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Add Flask/Python backend server

Browse Source 
- Create app.py with Flask server on port 5002
- Add requirements.txt with Python dependencies
- Add run_flask.bat for Windows users
- Add run_flask.sh for Linux/Mac users
- Complete Flask setup documentation
- Database integration with PyMySQL
- Full LLM API support (Gemini, DeepSeek, OpenAI, Claude)
- CORS configuration
- Error handling middleware

Features:
✅ Runs on http://127.0.0.1:5002
✅ All LLM APIs supported
✅ Database connection
✅ API proxy for CORS fix
✅ Auto setup scripts

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
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2025-12-04 00:15:29 +08:00
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# Flask 伺服器設定指南
## 🐍 Python Flask 後端伺服器
本專案提供 **Python Flask** 版本的後端伺服器，運行於 `http://127.0.0.1:5002`
## 📋 系統需求
- **Python**: 3.8 或更高版本
- **pip**: Python 套件管理工具
- **MySQL**: 資料庫（已設定）
## 🚀 快速開始
### Windows 用戶
1. **雙擊執行啟動腳本**
```bash
run_flask.bat
```
腳本會自動：
- ✅ 檢查 Python 安裝
- ✅ 建立虛擬環境（第一次執行）
- ✅ 安裝所有依賴
- ✅ 啟動 Flask 伺服器
2. **或手動執行**
```bash
# 建立虛擬環境
python -m venv venv
# 啟動虛擬環境
venv\Scripts\activate
# 安裝依賴
pip install -r requirements.txt
# 啟動伺服器
python app.py
```
### Linux/Mac 用戶
1. **執行啟動腳本**
```bash
chmod +x run_flask.sh
./run_flask.sh
```
2. **或手動執行**
```bash
# 建立虛擬環境
python3 -m venv venv
# 啟動虛擬環境
source venv/bin/activate
# 安裝依賴
pip install -r requirements.txt
# 啟動伺服器
python3 app.py
```
## 📦 已安裝的套件
```
Flask==3.0.0 # Web 框架
Flask-Cors==4.0.0 # CORS 支援
PyMySQL==1.1.0 # MySQL 連接器
requests==2.31.0 # HTTP 請求
python-dotenv==1.0.0 # 環境變數管理
```
完整清單請參考 [requirements.txt](requirements.txt)
## 🌐 服務端點
### 基礎端點
```
GET http://127.0.0.1:5002/
- API 資訊
GET http://127.0.0.1:5002/health
- 健康檢查
GET http://127.0.0.1:5002/api-proxy-example.html
- API 使用範例頁面
```
### 資料庫 API
```
POST http://127.0.0.1:5002/api/db/test
- 測試資料庫連線
GET http://127.0.0.1:5002/api/db/tables
- 列出所有資料表
```
### LLM API
```
POST http://127.0.0.1:5002/api/llm/test/gemini
- 測試 Gemini API
POST http://127.0.0.1:5002/api/llm/test/deepseek
- 測試 DeepSeek API
POST http://127.0.0.1:5002/api/llm/test/openai
- 測試 OpenAI API
POST http://127.0.0.1:5002/api/llm/test/claude
- 測試 Claude API
POST http://127.0.0.1:5002/api/llm/test/all
- 測試所有 LLM
POST http://127.0.0.1:5002/api/llm/generate
- 生成內容
```
## 💡 使用範例
### Python 範例
```python
import requests
# 測試資料庫連線
response = requests.post('http://127.0.0.1:5002/api/db/test')
print(response.json())
# 測試 Claude API
response = requests.post('http://127.0.0.1:5002/api/llm/test/claude')
print(response.json())
# 生成內容
response = requests.post(
'http://127.0.0.1:5002/api/llm/generate',
json={
'prompt': '介紹 HR 績效評核系統',
'provider': 'claude',
'options': {
'temperature': 0.7,
'maxTokens': 200
}
}
)
print(response.json())
```
### JavaScript 範例
```javascript
// 測試資料庫連線
fetch('http://127.0.0.1:5002/api/db/test', {
method: 'POST'
})
.then(res => res.json())
.then(data => console.log(data));
// 生成內容
fetch('http://127.0.0.1:5002/api/llm/generate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
prompt: '介紹 HR 績效評核系統',
provider: 'claude',
options: {
temperature: 0.7,
maxTokens: 200
}
})
})
.then(res => res.json())
.then(data => console.log(data));
```
### cURL 範例
```bash
# 測試資料庫連線
curl -X POST http://127.0.0.1:5002/api/db/test
# 測試 Claude API
curl -X POST http://127.0.0.1:5002/api/llm/test/claude
# 生成內容
curl -X POST http://127.0.0.1:5002/api/llm/generate \
-H "Content-Type: application/json" \
-d '{
"prompt": "介紹 HR 績效評核系統",
"provider": "claude",
"options": {
"temperature": 0.7,
"maxTokens": 200
}
}'
```
## ⚙️ 環境變數設定
確保 [.env](.env) 檔案包含以下設定：
```env
# 資料庫設定
DB_HOST=mysql.theaken.com
DB_PORT=33306
DB_NAME=db_A102
DB_USER=A102
DB_PASSWORD=Bb123456
# LLM API 金鑰
GEMINI_API_KEY=your_gemini_api_key
DEEPSEEK_API_KEY=your_deepseek_api_key
OPENAI_API_KEY=your_openai_api_key
CLAUDE_API_KEY=your_claude_api_key
# 應用設定
NODE_ENV=development
FRONTEND_URL=http://127.0.0.1:5002
```
## 🔧 開發模式
Flask 在開發模式下會：
- ✅ 自動重新載入程式碼變更
- ✅ 顯示詳細錯誤訊息
- ✅ 啟用偵錯模式
```python
# app.py 最後一行
app.run(
host='127.0.0.1',
port=5002,
debug=True # 開發模式
)
```
## 📊 伺服器啟動畫面
```
============================================================
🚀 HR Performance System API Server (Flask/Python)
============================================================
📡 Server running on: http://127.0.0.1:5002
🌍 Environment: development
📅 Started at: 2025-12-03 23:59:59
============================================================
📚 Available endpoints:
GET / - API information
GET /health - Health check
POST /api/db/test - Test database connection
GET /api/db/tables - List all tables
POST /api/llm/test/* - Test LLM connections
POST /api/llm/generate - Generate content with LLM
GET /api-proxy-example.html - API example page
✨ Server is ready to accept connections!
✅ Database connection: OK
* Serving Flask app 'app'
* Debug mode: on
WARNING: This is a development server. Do not use it in production.
Use a production WSGI server instead.
* Running on http://127.0.0.1:5002
Press CTRL+C to quit
* Restarting with stat
```
## 🎯 與 Node.js 版本的比較
| 功能 | Flask (Python) | Express (Node.js) |
|------|----------------|-------------------|
| **端口** | 5002 | 3000 |
| **語言** | Python 3.8+ | Node.js 16+ |
| **安裝** | `pip install -r requirements.txt` | `npm install` |
| **啟動** | `python app.py` | `npm start` |
| **優點** | Python 生態系統、機器學習整合 | JavaScript 全棧、效能較好 |
兩個版本功能完全相同，可以根據團隊技術棧選擇使用！
## 🐛 常見問題
### Q1: 執行 run_flask.bat 出現錯誤
**A:** 確認：
1. Python 是否已安裝並在 PATH 中
2. 執行 `python --version` 檢查版本
3. 是否有權限建立虛擬環境
### Q2: pip install 失敗
**A:** 嘗試：
```bash
# 升級 pip
python -m pip install --upgrade pip
# 使用國內鏡像（中國用戶）
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
```
### Q3: 資料庫連線失敗
**A:** 檢查：
1. MySQL 伺服器是否運行
2. `.env` 中的資料庫連線資訊是否正確
3. 防火牆是否阻擋 33306 端口
### Q4: CORS 錯誤
**A:** Flask-CORS 已設定，但確認：
1. 前端是否從正確的來源發送請求
2. `.env` 中的 `FRONTEND_URL` 設定
### Q5: 虛擬環境啟動失敗
**A:** Windows 使用者可能需要：
```bash
# 允許執行腳本（以管理員身份執行 PowerShell）
Set-ExecutionPolicy RemoteSigned
```
## 📁 專案結構
```
hr-performance-system/
├── app.py # Flask 主程式 ⭐
├── requirements.txt # Python 依賴 ⭐
├── run_flask.bat # Windows 啟動腳本 ⭐
├── run_flask.sh # Linux/Mac 啟動腳本 ⭐
├── server.js # Node.js 版本（可選）
├── package.json # Node.js 依賴（可選）
├── .env # 環境變數
├── .gitignore
├── venv/ # Python 虛擬環境（自動建立）
├── public/
│ └── api-proxy-example.html
├── config/
├── services/
├── routes/
├── utils/
└── database/
```
## 🔒 安全提醒
- ⚠️ **開發伺服器**：Flask 內建伺服器僅供開發使用
- ⚠️ **生產環境**：使用 Gunicorn、uWSGI 等 WSGI 伺服器
- ⚠️ **API 金鑰**：絕不提交 `.env` 到版本控制
- ⚠️ **HTTPS**：生產環境必須使用 HTTPS
## 🚀 生產環境部署
### 使用 Gunicorn
```bash
# 安裝 Gunicorn
pip install gunicorn
# 啟動
gunicorn -w 4 -b 127.0.0.1:5002 app:app
```
### 使用 Docker
```dockerfile
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:5002", "app:app"]
```
## 📚 相關文件
- [README.md](README.md) - 專案說明
- [CORS_FIX_GUIDE.md](CORS_FIX_GUIDE.md) - CORS 問題解決
- [database/README.md](database/README.md) - 資料庫文件
- [package.json](package.json) - Node.js 版本（可選）
---
**最後更新**: 2025-12-03
**Python 版本**: 3.8+
**Flask 版本**: 3.0.0

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"""
Flask Application
HR 績效評核系統 - Python Flask 後端伺服器
運行於 127.0.0.1:5002
"""
import os
import json
from datetime import datetime
from flask import Flask, request, jsonify, send_from_directory
from flask_cors import CORS
from dotenv import load_dotenv
import pymysql
import requests
from functools import wraps
# 載入環境變數
load_dotenv()
# 建立 Flask 應用
app = Flask(__name__, static_folder='public', static_url_path='')
# CORS 設定
CORS(app, resources={
r"/api/*": {
"origins": os.getenv('FRONTEND_URL', '*'),
"methods": ["GET", "POST", "PUT", "DELETE", "PATCH"],
"allow_headers": ["Content-Type", "Authorization"]
}
})
# 應用配置
app.config['JSON_AS_ASCII'] = False # 支援中文
app.config['JSON_SORT_KEYS'] = False
app.config['MAX_CONTENT_LENGTH'] = int(os.getenv('MAX_FILE_SIZE', 5242880)) # 5MB
# ============================================
# 資料庫連線
# ============================================
def get_db_connection():
"""建立資料庫連線"""
try:
connection = pymysql.connect(
host=os.getenv('DB_HOST'),
port=int(os.getenv('DB_PORT', 3306)),
user=os.getenv('DB_USER'),
password=os.getenv('DB_PASSWORD'),
database=os.getenv('DB_NAME'),
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor
)
return connection
except Exception as e:
print(f"資料庫連線錯誤: {e}")
return None
def test_db_connection():
"""測試資料庫連線"""
try:
conn = get_db_connection()
if conn:
with conn.cursor() as cursor:
cursor.execute("SELECT 1")
conn.close()
return True
return False
except:
return False
# ============================================
# LLM 服務整合
# ============================================
class LLMService:
"""LLM 服務類別"""
@staticmethod
def get_config(provider):
"""取得 LLM 配置"""
configs = {
'gemini': {
'api_key': os.getenv('GEMINI_API_KEY'),
'api_url': 'https://generativelanguage.googleapis.com/v1beta',
'model': os.getenv('GEMINI_MODEL', 'gemini-pro')
},
'deepseek': {
'api_key': os.getenv('DEEPSEEK_API_KEY'),
'api_url': os.getenv('DEEPSEEK_API_URL', 'https://api.deepseek.com/v1'),
'model': os.getenv('DEEPSEEK_MODEL', 'deepseek-chat')
},
'openai': {
'api_key': os.getenv('OPENAI_API_KEY'),
'api_url': os.getenv('OPENAI_API_URL', 'https://api.openai.com/v1'),
'model': os.getenv('OPENAI_MODEL', 'gpt-4')
},
'claude': {
'api_key': os.getenv('CLAUDE_API_KEY'),
'api_url': os.getenv('CLAUDE_API_URL', 'https://api.anthropic.com/v1'),
'model': os.getenv('CLAUDE_MODEL', 'claude-3-5-sonnet-20241022'),
'version': '2023-06-01'
}
}
return configs.get(provider)
@staticmethod
def test_gemini():
"""測試 Gemini API"""
try:
config = LLMService.get_config('gemini')
if not config['api_key']:
return {'success': False, 'message': 'Gemini API key not configured', 'provider': 'gemini'}
url = f"{config['api_url']}/models/{config['model']}:generateContent"
response = requests.post(
url,
params={'key': config['api_key']},
json={'contents': [{'parts': [{'text': 'Hello'}]}]},
timeout=30
)
if response.status_code == 200:
return {'success': True, 'message': 'Gemini API connection successful', 'provider': 'gemini', 'model': config['model']}
return {'success': False, 'message': f'HTTP {response.status_code}', 'provider': 'gemini'}
except Exception as e:
return {'success': False, 'message': str(e), 'provider': 'gemini'}
@staticmethod
def test_deepseek():
"""測試 DeepSeek API"""
try:
config = LLMService.get_config('deepseek')
if not config['api_key']:
return {'success': False, 'message': 'DeepSeek API key not configured', 'provider': 'deepseek'}
url = f"{config['api_url']}/chat/completions"
response = requests.post(
url,
headers={'Authorization': f"Bearer {config['api_key']}"},
json={'model': config['model'], 'messages': [{'role': 'user', 'content': 'Hello'}], 'max_tokens': 50},
timeout=30
)
if response.status_code == 200:
return {'success': True, 'message': 'DeepSeek API connection successful', 'provider': 'deepseek', 'model': config['model']}
return {'success': False, 'message': f'HTTP {response.status_code}', 'provider': 'deepseek'}
except Exception as e:
return {'success': False, 'message': str(e), 'provider': 'deepseek'}
@staticmethod
def test_openai():
"""測試 OpenAI API"""
try:
config = LLMService.get_config('openai')
if not config['api_key']:
return {'success': False, 'message': 'OpenAI API key not configured', 'provider': 'openai'}
url = f"{config['api_url']}/chat/completions"
response = requests.post(
url,
headers={'Authorization': f"Bearer {config['api_key']}"},
json={'model': config['model'], 'messages': [{'role': 'user', 'content': 'Hello'}], 'max_tokens': 50},
timeout=30
)
if response.status_code == 200:
return {'success': True, 'message': 'OpenAI API connection successful', 'provider': 'openai', 'model': config['model']}
return {'success': False, 'message': f'HTTP {response.status_code}', 'provider': 'openai'}
except Exception as e:
return {'success': False, 'message': str(e), 'provider': 'openai'}
@staticmethod
def test_claude():
"""測試 Claude API"""
try:
config = LLMService.get_config('claude')
if not config['api_key']:
return {'success': False, 'message': 'Claude API key not configured', 'provider': 'claude'}
url = f"{config['api_url']}/messages"
response = requests.post(
url,
headers={
'x-api-key': config['api_key'],
'anthropic-version': config['version'],
'content-type': 'application/json'
},
json={
'model': config['model'],
'max_tokens': 50,
'messages': [{'role': 'user', 'content': 'Hello'}]
},
timeout=30
)
if response.status_code == 200:
return {'success': True, 'message': 'Claude API connection successful', 'provider': 'claude', 'model': config['model']}
return {'success': False, 'message': f'HTTP {response.status_code}', 'provider': 'claude'}
except Exception as e:
return {'success': False, 'message': str(e), 'provider': 'claude'}
@staticmethod
def generate_content(prompt, provider='claude', options=None):
"""使用指定的 LLM 生成內容"""
if options is None:
options = {}
config = LLMService.get_config(provider)
if not config or not config['api_key']:
raise Exception(f'{provider} API not configured')
try:
if provider == 'claude':
url = f"{config['api_url']}/messages"
response = requests.post(
url,
headers={
'x-api-key': config['api_key'],
'anthropic-version': config['version'],
'content-type': 'application/json'
},
json={
'model': config['model'],
'max_tokens': options.get('maxTokens', 2000),
'temperature': options.get('temperature', 0.7),
'messages': [{'role': 'user', 'content': prompt}]
},
timeout=30
)
if response.status_code == 200:
data = response.json()
return {'success': True, 'content': data['content'][0]['text'], 'provider': provider}
elif provider == 'gemini':
url = f"{config['api_url']}/models/{config['model']}:generateContent"
response = requests.post(
url,
params={'key': config['api_key']},
json={
'contents': [{'parts': [{'text': prompt}]}],
'generationConfig': {
'temperature': options.get('temperature', 0.7),
'maxOutputTokens': options.get('maxTokens', 2000)
}
},
timeout=30
)
if response.status_code == 200:
data = response.json()
return {'success': True, 'content': data['candidates'][0]['content']['parts'][0]['text'], 'provider': provider}
elif provider in ['deepseek', 'openai']:
url = f"{config['api_url']}/chat/completions"
response = requests.post(
url,
headers={'Authorization': f"Bearer {config['api_key']}"},
json={
'model': config['model'],
'messages': [{'role': 'user', 'content': prompt}],
'temperature': options.get('temperature', 0.7),
'max_tokens': options.get('maxTokens', 2000)
},
timeout=30
)
if response.status_code == 200:
data = response.json()
return {'success': True, 'content': data['choices'][0]['message']['content'], 'provider': provider}
raise Exception(f'Failed to generate content: HTTP {response.status_code}')
except Exception as e:
raise Exception(f'{provider} API error: {str(e)}')
# ============================================
# 錯誤處理
# ============================================
def handle_error(error, status_code=500):
"""統一錯誤處理"""
return jsonify({
'success': False,
'error': {
'statusCode': status_code,
'message': str(error),
'timestamp': datetime.now().isoformat(),
'path': request.path
}
}), status_code
@app.errorhandler(404)
def not_found(error):
"""404 錯誤處理"""
return jsonify({
'success': False,
'error': {
'statusCode': 404,
'message': f'Cannot {request.method} {request.path}',
'timestamp': datetime.now().isoformat(),
'path': request.path
}
}), 404
@app.errorhandler(500)
def internal_error(error):
"""500 錯誤處理"""
return handle_error(error, 500)
# ============================================
# 路由
# ============================================
@app.route('/')
def index():
"""根路由"""
return jsonify({
'name': 'HR Performance System API',
'version': '1.0.0',
'description': '四卡循環績效管理系統 (Python Flask)',
'server': 'Flask/Python',
'endpoints': {
'health': '/health',
'database': '/api/db/test',
'llm': '/api/llm',
'example': '/api-proxy-example.html'
}
})
@app.route('/health')
def health():
"""健康檢查"""
db_status = test_db_connection()
return jsonify({
'success': True,
'message': 'HR Performance System API is running',
'timestamp': datetime.now().isoformat(),
'environment': os.getenv('NODE_ENV', 'development'),
'database': 'connected' if db_status else 'disconnected',
'server': 'Flask/Python'
})
# ============================================
# 資料庫 API
# ============================================
@app.route('/api/db/test', methods=['POST'])
def test_database():
"""測試資料庫連線"""
try:
conn = get_db_connection()
if not conn:
return handle_error('無法連接到資料庫', 500)
with conn.cursor() as cursor:
cursor.execute("SELECT VERSION() as version")
result = cursor.fetchone()
cursor.execute("SELECT DATABASE() as database_name")
db_info = cursor.fetchone()
conn.close()
return jsonify({
'success': True,
'message': '資料庫連線成功',
'database': db_info['database_name'],
'version': result['version']
})
except Exception as e:
return handle_error(e, 500)
@app.route('/api/db/tables', methods=['GET'])
def list_tables():
"""列出所有資料表"""
try:
conn = get_db_connection()
if not conn:
return handle_error('無法連接到資料庫', 500)
with conn.cursor() as cursor:
cursor.execute("SHOW TABLES")
tables = [list(row.values())[0] for row in cursor.fetchall()]
conn.close()
return jsonify({
'success': True,
'count': len(tables),
'tables': tables
})
except Exception as e:
return handle_error(e, 500)
# ============================================
# LLM API
# ============================================
@app.route('/api/llm/test/gemini', methods=['POST'])
def test_llm_gemini():
"""測試 Gemini API"""
result = LLMService.test_gemini()
return jsonify(result)
@app.route('/api/llm/test/deepseek', methods=['POST'])
def test_llm_deepseek():
"""測試 DeepSeek API"""
result = LLMService.test_deepseek()
return jsonify(result)
@app.route('/api/llm/test/openai', methods=['POST'])
def test_llm_openai():
"""測試 OpenAI API"""
result = LLMService.test_openai()
return jsonify(result)
@app.route('/api/llm/test/claude', methods=['POST'])
def test_llm_claude():
"""測試 Claude API"""
result = LLMService.test_claude()
return jsonify(result)
@app.route('/api/llm/test/all', methods=['POST'])
def test_llm_all():
"""測試所有 LLM API"""
results = {
'gemini': LLMService.test_gemini(),
'deepseek': LLMService.test_deepseek(),
'openai': LLMService.test_openai(),
'claude': LLMService.test_claude()
}
return jsonify(results)
@app.route('/api/llm/generate', methods=['POST'])
def generate_content():
"""使用 LLM 生成內容"""
try:
data = request.get_json()
if not data or 'prompt' not in data:
return handle_error('缺少必要參數: prompt', 400)
prompt = data['prompt']
provider = data.get('provider', 'claude')
options = data.get('options', {})
result = LLMService.generate_content(prompt, provider, options)
return jsonify(result)
except Exception as e:
return handle_error(e, 500)
# ============================================
# 靜態檔案
# ============================================
@app.route('/api-proxy-example.html')
def api_example():
"""API 範例頁面"""
return send_from_directory('public', 'api-proxy-example.html')
# ============================================
# 啟動伺服器
# ============================================
if __name__ == '__main__':
print('=' * 60)
print('🚀 HR Performance System API Server (Flask/Python)')
print('=' * 60)
print(f'📡 Server running on: http://127.0.0.1:5002')
print(f'🌍 Environment: {os.getenv("NODE_ENV", "development")}')
print(f'📅 Started at: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}')
print('=' * 60)
print('\n📚 Available endpoints:')
print(' GET / - API information')
print(' GET /health - Health check')
print(' POST /api/db/test - Test database connection')
print(' GET /api/db/tables - List all tables')
print(' POST /api/llm/test/* - Test LLM connections')
print(' POST /api/llm/generate - Generate content with LLM')
print(' GET /api-proxy-example.html - API example page')
print('\n✨ Server is ready to accept connections!\n')
# 測試資料庫連線
if test_db_connection():
print('✅ Database connection: OK')
else:
print('⚠️ Database connection: FAILED')
print('')
# 啟動伺服器
app.run(
host='127.0.0.1',
port=5002,
debug=os.getenv('NODE_ENV') == 'development'
)

27
requirements.txt Normal file
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@@ -0,0 +1,27 @@
# Flask 核心
Flask==3.0.0
Werkzeug==3.0.1
# CORS 支援
Flask-Cors==4.0.0
# 資料庫
PyMySQL==1.1.0
cryptography==41.0.7
# HTTP 請求
requests==2.31.0
# 環境變數
python-dotenv==1.0.0
# JSON 處理
jsonschema==4.20.0
# 日期時間
python-dateutil==2.8.2
# 開發工具（可選）
# pytest==7.4.3
# black==23.12.1
# flake8==6.1.0

59
run_flask.bat Normal file
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@echo off
REM Flask 伺服器啟動腳本
echo ========================================
echo HR Performance System - Flask Server
echo ========================================
echo.
REM 檢查 Python 是否安裝
python --version >nul 2>&1
if errorlevel 1 (
echo [ERROR] Python is not installed or not in PATH
echo Please install Python 3.8 or higher
pause
exit /b 1
)
REM 檢查虛擬環境
if not exist "venv\" (
echo [INFO] Creating virtual environment...
python -m venv venv
if errorlevel 1 (
echo [ERROR] Failed to create virtual environment
pause
exit /b 1
)
echo [SUCCESS] Virtual environment created
echo.
)
REM 啟動虛擬環境
echo [INFO] Activating virtual environment...
call venv\Scripts\activate.bat
REM 安裝依賴
echo [INFO] Installing dependencies...
pip install -r requirements.txt
if errorlevel 1 (
echo [ERROR] Failed to install dependencies
pause
exit /b 1
)
echo.
REM 檢查 .env 檔案
if not exist ".env" (
echo [WARNING] .env file not found
echo Please create .env file with required configuration
echo.
)
REM 啟動 Flask 伺服器
echo [INFO] Starting Flask server...
echo Server will run on http://127.0.0.1:5002
echo Press Ctrl+C to stop the server
echo.
python app.py
pause

54
run_flask.sh Normal file
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#!/bin/bash
# Flask 伺服器啟動腳本
echo "========================================"
echo "HR Performance System - Flask Server"
echo "========================================"
echo ""
# 檢查 Python 是否安裝
if ! command -v python3 &> /dev/null; then
echo "[ERROR] Python 3 is not installed"
echo "Please install Python 3.8 or higher"
exit 1
fi
# 檢查虛擬環境
if [ ! -d "venv" ]; then
echo "[INFO] Creating virtual environment..."
python3 -m venv venv
if [ $? -ne 0 ]; then
echo "[ERROR] Failed to create virtual environment"
exit 1
fi
echo "[SUCCESS] Virtual environment created"
echo ""
fi
# 啟動虛擬環境
echo "[INFO] Activating virtual environment..."
source venv/bin/activate
# 安裝依賴
echo "[INFO] Installing dependencies..."
pip install -r requirements.txt
if [ $? -ne 0 ]; then
echo "[ERROR] Failed to install dependencies"
exit 1
fi
echo ""
# 檢查 .env 檔案
if [ ! -f ".env" ]; then
echo "[WARNING] .env file not found"
echo "Please create .env file with required configuration"
echo ""
fi
# 啟動 Flask 伺服器
echo "[INFO] Starting Flask server..."
echo "Server will run on http://127.0.0.1:5002"
echo "Press Ctrl+C to stop the server"
echo ""
python3 app.py