OpenAI Toolchain

A Python library for working with OpenAI's function calling API, making it easier to create and manage tools that can be used with OpenAI's chat models.

Features

• 🛠️ Simple function registration with @tool decorator
• 🤖 Automatic tool schema generation
• 🔄 Seamless integration with OpenAI's API
• ⚡ Support for both sync and async operations
• 📚 Clean and intuitive API

Installation

pip install openai-toolchain

Quick Start

1. Define your tools using the @tool decorator:

from openai_toolchain import tool, OpenAIClient

@tool
def get_weather(location: str, unit: str = "celsius") -> str:
    """Get the current weather in a given location.

    Args:
        location: The city to get the weather for
        unit: The unit of temperature (celsius or fahrenheit)
    """
    return f"The weather in {location} is 22 {unit}"

@tool("get_forecast")
def get_forecast_function(location: str, days: int = 1) -> str:
    """Get a weather forecast for a location.

    Args:
        location: The city to get the forecast for
        days: Number of days to forecast (1-5)
    """
    return f"{days}-day forecast for {location}: Sunny"

2. Use the tools with OpenAI:

# Initialize the client with your API key
client = OpenAIClient(api_key="your-api-key")

# Use the client
response = client.chat_with_tools(
    messages=[{"role": "user", "content": "What's the weather in Toronto?"}]
)
print(response)

Documentation

For detailed documentation, including API reference and examples, please visit:

📚 Documentation

Or run the documentation locally:

pip install -e ".[docs]"
mkdocs serve

Contributing

Contributions are welcome! Please see our Contributing Guide for details.

Pre-commit Hooks

This project uses pre-commit to ensure code quality and style consistency. To set it up:

1. Install pre-commit:

   pip install pre-commit
   

2. Install the git hook scripts:

   pre-commit install
   

3. (Optional) Run against all files:

   pre-commit run --all-files
   

The hooks will now run automatically on every commit. To skip the pre-commit checks, use:

git commit --no-verify -m "Your commit message"

License

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

Initialize the client with your API key

client = OpenAIClient(api_key="your-api-key")

Chat with automatic tool calling

response = client.chat_with_tools( messages=[{"role": "user", "content": "What's the weather in Toronto?"}], tools=["get_weather"] # Optional: specify which tools to use )

print(response)

## Features

### 1. Tool Registration

Use the `@tool` decorator to register functions as tools:

```python
from openai_toolchain import tool

@tool
def search_web(query: str) -> str:
    """Search the web for information."""
    return f"Search results for: {query}"

2. Chat with Automatic Tool Calling

The chat_with_tools method handles tool calls automatically:

client = OpenAIClient(api_key="your-api-key")

response = client.chat_with_tools(
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Search for the latest Python news"}
    ],
    tools=["search_web"],
    model="gpt-4"  # Optional: specify a different model
)

3. Accessing Registered Tools

You can access registered tools directly:

from openai_toolchain import tool_registry

# Get all registered tools
tools = tool_registry.get_openai_tools()

# Call a tool directly
result = tool_registry.call_tool("get_weather", {"location": "Paris", "unit": "fahrenheit"})

API Reference

@tool decorator

Register a function as a tool:

from openai_toolchain import tool

# Basic usage
@tool
def my_function(param: str) -> str:
    """Function documentation."""
    return f"Result for {param}"

# With non-AI parameters
@tool(non_ai_params=["db_connection"])
def get_data(query: str, db_connection: Database) -> str:
    """Get data from the database.
    
    Args:
        query: The search query
        db_connection: Database connection (handled by the system, not AI)
    """
    return db_connection.execute(query)

Non-AI Parameters

You can mark certain parameters as non-AI parameters, which means they will be provided by the system rather than the AI. This is useful for passing in dependencies like database connections, configuration, or other runtime objects.

1. Specify non-AI parameters using the non_ai_params argument in the @tool decorator
2. These parameters will be excluded from the AI's schema
3. You must provide these parameters when calling chat_with_tools using the tool_params argument

Example usage with chat_with_tools:

# Initialize client and dependencies
client = OpenAIClient(api_key="your-api-key")
db = DatabaseConnection()

# Call with non-AI parameters
response = client.chat_with_tools(
    messages=[{"role": "user", "content": "Get me user data for John"}],
    tools=["get_data"],
    tool_params={
        "get_data": {
            "db_connection": db
        }
    }
)

tool_registry

The global registry instance with these methods:

• register(func, **kwargs): Register a function as a tool
• get_tool(name): Get a registered tool by name
• call_tool(name, arguments): Call a registered tool by name with arguments
• get_openai_tools(): Get all tools in OpenAI format

Development

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

License

MIT