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Data Science
Towards Data Science·22d ago·5 min read
Agentic RAG: Let the Agent Search
TL;DR
Agentic RAG introduces a search-read-decide loop for retrieval-augmented generation (RAG) applications, addressing common challenges in document retrieval. By implementing a minimal OpenAI Agents SDK, it enhances the relevance of retrieved information.
✦ Why It Matters
Engineers can implement the Agentic RAG framework to improve the accuracy of information retrieval in their applications today.
Key Takeaways
- Utilize iterative retrieval to enhance answer accuracy.
- Define clear agent instructions for effective information gathering.
- Consider using multiple agents for complex tasks.
- Start with curated tools before expanding agent capabilities.
How It Works
Agentic RAG allows models to perform iterative searches, reading relevant documents and refining answers based on the gathered evidence. This process involves using specific tools to list available documents, search for keywords, and read document contents, enabling the agent to build a comprehensive understanding before providing a final answer.