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General Agent Framework by LinXueyuan

Project description

AgentLin

通用 Agent 架构

开始使用

1. 安装

pip install agentlin

本地安装

pip install -e .
# plotly 需要额外下载 chrome 内核用于渲染图表
plotly_get_chrome

2. 创建 .env 文件

复制 .env.example 文件为 .env 并填写所需的环境变量。

环境变量定义了访问 o3 模型的 API 密钥和其他配置。

3. 创建软链接

将公共数据目录 /mnt/aime/datasets/agent/agent_data 软链接到你本地项目的 data 目录下

ln -s /mnt/aime/datasets/agent/agent_data data

4. 运行应用程序

streamlit run chart_o3_toolcall.py

注意:如果你不是在交互式建模的容器里运行的,需要挂一个代理服务将本地请求转发到北美:

cd tool_server
bash run_aime_proxy_server.sh

目录结构

agentlin/
├── core/                     # 核心架构组件   ├── agent_schema.py       # Agent 模式定义   ├── simulator.py          # 仿真器   ├── multimodal.py         # 多模态支持   └── types.py              # 数据类型定义
├── route/                    # 路由和代理管理   ├── client.py             # 客户端   ├── mcp_proxy_*.py        # MCP 代理相关   ├── session_manager.py    # 会话管理   └── *_task_manager.py     # 任务管理器
├── code_interpreter/         # 代码解释器   ├── client.py             # 解释器客户端   ├── jupyter_*.py          # Jupyter 集成   ├── tool_call_display.py  # 工具调用显示   └── ...                   # 其他组件
└── tools/                    # 工具集合
    ├── tool_aime.py          # AIME 工具
    ├── tool_code_interpreter.py # 代码解释器工具
    ├── tool_chart.py         # 图表工具
    └── tool_*.py             # 其他工具

chart_agent/                  # 图表 Agent
table_agent/                  # 表格 Agent
tool_server/                  # 工具服务器
docs/                        # 项目文档
assets/                      # 配置文件
data/                        # 数据文件,软链接到 /mnt/aime/datasets/agent/agent_data

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