Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
Data Science
Towards AI·20d ago·5 min read
I Built a Hybrid RAG App That Talks to My PDF — and Knows When to Say “I Don’t Know”
TL;DR
A hybrid Retrieval-Augmented Generation (RAG) app was developed to interact with PDF documents, specifically insurance policies. It effectively retrieves relevant information while also recognizing when to refrain from providing incorrect answers.
✦ Why It Matters
Engineers can implement similar RAG systems to ensure accurate information retrieval in applications requiring document analysis.
Key Takeaways
- Utilize both semantic and keyword searches for better retrieval accuracy.
- Implement anti-hallucination techniques to prevent AI from fabricating answers.
- Ensure users can see source excerpts for transparency in responses.
- Run applications locally to avoid dependency on external APIs.
How It Works
The app uses a two-step retrieval process: first, it employs semantic search to gather a broad set of relevant text chunks, then it applies BM25 ranking to refine these results based on exact keyword matches. This ensures that the AI only answers questions with strong supporting evidence from the document.