agsamantha/node_modules/langchain/dist/evaluation/loader.js
2024-10-02 15:15:21 -05:00

56 lines
2.4 KiB
JavaScript

import { ChatOpenAI } from "@langchain/openai";
import { BaseChatModel } from "@langchain/core/language_models/chat_models";
import { CriteriaEvalChain, LabeledCriteriaEvalChain, } from "./criteria/index.js";
import { LabeledPairwiseStringEvalChain, PairwiseStringEvalChain, } from "./comparison/index.js";
import { EmbeddingDistanceEvalChain, PairwiseEmbeddingDistanceEvalChain, } from "./embedding_distance/index.js";
import { TrajectoryEvalChain } from "./agents/index.js";
/**
* Load the requested evaluation chain specified by a string
* @param type The type of evaluator to load.
* @param options
* - llm The language model to use for the evaluator.
* - criteria The criteria to use for the evaluator.
* - agentTools A list of tools available to the agent,for TrajectoryEvalChain.
*/
export async function loadEvaluator(type, options) {
const { llm, chainOptions, criteria, agentTools } = options || {};
const llm_ = llm ??
new ChatOpenAI({
modelName: "gpt-4",
temperature: 0.0,
});
let evaluator;
switch (type) {
case "criteria":
evaluator = await CriteriaEvalChain.fromLLM(llm_, criteria, chainOptions);
break;
case "labeled_criteria":
evaluator = await LabeledCriteriaEvalChain.fromLLM(llm_, criteria, chainOptions);
break;
case "pairwise_string":
evaluator = await PairwiseStringEvalChain.fromLLM(llm_, criteria, chainOptions);
break;
case "labeled_pairwise_string":
evaluator = await LabeledPairwiseStringEvalChain.fromLLM(llm_, criteria, chainOptions);
break;
case "trajectory":
// eslint-disable-next-line no-instanceof/no-instanceof
if (!(llm_ instanceof BaseChatModel)) {
throw new Error("LLM must be an instance of a base chat model.");
}
evaluator = await TrajectoryEvalChain.fromLLM(llm_, agentTools, chainOptions);
break;
case "embedding_distance":
evaluator = new EmbeddingDistanceEvalChain({
embedding: options?.embedding,
distanceMetric: options?.distanceMetric,
});
break;
case "pairwise_embedding_distance":
evaluator = new PairwiseEmbeddingDistanceEvalChain({});
break;
default:
throw new Error(`Unknown type: ${type}`);
}
return evaluator;
}