Getting Started

This guide will get you running YAAAF in under 5 minutes.

YAAAF is an artifact-first framework. When you send a query, the system plans a railway for artifacts to flow from sources (databases, documents, APIs) through transformation stations (agents) to their final destination (your answer). You will see this in action once you run your first query.

Prerequisites

Before installing YAAAF, ensure you have:

  1. Python 3.11 or higher

    python --version  # Should show 3.11+

  2. Ollama installed and running

    Ollama is the LLM backend that YAAAF uses. Install it from https://ollama.ai/

    # Verify Ollama is running
curl http://localhost:11434/api/tags

  3. A compatible model pulled in Ollama

    # Pull the recommended model
ollama pull qwen2.5:32b

# Or a smaller model for testing
ollama pull qwen2.5:14b

  4. Node.js 18+ and pnpm (for frontend, optional)

    node --version  # Should show 18+
pnpm --version

Installation

Clone and install YAAAF:

# Clone the repository
git clone <repository-url>
cd agents_framework

# Install Python package
pip install -e .

# Install frontend dependencies (optional)
cd frontend
pnpm install
cd ..

Running the Backend

The backend is a FastAPI server that handles all agent execution:

# Start on default port 4000
python -m yaaaf backend

# Or specify a custom port
python -m yaaaf backend 8080

You should see output like:

INFO:     Uvicorn running on http://0.0.0.0:4000
INFO:     Successfully connected to Ollama at http://localhost:11434
INFO:     Model 'qwen2.5:32b' is available

The backend is now ready to accept requests.

Running the Frontend

The frontend is a Next.js application providing a chat interface:

# Start on default port 3000
python -m yaaaf frontend

# Or specify a custom port
python -m yaaaf frontend 3001

Open your browser to http://localhost:3000 to access the chat interface.

Running Both Together

For a complete setup, run both in separate terminals:

Terminal 1 - Backend:

python -m yaaaf backend

Terminal 2 - Frontend:

python -m yaaaf frontend

Then open http://localhost:3000 in your browser.

Your First Query

Once both servers are running, try these example queries in the chat interface:

  1. Simple question (uses AnswererAgent):

    What is the capital of France?

  2. Database query (uses SqlAgent, requires configured database):

    How many records are in the users table?

  3. Web search (uses BraveSearchAgent or DuckDuckGoSearchAgent):

    Search for the latest news about artificial intelligence

  4. Visualization (uses SqlAgent + VisualizationAgent pipeline):

    Show me a chart of sales by month from the database

Watch the chat interface - you will see the system:

  1. Extract your goal

  2. Generate a workflow plan

  3. Execute agents in sequence

  4. Return the final artifact

Verifying the Installation

Test that everything is working:

# Test backend health
curl http://localhost:4000/health

# Run unit tests
python -m unittest discover tests/

Common Issues

Ollama not running:

Connection Error: Cannot connect to Ollama

Solution: Start Ollama with ollama serve or check if it’s running.

Model not found:

Model 'qwen2.5:32b' is not available

Solution: Pull the model with ollama pull qwen2.5:32b

Port already in use:

Address already in use

Solution: Use a different port with python -m yaaaf backend 8080

Frontend build issues:

# Clear cache and reinstall
cd frontend
rm -rf node_modules .next
pnpm install

Next Steps