ChatAgent-py 0.0.1

Pure Python Based Agents for Large Language Models

ChatAgent

中文说明

A Python-based large language model agent framework. The online agents deployed through ChatAgent have provided over a million stable API calls for the internal OpenRL team.

Features

• Supports multimodal large language models
• Supports OpenAI API
• Supports API calls to Qwen on Alibaba Cloud, Zhipu AI's GLM, Microsoft Azure, etc.
• Supports parallel and sequential calls of different agents
• Supports adding an api key for access control
• Supports setting a maximum number of concurrent requests, i.e., the maximum number of requests a model can handle at the same time
• Supports customizing complex agent interaction strategies

Installation

pip install ChatAgent-py

Usage

We provide some examples in the examples directory, which you can run them directly to explore ChatAgent's abilities.

1. Example for Qwen/ZhiPu API to OpenAI API

With just over a dozen lines of code, you can convert the Qwen/ZhiPu API to the OpenAI API. For specific code and test cases, please refer to examples/qwen2openai and examples/glm2openai.

import os
from ChatAgent import serve
from ChatAgent.chat_models.base_chat_model import BaseChatModel
from ChatAgent.agents.dashscope_chat_agent import DashScopeChatAgent
from ChatAgent.protocol.openai_api_protocol import MultimodalityChatCompletionRequest
class QwenMax(BaseChatModel):
    def init_agent(self):
        self.agent = DashScopeChatAgent(model_name='qwen-max',api_key=os.getenv("QWEN_API_KEY"))
    def create_chat_completion(self, request):
        return self.agent.act(request)
@serve.create_chat_completion()
async def implement_completions(request: MultimodalityChatCompletionRequest):
    return QwenMax().create_chat_completion(request)
serve.run(host="0.0.0.0", port=6367)

2. Ensemble with Multiple Agents

We provide an example in examples/multiagent_ensemble where multiple agents perform ensemble to answer user questions.

3. Agent Q&A Based on RAG Query Results

We provide an example in examples/rag of agent Q&A based on RAG query results.

Citation

If you use ChatAgent, please cite us:

@misc{ChatAgent2024,
    title={ChatAgent},
    author={Shiyu Huang},
    publisher = {GitHub},
    howpublished = {\url{https://github.com/OpenRL-Lab/ChatAgent}},
    year={2024},
}