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智能体开发系列教程

1.事先配置

  • 下载并安装 miniconda (或者其它喜欢的Python环境创建方式):
conda create -n hepai python=3.11
conda activate hepai
  • 安装hepai高能AI智能体框架:
pip install hepai -U
  • 配置OpenWebUI前端:
conda create -n openwebui python=3.11
conda activate openwebui
pip install open-webui 
  • 设置HuggingFace镜像: 将HuggingFace镜像:'HF_ENDPOINT '= 'https://hf-mirror.com'加入到本地的环境。对于Linux系统,可以将其加入到~/.bashrc文件中:
export HF_ENDPOINT=https://hf-mirror.com
  • 启动OpenWebUI前端:
open-webui serve --port 8088
  • 在环境变量中设置大模型相关环境变量,这里以Linux系统为例,以HEPAI平台的大模型为变量值,但是适配任何OpenAI格式的大模型API调用,只需要更改相应的值即可:
export HEPAI_MODEL="hepai/deepseek-r1:671b" # 大模型名称,如"hepai/deepseek-r1:671b"
export HEPAI_API_KEY="Your_API_Key" # 大模型API Key
export HEPAI_API_URL="https://aiapi.ihep.ac.cn/apiv2" # 大模型API URL

智能体后端目录

amap 高德地图MCP工具调用智能体

具体见:amap/assistant_amaps.md

arXiv 科学文献MCP工具调用智能体

具体见:arXiv/assistant_arXiv.md

MCPO与OpenWebUI集成,作为前端大模型的访问工具

具体见:openwebui-mcpos/mcpo.md

About

This repository provides a series of tutorials for developing intelligent agents using the HEPAI framework. It includes setup instructions, example agents leveraging tools like AMap and arXiv, and integration with the OpenWebUI frontend.

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