🧠 FAHEM.AI — Multimodal Educational Platform (RAG + Gemini + LipSync)

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🎥 Watch Demo Video
(Click to see FAHEM in action — full walkthrough of features and UI!)

Overview

FAHEM is an interactive multimodal educational assistant built with Streamlit.
It combines Retrieval-Augmented Generation (RAG) using ColPali, Google Gemini for reasoning and explanation generation, and Wav2Lip for realistic lip-synced video narration.

The chatbot provides personalized learning experiences by adapting to each user's learning style — whether they prefer reading, listening, visuals, or video explanations.

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Key Features

🔍 1. Intelligent PDF-Based Q&A

• Upload any educational PDF.
• The system retrieves relevant knowledge using ColPali embeddings.
• Every answer includes citations linked to the exact PDF pages.

💬 2. Conversational AI in English & Arabic

• Uses Google Gemini for natural dialogue.
• Supports bilingual interaction (English and Arabic).

🔊 3. Text-to-Speech (TTS)

• Converts answers into spoken narration.
• Supports male or female voices using Google Cloud TTS.

🎬 4. Lip-Synced Video Narration

• Generates a realistic talking-head educational video using Wav2Lip.
• Ideal for visual and auditory learners.

🧠 5. Learning Style Personalization

• Built-in Learning Style Test determines your dominant style:
  • ✏️ Reading/Writing
  • 🎧 Auditory
  • 🎥 Visual or Video-Based
• Adapts answers accordingly.

🗂️ 6. Flashcards Generator

-Automatically generates interactive flashcards from PDF content or chatbot responses.

• Designed to enhance active recall and memory retention.
• Suitable for quick revision sessions or self-testing.

🧩 7. Mind Map Visualizer

-Transforms retrieved knowledge into structured mind maps.

• Helps learners visualize relationships between concepts.
• Perfect for spatial and conceptual understanding.

⚙️ 8. Configurable & Modular

• Simple configuration through the Settings tab.
• Modular code design — easy to extend or integrate.

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🏗️ Project Structure

FAHEM/
│
├── app.py                     # Main Streamlit app entry point
│
├── modules/                   # Core modules of the FAHEM system
│   ├── chatbot.py             # Gemini-based chatbot logic
│   ├── rag_colpali.py         # ColPali retrieval and embedding
│   ├── response_router.py     # Routes response modes (text, audio, video)
│   ├── preference_test.py     # Learning style test logic and UI
│   ├── utils.py               # Utility helpers (JSON, file ops, formatting)
│   └── google_tts.py          # Text-to-speech implementation
│
├── lipsync.py                 # Lip-syncing using Wav2Lip
│
├── config.py                  # Configuration (API keys, model names, URLs)
│
├── cache/                     # Cached data and temporary files
│
├── requirements.txt           # Python dependencies
│
└── README.md                  # Project documentation

⚙️ Installation Guide

1. Clone the Repository

git clone https://github.com/Ayaabdelmoneam/FAHEM.AI.git

cd FAHEM.AI

2. Create and Activate a Virtual Environment

python -m venv venv

venv\Scripts\activate   # Windows

or

source venv/bin/activate  # macOS/Linux

3. Install Requirements

pip install -r requirements.txt

4. Run the App

streamlit run app.py