@dooor-ai/toolkit/src/evals/faithfulness.ts

Guards, Evals & Observability for AI applications - works seamlessly with LangChain/LangGraph

import { Eval } from "./base";
import { EvalResult, EvalConfig } from "../core/types";
import { getCortexDBClient, getGlobalProviderName } from "../observability/cortexdb-client";

export interface FaithfulnessConfig extends EvalConfig {
  /** Context/retrieved documents to check against */
  context?: string;
}

/**
 * FaithfulnessEval - Measures if the LLM's answer is grounded in the provided context
 *
 * Critical for RAG systems to prevent hallucination. Checks if claims in the answer
 * are supported by the retrieved context.
 *
 * Example:
 * ```typescript
 * const eval = new FaithfulnessEval({
 *   threshold: 0.8,
 *   context: "The Eiffel Tower is 330 meters tall."
 * });
 * const result = await eval.evaluate(
 *   "How tall is the Eiffel Tower?",
 *   "The Eiffel Tower is 330 meters tall."
 * );
 * // result.score = 1.0, result.passed = true
 * ```
 */
export class FaithfulnessEval extends Eval {
  private context?: string;

  constructor(config: FaithfulnessConfig = {}) {
    super(config);
    this.context = config.context;
  }

  get name(): string {
    return "FaithfulnessEval";
  }

  /**
   * Set context dynamically (useful for RAG pipelines)
   */
  setContext(context: string): void {
    this.context = context;
  }

  async evaluate(
    input: string,
    output: string,
    metadata?: Record<string, any>
  ): Promise<EvalResult> {
    const startTime = Date.now();

    // Get context from metadata if not set directly
    const context = this.context || metadata?.context || metadata?.retrievedDocs;

    if (!context) {
      return {
        name: this.name,
        score: 0.5,
        passed: false,
        details: "No context provided for faithfulness evaluation. Pass context via config or metadata.",
        metadata: {
          latency: Date.now() - startTime,
        },
        timestamp: new Date(),
      };
    }

    try {
      const cortexClient = getCortexDBClient();
      const providerName = getGlobalProviderName();

      const prompt = this.buildPrompt(input, output, context);

      const response = await cortexClient.invokeAI({
        prompt,
        usage: "evaluation",
        providerName: providerName || undefined,
        temperature: 0.0,
        maxTokens: 300,
      });

      const score = this.parseScore(response.text);
      const passed = score >= this.getThreshold();

      return {
        name: this.name,
        score,
        passed,
        details: `Faithfulness score: ${score.toFixed(2)}. ${passed ? "PASSED" : "FAILED"} (threshold: ${this.getThreshold()})`,
        metadata: {
          latency: Date.now() - startTime,
          judgeResponse: response.text,
          contextLength: context.length,
        },
        timestamp: new Date(),
      };
    } catch (error) {
      console.error("FaithfulnessEval failed:", error);

      return {
        name: this.name,
        score: 0.5,
        passed: false,
        details: `Eval failed: ${error instanceof Error ? error.message : "Unknown error"}`,
        metadata: {
          error: String(error),
          latency: Date.now() - startTime,
        },
        timestamp: new Date(),
      };
    }
  }

  private buildPrompt(question: string, answer: string, context: string): string {
    return `You are an expert evaluator. Your task is to assess if the answer is faithful to (grounded in) the provided context.

Context: """
${context}
"""

Question: "${question}"
Answer: "${answer}"

Evaluate faithfulness:
- 1.0 = All claims in answer are directly supported by context
- 0.7-0.9 = Most claims supported, minor unsupported details
- 0.4-0.6 = Some claims supported, some not found in context
- 0.0-0.3 = Answer contains hallucinations or unsupported claims

Output ONLY a JSON object in this exact format:
{
  "score": 0.9,
  "reasoning": "Brief explanation of what's supported and what's not"
}`;
  }

  private parseScore(response: string): number {
    try {
      const jsonMatch = response.match(/\{[\s\S]*\}/);
      if (jsonMatch) {
        const parsed = JSON.parse(jsonMatch[0]);
        if (typeof parsed.score === "number") {
          return Math.max(0, Math.min(1, parsed.score));
        }
      }

      const numberMatch = response.match(/\b0?\.\d+\b|\b1\.0\b|\b[01]\b/);
      if (numberMatch) {
        return Math.max(0, Math.min(1, parseFloat(numberMatch[0])));
      }

      console.warn("Could not parse score from response:", response);
      return 0.5;
    } catch (error) {
      console.error("Error parsing score:", error);
      return 0.5;
    }
  }
}