1st_fix_login_issue

2025-09-02 10:31:35 +08:00
commit a60d965317
103 changed files with 12402 additions and 0 deletions
--- a/app/models/stats.py
+++ b/app/models/stats.py
@@ -0,0 +1,222 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+API使用統計資料模型
+
+Author: PANJIT IT Team
+Created: 2024-01-28
+Modified: 2024-01-28
+"""
+
+from datetime import datetime, timedelta
+from sqlalchemy.sql import func
+from app import db
+
+
+class APIUsageStats(db.Model):
+    """API使用統計表 (dt_api_usage_stats)"""
+    __tablename__ = 'dt_api_usage_stats'
+    
+    id = db.Column(db.Integer, primary_key=True, autoincrement=True)
+    user_id = db.Column(db.Integer, db.ForeignKey('dt_users.id'), nullable=False, comment='使用者ID')
+    job_id = db.Column(db.Integer, db.ForeignKey('dt_translation_jobs.id'), comment='任務ID')
+    api_endpoint = db.Column(db.String(200), nullable=False, comment='API端點')
+    prompt_tokens = db.Column(db.Integer, default=0, comment='Prompt token數')
+    completion_tokens = db.Column(db.Integer, default=0, comment='Completion token數')
+    total_tokens = db.Column(db.Integer, default=0, comment='總token數')
+    prompt_unit_price = db.Column(db.Numeric(10, 8), default=0.00000000, comment='單價')
+    prompt_price_unit = db.Column(db.String(20), default='USD', comment='價格單位')
+    cost = db.Column(db.Numeric(10, 4), default=0.0000, comment='成本')
+    response_time_ms = db.Column(db.Integer, default=0, comment='回應時間(毫秒)')
+    success = db.Column(db.Boolean, default=True, comment='是否成功')
+    error_message = db.Column(db.Text, comment='錯誤訊息')
+    created_at = db.Column(db.DateTime, default=func.now(), comment='建立時間')
+    
+    def __repr__(self):
+        return f'<APIUsageStats {self.api_endpoint}>'
+    
+    def to_dict(self):
+        """轉換為字典格式"""
+        return {
+            'id': self.id,
+            'user_id': self.user_id,
+            'job_id': self.job_id,
+            'api_endpoint': self.api_endpoint,
+            'prompt_tokens': self.prompt_tokens,
+            'completion_tokens': self.completion_tokens,
+            'total_tokens': self.total_tokens,
+            'prompt_unit_price': float(self.prompt_unit_price) if self.prompt_unit_price else 0.0,
+            'prompt_price_unit': self.prompt_price_unit,
+            'cost': float(self.cost) if self.cost else 0.0,
+            'response_time_ms': self.response_time_ms,
+            'success': self.success,
+            'error_message': self.error_message,
+            'created_at': self.created_at.isoformat() if self.created_at else None
+        }
+    
+    @classmethod
+    def record_api_call(cls, user_id, job_id, api_endpoint, metadata, response_time_ms, success=True, error_message=None):
+        """記錄 API 呼叫統計"""
+        # 從 Dify API metadata 解析使用量資訊
+        prompt_tokens = metadata.get('usage', {}).get('prompt_tokens', 0)
+        completion_tokens = metadata.get('usage', {}).get('completion_tokens', 0)
+        total_tokens = metadata.get('usage', {}).get('total_tokens', prompt_tokens + completion_tokens)
+        
+        # 計算成本
+        prompt_unit_price = metadata.get('usage', {}).get('prompt_unit_price', 0.0)
+        prompt_price_unit = metadata.get('usage', {}).get('prompt_price_unit', 'USD')
+        
+        # 成本計算：通常是 prompt_tokens * prompt_unit_price
+        cost = prompt_tokens * float(prompt_unit_price) if prompt_unit_price else 0.0
+        
+        stats = cls(
+            user_id=user_id,
+            job_id=job_id,
+            api_endpoint=api_endpoint,
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
+            total_tokens=total_tokens,
+            prompt_unit_price=prompt_unit_price,
+            prompt_price_unit=prompt_price_unit,
+            cost=cost,
+            response_time_ms=response_time_ms,
+            success=success,
+            error_message=error_message
+        )
+        
+        db.session.add(stats)
+        db.session.commit()
+        return stats
+    
+    @classmethod
+    def get_user_statistics(cls, user_id, start_date=None, end_date=None):
+        """取得使用者統計資料"""
+        query = cls.query.filter_by(user_id=user_id)
+        
+        if start_date:
+            query = query.filter(cls.created_at >= start_date)
+        if end_date:
+            query = query.filter(cls.created_at <= end_date)
+        
+        # 統計資料
+        total_calls = query.count()
+        successful_calls = query.filter_by(success=True).count()
+        total_tokens = query.with_entities(func.sum(cls.total_tokens)).scalar() or 0
+        total_cost = query.with_entities(func.sum(cls.cost)).scalar() or 0.0
+        avg_response_time = query.with_entities(func.avg(cls.response_time_ms)).scalar() or 0
+        
+        return {
+            'total_calls': total_calls,
+            'successful_calls': successful_calls,
+            'failed_calls': total_calls - successful_calls,
+            'success_rate': (successful_calls / total_calls * 100) if total_calls > 0 else 0,
+            'total_tokens': total_tokens,
+            'total_cost': float(total_cost),
+            'avg_response_time': float(avg_response_time) if avg_response_time else 0
+        }
+    
+    @classmethod
+    def get_daily_statistics(cls, days=30):
+        """取得每日統計資料"""
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=days)
+        
+        # 按日期分組統計
+        daily_stats = db.session.query(
+            func.date(cls.created_at).label('date'),
+            func.count(cls.id).label('total_calls'),
+            func.sum(cls.total_tokens).label('total_tokens'),
+            func.sum(cls.cost).label('total_cost'),
+            func.count().filter(cls.success == True).label('successful_calls')
+        ).filter(
+            cls.created_at >= start_date,
+            cls.created_at <= end_date
+        ).group_by(func.date(cls.created_at)).all()
+        
+        return [
+            {
+                'date': stat.date.isoformat(),
+                'total_calls': stat.total_calls,
+                'successful_calls': stat.successful_calls,
+                'failed_calls': stat.total_calls - stat.successful_calls,
+                'total_tokens': stat.total_tokens or 0,
+                'total_cost': float(stat.total_cost or 0)
+            }
+            for stat in daily_stats
+        ]
+    
+    @classmethod
+    def get_top_users(cls, limit=10, start_date=None, end_date=None):
+        """取得使用量排行榜"""
+        query = db.session.query(
+            cls.user_id,
+            func.count(cls.id).label('total_calls'),
+            func.sum(cls.total_tokens).label('total_tokens'),
+            func.sum(cls.cost).label('total_cost')
+        )
+        
+        if start_date:
+            query = query.filter(cls.created_at >= start_date)
+        if end_date:
+            query = query.filter(cls.created_at <= end_date)
+        
+        top_users = query.group_by(cls.user_id).order_by(
+            func.sum(cls.cost).desc()
+        ).limit(limit).all()
+        
+        return [
+            {
+                'user_id': user.user_id,
+                'total_calls': user.total_calls,
+                'total_tokens': user.total_tokens or 0,
+                'total_cost': float(user.total_cost or 0)
+            }
+            for user in top_users
+        ]
+    
+    @classmethod
+    def get_cost_trend(cls, days=30):
+        """取得成本趨勢"""
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=days)
+        
+        # 按日期統計成本
+        cost_trend = db.session.query(
+            func.date(cls.created_at).label('date'),
+            func.sum(cls.cost).label('daily_cost')
+        ).filter(
+            cls.created_at >= start_date,
+            cls.created_at <= end_date
+        ).group_by(func.date(cls.created_at)).order_by(
+            func.date(cls.created_at)
+        ).all()
+        
+        return [
+            {
+                'date': trend.date.isoformat(),
+                'cost': float(trend.daily_cost or 0)
+            }
+            for trend in cost_trend
+        ]
+    
+    @classmethod
+    def get_endpoint_statistics(cls):
+        """取得 API 端點統計"""
+        endpoint_stats = db.session.query(
+            cls.api_endpoint,
+            func.count(cls.id).label('total_calls'),
+            func.sum(cls.cost).label('total_cost'),
+            func.avg(cls.response_time_ms).label('avg_response_time')
+        ).group_by(cls.api_endpoint).order_by(
+            func.count(cls.id).desc()
+        ).all()
+        
+        return [
+            {
+                'endpoint': stat.api_endpoint,
+                'total_calls': stat.total_calls,
+                'total_cost': float(stat.total_cost or 0),
+                'avg_response_time': float(stat.avg_response_time or 0)
+            }
+            for stat in endpoint_stats
+        ]