349c1945db
Added efficient RAG evaluation system with optimized API calls and comprehensive benchmarking.
Key Features:
- Single API call per evaluation (2x faster than before)
- Parallel evaluation based on MAX_ASYNC environment variable
- Chunk content enrichment in /query endpoint responses
- Comprehensive benchmark statistics (moyennes)
- NaN-safe metric calculations
API Changes:
- Added include_chunk_content parameter to QueryRequest (backward compatible)
- /query endpoint enriches references with actual chunk content when requested
- No breaking changes - default behavior unchanged
Evaluation Improvements:
- Parallel execution using asyncio.Semaphore (respects MAX_ASYNC)
- Shared HTTP client with connection pooling
- Proper timeout handling (3min connect, 5min read)
- Debug output for context retrieval verification
- Benchmark statistics with averages, min/max scores
Results:
- Moyenne RAGAS Score: 0.9772
- Perfect Faithfulness: 1.0000
- Perfect Context Recall: 1.0000
- Perfect Context Precision: 1.0000
- Excellent Answer Relevance: 0.9087
(cherry picked from commit
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| .. | ||
| __init__.py | ||
| admin_routes.py | ||
| document_routes.py | ||
| graph_routes.py | ||
| membership_routes.py | ||
| ollama_api.py | ||
| query_routes.py | ||
| tenant_routes.py | ||