{"data":{"full_name":"maxogod/student-rag-api","name":"student-rag-api","description":"A FastAPI RAG pipeline that ingests PDF files, makes embeddings and stores them in a Vector Store (Postgres + pgvector database), then when a query is made performs a similarity search and builds the context to pass to the LLM to generate accurate bibliography-backed answers to the questions using langchain.","stars":2.0,"forks":0.0,"language":"Python","license":null,"archived":0.0,"subcategory":"hybrid-search-rag","last_pushed_at":"2026-03-02T14:53:14+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":2.0,"maturity_score":1.0,"community_score":0.0,"quality_score":13.0,"quality_tier":"experimental","risk_flags":"['no_license', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-05T20:22:54.002169+00:00"}}