BerriAI / litellm
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GitHub Trending·9d ago·5 min read
jamwithai / production-agentic-rag-course
TL;DR
Build a research assistant system using Retrieval-Augmented Generation (RAG) techniques that fetches and understands academic papers to answer research questions. This project emphasizes foundational keyword search before integrating advanced AI methods.
✦ Why It Matters
Start building a RAG system today to enhance your research capabilities and automate paper retrieval.
Key Takeaways
- Set up a complete infrastructure using Docker and FastAPI.
- Implement automated data pipelines for fetching academic papers.
- Master keyword search and hybrid retrieval techniques.
- Integrate intelligent agents for adaptive query handling.
How It Works
The course emphasizes a foundational approach to building RAG systems, starting with keyword search before integrating AI techniques. Participants will learn to create a data ingestion pipeline that fetches papers from arXiv, processes them, and stores metadata in PostgreSQL.
The hybrid search combines traditional keyword methods with semantic understanding, enhancing retrieval accuracy. Additionally, intelligent agents are developed to adaptively refine queries and assess document relevance.