A package for managing AI agents and chatrooms
Project description
AgentFleet
A Python package for managing AI agents and chatrooms that work with LLM-based capabilities.
Installation
pip install agentfleet
Usage
from agentfleet import Agent, Chatroom, create_chatroom
# Example: Create an agent
from langchain_openai import ChatOpenAI
llm = ChatOpenAI()
agent = Agent(name="Assistant", llm=llm, sys_prompt="You are a helpful assistant")
# Example: Set up a chatroom
chatroom = Chatroom(llm=llm, agents=[agent], current_agent=agent)
Using Custom Tools
from agentfleet import create_chatroom
from langchain_core.tools import tool
# Define your custom tool functions
@tool
def lookup_data(query: str) -> str:
"""Look up data from a database."""
# Implementation...
return f"Data for {query}"
@tool
def process_request(request_id: str) -> str:
"""Process a request with the given ID."""
# Implementation...
return f"Processed request {request_id}"
# Create a dictionary mapping tool names to functions
tool_dict = {
'lookup_data': lookup_data,
'process_request': process_request
}
# Create a chatroom with tool dictionary
chatroom_config = {
"states": [...],
"agents": [
{
"name": "support_agent",
"sys_prompt": "You are a support agent...",
"util_tools": ["lookup_data", "process_request"],
"transfer_tools": []
}
],
"initial_agent": "support_agent"
}
chatroom = create_chatroom(chatroom_config, llm, tool_dict=tool_dict)
Features
- Create AI agents with different capabilities
- Build chatrooms with multiple specialized agents
- Transfer conversation control between agents
- Maintain conversation state across interactions
- Pass custom tools to agents via tool dictionary
License
MIT License
Copyright (c) 2025 Wei Zhou
Contributing
Individual Contributor: Wei Zhou
We welcome contributions! Please review our contribution guidelines for details on our code of conduct, and the process for submitting pull requests.
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