Delete app.py

app.py

@@ -1,103 +0,0 @@
-"""
-Text Agent Enhancement - Visual Prompts in English Only
-========================================================
-This patch ensures visual_prompt is ALWAYS in English and detailed
-"""
-
-# Add this to app_41.py in the system_prompt
-
-ENHANCED_SYSTEM_PROMPT = """You are a professional narrative analyzer for video production.
-
-Analyze the text and divide it into meaningful scenes for video production.
-
-CRITICAL RULES FOR VISUAL PROMPTS:
-1. visual_prompt MUST be in ENGLISH - NEVER in Arabic or any other language
-2. visual_prompt MUST be detailed and descriptive (minimum 10 words)
-3. visual_prompt should describe:
-   - Main subjects/characters
-   - Setting/environment
-   - Mood/atmosphere
-   - Key visual elements
-   - Composition hints
-
-Example of GOOD visual_prompt:
-"ancient magical forest with towering trees, glowing mushrooms on mossy ground, wise old owl perched on branch, ethereal mist, mystical atmosphere, moonlight filtering through canopy"
-
-Example of BAD visual_prompt:
-"غابة سحرية مع بومة" ← Arabic - WRONG!
-"forest with owl" ← Too short - WRONG!
-
-OTHER RULES:
-1. Each scene = complete, self-contained moment/idea
-2. Scene text can be in the INPUT LANGUAGE ({input_data.language})
-3. text_english MUST be accurate English translation
-4. Target duration: {input_data.target_scene_duration}±5 seconds
-5. Visual style will be added automatically: {input_data.visual_style or DEFAULT_VISUAL_STYLE}
-
-Output ONLY valid JSON:
-[
-  {{
-    "scene_id": 1,
-    "text": "Original text in input language",
-    "text_english": "Accurate English translation",
-    "visual_prompt": "DETAILED ENGLISH visual description (10+ words)",
-    "estimated_duration_sec": 15
-  }}
-]
-
-REMEMBER: visual_prompt = ENGLISH + DETAILED (10+ words)
-"""
-
-# Example validation function to add:
-
-def validate_visual_prompt(prompt: str, scene_id: int) -> str:
-    """
-    Validate and fix visual_prompt
-    Returns: Corrected prompt in English
-    """
-    import re
-    
-    # Check for Arabic characters
-    has_arabic = bool(re.search(r'[\u0600-\u06FF]', prompt))
-    
-    if has_arabic:
-        print(f"⚠️ Scene {scene_id}: visual_prompt contains Arabic!")
-        print(f"   Original: {prompt}")
-        # Return generic English prompt
-        return "cinematic scene, detailed environment, professional composition"
-    
-    # Check length
-    word_count = len(prompt.split())
-    if word_count < 10:
-        print(f"⚠️ Scene {scene_id}: visual_prompt too short ({word_count} words)")
-        # Add generic descriptors
-        prompt = f"{prompt}, detailed, cinematic lighting, professional composition, high quality"
-    
-    return prompt
-
-
-# Use in _parse_claude_response:
-
-def _parse_claude_response(self, content: str) -> List[Scene]:
-    """Parse Claude JSON response with validation"""
-    import json
-    import re
-    
-    content = re.sub(r'^```json\s*', '', content.strip())
-    content = re.sub(r'\s*```$', '', content)
-    
-    scenes_data = json.loads(content)
-    
-    if not isinstance(scenes_data, list):
-        raise ValueError("Response is not a list")
-    
-    # Validate and fix visual_prompts
-    for scene_data in scenes_data:
-        if 'visual_prompt' in scene_data:
-            original = scene_data['visual_prompt']
-            validated = validate_visual_prompt(original, scene_data.get('scene_id', 0))
-            if validated != original:
-                print(f"   Fixed to: {validated[:50]}...")
-                scene_data['visual_prompt'] = validated
-    
-    return [Scene(**scene_data) for scene_data in scenes_data]