Demo Link - https://youtu.be/_Ro0p-IMPIA
Neet-AI Agent is an AI-powered study companion designed specifically for NEET aspirants. The tool uses advanced generative AI Agents and vector-based search to assist students by generating high-quality, NEET-standard questions, explanations, and tips. It also processes uploaded study materials and images to create personalized and relevant content.
- Neet-AI Agent is an interactive AI platform for NEET aspirants to study effectively using generative AI.
- NEET aspirants often struggle to find high-quality, exam-relevant questions and detailed explanations. Neet-AI Agent bridges this gap by generating custom questions, explanations, and tips based on user input and uploaded study materials.
- To serve as a one-stop AI-powered solution for generating high-quality NEET questions, explanations, and study guidance, enhancing students' preparation and confidence.
- Programming Languages: Python Libraries/Frameworks: Streamlit (for UI) FAISS (for vector-based search) HuggingFace (for embeddings) LangChain (for document handling and splitting) PyPDFLoader (for processing PDFs) CrewAI (for agent and task management) API Services: Google Generative AI (Gemini Model v1.5) Other Tools: PIL (for image handling) dotenv (for environment variable management)
- Upload Study Materials: Users can upload PDFs, which are processed for context-based question generation.
- Input Flexibility: Text-based input for topic descriptions or concepts. Image-based input for diagram interpretation.
- Question Generation: Generates NEET-standard questions (MCQs, theoretical, or numerical). Provides detailed answers, explanations, and exam tips.
- Subject and Topic-Specific Agents: Physics, Chemistry, and Biology experts generate domain-specific questions.
- ReAct Framework: Employs a structured Reasoning and Acting framework for precise question generation.
All dependencies are listed in the Python environment. Key requirements include:
Python 3.8+ Streamlit
Gemini
FAISS
HuggingFace
CrewAI
dotenv
PyPDFLoader
- Clone the project repository.
- Install required dependencies using pip install -r requirements.txt.
- Set up environment variables using a .env file for API keys.
- Run the Streamlit application using streamlit run app.py.
How to Use:
Upload PDFs or input concepts via text/image. Choose the subject (Physics, Chemistry, Biology). Optionally specify a topic for contextual relevance. Generate NEET questions with detailed answers and tips.
Use Cases:
Preparing for NEET exams with targeted practice. Analyzing specific weak areas through custom question sets. Supplementing self-study with AI-generated guidance.