by zhuqn1021 · Agent Tool · ★ 114
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Agent Template 项目指南 一个面向生产原型的 Python AI Agent 项目模板，内置多模型切换、Function Calling 工具调用、RAG 多路召回、对话记忆、LangGraph 编排示例，以及完整执行过程 Trace 复盘能力。 能力概览 多模型抽象：统一封装 DashScope 和 OpenAI 兼容接口，支持 DeepSeek、GLM、Moonshot、Ollama 等。 Agent 分层：提供纯对话 和支持 ReAct 工具循环的 。 工具系统：基于 OpenAI Function Calling schema，支持工具注册、自动执行、结果回传。 RAG 增强：支持 Qdrant 向量检索、关键词召回、多路召回、RRF 融合排序。 记忆系统：支持本地内存和 Redis 滑动窗口记忆。 LangGraph 示例：展示如何把检索、规划、工具调用、回答生成编排成显式图流程。 Trace 复盘：记录一次请求中的 RAG、Memory、LLM、Tool 调用全过程，便于排查和评估。 目录结构 text agenttemplate/ ├── agents/ # Agent 核心层 │ ├── base.py # AgentBase + AgentResponse │ ├── chatagent.py # 对话型 Agent │ └── taskagent.py # ReAct 工具调用 Agent │ ├── config/ # 配置管理 │ ├── loader.py # YAML + ENV 配置加载 │ ├── settings.py # dataclass 配置结构 │ ├── settings.yaml # 基础配置 │ └── settings.development.yaml # 开发环境覆盖配置 │ ├── examples/ # 示例代码 │ ├── chatexample.py # 基础对话 │ ├── toolagentexample.py # 工具调用 │ ├── modelswitchexample.py # 模型热切换 │ ├── ragexample.py # RAG 多路召回问答 │ ├── multiagentexample.py # 多 Agent 协作 │ └── langgraphorchestrationexample.py # LangGraph 编排 │ ├── llm/ # LLM 多模型抽象层 │ ├── base.py # ChatMessage / LLMResponse / L
| Stars | 114 |
| Forks | 3 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 64.3560008467361/100 |
| Last Updated | 2026-04-24 |
| Created | 2026-04-17 |
| Platforms | python |
| Est. Tokens | ~9k |
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Agent-template is 一个开箱即用的现代化的 AI Agent 项目模板，采用分层架构设计，包含LLM 多模型抽象层、Tools 工具链系统、Skills 技能系统、Agent 核心层 、RAG 检索增强多路召回、Memory 记忆系统、 配置系统、以及多Agent编排示例等企业级功能。. It is categorized as a Agent Tool with 114 GitHub stars.
Agent-template is primarily written in Python.
You can find installation instructions and usage details in the Agent-template GitHub repository at github.com/zhuqn1021/Agent-template. The project has 114 stars and 3 forks, indicating an active community.
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