Tools for AI agents
Project description
ToolFuse
A common protocol for AI agent tools
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ToolFuse provides a common protocol for AI agent tools, use them with your favorite agent framework or model.
Installation
pip install toolfuse
Usage
A simple weather logger tool
from toolfuse import Tool, action, observation
from selenium import webdriver
class WeatherLogger(Tool):
"""A simple weather logger."""
@action
def log(self, message: str) -> None:
"""Logs a message to the log file."""
with open("weather.txt", "a") as file:
file.write("***\n" + message + "\n")
@observation
def weather(self, location: str) -> str:
"""Checks the current weather from the internet using wttr.in."""
weather_api_url = f"http://wttr.in/{location}?format=%l:+%C+%t"
response = requests.get(weather_api_url)
response.raise_for_status()
return response.text
The functions to be made available to the agent as
@action
if they mutate the environment@observation
if they are read only.
Use the tool in a prompt
weather_logger = WeatherLogger()
msg = f"Please select the appropriate action from {weather_logger.json_schema()}"
Create a tool from an existing class
from toolfuse import tool
class Foo:
def echo(self, txt: str) -> str:
return txt
foo_tool = tool(Foo())
Create a tool from an existing function
from toolfuse import tool
def echo(txt: str) -> str:
return txt
echo_tool = tool(echo)
Function Calling
Use a tool with OpenAI function calling
from openai import OpenAI
client = OpenAI()
weatherlogger = WeatherLogger()
schemas = weatherlogger.json_schema()
messages = []
messages.append({"role": "system", "content": "Don't make assumptions about what values to plug into functions. Ask for clarification if a user request is ambiguous."})
messages.append({"role": "user", "content": "What is the weather in Paris?"})
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer " + openai.api_key,
}
json_data = {"model": model, "messages": messages, "tools": schemas}
response = requests.post(
"https://api.openai.com/v1/chat/completions",
headers=headers,
json=json_data,
)
assistant_message = response.json()["choices"][0]["message"]
messages.append(assistant_message)
assistant_message
{
"role": "assistant",
"tool_calls": [
{
"id": "call_RYXaDjxpUCfWmpXU7BZEYVqS",
"type": "function",
"function": {
"name": "weather",
"arguments": "{\n \"location\": \"Paris\"}"
}
}
]
}
Then to use this action
for tool in assistant_message["tool_calls"]:
action = weatherlogger.find_action(tool["function"]["name"])
args = json.loads(tool["function"]["arguments"])
resp = weatherlogger.use(action, **args)
MultiTool
Combine tools with MultiTool
from toolfuse import Tool, MultiTool
class Chat(Tool):
"""A simple chat tool"""
@action
def send_message(self, message: str) -> None:
"""Logs a message to the log file."""
with open("chat.txt", "a") as file:
file.write("***\n" + message + "\n")
multitool = MultiTool(tools=[WeatherLogger(), Chat()])
multitool.json_schema()
Merge one tools actions into another
chat_tool = Chat()
chat_tool.merge(WeatherLogger())
Add an action to a tool
def echo(txt: str) -> str:
return txt
weather_tool = WeatherLogger()
weather_tool.add_action(echo)
Available Tools
:computer: AgentDesk provides AI agents with a full GUI desktop locally or in the cloud.
:wrench: AgentUtils provides some basic utilities for agentic tool use
Roadmap
- Integrate with langchain
- Integrate with babyagi
- Integrate with autogen
- Integrate with llamaindex
Project details
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