ChatAgent-python 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

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},
}