asktheapi-team-builder 0.2.1

A high-level library for building and managing teams of AutoGen agents

AskTheApi Team Builder

A high-level Python library for easily building and managing autonomous agents networks that solve complex tasks using APIs defined with OpenAPI standard format. This package provides a clean, type-safe interface for creating, configuring, and running teams of agents that can work together to solve complex tasks.

Features

• 🚀 Easy creation of agent networks with custom tools and capabilities based on openAPI specification
• 🤝 Team building with automatic coordination through a planning agent
• 📡 Support for streaming agent interactions
• 🔧 Built-in HTTP client for tool implementation
• ✨ Pydantic models for type safety and validation
• 🎯 Clean, intuitive API design

Installation

pip install asktheapi-team-builder

Quick Start

Here's how to use the package:

1. Create agents from OpenAPI spec

from asktheapi_team_builder import TeamBuilder, Agent, Tool, Message, APISpecHandler
from typing import List
async def create_agents_from_spec():
    # Initialize handlers
    api_spec_handler = APISpecHandler(llm_service)  # llm_service is your LLM provider
    
    # Download and parse OpenAPI spec
    spec_content = await api_spec_handler.download_url_spec("https://api.example.com/openapi.json")
    
    # Classify endpoints into logical groups
    classification_result = await api_spec_handler.classify_spec(
        spec_content
    )
    
    # Generate agents for each group
    agents = []
    for group_spec in classification_result.specs:
        agent_result = await api_spec_handler.generate_agent_for_group(
            group_spec,
            spec_content
        )
        agents.append(agent_result)
    
    return agents

# 3. Build and run a team
async def run_agent_team(agents: List[Agent], query: str):
    # Initialize team builder
    team_builder = TeamBuilder(
        model="gpt-4",
        model_config={"temperature": 0.7}
    )
    
    # Build the team
    team = await team_builder.build_team(agents)
    
    # Create messages
    messages = [
        Message(
            role="user",
            content=query
        )
    ]
    
    # Run the team with streaming
    async for event in team_builder.run_team(team, messages, stream=True):
        if isinstance(event, ChatMessage):
            print(f"{event.source}: {event.content}")
        
# Example usage
async def main():
    # Create agents from spec
    api_agents = await create_agents_from_spec()
    
    # Combine with manual agents
    all_agents = [weather_agent] + api_agents
    
    # Run the team
    await run_agent_team(
        all_agents,
        "What's the weather like in London and how might it affect local businesses?"
    )

Custom Headers and Configuration

You can configure the team builder with custom headers and model settings:

team_builder = TeamBuilder(
    model="gpt-4",
    model_config={
        "temperature": 0.7,
        "default_headers": {
            "Authorization": "Bearer your-token",
            "Custom-Header": "custom-value"
        }
    }
)

# Run team with extra headers for specific requests
team = await team_builder.build_team(agents)
result = await team_builder.run_team(
    team,
    messages,
    extra_headers={"Request-ID": "123"}
)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Setup

# Clone the repository
git clone https://github.com/alexalbala/asktheapi-team-builder.git
cd asktheapi-team-builder

# Install dependencies
pip install -e ".[dev]"

# Run tests
pytest

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built on top of Microsoft's AutoGen
• Inspired by the need for a higher-level interface for agent team management