VRA - Virtual Research Assistant

Overview

VRA is a simple Streamlit app that searches ArXiv for papers on a topic, summarizes each using a Groq LLM, and lists advantages and disadvantages.

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Demo

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Quick start

1. Python 3.12+ and Git installed
2. Create and activate a virtual environment

python -m venv .venv
.\.venv\Scripts\Activate.ps1

3. Install dependencies

python -m pip install --upgrade pip
pip install -r requirements.txt

4. Configure environment

Create a .env file in the project root with:

GROQ_API_KEY=your_groq_api_key
# Optional: override default model
GROQ_MODEL=llama-3.3-70b-versatile

5. Run the app

python -m streamlit run app.py

Configuration

• Copy .env.example to .env and add your keys
• Supported environment variables:
  • GROQ_API_KEY (required)
  • GROQ_MODEL (optional; default: llama-3.3-70b-versatile)

Features

• Search ArXiv for top papers by topic
• Summarize each paper using Groq LLM
• List advantages and disadvantages per paper

Tech stack

• Python 3.12+
• Streamlit UI
• Groq LLM via autogen
• ArXiv API

Notes

• If you encounter model deprecation errors, set GROQ_MODEL in .env to a supported model.
• If streamlit command fails to launch on Windows, use python -m streamlit run app.py.

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

License

MIT. See LICENSE for details.