DocuMind AI — An Intelligent Document Assistant

DocuMind AI is an AI-powered document analysis and interaction tool built with Google Gemini AI and Streamlit. It enables users to upload PDF and TXT documents, generate executive summaries, ask context-grounded questions with precise page citations, extract domain-specific terminology, create visual mind maps, and test their understanding through interactive knowledge challenges.

The system combines document parsing, retrieval-augmented generation (RAG), contextual retrieval, and AI-powered analysis to provide reliable, document-grounded responses while maintaining traceability to the original source content.

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✨ Features

• 📄 Document Upload & Parsing: Supports PDF and TXT files with high-fidelity text extraction and page-level chunk tracking.
• 🧠 AI Executive Summaries: Generates concise executive summaries along with important key takeaways from uploaded documents.
• 💬 Grounded Q&A: Ask natural-language questions and receive context-aware answers based on the uploaded document.
• 📑 Precise Page Citations: Provides page references and relevant source snippets to help users verify generated answers.
• 🔍 RAG-Based Retrieval: Retrieves relevant document content before generating answers, improving contextual accuracy and reducing unsupported responses.
• 🗺️ Interactive Mind Maps: Automatically converts document concepts and relationships into visual mind maps using Mermaid diagrams.
• 📚 Glossary & Jargon Extraction: Identifies technical terms, acronyms, and domain-specific terminology and generates their definitions.
• 🎯 Knowledge Challenge: Automatically generates multiple-choice and conceptual questions based on document content and evaluates user responses.
• 🔄 Context-Aware Interaction: Supports document-based conversations and follow-up questions using retrieved contextual information.
• 📤 Multi-Format Export: Export summaries, Q&A history, glossaries, mind maps, and quiz evaluations in Markdown and HTML formats.
• 🌐 Interactive Streamlit Interface: Provides a clean and intuitive interface for uploading documents, analyzing content, asking questions, and exploring generated insights.

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📁 Project Structure

DocuMind AI
├── app.py                   # Main Streamlit web application interface
├── requirements.txt         # Project dependencies
├── .env.example             # Example environment configuration template
├── .gitignore               # Git ignore configuration file
├── assets/                  # Application logos and brand assets
│   ├── DocuMind_favicon_rounded.png
│   └── DocuMind_logo_white.png
└── src/                     # Core backend engine modules
    ├── parser.py            # PDF & TXT document parsing & chunking engine
    ├── summarizer.py        # Executive summary & takeaway generator
    ├── retriever.py         # TF-IDF & vector similarity search retriever
    ├── qa_engine.py         # RAG-based Q&A engine with citations
    ├── challenge_engine.py  # Quiz generation & automated evaluation engine
    ├── glossary_engine.py   # Jargon & domain terminology extraction
    ├── mindmap_engine.py    # Structured mind map generator (Mermaid)
    ├── exporter.py          # Report export manager (Markdown, HTML)
    ├── session_cache.py     # Disk-backed session persistence manager
    ├── validator.py         # Gemini API key validation engine
    └── styles.py            # Custom Streamlit CSS design system

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🛠️ Tech Stack

• Frontend / Framework: Streamlit
• LLM Provider: Google Gemini API (google-genai / google-generativeai)
• Document Processing: pypdf, pdfplumber
• Vector Retrieval: scikit-learn (TF-IDF & Cosine Similarity)
• Environment Management: python-dotenv

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🚀 Quick Start

1. Prerequisites

Ensure you have Python 3.9+ installed on your system.

2. Navigate to Project Directory

cd "DocuMind AI"

3. Create & Activate a Virtual Environment

Windows (PowerShell):

python -m venv .venv
.\.venv\Scripts\Activate.ps1

macOS / Linux:

python3 -m venv .venv
source .venv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

5. Configure API Keys

Copy .env.example to create a .env file in the project root:

cp .env.example .env

Open .env and add your Google Gemini API Key:

GEMINI_API_KEY=your_actual_gemini_api_key_here

(Alternatively, you can enter your API key directly within the app sidebar at runtime).

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🏃 Running the Application

Launch the Streamlit web application with:

streamlit run app.py

The app will open automatically in your default browser at http://localhost:8501.

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.