Update app.py

app.py

@@ -172,13 +172,13 @@ def get_image_prompt(sentiment, transcribed_text, chunk_idx, total_chunks):
     base_prompt = f"Chunk {chunk_idx+1}/{total_chunks}: "
     
     if sentiment == "positive":
-        return   f"Generate a carbon sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use low histogram frequency in bright bins, dominant color in high RGB range, and high brightness and color variance. Apply high-frequency texture with strong filter energy, pronounced gradient magnitude, and strong local contrast. Use high spatial complexity, increased horizontal and vertical symmetry, high edge density, bright gray levels, and high contrast. Emphasize rich visual structure, color variation, and texture intensity across spatial composition."
+        return   f"Generate an equirectangular 360° panoramic graphite sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use low histogram frequency in bright bins, dominant color in high RGB range, and high brightness and color variance. Apply high-frequency texture with strong filter energy, pronounced gradient magnitude, and strong local contrast. Use high spatial complexity, increased horizontal and vertical symmetry, high edge density, bright gray levels, and high contrast. Emphasize rich visual structure, color variation, and texture intensity across spatial composition."
     
     elif sentiment == "negative":
-        return  f"Generate a carbon sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use high histogram frequency in dark bins, dominant color in low RGB range, and low brightness and color variance. Apply low-frequency texture with low filter energy, weak gradient magnitude, and low local contrast. Use low spatial complexity, reduced horizontal and vertical symmetry, low edge density, dark gray levels, and moderate contrast. Emphasize coarse structure and limited variation in color, texture, and spatial distribution."
+        return  f"Generate an equirectangular 360° panoramic graphite sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use high histogram frequency in dark bins, dominant color in low RGB range, and low brightness and color variance. Apply low-frequency texture with low filter energy, weak gradient magnitude, and low local contrast. Use low spatial complexity, reduced horizontal and vertical symmetry, low edge density, dark gray levels, and moderate contrast. Emphasize coarse structure and limited variation in color, texture, and spatial distribution."
     
     else:  # neutral
-        return  f"Generate a carbon sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use a balanced histogram frequency across bins, dominant color in a mid RGB range, and moderate brightness and color variance. Apply medium-frequency texture with moderate filter energy, standard gradient magnitude, and average local contrast. Use medium spatial complexity, balanced horizontal and vertical symmetry, medium edge density, mid-range gray levels, and standard contrast. Emphasize naturalistic structure and typical variation in color, texture, and spatial distribution."
+        return  f"Generate an equirectangular 360° panoramic graphite sketch drawing, detailed pencil texture with faint neon glows, cinematic lighting of:{transcribed_text}. Use a balanced histogram frequency across bins, dominant color in a mid RGB range, and moderate brightness and color variance. Apply medium-frequency texture with moderate filter energy, standard gradient magnitude, and average local contrast. Use medium spatial complexity, balanced horizontal and vertical symmetry, medium edge density, mid-range gray levels, and standard contrast. Emphasize naturalistic structure and typical variation in color, texture, and spatial distribution."
 
 # Function to get music prompt based on emotion
 def get_music_prompt(emotion, transcribed_text, chunk_idx, total_chunks):