{"data":{"full_name":"Ysen1903/RAG_Engine","name":"RAG_Engine","description":"A professional Retrieval-Augmented Generation (RAG) pipeline designed for efficient document interrogation and semantic search. This engine leverages state-of-the-art language models and vector databases to provide accurate, context-aware answers based on private PDF documents.","stars":1.0,"forks":0.0,"language":"Python","license":null,"archived":0.0,"subcategory":"evaluation","last_pushed_at":"2026-02-07T12:05:23+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":10.0,"adoption_score":1.0,"maturity_score":3.0,"community_score":0.0,"quality_score":14.0,"quality_tier":"experimental","risk_flags":"['no_license', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-07T10:49:15.069088+00:00"}}