Document-Intelligence

Description:
A Retrieval-Augmented Generation (RAG) system that uses Ollama to enable intelligent document understanding. It employs two separate models — one for embedding documents and another for semantic question answering — to provide contextual responses based on the ingested content.

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Features

• Document embedding for efficient vector search
• Semantic answering based on document context
• Node.js-based frontend for interaction
• Python backend to orchestrate retrieval and generation

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Installation & Setup

1. Install Ollama

Follow the installation instructions for your operating system:
https://ollama.com/download

2. Add Required Models

Open a terminal and pull the necessary models:

ollama pull nomic-embed-text      # For document embedding
ollama pull llama3                # For question answering

3. Set Up the Frontend

cd app
npm install
npm run dev

4. Start the Backend

pip install -r requirements.txt

4.a Create environment

python3 -m venv .venv 

4.b Activate Environment

.venv\Scripts\activate

4.c Start server

python main.py