ScholarRAG Elite is a professional, market-ready RAG (Retrieval-Augmented Generation) application designed for students and researchers. It allows users to upload PDF notes and interact with them using a state-of-the-art AI tutor that can explain complex topics and generate Mermaid.js mind maps.
- Interactive RGB UI: A sleek dark-mode interface with Yellow-Red RGB interactive glow effects.
- Pinned Header: All controls (Language, Sync, Clear, Upload) are locked in a professional gray-white header line.
- Multi-Format Tutoring: Get explanations in English, Hindi, or Hinglish with automated mind-map generation.
- Responsive Design: Fully optimized for both Desktop and Mobile views with zero gaps.
- Social Integration: One-click access to developer profiles (LinkedIn, GitHub, Substack).
- Core Framework: LangChain (for RAG orchestration).
- AI Model:
llama-3.3-70b-versatilevia Groq API (Ultra-fast response). - Embeddings:
sentence-transformers/all-MiniLM-L6-v2(HuggingFace). - Vector Store: FAISS (for efficient local semantic search).
- Frontend: Streamlit (with custom CSS for ChatGPT-like experience).
- Python 3.10+
- Groq API Key
- Clone the repository:
git clone [https://github.com/ankitmodanwall/ScholarRAG.git](https://github.com/ankitmodanwall/ScholarRAG.git) cd ScholarRAG