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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