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Development Workflow

This guide explains the complete workflow for developing AI agents using Agent-as-Code.

Prerequisites

  • Go 1.21 or later
  • Python 3.8 or later
  • Docker (optional, for container-based deployment)
  • Git

Project Structure

A typical agent project has the following structure:

my-agent/
├── agent.yaml           # Agent configuration
├── src/
│   ├── main.py         # Main agent code
│   ├── capabilities/   # Agent capabilities
│   ├── models/        # Model integrations
│   └── utils/         # Utility functions
├── tests/             # Test files
├── requirements.txt   # Python dependencies
└── README.md         # Project documentation

Development Steps

1. Initialize Project

# Create new agent from template
agent init my-agent --template chatbot

# Or create custom agent
agent init my-agent --runtime python

2. Configure Agent

Edit agent.yaml:

apiVersion: agent.dev/v1
kind: Agent
metadata:
  name: my-agent
  version: 1.0.0
spec:
  runtime: python:3.11
  model:
    provider: openai
    name: gpt-4
  capabilities:
    - text-generation
    - chat

3. Implement Agent Logic

Example src/main.py:

from agent_as_code import Agent

class MyAgent(Agent):
    async def process(self, input: str) -> str:
        # Implement agent logic
        response = await self.model.generate(input)
        return response

if __name__ == "__main__":
    agent = MyAgent()
    agent.run()

4. Local Development

# Build agent
agent build -t my-agent:dev .

# Run locally
agent run my-agent:dev

# View logs
agent logs my-agent:dev

# Test agent
agent test my-agent:dev

5. Testing

Create tests in tests/ directory:

# tests/test_agent.py
from my_agent import MyAgent

async def test_process():
    agent = MyAgent()
    response = await agent.process("Hello")
    assert response is not None

Run tests:

agent test my-agent:dev

6. Debugging

# Run with debug logging
agent run my-agent:dev --log-level debug

# Inspect agent
agent inspect my-agent:dev

# Check health
agent health my-agent:dev

7. Version Control

# Initialize git
git init

# Add files
git add agent.yaml src/ tests/

# Commit
git commit -m "Initial agent implementation"

8. Deployment

# Build production version
agent build -t my-agent:1.0.0 .

# Push to registry
agent push my-agent:1.0.0

# Deploy
agent deploy my-agent:1.0.0

Development Best Practices

1. Configuration Management

  • Use version control for agent.yaml
  • Keep secrets in environment variables
  • Document configuration options

2. Code Organization

  • Follow template structure
  • Separate concerns
  • Use type hints
  • Add documentation

3. Testing

  • Write unit tests
  • Test capabilities separately
  • Use mock models for testing
  • Test error handling

4. Error Handling

from agent_as_code import Agent, AgentError

class MyAgent(Agent):
    async def process(self, input: str) -> str:
        try:
            response = await self.model.generate(input)
            return response
        except Exception as e:
            raise AgentError(f"Processing failed: {e}")

5. Logging

import logging
from agent_as_code import Agent

class MyAgent(Agent):
    def __init__(self):
        self.logger = logging.getLogger(__name__)
        
    async def process(self, input: str) -> str:
        self.logger.info(f"Processing input: {input}")
        response = await self.model.generate(input)
        self.logger.info(f"Generated response: {response}")
        return response

6. Resource Management

  • Set appropriate resource limits
  • Monitor memory usage
  • Handle cleanup properly

7. Security

  • Validate inputs
  • Sanitize outputs
  • Use secure dependencies
  • Keep dependencies updated

Common Development Tasks

Adding New Capabilities

  1. Create capability module:
# src/capabilities/summarization.py
class SummarizationCapability:
    async def summarize(self, text: str) -> str:
        # Implement summarization
        pass
  1. Update agent.yaml:
spec:
  capabilities:
    - summarization

Integrating New Models

  1. Add model configuration:
spec:
  model:
    provider: anthropic
    name: claude-3
  1. Implement model integration:
from agent_as_code.models import ModelIntegration

class ClaudeIntegration(ModelIntegration):
    async def generate(self, prompt: str) -> str:
        # Implement Claude integration
        pass

Adding Health Checks

spec:
  healthCheck:
    command: ["curl", "http://localhost:8080/health"]
    interval: 30s
    timeout: 10s
    retries: 3

Troubleshooting

Common Issues

  1. Build Failures
# Check build logs
agent build -t my-agent:dev . --verbose
  1. Runtime Errors
# Check agent logs
agent logs my-agent:dev
  1. Model Issues
# Test model connection
agent test my-agent:dev --test-model

See Also