ResearchMate is an AI-powered research assistant built for students and researchers to simplify academic paper discovery, understanding, comparison, and analysis.
It combines research paper search, summarization, retrieval-augmented question answering (RAG), literature review generation, paper comparison, and viva question generation in a single application.
- Search research papers by topic
- Search research papers by author
- Search using topic + author together
- Retrieve metadata including:
- Title
- Authors
- Abstract
- Publication year
- Paper link
Upload a research paper PDF and:
- Extract major paper topics automatically
- Summarize selected topics
- Generate full paper summaries
- Produce structured summaries with:
- Summary
- Key bullet points
Ask questions directly from uploaded papers using Retrieval-Augmented Generation.
Examples:
- What methodology is used?
- What are the main results?
- What are the limitations?
- How many pages does this paper have?
Features:
- Context-aware Q&A
- Follow-up questions
- Persistent chat history during session
- Supporting context retrieval
Automatically generate viva or defense questions from uploaded research papers.
Includes:
- Basic conceptual questions
- Methodology questions
- Result interpretation questions
- Critical-thinking questions
Upload two papers and compare:
- Problem statement
- Methodology
- Dataset
- Results
- Limitations
Upload multiple papers and generate:
- Major themes
- Similar findings
- Contradictions
- Research gaps
- Future research directions
- Streamlit
- Python
- Groq API (Llama 3.3 70B)
- Sentence Transformers
- ChromaDB / FAISS
- OpenAlex API
- PyMuPDF
User Input
↓
Streamlit Interface
↓
PDF Processing
↓
Topic Extraction
↓
Embeddings + Vector Store
↓
RAG Question Answering / Summarization / Comparison / Literature Review
↓
Groq LLM Response
Clone the repository:
git clone https://github.com/23f3001369/ResearchMate.git
cd ResearchMateCreate virtual environment:
python -m venv researchenvActivate environment:
Windows:
researchenv\Scripts\activateInstall dependencies:
pip install -r requirements.txtCreate a .env file:
GROQ_API_KEY=your_api_key_herestreamlit run app.py- Understand research papers faster
- Prepare for viva examinations
- Compare related papers
- Generate literature reviews
- Chat with academic papers
- Discover relevant research
- Citation-backed answers
- Related paper recommendations
- Auto slide generation from papers
- Research gap detection
- User authentication and saved chat history
Aman Sagar
MIT License