diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/.env.example b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/.env.example
new file mode 100644
index 00000000..8b888822
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/.env.example
@@ -0,0 +1,13 @@
+LLM_MODEL_ID=""
+LLM_API_KEY=""
+LLM_BASE_URL=""
+
+# 超时时间（可选，默认60秒）
+LLM_TIMEOUT=""
+
+# 服务器配置
+HOST=""
+PORT=""
+
+# CORS配置
+CORS_ORIGINS=""
\ No newline at end of file
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/README.md b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/README.md
new file mode 100644
index 00000000..85311b4b
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/README.md
@@ -0,0 +1,183 @@
+# FitnessPlannerAgent - 健身训练规划助手
+
+> 基于HelloAgents框架的健身规划助手
+
+## 📝 项目简介
+
+FitnessPlannerAgent是一个健身训练规划助手,能够根据用户基本信息自动规划每周期的健身计划。
+
+### 核心功能
+- ✅ 智能建议：基于LLM和用户提供的基本信息进行分析和规划训练。
+
+
+## 🛠️ 技术栈
+
+- HelloAgents框架（SimpleAgent）
+- QWEN API（智能分析）
+
+## 🚀 快速开始
+
+### 安装依赖
+
+```bash
+pip install -r requirements.txt
+```
+
+### 配置LLM参数
+
+**方式1: 使用.env文件(推荐)**
+
+```bash
+# 复制示例文件
+cp .env.example .env
+
+# 编辑.env文件,填入你的配置
+# LLM_MODEL_ID=Qwen/Qwen2.5-72B-Instruct
+# LLM_API_KEY=your_api_key_here
+# LLM_BASE_URL=https://api-inference.modelscope.cn/v1/
+```
+
+### 运行项目
+
+在终端进入当项目所在的EugeneChanQAQ-smart_fitness_planner目录激活虚拟环境。
+
+```bash
+venv_fit/Scripts/activate
+# 激活虚拟环境
+python -m uvicorn app.api.main:app --reload --host 0.0.0.0 --port 8000
+# 启动项目
+```
+
+## 📖 使用示例
+
+### 完整功能
+
+1. 用户输入自己的基本信息（身高、体重、年龄）
+2. 系统生成周期性的健身规划
+
+## 🎯 项目亮点
+
+- **智能化**：利用LLM根据个人身体基本数据,提供专业的健身训练建议
+- **可扩展**：易于添加新的工具
+
+## 📂 项目结构
+
+```
+EugeneChanQAQ-smart_fitness_planner/
+│
+├── app/ # 🍱 FastAPI 服务主体
+│ ├── config.py # 配置文件（应用名、版本、路径等）
+│ ├── api/ # FastAPI 相关
+│ │ ├── routers # 路由
+│ │ │ └──train.py # 路由
+│ │ ├── main.py # FastAPI 主入口
+│ ├── agents/ # 核心 Agent 逻辑模块
+│ │ ├── train_planner.py #
+│ │ ├── state_manager.py # 暂空
+│ │ ├── \_\_init__.py
+│ ├── models/ # Pydantic 请求模型
+│ │ └── schemas.py # 数据模型
+│ └── services/
+│ └── llm_service.py #
+│
+├── tests/
+│ └── test_agent.py # 暂空
+│
+├── requirements.txt # Python依赖
+└── README.md # 项目说明
+```
+
+## 🔧 技术实现
+
+
+### 智能体设计
+
+使用HelloAgents的SimpleAgent。
+
+## 📊 示例输出
+
+```markdown
+============================================================
+🚀 HelloAgents健身规划助手 v1.0.0
+============================================================
+应用名称: HelloAgents健身规划助手
+版本: 1.0.0
+服务器: 0.0.0.0:8000
+LLM API Key: 已配置
+LLM Base URL: https://dashscope.aliyuncs.com/compatible-mode/v1
+LLM Model: qwen-max
+日志级别: INFO
+
+ ✔验证通过
+
+============================================================
+📚 API文档: http://localhost:8000/docs
+📖 ReDoc文档: http://localhost:8000/redoc
+============================================================
+
+INFO: Application startup complete.
+INFO: 127.0.0.1:57008 - "GET / HTTP/1.1" 307 Temporary Redirect
+INFO: 127.0.0.1:57008 - "GET /train/ HTTP/1.1" 200 OK
+INFO: 127.0.0.1:57008 - "GET /favicon.ico HTTP/1.1" 404 Not Found
+
+============================================================
+📥 收到训练计划制定请求:
+ 身高: 183
+ 体重: 76
+ 年龄: 21
+============================================================
+
+获取Agent系统
+开始初始化智能体健身规划系统
+✅ LLM服务初始化成功
+ 提供商: qwen
+ 模型: qwen-max
+创建健身规划Agent
+
+============================================================
+🚀 开始智能体规划训练...
+身高：183
+体重：76
+年龄：21
+
+============================================================
+制定训练计划中...
+训练规划结果: [
+ {"day":1,"action":"深蹲","muscle":"腿部","group_num":3,"amount":12},
+ {"day":1,"action":"卧推","muscle":"胸部","group_num":3,"amount":10},
+ {"day":1,"action":"引体向上","muscle":"背部","group_num":3,"amount":8},
+ {"day":2,"action":"休息"},
+ {"day":3,"action":"硬拉","muscle":"背部","group_num":3,"amount":10},
+ ...
+
+============================================================
+✅ 训练计划生成完成!
+============================================================
+
+✅ 训练计划生成成功,准备返回响应
+
+INFO: 127.0.0.1:61389 - "POST /train/plan HTTP/1.1" 200 OK
+```
+
+## 🚧 未来改进
+
+- [ ] 提供更多的基础信息以及特殊需求填写（性别、健身目的等）
+- [ ] 添加食谱规划Agent（帮助提高健身效率）
+- [ ] 调用API查找附近的健身餐食
+- [ ] 提供周期性反馈，根据用户的最新数据更改健身策略和方案
+- [ ] 生成用户身体数据报告
+
+## 👤 作者
+
+- GitHub: [@EugeneChanQAQ](https://github.com/EugeneChanQAQ)
+- 项目链接：[FitnessPlannerAgent](https://github.com/datawhalechina/Hello-Agents/tree/main/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner)
+
+## 🙏 致谢
+
+感谢Datawhale社区和Hello-Agents项目！
+
+## 📄 许可证
+
+所有共创项目遵循CC BY-NC-SA 4.0 License，欢迎学习和共创。
+
+
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/__init__.py b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/__init__.py
new file mode 100644
index 00000000..2d66a7db
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/__init__.py
@@ -0,0 +1,4 @@
+__all__ = [
+ "train_planner.py",
+ "state_manager",
+]
\ No newline at end of file
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/state_manager.py b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/state_manager.py
new file mode 100644
index 00000000..e69de29b
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/train_planner.py b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/train_planner.py
new file mode 100644
index 00000000..b417836c
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/agents/train_planner.py
@@ -0,0 +1,185 @@
+import json
+from typing import Dict, Any, List
+from hello_agents import SimpleAgent
+
+from ..models.schemas import FitnessRequest, TrainPlan
+from ..services.llm_service import get_llm
+from ..config import get_settings
+
+# ========== Agent 提示词 ==========
+PLANNER_AGENT_PROMPT = """你是健身规划专家，你的任务是根据客户的身高、体重和年龄，生成详细的健身计划。
+
+请为以下用户生成个性化的健身计划：
+- 年龄：{request.age}岁
+- 身高：{request.height}cm
+- 体重：{request.weight}kg
+
+要求：
+1. 包含训练计划（每周3-5天）
+2. 包含营养建议
+3. 包含注意事项
+4. 用中文回复，格式美观
+
+"""
+
+class FitnessPlanner:
+
+ def __init__(self):
+ print("开始初始化智能体健身规划系统")
+
+ try:
+ settings = get_settings()
+ self.llm = get_llm()
+
+ print("创建健身规划Agent")
+ self.planner_agent = SimpleAgent(
+ name="健身规划专家",
+ llm=self.llm,
+ system_prompt=PLANNER_AGENT_PROMPT
+ )
+
+ except Exception as e:
+ print(f"❌ 智能体系统初始化失败: {str(e)}")
+ import traceback
+ traceback.print_exc()
+ raise
+
+ def plan_train(self, request: FitnessRequest) -> List[TrainPlan]:
+ try:
+ print(f"\n{'=' * 60}")
+ print(f"🚀 开始智能体规划训练...")
+ print(f"身高：{request.height}")
+ print(f"体重：{request.weight}")
+ print(f"年龄：{request.age}")
+ print(f"\n{'=' * 60}")
+
+ print("制定训练计划中...")
+ planner_query = self._build_planner_query(request)
+ planner_response = self.planner_agent.run(planner_query)
+ print(f"训练规划结果: {planner_response[:300]}...\n")
+
+ # 解析响应为列表
+ train_plan_list = self._parse_response(planner_response, request)
+
+ # 确保返回 7 天列表，如果不足则用休息日填充
+ full_plan = []
+ for day in range(1, 8):
+ day_plan = next((p for p in train_plan_list if p.get("day") == day), None)
+ if day_plan:
+ # 转换为 TrainPlan 对象
+ full_plan.append(TrainPlan(**day_plan))
+ else:
+ # 休息日占位
+ full_plan.append(TrainPlan(
+ day=day,
+ action="休息",
+ muscle=None,
+ group_num=None,
+ amount=None
+ ))
+
+ print(f"{'=' * 60}")
+ print(f"✅ 训练计划生成完成!")
+ print(f"{'=' * 60}\n")
+
+ return full_plan
+
+ except Exception as e:
+ print(f"❌ 生成训练计划失败: {str(e)}")
+ import traceback
+ traceback.print_exc()
+ return self._create_fallback_plan(request)
+
+ def _build_planner_query(self, request: FitnessRequest) -> str:
+
+ query = f"""
+ 你是一个健身训练计划生成器，只能返回 JSON 格式。
+
+ 请根据以下信息生成 **7 天训练计划**，并严格按下面的 JSON schema 输出：
+
+ 每条数据格式必须如下：
+ {{
+ "day": int,
+ "action": str,
+ "muscle": str,
+ "group_num": int,
+ "amount": int
+ }}
+
+ 输出格式必须是一个 JSON 数组，例如：
+ [
+ {{ ... }},
+ {{ ... }},
+ ...
+ ]
+
+ 用户信息：
+ - 身高: {request.height}
+ - 体重: {request.weight}
+ - 年龄: {request.age}
+
+ 生成要求：
+ 1. 输出完整 7 天计划，每天 3~4 个动作（可拆成多条 JSON）
+ 2. 返回标准 JSON 数组
+ 3. 严禁输出解释、文字、标题，只能输出 JSON
+
+ """
+ return query
+
+ def _parse_response(self, response: str, request: FitnessRequest) -> List[dict]:
+ """
+ 解析 Agent 响应为字典列表，每个元素对应一天训练计划
+ """
+ try:
+ import json
+
+ # 提取 JSON 部分
+ if "```json" in response:
+ start = response.find("```json") + 7
+ end = response.find("```", start)
+ json_str = response[start:end].strip()
+ elif "```" in response:
+ start = response.find("```") + 3
+ end = response.find("```", start)
+ json_str = response[start:end].strip()
+ else:
+ # 尝试直接解析 JSON
+ json_str = response.strip()
+
+ data = json.loads(json_str)
+
+ # 确保返回的是列表
+ if isinstance(data, dict):
+ return [data]
+ elif isinstance(data, list):
+ return data
+ else:
+ raise ValueError("Agent 返回数据格式不正确")
+
+ except Exception as e:
+ print(f"⚠️ 解析响应失败: {str(e)}")
+ print(f" 将使用备用方案生成计划")
+ return [p.dict() for p in self._create_fallback_plan(request)]
+
+ def _create_fallback_plan(self, request: FitnessRequest) -> List[TrainPlan]:
+ """
+ 生成 7 天 fallback 计划
+ """
+ fallback = []
+ for day in range(1, 8):
+ if day % 2 == 0:
+ fallback.append(TrainPlan(day=day, action="休息", muscle=None, group_num=None, amount=None))
+ else:
+ fallback.append(TrainPlan(day=day, action="深蹲", muscle="腿部", group_num=4, amount=12))
+ return fallback
+
+
+_fitness_planner = None
+
+def get_fitness_planner_agent() -> FitnessPlanner:
+ global _fitness_planner
+
+ if _fitness_planner is None:
+ _fitness_planner = FitnessPlanner()
+
+ return _fitness_planner
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/main.py b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/main.py
new file mode 100644
index 00000000..51d96de8
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/main.py
@@ -0,0 +1,98 @@
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import RedirectResponse
+from ..config import get_settings, valid_config, print_config
+from .routers import train
+import asyncio
+
+settings = get_settings()
+
+app = FastAPI(
+ title=settings.app_name,
+ version=settings.app_version,
+ description="基于HelloAgents框架的健身助手Agent",
+ docs_url="/docs",
+ redoc_url="/redoc"
+)
+
+# 配置CORS
+app.add_middleware(
+ CORSMiddleware,
+ allow_origins=settings.get_cors_origins(),
+ allow_credentials=True,
+ allow_methods=["*"],
+ allow_headers=["*"]
+)
+
+# 注册路由
+app.include_router(train.router)
+
+@app.on_event("startup")
+async def startup_event():
+ """应用启动事件"""
+ print("\n" + "=" * 60)
+ print(f"🚀 {settings.app_name} v{settings.app_version}")
+ print("=" * 60)
+
+ # 打印config配置信息
+ print_config()
+
+ # 验证配置
+ try:
+ valid_config()
+ print("\n ✔验证通过")
+ except ValueError as e:
+ print(f"\n❌ 配置验证失败:\n{e}")
+ print("\n请检查.env文件并确保所有必要的配置项都已设置")
+ raise
+
+ print("\n" + "=" * 60)
+ print("📚 API文档: http://localhost:8000/docs")
+ print("📖 ReDoc文档: http://localhost:8000/redoc")
+ print("=" * 60 + "\n")
+
+@app.on_event("shutdown")
+async def shutdown_event():
+ """应用关闭事件"""
+ print("\n" + "="*60)
+ print("👋 应用正在关闭...")
+ print("="*60 + "\n")
+
+# @app.get("/")
+# async def root():
+# """根路径"""
+# return {
+# "name": settings.app_name,
+# "version": settings.app_version,
+# "status": "running",
+# "docs": "/docs",
+# "redoc": "/redoc"
+# }
+
+@app.get("/")
+async def root():
+ return RedirectResponse(url="/train/")
+
+
+@app.get("/health")
+async def health():
+ """健康检查"""
+ return {
+ "status": "healthy",
+ "service": settings.app_name,
+ "version": settings.app_version
+ }
+
+
+if __name__ == "__main__":
+ import uvicorn
+
+ uvicorn.run(
+ "app.api.main:app",
+ host=settings.host,
+ port=settings.port,
+ reload=True
+ )
+
diff --git a/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/routers/train.py b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/routers/train.py
new file mode 100644
index 00000000..2ed9b35c
--- /dev/null
+++ b/Co-creation-projects/EugeneChanQAQ-smart_fitness_planner/app/api/routers/train.py
@@ -0,0 +1,361 @@
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import HTMLResponse
+from ...models.schemas import (
+ FitnessRequest,
+ FitnessResponse,
+ ErrorResponse
+)
+from ...agents.train_planner import get_fitness_planner_agent
+
+router = APIRouter(prefix="/train", tags=["训练计划"])
+
+# 前端界面HTML
+TRAINING_HTML = """
+
+
+
+
+
+ 健身计划生成器
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+