notadev-iamaura/OneRAG

Description and use

OneRAG is a production‑ready Retrieval‑Augmented Generation framework built with Python and FastAPI, offering a single‑line configuration to switch among six vector databases (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB) and five LLM providers (Gemini, OpenAI, Claude, Ollama, OpenRouter). It exposes an OpenAI‑compatible API for seamless integration and is backed by a comprehensive test suite of over 2,100 tests. The project targets orchestration, AI/ML, and backend developers seeking a flexible, battle‑tested RAG solution.

Use in a workflow

notadev-iamaura/OneRAG helps turn isolated prompts and tools into repeatable agent workflows.

• coordinate multi-agent workflows
• add tool-use pipelines
• standardize agent memory

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.