openai-agents-chat-demo
openai agents chat demo. integration custom llm and mcp server and function tool
Documentation
openai-agents-chat-demo
openai agents chat demo. integration custom llm and mcp server and function tool
基于openai-agents框架实现的聊天对话机器人。
功能特点
- 使用OpenAI Agents框架实现智能对话
- 支持自定义工具函数扩展能力
- 提供简洁的Web界面进行交互
- 支持对话历史记录和上下文管理
安装与使用
环境要求
- Python 3.8+
- llm API密钥
安装依赖
pip install -r requirements.txt配置
1. 查看config,进行自定义配置
运行
python app.py访问 http://localhost:8050 开始使用聊天机器人。
项目结构
- `app.py`: Web应用主入口
- `agent.py`: 聊天代理实现
- `config.py`: 配置文件
- `templates/`: HTML模板
- `static/`: 静态资源文件
- `utils/`: 工具函数
Frequently asked questions
What is openai-agents-chat-demo?
openai-agents-chat-demo is openai agents chat demo. integration custom llm and mcp server and function tool
How do I install openai-agents-chat-demo?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is openai-agents-chat-demo open source?
Yes — it is hosted on GitHub at https://github.com/zzqfsy/openai-agents-chat-demo and has 2 stars.
Related MCP tools
🙌 OpenHands: Code Less, Make More for the Model Context Protocol. Enhance AI assistants with powerful integrations. Python-based implementation.
基于大模型搭建的聊天机器人,同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入,可选择ChatGPT/Claude/DeepSeek/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Kimi/LinkAI,能处理文本、语音和图片,访问操作系统和互联网,支持基于自有知识库进行定制企业智能客服。
🔥 MaxKB is an open-source platform for building enterprise-grade agents. MaxKB 是强大易用的开源企业级智能体平台。 for the Model Context Protocol. Enhance AI assistants with po
🤩 Easy-to-use global IM bot platform designed for LLM era / 简单易用的大模型即时通信机器人开发平台 ⚡️ Bots for QQ / QQ频道 / Discord / LINE / WeChat(微信, 企业微信)/ Telegram / 飞书 / 钉...
Agent Framework For Fintech for the Model Context Protocol. Enhance AI assistants with powerful integrations. Python-based implementation.
A middleware to provide an openAI compatible endpoint that can call MCP tools Python-based implementation. Trusted by 800+ developers.
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP