Metadata-Version: 2.4
Name: toolregistry
Version: 0.9.0
Summary: ToolRegistry: A Protocol-Agnostic Tool Management Library for Function-Calling LLMs (OpenAI, Anthropic, Gemini, LangChain, MCP)
Author-email: Oaklight <oaklight@gmx.com>
License-Expression: MIT
Project-URL: Documentation, https://toolregistry.readthedocs.io
Project-URL: Repository, https://github.com/Oaklight/ToolRegistry
Project-URL: Issues, https://github.com/Oaklight/ToolRegistry/issues
Keywords: llm,tool-calling,function-calling,ai-agents,openai,anthropic,gemini,mcp,openapi,langchain,tool-use,agentic-ai
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pydantic<3.0.0,>=2.7.2
Requires-Dist: cloudpickle>=3.0.0
Requires-Dist: llm-rosetta<0.6.0,>=0.5.1
Provides-Extra: mcp
Requires-Dist: mcp<2.0.0,>=1.0.0; extra == "mcp"
Requires-Dist: httpx>=0.28.1; extra == "mcp"
Provides-Extra: openapi
Provides-Extra: langchain
Requires-Dist: langchain-core<0.4,>=0.3; extra == "langchain"
Requires-Dist: langchain-community<0.4,>=0.3; extra == "langchain"
Provides-Extra: dev
Requires-Dist: python-dotenv>=1.0.1; extra == "dev"
Requires-Dist: openai>=1.79.0; extra == "dev"
Requires-Dist: fastapi>=0.115.12; extra == "dev"
Requires-Dist: ty>=0.0.21; extra == "dev"
Requires-Dist: ruff>=0.1.0; extra == "dev"
Requires-Dist: build>=1.2.2.post1; extra == "dev"
Requires-Dist: twine>=6.1.0; extra == "dev"
Requires-Dist: deprecated>=1.2.18; extra == "dev"
Provides-Extra: test
Requires-Dist: pytest>=7.0.0; extra == "test"
Requires-Dist: pytest-cov>=4.0.0; extra == "test"
Requires-Dist: pytest-asyncio>=0.21.0; extra == "test"
Requires-Dist: pytest-mock>=3.10.0; extra == "test"
Requires-Dist: coverage>=7.0.0; extra == "test"
Dynamic: license-file

# ToolRegistry

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[English Version](README_en.md) | [中文版](README_zh.md)

A Python library for managing and executing tools in a structured way.

## Full Documentation

Full documentation is available at [https://toolregistry.readthedocs.io](https://toolregistry.readthedocs.io)

## 📦 Related Package: [toolregistry-hub](https://github.com/Oaklight/toolregistry-hub/)

> **Important Notice**: As of version 0.4.14, the hub tools have been spun off into a separate package [`toolregistry-hub`](https://pypi.org/project/toolregistry-hub/). This standalone package provides a collection of ready-to-use tools for LLM function calling and can be used independently or alongside ToolRegistry. This spinoff enables separate development, distribution, and versioning of the hub tools, making it easier to maintain and update them without affecting the core ToolRegistry functionality.

- **Install**: [`pip install toolregistry-hub`](https://pypi.org/project/toolregistry-hub/)
- **PyPI**: [toolregistry-hub on PyPI](https://pypi.org/project/toolregistry-hub/)
- **GitHub**: [toolregistry-hub on GitHub](https://github.com/Oaklight/toolregistry-hub/)

## Features

- Tool registration and management
- JSON Schema generation for tool parameters
- Tool execution and result handling
- Support for both synchronous and asynchronous tools
- Support native Python functions and class methods as tools
- Support multiple [MCP](https://toolregistry.readthedocs.io/en/stable/usage/integrations/mcp.html) transport methods: STDIO, streamable HTTP, SSE, WebSocket, FastMCP instance, etc.
- Support [OpenAPI]https://toolregistry.readthedocs.io/en/stable/usage/integrations/openapi.html) tools

## Installation

### Basic Installation

Install the core package (requires **Python >= 3.10**):

```bash
pip install toolregistry
```

### Installing with Extra Support Modules

Extra modules can be installed by specifying extras in brackets. For example, to install specific extra supports:

```bash
pip install toolregistry[mcp,openapi]
```

Below is a table summarizing available extra modules:

| Extra Module | Example Command                     |
| ------------ | ----------------------------------- |
| mcp          | pip install toolregistry[mcp]       |
| openapi      | pip install toolregistry[openapi]   |
| langchain    | pip install toolregistry[langchain] |

### Hub Tools Installation

The hub tools are available as a separate package `toolregistry-hub`:

```bash
pip install toolregistry-hub
```

This allows you to use hub tools independently or alongside ToolRegistry.

## Examples

### OpenAI Implementation

The [openai_tool_usage_example.py](examples/openai_tool_usage_example.py) shows how to integrate ToolRegistry with OpenAI's API.

### Cicada Implementation

The [cicada_tool_usage_example.py](examples/cicada_tool_usage_example.py) demonstrates how to use ToolRegistry with the Cicada MultiModalModel.

## Basic Tool Invocation

This section demonstrates how to invoke a basic tool. Example:

```python
from toolregistry import ToolRegistry

registry = ToolRegistry()

@registry.register
def add(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b

available_tools = registry.list_tools()

print(available_tools) # ['add']

add_func = registry.get_callable('add')
print(type(add_func)) # <class 'function'>
add_result = add_func(1, 2)
print(add_result) # 3

add_func = registry['add']
print(type(add_func)) # <class 'function'>
add_result = add_func(4, 5)
print(add_result) # 9
```

For more usage examples, please refer to [Documentation - Usage](https://toolregistry.readthedocs.io/en/stable/usage/basics.html)

## MCP Integration

The ToolRegistry provides first-class support for MCP (Model Context Protocol) tools with multiple transport options:

```python
# transport can be a URL string, script path, transport instance, or MCP instance.
transport = "https://mcphub.url/mcp"  # Streamable HTTP MCP
transport = "http://localhost:8000/sse/test_group"  # Legacy HTTP+SSE
transport = "examples/mcp_related/mcp_servers/math_server.py"  # Local path
transport = {
    "mcpServers": {
        "make_mcp": {
            "command": f"{Path.home()}/mambaforge/envs/toolregistry_dev/bin/python",
            "args": [
                f"{Path.home()}/projects/toolregistry/examples/mcp_related/mcp_servers/math_server.py"
            ],
            "env": {},
        }
    }
}  # MCP configuration dictionary example
transport = FastMCP(name="MyFastMCP")  # FastMCP instance
transport = StreamableHttpTransport(url="https://mcphub.example.com/mcp", headers={"Authorization": "Bearer token"})  # Transport instance with custom headers

registry.register_from_mcp(transport)

# Get all tools' JSON, including MCP tools
tools_json = registry.get_schemas()
```

## OpenAPI Integration

The `register_from_openapi` method now accepts two parameters:

- `client_config`: a `toolregistry.integrations.openapi.HttpxClientConfig` object that configures the HTTP client used to interact with the API. You can configure the headers, authorization, timeout, and other settings. Allowing greater flexibility than the previous version.
- `openapi_spec`: The OpenAPI specification as `Dict[str, Any]`, loaded with a function like `load_openapi_spec` or `load_openapi_spec_async`. These functions accept a file path or a URL to the OpenAPI specification or a URL to the base api and return the parsed OpenAPI specification as a dictionary.

Example:

```python
from toolregistry.integrations.openapi import HttpxClientConfig, load_openapi_spec

client_config = HttpxClientConfig(base_url="http://localhost:8000")
openapi_spec = load_openapi_spec("./openapi_spec.json")
openapi_spec = load_openapi_spec("http://localhost:8000")
openapi_spec = load_openapi_spec("http://localhost:8000/openapi.json")

registry.register_from_openapi(
    client_config=client_config,
    openapi_spec=openapi_spec
)

# Get all tools' JSON, including OpenAPI tools
tools_json = registry.get_schemas()
```

### Note

When using the functions `load_openapi_spec` or `load_openapi_spec_async`, the following behaviors apply:

1. **Base URL provided**: If you specify only a base URL (e.g., `http://localhost:8000`), the loader will attempt "best effort" auto-discovery to locate the OpenAPI specification file. It checks endpoints such as `http://<base_url>/openapi.json` or `http://<base_url>/swagger.json`. If auto-discovery fails, ensure the base URL is accurate and the specification is accessible.

2. **File path provided**: If you provide a file path (e.g., `./openapi_spec.json`), the function will load the OpenAPI specification directly from the file. Unlike simple direct load, the functionality includes unwinding `$ref` blocks commonly found in OpenAPI specifications. This ensures that any schema references are fully resolved within the returned dictionary.

## LangChain Integration

The LangChain integration module allows ToolRegistry to register and invoke LangChain tools seamlessly, supporting both synchronous and asynchronous calls.

```python
from langchain_community.tools import ArxivQueryRun, PubmedQueryRun
from toolregistry import ToolRegistry

registry = ToolRegistry()

registry.register_from_langchain([ArxivQueryRun(), PubmedQueryRun()])
tools_json = registry.get_schemas()
```

## Registering Class Tools

Class tools are registered to ToolRegistry using the `register_from_class` method. This allows developers to extend the functionality of ToolRegistry by creating custom tool classes with reusable methods.

Example:

```python
from toolregistry import ToolRegistry

class StaticExample:
    @staticmethod
    def greet(name: str) -> str:
        return f"Hello, {name}!"

class InstanceExample:
    def __init__(self, name: str):
        self.name = name

    def greet(self, name: str) -> str:
        return f"Hello, {name}! I'm {self.name}."

registry = ToolRegistry()
registry.register_from_class(StaticExample, namespace=True)
print(registry.list_tools())  # ['static_example.greet']
print(registry["static_example.greet"]("Alice"))  # Hello, Alice!

registry = ToolRegistry()
registry.register_from_class(InstanceExample("Bob"), namespace=True)
print(registry.list_tools())  # ['instance_example.greet']
print(registry["instance_example.greet"]("Alice"))  # Hello, Alice! I'm Bob.
```

### Hub Tools

[Available Tools](src/toolregistry/hub/)

Hub tools encapsulate commonly used functionalities as methods in classes. Examples of available hub tools include:

- **Calculator**: Basic arithmetic, scientific operations, statistical functions, financial calculations, and more.
- **DateTime**: Comprehensive datetime utilities with timezone support, including current time retrieval and timezone conversions.
- **FileOps**: File manipulation like diff generation, patching, verification, merging, and splitting.
- **Filesystem**: Comprehensive file system operations such as directory listing, file read/write, path normalization, and querying file attributes.
- **ThinkTool**: Simple reasoning and brainstorming utility for structured thought processes.
- **UnitConverter**: Extensive unit conversions such as temperature, length, weight, volume, etc.
- **WebSearch**: Web search functionality supporting multiple engines like Bing, Google and SearXNG, etc.
- **Fetch**: Fetching content from URL.

To register hub tools:

```python
from toolregistry import ToolRegistry
from toolregistry.hub import Calculator

registry = ToolRegistry()
registry.register_from_class(Calculator, namespace=True)

# Get available tools list
print(registry.list_tools())
# ['calculator-list_allowed_fns', 'calculator-help', 'calculator-evaluate']
```

### Community Contribution

We welcome community contributions of new tool classes to ToolRegistry! If you have designs or implementations for other commonly used tools, feel free to submit them through a Pull Request on the [GitHub Repository](https://github.com/yourrepository/toolregistry). Your contributions will help expand the diversity and usability of the tools.

## Citation

If you use ToolRegistry in your research or project, please consider cite it as:

```bibtex
@software{toolregistry2025,
  title={ToolRegistry: A Protocol-Agnostic Tool Management Library for OpenAI-Compatible LLM Applications},
  author={Peng Ding},
  year={2025},
  url={https://github.com/Oaklight/ToolRegistry},
  note={A Python library for unified tool registration, execution, and management across multiple protocols in OpenAI-compatible LLM applications}
}

@article{ding2025toolregistry,
  title={ToolRegistry: A Protocol-Agnostic Tool Management Library for Function-Calling LLMs},
  author={Ding, Peng},
  journal={arXiv preprint arXiv:2507.10593},
  year={2025}
}
```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
