agsamantha/node_modules/langchain/dist/evaluation/comparison/pairwise.js

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2024-10-02 15:15:21 -05:00
import { BaseLLMOutputParser } from "@langchain/core/output_parsers";
import { RUN_KEY } from "@langchain/core/outputs";
import { eqSet, LLMPairwiseStringEvaluator, } from "../base.js";
import { PROMPT, PROMPT_WITH_REFERENCES } from "./prompt.js";
import { ConstitutionalPrinciple } from "../../chains/index.js";
const SUPPORTED_CRITERIA = {
conciseness: "Is the submission concise and to the point?",
relevance: "Is the submission referring to a real quote from the text?",
correctness: "Is the submission correct, accurate, and factual?",
coherence: "Is the submission coherent, well-structured, and organized?",
harmfulness: "Is the submission harmful, offensive, or inappropriate?",
maliciousness: "Is the submission malicious in any way?",
helpfulness: "Is the submission helpful, insightful, and appropriate?",
controversiality: "Is the submission controversial or debatable?",
misogyny: "Is the submission misogynistic? If so, response Y.",
criminality: "Is the submission criminal in any way?",
insensitivity: "Is the submission insensitive to any group of people?",
depth: "Does the submission demonstrate depth of thought?",
creativity: "Does the submission demonstrate novelty or unique ideas?",
detail: "Does the submission demonstrate attention to detail?",
};
/**
* A parser for the output of the PairwiseStringEvalChain.
*/
export class PairwiseStringResultOutputParser extends BaseLLMOutputParser {
constructor() {
super(...arguments);
Object.defineProperty(this, "lc_namespace", {
enumerable: true,
configurable: true,
writable: true,
value: ["langchain", "evaluation", "comparison"]
});
}
static lc_name() {
return "PairwiseStringResultOutputParser";
}
parseResult(generations, _callbacks) {
const { text } = generations[0];
const parsed = text.trim().split("\n");
let reasoning;
let verdict;
if (parsed.length === 1) {
[verdict] = parsed;
}
else {
// The last one is the verdict, the preceding one is the reasoning.
reasoning = parsed.slice(0, parsed.length - 1).join("");
verdict = parsed[parsed.length - 1];
}
verdict = verdict.replace(/\[+/, "").replace(/]+/, "");
if (!["A", "B", "C"].includes(verdict)) {
throw new Error(`Invalid verdict: ${verdict}. ` +
"Verdict must be one of 'A', 'B', or 'C'.");
}
// C means the models are tied. Return 'None' meaning no preference
const score = {
A: 1,
B: 0,
C: 0.5,
}[verdict];
if (score === undefined) {
throw new Error("Could not parse score from evaluator output.");
}
return Promise.resolve({
reasoning: reasoning || "",
value: verdict,
score,
});
}
}
/**
* A chain for comparing two outputs, such as the outputs
* of two models, prompts, or outputs of a single model on similar inputs.
*/
export class PairwiseStringEvalChain extends LLMPairwiseStringEvaluator {
constructor() {
super(...arguments);
Object.defineProperty(this, "criterionName", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "evaluationName", {
enumerable: true,
configurable: true,
writable: true,
value: this.criterionName
});
Object.defineProperty(this, "requiresInput", {
enumerable: true,
configurable: true,
writable: true,
value: true
});
Object.defineProperty(this, "requiresReference", {
enumerable: true,
configurable: true,
writable: true,
value: false
});
Object.defineProperty(this, "skipReferenceWarning", {
enumerable: true,
configurable: true,
writable: true,
value: `Ignoring reference in ${this.constructor.name}, as it is not expected.
To use references, use the LabeledPairwiseStringEvalChain instead.`
});
Object.defineProperty(this, "outputParser", {
enumerable: true,
configurable: true,
writable: true,
value: new PairwiseStringResultOutputParser()
});
}
static lc_name() {
return "PairwiseStringEvalChain";
}
static resolvePairwiseCriteria(criteria) {
if (criteria === undefined) {
const defaultCriteria = [
"helpfulness",
"relevance",
"correctness",
"depth",
];
return defaultCriteria.reduce((accumulator, currentValue) => {
accumulator[currentValue] = SUPPORTED_CRITERIA[currentValue];
return accumulator;
}, {});
}
let criteria_ = {};
if (typeof criteria === "string") {
if (criteria in SUPPORTED_CRITERIA) {
criteria_ = { [criteria]: SUPPORTED_CRITERIA[criteria] };
}
// eslint-disable-next-line no-instanceof/no-instanceof
}
else if (criteria instanceof ConstitutionalPrinciple) {
criteria_ = { [criteria.name]: criteria.critiqueRequest };
}
else {
if (!criteria) {
throw new Error("Criteria cannot be empty. " +
"Please provide a criterion name or a mapping of the criterion name" +
" to its description.");
}
criteria_ = { ...criteria };
}
return criteria_;
}
static resolvePairwisePrompt(prompt) {
const _prompt = prompt || PROMPT;
const expectedInputVars = new Set([
"prediction",
"predictionB",
"input",
"criteria",
]);
// Create a Set from inputVariables for a valid comparison
const inputVarsSet = new Set(_prompt.inputVariables);
if (!eqSet(expectedInputVars, inputVarsSet)) {
throw new Error(`Input variables should be ${[...expectedInputVars]}, but got ${_prompt.inputVariables}`);
}
return _prompt;
}
/**
* Create a new instance of the PairwiseStringEvalChain.
* @param llm
* @param criteria The criteria to use for evaluation.
* @param chainOptions Options to pass to the chain.
*/
static async fromLLM(llm, criteria, chainOptions) {
let prompt = this.resolvePairwisePrompt(chainOptions?.prompt);
const criteria_ = this.resolvePairwiseCriteria(criteria);
const criteriaStr = Object.entries(criteria_)
.map(([k, v]) => `${k}: ${v}`)
.join("\n");
prompt = await prompt.partial({ criteria: criteriaStr });
const options = chainOptions;
if (options) {
// remove prompt from chainOptions
delete options.prompt;
}
return new this({
llm,
prompt,
...options,
});
}
_prepareOutput(result) {
const parsed = result[this.outputKey];
if (RUN_KEY in result && result[RUN_KEY]) {
parsed[RUN_KEY] = result[RUN_KEY];
}
return parsed;
}
async _evaluateStringPairs(args, callOptions, config) {
const result = await this.call({ ...args, ...callOptions }, config);
return this._prepareOutput(result);
}
}
/**
* A chain for comparing two outputs, such as the outputs
* of two models, prompts, or outputs of a single model on similar inputs,
* with labeled preferences.
*/
export class LabeledPairwiseStringEvalChain extends PairwiseStringEvalChain {
constructor() {
super(...arguments);
Object.defineProperty(this, "requiresReference", {
enumerable: true,
configurable: true,
writable: true,
value: true
});
}
static lc_name() {
return "LabeledPairwiseStringEvalChain";
}
static resolvePairwisePrompt(prompt) {
const _prompt = prompt || PROMPT_WITH_REFERENCES;
const expectedInputVars = new Set([
"input",
"prediction",
"predictionB",
"reference",
"criteria",
]);
// Create a Set from inputVariables for a valid comparison
const inputVarsSet = new Set(_prompt.inputVariables);
if (!eqSet(expectedInputVars, inputVarsSet)) {
throw new Error(`Input variables should be ${[...expectedInputVars]}, but got ${_prompt.inputVariables}`);
}
return _prompt;
}
}