Having proper tool abstractions is at the core of building data agents. Defining a set of Tools is similar to defining any API interface, with the exception that these Tools are meant for agent rather than human use. We allow users to define both a Tool as well as a ToolSpec containing a series of functions under the hood.

A Tool implements a very generic interface - simply define __call__ and also return some basic metadata (name, description, function schema).

A Tool Spec defines a full API specification of any service that can be converted into a list of Tools.

We offer a few different types of Tools:

  • FunctionTool: A function tool allows users to easily convert any user-defined function into a Tool. It can also auto-infer the function schema.

  • QueryEngineTool: A tool that wraps an existing query engine. Note: since our agent abstractions inherit from BaseQueryEngine, these tools can also wrap other agents.

We offer a rich set of Tools and Tool Specs through LlamaHub 🦙.

Blog Post#

For full details, please check out our detailed blog post.

Usage Pattern#

Our Tool Specs and Tools can be imported from the llama-hub package.

To use with our agent,

from llama_index.agent.openai import OpenAIAgent
from import GmailToolSpec

tool_spec = GmailToolSpec()
agent = OpenAIAgent.from_tools(tool_spec.to_tool_list(), verbose=True)

See our Usage Pattern Guide for more details.

LlamaHub Tools Guide 🛠️#

Check out our guide for a full overview of the Tools/Tool Specs in LlamaHub!