "langchain/output_parsers";
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*
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* const jsonSchema = {
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* title: "Person",
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* description: "Identifying information about a person.",
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* type: "object",
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* properties: {
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* name: { title: "Name", description: "The person's name", type: "string" },
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* age: { title: "Age", description: "The person's age", type: "integer" },
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* fav_food: {
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* title: "Fav Food",
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* description: "The person's favorite food",
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* type: "string",
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* },
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* },
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* required: ["name", "age"],
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* };
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*
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* const model = new ChatOpenAI();
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* const prompt = ChatPromptTemplate.fromMessages([
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* ["human", "Human description: {description}"],
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* ]);
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*
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* const outputParser = new JsonOutputFunctionsParser();
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*
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* // Also works with Zod schema
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* const runnable = createStructuredOutputRunnable({
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* outputSchema: jsonSchema,
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* llm: model,
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* prompt,
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* outputParser
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* });
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*
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* const response = await runnable.invoke({
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* description:
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* "My name's John Doe and I'm 30 years old. My favorite kind of food are chocolate chip cookies.",
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* });
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*
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* console.log(response);
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*
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* // { name: 'John Doe', age: 30, fav_food: 'chocolate chip cookies' }
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* ```
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*/
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function createStructuredOutputRunnable(config) {
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const { outputSchema, llm, prompt, outputParser } = config;
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const jsonSchema = isZodSchema(outputSchema)
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? (0, zod_to_json_schema_1.zodToJsonSchema)(outputSchema)
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: outputSchema;
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const oaiFunction = {
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name: "outputFormatter",
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description: "Output formatter. Should always be used to format your response to the user",
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parameters: jsonSchema,
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};
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return createOpenAIFnRunnable({
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functions: [oaiFunction],
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llm,
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prompt,
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enforceSingleFunctionUsage: true,
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outputParser,
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});
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}
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exports.createStructuredOutputRunnable = createStructuredOutputRunnable;
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