demo_instructions.md

RAG System Demo -- Instructions

Getting Started

1. Wait for models to load. The first launch downloads and caches google/flan-t5-small and all-MiniLM-L6-v2. This may take a minute on the initial run.

2. Upload documents. Use the sidebar file uploader to add one or more documents (PDF, TXT, DOCX, or CSV). Click Process Documents to ingest them into the vector store. Alternatively, click Load Sample Document to use the bundled sample about AI and machine learning.

3. Ask questions. Type a question in the chat input at the bottom of the main area. The system will:

   • Search for the most relevant chunks in your uploaded documents.
   • Pass the top results as context to the language model.
   • Return a generated answer with source attribution.

4. Review sources. The right column shows the retrieved document chunks ranked by relevance score. Click View Sources in the chat to see which chunks informed each answer.

Tips

• Upload multiple documents and ask comparative questions.
• Shorter, focused questions tend to produce better answers.
• The relevance score (0-100%) indicates how closely a chunk matches your query.
• Use Clear All Documents in the sidebar to reset and start fresh.

Limitations

• flan-t5-small is a compact model. For complex reasoning, a larger model would perform better.
• Very long documents are split into chunks; some context may be lost at chunk boundaries.
• The vector store is in-memory and resets when the app restarts.