Installation
AGENT-K requires Python 3.11+ and uses uv for dependency management.
Prerequisites
- Python 3.11+ — Download Python
- uv — Fast Python package manager
- Node.js 20+ — For the frontend (optional)
- pnpm — For frontend dependencies (optional)
Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
pip install uv
Backend Installation
1. Clone the Repository
git clone https://github.com/mikewcasale/agent-k.git
cd agent-k
2. Install Dependencies
cd backend
uv sync
This creates a virtual environment in .venv and installs all dependencies.
3. Activate the Environment
source .venv/bin/activate
.venv\Scripts\activate
4. Configure Environment Variables
Create a .env file in the backend/ directory:
# Kaggle API (required)
KAGGLE_USERNAME=your_username
KAGGLE_KEY=your_api_key
# Model providers (at least one required)
ANTHROPIC_API_KEY=sk-ant-...
OPENROUTER_API_KEY=sk-or-v1-...
OPENAI_API_KEY=sk-...
# Optional: Local LM Studio endpoint
DEVSTRAL_BASE_URL=http://192.168.105.1:1234/v1
# Optional: Observability
LOGFIRE_TOKEN=...
Getting Kaggle Credentials
- Log in to Kaggle
- Go to Account → API → Create New Token
- This downloads
kaggle.jsonwith your credentials
Frontend Installation (Optional)
The frontend provides a real-time mission monitoring dashboard.
cd frontend
pnpm install
Create frontend/.env.local:
NEXT_PUBLIC_API_URL=http://localhost:9000
AUTH_SECRET=your-secret-key
Verify Installation
cd backend
uv run python -c "from agent_k import LycurgusOrchestrator; print('✓ AGENT-K installed')"
Development Installation
For development with linting and testing tools:
uv sync --all-extras
This installs the dev and docs optional dependencies.
Running the Servers
Backend Only
cd backend
source .venv/bin/activate
python -m agent_k.ui.agui
The API server runs at http://localhost:9000.
Frontend Only
cd frontend
pnpm dev
The dashboard runs at http://localhost:3000.
Both Servers
From the project root:
./run.sh
This starts both servers and handles cleanup on exit.
Next Steps
- Quick Start — Run your first mission
- Concepts — Understand the architecture
- Examples — See full examples