Update app.py

app.py

@@ -3,31 +3,30 @@ import os
 from huggingface_hub import HfApi
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-# Hugging Face token and space info
-HF_TOKEN = "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"
-HF_SPACE = "Hardik5456/Wan2.1playground"
-
-# Initialize Hugging Face API
-api = HfApi(token=HF_TOKEN)
-
 # We'll use Mistral-7B as it's a good balance of quality and performance
 MODEL_NAME = "mistralai/Mistral-7B-Instruct-v0.2"
 
-# Load configuration content
-with open("spectral_satya_gpt_configuration.md", "r") as f:
-    config_content = f.read()
-
-with open("spectral_satya_book_integration.md", "r") as f:
-    book_integration = f.read()
-
-with open("spectral_satya_prompt_examples.md", "r") as f:
-    prompt_examples = f.read()
-
 # System prompt that incorporates the configuration
-SYSTEM_PROMPT = f"""
+SYSTEM_PROMPT = """
 You are Spectral Satya, a specialized AI assistant focused on crafting cinematic reality through expert prompt engineering for AI video generation.
 
-{config_content}
+Your primary purpose is to help users create highly realistic, professional-quality cinematic scene prompts for platforms including RunwayML, Pika, Kling, Haiper, Vidu, Veo, PixVerse, and other T2V/I2V models.
+
+Core Principles:
+- Realism Above All: Always prioritize photorealistic, cinematic quality over stylized or animated looks
+- Specificity is King: Eliminate vagueness in all prompts; be precise about subjects, actions, environments, camera work, and lighting
+- Show, Don't Tell: Use visual language that paints clear pictures rather than abstract concepts
+- Defensive Prompting: Always include robust negative prompts to ward off unwanted styles and artifacts
+
+Always structure prompts with these essential elements:
+1. Style Declaration: Begin with "cinematic, photorealistic" or similar terms establishing the desired realism
+2. Camera Specifications: Include shot type, angle, movement, and focus details
+3. Subject Definition: Clearly define characters/subjects with specific visual attributes
+4. Action Description: Detail precise movements and interactions
+5. Environment Details: Describe setting with specific visual elements
+6. Lighting & Atmosphere: Specify lighting conditions, mood, and atmospheric elements
+7. Color & Grading: Include color palette or grading style information
+8. Negative Prompts: Always provide comprehensive negative prompting to prevent unwanted styles
 
 Your responses should follow the principles and techniques outlined in "The Prompt Engineer's Codex: Crafting Cinematic Reality with AI Video".
 """
@@ -132,72 +131,8 @@ def generate_cinematic_prompt(scene_description, subject_details, camera_prefere
     
     return response
 
-def show_examples():
-    """Return example prompts from the configuration."""
-    return prompt_examples
-
-# Define the Gradio interface
-with gr.Blocks(title="Spectral Satya - Cinematic Prompt Engineer") as demo:
-    gr.Markdown("# 🎬 Spectral Satya - Cinematic Prompt Engineer")
-    gr.Markdown("### Your specialized AI assistant for crafting cinematic reality through expert prompt engineering")
-    
-    with gr.Tab("Chat Interface"):
-        chatbot = gr.Chatbot(height=500)
-        msg = gr.Textbox(label="Ask about cinematic prompting or request prompt creation", placeholder="e.g., 'Create a cinematic prompt for a detective in a rainy alleyway'")
-        clear = gr.Button("Clear")
-        
-        msg.submit(spectral_satya_chat, [msg, chatbot], [msg, chatbot])
-        clear.click(lambda: None, None, chatbot, queue=False)
-    
-    with gr.Tab("Prompt Generator"):
-        with gr.Row():
-            with gr.Column():
-                scene_description = gr.Textbox(label="Scene Description", placeholder="Describe the overall scene you want to create", lines=3)
-                subject_details = gr.Textbox(label="Subject Details", placeholder="Describe the main character/subject in detail", lines=2)
-                camera_preferences = gr.Textbox(label="Camera Preferences", placeholder="Any specific shot types, angles, or movements", lines=2)
-                lighting_mood = gr.Textbox(label="Lighting and Mood", placeholder="Describe the lighting conditions and emotional tone", lines=2)
-                platform = gr.Dropdown(
-                    label="Target Platform", 
-                    choices=["RunwayML", "Pika", "Kling", "Haiper", "Vidu", "Veo", "PixVerse", "Any/Universal"],
-                    value="Any/Universal"
-                )
-                generate_btn = gr.Button("Generate Cinematic Prompt")
-            
-            with gr.Column():
-                output = gr.Textbox(label="Generated Prompt", lines=15)
-        
-        generate_btn.click(
-            generate_cinematic_prompt, 
-            [scene_description, subject_details, camera_preferences, lighting_mood, platform], 
-            output
-        )
-    
-    with gr.Tab("Example Prompts"):
-        examples_output = gr.Markdown()
-        show_examples_btn = gr.Button("Show Example Prompts")
-        show_examples_btn.click(show_examples, None, examples_output)
-    
-    with gr.Tab("About"):
-        gr.Markdown("""
-        ## About Spectral Satya
-        
-        Spectral Satya is a specialized AI assistant focused on crafting cinematic reality through expert prompt engineering for AI video generation. Drawing from "The Prompt Engineer's Codex," Spectral Satya helps users create highly realistic, professional-quality cinematic scene prompts for platforms including RunwayML, Pika, Kling, Haiper, Vidu, Veo, PixVerse, and other T2V/I2V models.
-        
-        ### Core Principles
-        
-        - **Realism Above All**: Always prioritizes photorealistic, cinematic quality
-        - **Specificity is King**: Eliminates vagueness in all prompts
-        - **Show, Don't Tell**: Uses visual language that paints clear pictures
-        - **Defensive Prompting**: Includes robust negative prompts to ward off unwanted styles
-        
-        ### How to Use
-        
-        1. **Chat Interface**: Ask questions about cinematic prompting or request specific prompts
-        2. **Prompt Generator**: Fill in the form fields to generate structured cinematic prompts
-        3. **Example Prompts**: Browse example prompts across different scenarios
-        
-        Created by Hardik Kumawat
-        """)
+# Define example prompts
+EXAMPLE_PROMPTS = """
+# Example Cinematic Prompts
 
-# Launch the app
-demo.launch()
+## Urban Character Scene