chore: import upstream snapshot with attribution
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# Sample Documents for Evaluation
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These markdown files correspond to test questions in `../sample_dataset.json`.
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## Usage
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1. **Index documents** into LightRAG (via WebUI, API, or Python)
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2. **Run evaluation**: `python lightrag/evaluation/eval_rag_quality.py`
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3. **Expected results**: ~91-100% RAGAS score per question
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## Files
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- `01_lightrag_overview.md` - LightRAG framework and hallucination problem
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- `02_rag_architecture.md` - RAG system components
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- `03_lightrag_improvements.md` - LightRAG vs traditional RAG
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- `04_supported_databases.md` - Vector database support
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- `05_evaluation_and_deployment.md` - Metrics and deployment
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## Note
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Documents use clear entity-relationship patterns for LightRAG's default entity extraction prompts. For better results with your data, customize `lightrag/prompt.py`.
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