feat: Phase 3 - Metrics System

[himanshu231204]

Summary

Implement the complete Phase 3 Metrics System for OpenAgent Eval, including:

• BaseMetric ABC interface and MetricResult dataclass
• 7 retrieval metrics (ContextPrecision, ContextRecall, RecallAtK, PrecisionAtK, HitRate, MRR, NDCG)
• 9 generation metrics (Faithfulness, AnswerRelevancy, HallucinationDetection, SemanticSimilarity, ExactMatch, F1Score, BLEU, ROUGE, BERTScore)
• Performance metric (LatencyMetric)
• Cost metric (TokenCountMetric)
• Metric registry with get_metric() and list_metrics()
• Pydantic validation models
• 86 unit tests (136 total tests passing)

Motivation

Phase 3 is the core evaluation capability of OpenAgent Eval. These metrics enable developers to measure retrieval quality, answer quality, performance, and cost of their RAG systems.

Files Modified

• openagent_eval/metrics/base.py - BaseMetric ABC + MetricResult
• openagent_eval/metrics/models.py - Pydantic validation models
• openagent_eval/metrics/retrieval/ - 7 retrieval metrics
• openagent_eval/metrics/generation/ - 9 generation metrics
• openagent_eval/metrics/performance/latency.py - Latency tracking
• openagent_eval/metrics/cost/tokens.py - Token counting + cost estimation
• openagent_eval/metrics/init.py - Exports + registry
• ests/unit/test_metrics/ - 86 unit tests
• .ai/05_TASKS.md - Updated task tracking

Architectural Decisions

• All metrics implement BaseMetric ABC with evaluate() -> MetricResult
• Generation metrics use fallback implementations with optional external library integration (Ragas, DeepEval, HF Evaluate, sentence-transformers)
• Retrieval metrics are pure Python (no external dependencies)
• Cost estimation covers OpenAI, Anthropic, Gemini, and Groq pricing

Breaking Changes

None

Testing

• 136 tests passing (50 existing + 86 new)
• All metrics tested with happy path, edge cases, and error cases
• AAA testing pattern followed

Remaining TODOs

• Phase 4: Reports (Terminal, Markdown, HTML, JSON)
• Phase 5: Providers (OpenAI, Gemini, Anthropic adapters)

Assumptions & Limitations

• Generation metrics (Faithfulness, Relevancy, Hallucination) use simple word overlap as fallback when external libraries (Ragas, DeepEval) are not installed
• BERTScore and SemanticSimilarity use sentence-transformers as primary implementation
• Cost estimation uses published pricing as of 2026-07-08

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