u/CandidateNo4820

Built a Agentic RAG system using LangGraph to explore adaptive and self-correcting retrieval workflows.
Traditional RAG often fails when retrieval quality is poor, so this project focuses on improving reliability through agent-based control instead of a fixed pipeline.
Implemented:
- Standard, Reflective, Self-RAG, and Adaptive RAG
- Retrieval grading + reflection loops
- Query-based adaptive routing
- LangSmith tracing for full observability
Goal: reduce hallucinations and improve retrieval quality in LLM applications
Stack:
Python - LangGraph - LangChain - ChromaDB • Gemini or OpenAi
Repo : https://github.com/Oussama-lasri/RAG-Agent