SecureDoc — Private QA Bot

A fully local, private PDF question-answering bot. No cloud. No data leaks. Everything runs on your machine.

Quick Setup (Do this once)

1. Install Ollama

Download from https://ollama.com and install it.

Then pull the required models:

ollama pull llama3
ollama pull nomic-embed-text

2. Install Python dependencies

pip install -r requirements.txt

3. Run the app

streamlit run app.py

How to Use

1. Upload a PDF using the sidebar
2. Click "Index Document" — this embeds it into ChromaDB locally
3. Ask questions in the chat box
4. Get answers with page citations ✅

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Project Structure

securedoc/
├── app.py            ← Streamlit UI
├── rag_engine.py     ← ChromaDB + Ollama RAG logic
├── pdf_loader.py     ← PDF reading & chunking
├── requirements.txt  ← Python packages
└── chroma_db/        ← Auto-created vector database (local)

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Configuration

In rag_engine.py you can change:

Variable	Default	Description
LLM_MODEL	llama3	Any model you've pulled in Ollama
EMBED_MODEL	nomic-embed-text	Embedding model
TOP_K	5	Number of chunks retrieved per query

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Privacy Guarantee

• ChromaDB stores all vectors locally in ./chroma_db/
• Ollama runs the LLM on your GPU — no API calls
• Zero internet traffic after initial model download