mirror of
https://github.com/google-gemini/gemini-cli.git
synced 2026-06-10 02:52:54 -07:00
Abhijit Balaji
59d377e5e0
- Implement `extract.ts` with robust character-aware parsing for snippets and tools. - Consolidate research dependencies by moving `@ax-llm/ax` to root `optionalDependencies`. - Relocate evaluation logic from `packages/core` to `scripts/optimization/lib/evals` to keep the production core lean. - Add `optimization_targets` to `data/manifest.json` as the single source of truth for the pipeline. - Implement comprehensive unit tests for extraction and variable masking with 100% pass rate. - Update global config and linting rules to support the new optimization infrastructure.
107 lines
2.7 KiB
TypeScript
107 lines
2.7 KiB
TypeScript
/**
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* @license
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* Copyright 2026 Google LLC
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* SPDX-License-Identifier: Apache-2.0
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*/
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/**
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* Configuration for the Tool Alignment objective (The Accuracy Dimension).
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*/
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export interface AlignmentConfig {
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/**
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* The relative importance of accuracy vs other objectives in the Pareto frontier.
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*/
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weight: number;
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/**
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* Strongest negative signal (0.0): used when model falls into a known shell trap.
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*/
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hardFailureScore: number;
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/**
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* Neutral negative signal (0.1): used when model fails to produce a valid tool call.
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*/
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invalidResponseScore: number;
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/**
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* Partial positive signal (0.4): model chose the right tool but hallucinated arguments.
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*/
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toolNameMatchOnlyScore: number;
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/**
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* Maximum positive signal (1.0): model matched the golden signature perfectly.
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*/
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functionalSuccessScore: number;
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}
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/**
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* Configuration for the Brevity objective (The Density Dimension).
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* Uses a word-count step-function to provide high-contrast signal for GEPA.
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*/
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export interface BrevityConfig {
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/**
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* Importance of brevity relative to accuracy.
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*/
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weight: number;
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/**
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* TIER 1: Response is perfectly succinct (e.g., <= 10 words).
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*/
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succinctThresholdWords: number;
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succinctScore: number; // 1.0
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/**
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* TIER 2: Response is acceptable but slightly verbose (e.g., <= 25 words).
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*/
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acceptableThresholdWords: number;
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acceptableScore: number; // 0.7
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/**
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* TIER 3: Response is verbose (e.g., <= 50 words).
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*/
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verboseThresholdWords: number;
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verboseScore: number; // 0.4
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/**
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* TIER 4: Response is very heavy (e.g., > 50 words).
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*/
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heavyScore: number; // 0.1
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}
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/**
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* Global evaluation configuration for multi-objective optimization.
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*/
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export interface EvalConfig {
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objectives: {
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alignment: AlignmentConfig;
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brevity: BrevityConfig;
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};
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}
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/**
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* Default weights and thresholds for the Genetic-Pareto (GEPA) engine.
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* These constants drive the 'Selection Pressure' that evolves the prompt.
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* GEPA always MAXIMIZES, so higher scores represent better performance.
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*/
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export const DEFAULT_EVAL_CONFIG: EvalConfig = {
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objectives: {
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alignment: {
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weight: 1.0, // PRIMARY: Accuracy cannot be sacrificed.
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hardFailureScore: 0.0,
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invalidResponseScore: 0.1,
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toolNameMatchOnlyScore: 0.4,
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functionalSuccessScore: 1.0,
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},
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brevity: {
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weight: 0.6, // SECONDARY: Reward brevity once accuracy is high.
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succinctThresholdWords: 10,
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succinctScore: 1.0,
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acceptableThresholdWords: 25,
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acceptableScore: 0.7,
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verboseThresholdWords: 50,
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verboseScore: 0.4,
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heavyScore: 0.1, // Never hard-zero brevity to allow gradient improvement.
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},
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},
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};
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