Upload any research paper and instantly get summaries, Q&A, interview prep, implementation roadmaps and critical analysis — powered by RAG + Groq LLaMA 3.1.
| Feature | Description |
|---|---|
| 📄 Summarization | Concise summary of any research paper |
| 🧠 Semantic Q&A | Ask any question, get contextual answers |
| 🎯 Interview Prep | Auto-generated interview questions + answers |
| 🛠️ Implementation Roadmap | Step-by-step plan to implement the paper |
| 🔍 Critical Analysis | Strengths, weaknesses and future directions |
PDF Upload → PyMuPDF Parsing → Chunking (500 words, 50 overlap)
→ SentenceTransformer Embeddings → FAISS Vector Store
→ Semantic Retrieval → Groq LLaMA 3.1 → Response
| Component | Technology |
|---|---|
| Vector Store | FAISS |
| Embeddings | SentenceTransformers (all-MiniLM-L6-v2) |
| LLM | Groq LLaMA 3.1 (8B Instant) |
| RAG Framework | LangChain |
| PDF Parsing | PyMuPDF |
| UI | Gradio |
# Install dependencies
pip install faiss-cpu sentence-transformers groq langchain gradio pymupdf
# Set your Groq API key (free at console.groq.com)
export GROQ_API_KEY="your_key_here"
# Run
python app.pyOr run directly in Google Colab using the badge above.
groq
faiss-cpu
sentence-transformers
pymupdf
langchain
langchain-community
gradio
- 🤗 Live Demo: huggingface.co/spaces/Vi-bha/PaperLens
- 🧬 ResearchMind: huggingface.co/spaces/Vi-bha/ResearchMind
- 🔬 MedLens: huggingface.co/spaces/Vi-bha/MedLens
Built by Vibhavari Tummewar | MTech Advanced Computing, MANIT Bhopal