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@tylerwelsh tylerwelsh commented Sep 17, 2025

Implements complete RAG system for PDF-based Q&A using aimakerspace library. See MERGE.md for details.

✅ RAG System

  • PDF content is chunked and embedded using OpenAI embeddings
  • Vector similarity search retrieves top 3 relevant chunks per question
  • LLM responds only based on provided context from PDF

✅ Context-Only Responses

  • Strict prompt engineering ensures answers come only from PDF content
  • Returns "I am not sure." when no relevant context is found
  • No general knowledge responses allowed

✅ PDF Management

  • Single PDF replacement system (upload new PDF replaces previous)
  • Temporary in-memory storage during session
  • Lazy loading (PDF processed on first question)

✅ Professional UI/UX

  • Clean, modern interface with visual status indicators
  • Drag-and-drop upload with file validation
  • Real-time processing status
  • Source attribution in responses

- Complete backend rewrite with RAG endpoints using aimakerspace library
- PDF upload, indexing, and context-only chat functionality
- Frontend redesign with drag-and-drop upload and simplified Q&A interface
- Vector similarity search with OpenAI embeddings
- Strict context-only responses with 'I am not sure' fallback
- Professional UI with status indicators and source attribution
- Added dependencies: PyPDF2, numpy, python-dotenv
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