sinanuozdemir/oreilly-retrieval-augmented-gen-ai

See how to augment LLMs with real-time data for dynamic, context-aware apps - Rag + Agents + GraphRAG.

51
/ 100
Established

Implements end-to-end RAG workflows using vector databases (Pinecone), multiple LLM providers (OpenAI, Anthropic, Gemini, Cohere), and LangGraph for orchestration with built-in evaluation components. Covers advanced patterns including knowledge graph-based retrieval (GraphRAG with Neo4j), embedding fine-tuning with synthetic data, multimodal search, and agentic workflows with semantic re-ranking.

167 stars.

No License No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 23 / 25

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Stars

167

Forks

89

Language

Jupyter Notebook

License

—

Category

agentic-rag-systems

Last pushed

Feb 17, 2026

Commits (30d)

0

GitHub
Agentic RAG Systems · 240 tools

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