An AI-powered research paper assistant that allows users to upload PDF documents, summarize content, ask questions, and understand concepts using Retrieval-Augmented Generation (RAG) with Large Language Models (LLMs).
The application extracts information from research papers, retrieves relevant sections based on user queries, and generates context-aware responses using Llama 3 through Ollama.
- 📂 Upload research papers in PDF format
- 📑 Extract text from PDF documents
- ✂️ Split documents into smaller chunks for efficient processing
- 🔍 Retrieve relevant content based on user queries
- 🤖 Generate answers using Llama 3 LLM
- 📝 Summarize research papers into simple explanations
- 🧠 Explain complex concepts in an understandable way
- 💬 Interactive Streamlit-based user interface
- Python
- Large Language Model (LLM)
- Retrieval-Augmented Generation (RAG)
- Ollama
- Llama 3
- Prompt Engineering
- Streamlit
- PyPDF
- NumPy
- Pandas
- PDF Upload
- ↓
- Text Extraction (PyPDF)
- ↓
- Text Chunking
- ↓
- Relevant Chunk Retrieval
- ↓
- Context + User Query Prompt
- ↓
- Llama 3 Response
- ↓
- Answer / Summary