da9070ecf7
Remove deprecated storage backends and Kubernetes deployment configuration: - Delete unused storage implementations: FAISS, JSON, Memgraph, Milvus, MongoDB, Nano Vector DB, Neo4j, NetworkX, Qdrant, Redis - Remove Kubernetes deployment manifests and installation scripts - Delete legacy examples for deprecated backends - Consolidate to PostgreSQL-only storage backend Streamline dependencies and add new capabilities: - Remove deprecated code documentation and migration guides - Add full-text search caching layer with FTS cache module - Implement metrics collection and monitoring pipeline - Add explain and metrics API routes - Simplify configuration with PostgreSQL-focused setup Update documentation and configuration: - Rewrite README to focus on supported features - Update environment and configuration examples - Remove Kubernetes-specific documentation - Add new utility scripts for PDF uploads and pipeline monitoring
30 lines
766 B
Python
30 lines
766 B
Python
"""
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LightRAG Evaluation Module
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RAGAS-based evaluation framework for assessing RAG system quality.
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Usage:
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from lightrag.evaluation import RAGEvaluator
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evaluator = RAGEvaluator()
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results = await evaluator.run()
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Note: RAGEvaluator is imported lazily to avoid import errors
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when ragas/datasets are not installed.
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"""
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from typing import Any
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__all__ = ['RAGEvaluator']
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# Stub to satisfy static analyzers; lazily loaded in __getattr__
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RAGEvaluator: Any
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def __getattr__(name: str) -> Any:
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"""Lazy import to avoid dependency errors when ragas is not installed."""
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if name == 'RAGEvaluator':
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from .eval_rag_quality import RAGEvaluator
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return RAGEvaluator
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raise AttributeError(f'module {__name__!r} has no attribute {name!r}')
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