Agentic RAG: Reduce Cost and Improve Speed of Retrieval

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Code: https://github.com/KannamSridharKumar...

Summary:
- Build an agentic retriever to reduce cost and improve retrieval speed in RAG systems by dynamically selecting relevant data sources.
- Use Hugging Face tools and embeddings to create the retriever, with the agent filtering data sources dynamically.
- Agent identifies the right data sources, reducing the search scope from thousands to a few relevant chunks.
- If no results appear, default to searching all data sources to ensure retrieval.

Keywords:
RAG, Agentic RAG, Hugging Face, Dynamic Data Filtering, Latency Optimization
Semantic Search, OpenAI, Vector Database, Embedding Model

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