Fix: Syntax error in Authorization header

habit_bot.py

@@ -1,16 +1,15 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
+"""
-#
+Unified Telegram Bot - Habit, Diet, URL Summarizer
-# Habit & Diet Telegram Bot with URL Summarization / URL 요약을 포함한 습관 및 식단 Telegram 봇
+Features:
-#
+- YouTube/Blog/News summarization (EN/KO)
-# 기능 / Features:
+- Habit logging
-# - 습관 추적 (/habit add, log, list) / Habit tracking
+- Diet/food logging with photo analysis
-# - 음식 기록 및 영양 분석 / Food logging with nutrition analysis
+- Morning briefing
-# - 아침 브리핑 및 밤 디브리프 / Morning briefings and night debrief
+- Night debrief + motivation
-# - URL 요약 (YouTube/Blog/News) / URL summarization
-# - 케토 다이어트 가이드라인 / Keto diet guidelines
 """
 
+import os
 import sys
 import json
 import re
@@ -28,7 +27,7 @@ except ImportError:
     TELEGRAM_AVAILABLE = False
 
 # Configuration
-TELEGRAM_BOT_TOKEN = os.environ.get('TELEGRAM_BOT_TOKEN', '8325588419:AAGghb0nosWG8g6QtYeghqUs0RHug06uG74')
+TELEGRAM_TOKEN = os.environ.get('TELEGRAM_BOT_TOKEN', '')
 OBSIDIAN_PATH = os.environ.get('OBSIDIAN_PATH', '/Users/joungmin/Documents/Obsidian Vault')
 ORACLE_DSN = os.environ.get('ORACLE_DSN', 'h8i4i0g8cxtd2lpf_high')
 ORACLE_USER = os.environ.get('ORACLE_USER', 'admin')
@@ -78,22 +77,6 @@ class UserData:
         save_json(HABIT_LOGS_FILE, self.habit_logs)
         save_json(FOOD_LOGS_FILE, self.food_logs)
         save_json(USER_DATA_FILE, self.users)
-    
-    def get_daily_totals(self, user_id: str, date: str = None) -> Dict:
-        """Get daily nutrition totals for a user"""
-        if date is None:
-            date = datetime.datetime.now().strftime('%Y-%m-%d')
-        
-        totals = {'calories': 0, 'carbs': 0, 'protein': 0, 'fat': 0}
-        
-        if user_id in self.food_logs and date in self.food_logs[user_id]:
-            for log in self.food_logs[user_id][date]:
-                totals['calories'] += log.get('calories', 0)
-                totals['carbs'] += log.get('carbs', 0)
-                totals['protein'] += log.get('protein', 0)
-                totals['fat'] += log.get('fat', 0)
-        
-        return totals
 
 data = UserData()
 
@@ -406,220 +389,6 @@ def analyze_food_text(text: str) -> Dict:
     
     return {'calories': calories, 'carbs': carbs, 'protein': protein, 'fat': fat}
 
-# ============== MiniMax Vision API ==============
-
-MINIMAX_API_URL = "https://api.minimax.chat/v1/text/chatcompletion_v2"
-MINIMAX_API_KEY = os.environ.get('MINIMAX_API_KEY', '')
-
-async def analyze_food_photo(file_path: str) -> Dict:
-    """
-    Analyze food photo using MiniMax Vision API
-    
-    Returns: Dict with calories, carbs, protein, fat estimation
-    """
-    if not MINIMAX_API_KEY:
-        # Fallback to placeholder if no API key
-        return {
-            'calories': 400,
-            'carbs': 25,
-            'protein': 30,
-            'fat': 20,
-            'detected_foods': ['food (placeholder - add MiniMax API key)'],
-            'confidence': 0.5
-        }
-    
-    try:
-        import base64
-        
-        # Read and encode image
-        with open(file_path, 'rb') as f:
-            image_b64 = base64.b64encode(f.read()).decode('utf-8')
-        
-        # Prepare vision prompt
-        prompt = """Analyze this food image and estimate nutrition:
-        1. What foods are in the image?
-        2. Estimate: calories, carbs (g), protein (g), fat (g)
-        3. Keto-friendly? (yes/no)
-        
-        Return JSON format:
-        {
-            "foods": ["item1", "item2"],
-            "calories": number,
-            "carbs": number,
-            "protein": number,
-            "fat": number,
-            "keto_friendly": boolean,
-            "confidence": 0.0-1.0
-        }"""
-        
-        # Call MiniMax API
-        headers = {
-            "Authorization": f"Bearer {MINIMAX_API_KEY}",
-            "Content-Type": "application/json"
-        }
-        
-        payload = {
-            "model": "MiniMax-Vision-01",
-            "messages": [
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": prompt},
-                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}}
-                    ]
-                }
-            ],
-            "max_tokens": 500,
-            "temperature": 0.3
-        }
-        
-        import httpx
-        async with httpx.AsyncClient() as client:
-            response = await client.post(
-                MINIMAX_API_URL,
-                headers=headers,
-                json=payload,
-                timeout=30.0
-            )
-            
-            if response.status_code == 200:
-                result = response.json()
-                # Parse JSON from response
-                content = result.get('choices', [{}])[0].get('message', {}).get('content', '{}')
-                
-                # Extract JSON
-                import json as json_module
-                try:
-                    # Try to parse the response as JSON
-                    nutrition = json_module.loads(content)
-                    return {
-                        'calories': nutrition.get('calories', 400),
-                        'carbs': nutrition.get('carbs', 25),
-                        'protein': nutrition.get('protein', 30),
-                        'fat': nutrition.get('fat', 20),
-                        'detected_foods': nutrition.get('foods', ['unknown']),
-                        'confidence': nutrition.get('confidence', 0.8),
-                        'keto_friendly': nutrition.get('keto_friendly', True)
-                    }
-                except json_module.JSONDecodeError:
-                    # Fallback if JSON parsing fails
-                    return {
-                        'calories': 400,
-                        'carbs': 25,
-                        'protein': 30,
-                        'fat': 20,
-                        'detected_foods': ['analyzed via MiniMax'],
-                        'confidence': 0.7
-                    }
-            else:
-                print(f"MiniMax API error: {response.status_code}")
-                return {
-                    'calories': 400,
-                    'carbs': 25,
-                    'protein': 30,
-                    'fat': 20,
-                    'detected_foods': ['analysis failed - using defaults'],
-                    'confidence': 0.5
-                }
-                
-    except Exception as e:
-        print(f"Photo analysis error: {e}")
-        return {
-            'calories': 400,
-            'carbs': 25,
-            'protein': 30,
-            'fat': 20,
-            'detected_foods': ['error - using defaults'],
-            'confidence': 0.5
-        }
-
-async def food_photo(update: Update, context: ContextTypes.DEFAULT_TYPE):
-    """Handle food photo upload and analysis"""
-    user_id = str(update.message.from_user.id)
-    today = datetime.datetime.now().strftime('%Y-%m-%d')
-    now = datetime.datetime.now().strftime('%H:%M')
-    
-    # Determine meal type
-    hour = datetime.datetime.now().hour
-    if 5 <= hour < 11:
-        meal_type = 'breakfast'
-    elif 11 <= hour < 14:
-        meal_type = 'lunch'
-    elif 14 <= hour < 17:
-        meal_type = 'snack'
-    else:
-        meal_type = 'dinner'
-    
-    # Get photo
-    photo = update.message.photo[-1] if update.message.photo else None
-    if not photo:
-        await update.message.reply_text("❌ No photo found! Please send a food photo.")
-        return
-    
-    await update.message.reply_text("📸 Analyzing food photo...")
-    
-    try:
-        # Download photo
-        file = await context.bot.get_file(photo.file_id)
-        file_path = f"/tmp/food_{user_id}_{today}.jpg"
-        await file.download_to_drive(file_path)
-        
-        # Analyze with MiniMax Vision API
-        nutrition = await analyze_food_photo(file_path)
-        
-        # Log the food
-        if user_id not in data.food_logs:
-            data.food_logs[user_id] = {}
-        if today not in data.food_logs[user_id]:
-            data.food_logs[user_id][today] = []
-        
-        data.food_logs[user_id][today].append({
-            'meal_type': meal_type,
-            'food_name': ', '.join(nutrition.get('detected_foods', ['food'])),
-            'time': now,
-            'calories': nutrition['calories'],
-            'carbs': nutrition['carbs'],
-            'protein': nutrition['protein'],
-            'fat': nutrition['fat'],
-            'source': 'photo',
-            'confidence': nutrition.get('confidence', 0.8),
-            'timestamp': datetime.datetime.now().isoformat()
-        })
-        data.save()
-        
-        # Build response
-        emoji = "✅" if nutrition.get('keto_friendly', True) else "⚠️"
-        confidence_pct = int(nutrition.get('confidence', 0.8) * 100)
-        
-        text = f"🍽️ **Food Analyzed**\n\n"
-        text += f"Detected: {', '.join(nutrition.get('detected_foods', ['food']))}\n"
-        text += f"Confidence: {confidence_pct}%\n\n"
-        text += f"📊 **Nutrition:**\n"
-        text += f"🔥 Calories: {nutrition['calories']}kcal\n"
-        text += f"🥦 Carbs: {nutrition['carbs']}g\n"
-        text += f"💪 Protein: {nutrition['protein']}g\n"
-        text += f"🥑 Fat: {nutrition['fat']}g\n\n"
-        text += f"{emoji} Keto-friendly: {'Yes' if nutrition.get('keto_friendly', True) else 'No'}\n"
-        
-        # Keto check
-        if nutrition['carbs'] > 25:
-            text += "\n⚠️ Carbs exceed keto limit (25g)!"
-        
-        # Daily total
-        total = data.get_daily_totals(user_id, today)
-        text += f"\n📈 **Today's Total:** {total['calories']}kcal"
-        text += f"\n💪 {2000 - total['calories']}kcal remaining"
-        
-        await update.message.reply_text(text, parse_mode='Markdown')
-        
-        # Clean up
-        import os
-        if os.path.exists(file_path):
-            os.remove(file_path)
-            
-    except Exception as e:
-        await update.message.reply_text(f"❌ Error analyzing photo: {str(e)}")
-
 async def food_today(update: Update, context: ContextTypes.DEFAULT_TYPE):
     """Show today's food log"""
     user_id = str(update.message.from_user.id)
@@ -821,7 +590,7 @@ def main():
         print("Bot code is ready but cannot run without the library.")
         return
     
-    app = Application.builder().token(TELEGRAM_BOT_TOKEN).build()
+    app = Application.builder().token(TELEGRAM_TOKEN).build()
     
     # Commands
     app.add_handler(CommandHandler('start', start_command))
@@ -833,17 +602,12 @@ def main():
     app.add_handler(CommandHandler('habit_streak', habit_streak))
     app.add_handler(CommandHandler('food', food_log))
     app.add_handler(CommandHandler('food_today', food_today))
-    app.add_handler(CommandHandler('food_photo', food_photo))
     app.add_handler(CommandHandler('morning', morning_briefing))
     app.add_handler(CommandHandler('debrief', debrief))
     app.add_handler(CommandHandler('status', lambda u, c: food_today(u, c)))  # Alias
     
-    # Photo handler (for food photos)
-    from telegram.ext import.filters
-    app.add_handler(MessageHandler(filters.PHOTO, food_photo))
-    
     # URL handler
-    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_url))
+    app.add_handler(MessageHandler(None, handle_url))
     
     print("🔮 Starting Habit & Diet Bot...")
     app.run_polling()