AI-Powered Document Analysis Platform

🚀 Overview

CleverQuery is an AI-powered document analysis platform that helps users extract insights, answer questions, and analyze documents using advanced Retrieval-Augmented Generation (RAG). This project uses Django for the web framework, Gemini AI for text generation, and FAISS for efficient vector search.

With CleverQuery, you can:

• Upload PDF documents for analysis
• Ask questions about your documents and get intelligent answers
• Use specialized session types for different document categories
• Enjoy real-time streaming responses as the AI generates answers
• Create multiple document sessions for different use cases

✨ Features

📊 Specialized Document Analysis

Choose from various specialized analysis modes:

• Exam Preparation Guide: Study materials and educational content
• Technical Manual Interpreter: Technical documents and instruction manuals
• Legal Document Analysis: Contracts, agreements, and legal texts
• Nutritional Label Interpreter: Food labels and nutritional information
• Financial Report Analysis: Financial statements and reports
• Contract Review Assistant: Contract analysis and review

🧠 Advanced RAG Technology

CleverQuery uses a sophisticated Retrieval-Augmented Generation system:

• Document text is split into semantic chunks
• Vector embeddings are created using SentenceTransformers
• FAISS vector database enables semantic search
• Context-aware responses are generated based on the most relevant document sections

💬 Interactive Chat Interface

• Real-time streaming responses with typing indicators
• Predefined questions for each document type
• Conversation history for context-aware responses
• Markdown rendering with syntax highlighting for code
• Mobile-responsive design using Tailwind CSS

🛠️ Technology Stack

• Backend: Django 4.2
• AI: Google Generative AI (Gemini 2.0)
• Vector Database: FAISS
• Embedding Model: Sentence-Transformers (all-MiniLM-L6-v2)
• Frontend: HTML, JavaScript, Tailwind CSS
• Text Processing: NLTK, PyPDF2
• Markdown: Python-Markdown with extensions

📋 Installation

Prerequisites

• Python 3.9+
• pip package manager

Steps

1. Clone the repository:

git clone https://github.com/ghubrakesh/CleverQuery.git
cd CleverQuery

2. Create and activate a virtual environment:

python -m venv ccenv
source ccenv/bin/activate  # On Windows: ccenv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

# Create a .env file in the project root
echo "GENERATIVEAI_API_KEY=your_google_gemini_api_key" > .env

5. Run migrations:

python manage.py migrate

6. Create a superuser (optional):

python manage.py createsuperuser

7. Run the development server:

python manage.py runserver

8. Access the application at http://localhost:8000

🧑‍💻 Usage

1. Register/Login: Create an account or log in
2. Create Session: Choose a specialized session type for your document
3. Upload Document: Upload a PDF document for analysis
4. Ask Questions: Type your questions or use the predefined questions
5. Get Insights: Receive AI-generated answers based on your document content