Getting started

When setting up agents you can provide tools for them to use. Here you will find ready-to-use tools as well as simple helpers for you to create your own tools.

In order to create a new tool, you have to pick one of the available strategies.

Subclassing BaseTool

class MyTool(BaseTool):
    name: str = "Knowledge base"
    description: str = "A knowledge base with all the requirements for the project."

    def _run(self, question) -> str:
        return (
            tbl.search(embed_func([question])[0]).limit(3).to_pandas()["text"].tolist()
        )

As you can see, all you need to do is to create a new class that inherits from BaseTool, define name and description fields, as well as implement the _run method.

Create tool from a function or lambda

my_tool = Tool(
    name="Knowledge base",
    description="A knowledge base with all the requirements for the project.",
    func=lambda question: tbl.search(embed_func([question])[0])
    .limit(3)
    .to_pandas()["text"]
    .tolist(),
)

Here's it's a bit simpler, as you don't have to subclass. Simply create a Tool object with the three required fields and you are good to go.

Use the tool decorator.

@tool("Knowledge base")
def my_tool(question: str) -> str:
    """A knowledge base with all the requirements for the project."""
    return tbl.search(embed_func([question])[0]).limit(3).to_pandas()["text"].tolist()

By using the decorator you can easily wrap simple functions as tools. If you don't provide a name, the function name is going to be used. However, the docstring is required.

If you are using a linter you may see issues when passing your decorated tool in tools parameters that expect a list of BaseTool. If that's the case, you can use the as_tool helper.

Contribution

This repo is open-source and we welcome contributions. If you're looking to contribute, please:

• Fork the repository.
• Create a new branch for your feature.
• Add your feature or improvement.
• Send a pull request.
• We appreciate your input!

Installing Dependencies

poetry install

Virtual Env

poetry shell

Pre-commit hooks

pre-commit install

Running Tests

poetry run pytest

Running static type checks

poetry run pyright

Packaging

poetry build

Installing Locally

pip install dist/*.tar.gz