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@dooor-ai/toolkit

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

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import { EvalResult, EvalConfig } from "../core/types"; /** * Abstract base class for all evals */ export declare abstract class Eval { protected config: EvalConfig; constructor(config?: EvalConfig); /** * Get the name of this eval */ abstract get name(): string; /** * Evaluate the LLM response * @param input - The input that was sent to the LLM * @param output - The output from the LLM * @param metadata - Additional metadata (e.g., latency, tokens, cost) * @returns EvalResult with score and pass/fail */ abstract evaluate(input: string, output: string, metadata?: Record<string, any>): Promise<EvalResult> | EvalResult; /** * Check if this eval is enabled */ isEnabled(): boolean; /** * Get the threshold */ getThreshold(): number; } //# sourceMappingURL=base.d.ts.map