A multi-agent AI research assistant built with React, FastAPI, and Groq LLMs for research paper summarization and related work generation.
- Python 3.10 or later (recommended)
- Node.js 18 or later
- Windows PowerShell (commands below use PowerShell)
From the project root (multi-agent-research-assistant):
python -m venv .venv
.\.venv\Scripts\Activate.ps1If PowerShell blocks activation, run this once and try again:
Set-ExecutionPolicy -Scope CurrentUser RemoteSignedpython -m pip install --upgrade pip
pip install -r requirements.txtCreate a .env file in the project root.
The application looks for environment variables in:
multi-agent-research-assistant/.env- The parent directory (for example,
Gen-AI Project/.env)
Add your Groq API key:
GROQ_API_KEY=YOUR_GROQ_API_KEY| Agent | Purpose | Default Model |
|---|---|---|
| B | Summarization | llama-3.3-70b-versatile |
| C | Related Work | qwen/qwen3-32b |
GROQ_MODEL_SUMMARIZATION=llama-3.3-70b-versatile
GROQ_MODEL_RELATED_WORK=qwen/qwen3-32bFor the latest model IDs, see:
https://console.groq.com/docs/models
From the project root:
python main.pyThe API will be available at:
http://127.0.0.1:8000
Open a second terminal.
cd frontend
npm install
npm run devOpen:
http://localhost:5173
The React development server automatically proxies /api/* requests to the backend running on port 8000.
multi-agent-research-assistant/
│
├── frontend/ # React application
├── agents/ # AI agent implementations
├── uploads/ # Uploaded research papers
├── static/ # Static assets
├── templates/ # HTML templates
├── main.py # FastAPI entry point
├── requirements.txt
├── .env
└── README.md
Run:
Set-ExecutionPolicy -Scope CurrentUser RemoteSignedThen activate the environment again.
pip install -r requirements.txt- Ensure
python main.pyis running. - Verify that port 8000 is not already in use.
- Use Node.js 18+
- Delete the
frontend/node_modulesfolder. - Run:
npm installagain.
- React
- FastAPI
- Groq API
- Python
- JavaScript
- HTML
- CSS