Update app.py

app.py

@@ -1,60 +1,11 @@
-# Install necessary packages
-# !pip install huggingface_hub gradio pillow
-
+import os
 from huggingface_hub import InferenceClient
 import gradio as gr
 import random
-import json
 import logging
 import sys
-import os
-
-# Set up logging
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[logging.StreamHandler(sys.stdout)]
-)
-logger = logging.getLogger("visual_studio")
 
-# Setting up model clients
-def setup_client(api_key, provider=None):
-    try:
-        if provider:
-            client = InferenceClient(provider=provider, api_key=api_key)
-            logger.info(f"{provider} client initialized successfully")
-        else:
-            client = InferenceClient(api_key=api_key)
-            logger.info("Hugging Face client initialized successfully")
-        return client
-    except Exception as e:
-        logger.error(f"Error initializing client: {str(e)}")
-        return None
-
-# Initialize clients
-try:
-    # Replace with your actual HF API key
-    hf_api_key = os.getenv("HF_API_KEY1")
-    hf_client = setup_client(hf_api_key)
-    logger.info("Hugging Face client created successfully")
-    
-    # Set up Llama client if API key is provided
-    llama_api_key = os.getenv("HF_API_KEY2")  # Replace with actual key if available
-    try:
-        llama_client = setup_client(llama_api_key, "sambanova")
-        use_llama = True
-        logger.info("Llama client created successfully")
-    except Exception as e:
-        logger.warning(f"Llama client not available: {str(e)}. Will use fallback enhancement.")
-        llama_client = None
-        use_llama = False
-except Exception as e:
-    logger.error(f"Failed to create Hugging Face client: {str(e)}")
-    hf_client = None
-    llama_client = None
-    use_llama = False
-
-# Only Hugging Face hosted models
+# Define your dictionaries for image models, creation types, and art styles
 IMAGE_MODELS = {
     "stabilityai/stable-diffusion-xl-base-1.0": "SDXL (Best Quality)",
     "runwayml/stable-diffusion-v1-5": "Stable Diffusion 1.5 (Balanced)",
@@ -63,7 +14,6 @@ IMAGE_MODELS = {
     "dreamlike-art/dreamlike-diffusion-1.0": "Dreamlike Diffusion (Artistic)"
 }
 
-# Creation types 
 CREATION_TYPES = {
     "Realistic Photo": "Create a photorealistic image with natural details and lighting",
     "Digital Art": "Create colorful digital artwork with clean lines and vibrant colors",
@@ -77,7 +27,6 @@ CREATION_TYPES = {
     "Pixel Art": "Create retro-style pixel art with limited color palette"
 }
 
-# Art styles with detailed descriptions for better Llama prompt enhancement
 ART_STYLES = {
     "Photorealistic": "detailed realistic style that resembles a photograph with accurate lighting and textures",
     "Impressionist": "soft brushstrokes that capture light and atmosphere over precise details, like Monet",
@@ -87,140 +36,73 @@ ART_STYLES = {
     "Abstract": "non-representational style using shapes, colors, and forms to express ideas",
     "Cubist": "geometric shapes and multiple perspectives shown simultaneously, like Picasso",
     "Art Nouveau": "ornate, flowing lines inspired by natural forms with decorative elegance",
-    "Gothic": "dark, medieval-inspired aesthetic with dramatic lighting and architectural elements",
+    "Gothic": "gothic style with dark atmosphere and dramatic elements",
     "Cyberpunk": "futuristic dystopian style with neon colors, technology, and urban decay",
-    "Steampunk": "Victorian-era aesthetic combined with steam-powered technology and brass elements",
+    "Steampunk": "steampunk style with Victorian aesthetics and brass machinery",
     "Retro/Vintage": "nostalgic style reminiscent of past decades with period-appropriate elements",
-    "Art Deco": "geometric patterns, bold colors, and luxurious materials in a symmetrical style",
-    "Baroque": "dramatic, ornate style with rich details, contrast, and dynamic composition",
+    "Art Deco": "art deco style with geometric patterns, bold colors, and luxurious materials",
+    "Baroque": "baroque style with dramatic lighting and rich ornamentation",
     "Ukiyo-e": "traditional Japanese woodblock print style with flat areas of color and strong outlines",
-    "Comic Book": "bold outlines, bright colors, and action-oriented composition like classic comics",
-    "Psychedelic": "vibrant, swirling colors with abstract patterns inspired by 1960s art",
-    "Vaporwave": "glitch aesthetics with pastel colors, 80s/90s nostalgia and digital elements",
-    "Studio Ghibli": "whimsical, detailed animation style inspired by Japanese animated films",
-    "Hyperrealism": "extremely detailed realism that exceeds photograph-like precision"
+    "Comic Book": "comic book style with bold outlines and vibrant colors",
+    "Psychedelic": "psychedelic style with vibrant swirling colors and abstract patterns",
+    "Vaporwave": "vaporwave aesthetic with glitch art and 80s/90s nostalgia",
+    "Studio Ghibli": "Studio Ghibli anime style with whimsical detailed environments",
+    "Hyperrealism": "hyperrealistic style with extreme detail beyond photography"
 }
 
-# Function to enhance prompt with Llama 4 with improved logical understanding
-def enhance_prompt_with_llama(user_input, creation_type, art_style, mood):
-    try:
-        if not use_llama or llama_client is None:
-            logger.warning("Llama enhancement not available, using fallback")
-            return enhance_prompt_fallback(user_input, creation_type, art_style, mood)
-        
-        logger.info(f"Enhancing prompt with Llama 4 for creation type: {creation_type}, art style: {art_style}")
-        
-        # Enhanced Llama 4 system prompt
-        system_prompt = """You are a world-class prompt engineer who specializes in creating detailed, effective prompts for text-to-image AI models. 
-
-Your task is to transform a user's simple description into a comprehensive, detailed image generation prompt that will create stunning visuals. Consider all the provided elements (description, creation type, art style, mood) and combine them into a cohesive, detailed prompt.
-
-MOST IMPORTANTLY - ADD LOGICAL DETAILS:
-- Analyze what the user wants and add logical details that would make the scene realistic or coherent
-- If describing something fantastical (e.g., "flying cat"), add logical details about how this could work (e.g., "a cat with majestic feathered wings spread wide")
-- Think about environment, lighting, perspective, time of day, weather, and other contextual elements
-- Create a vivid, imaginable scene with spatial relationships clearly defined
-
-PROMPT STRUCTURE GUIDELINES:
-1. Start with the core subject and its primary characteristics
-2. Add environment and setting details
-3. Describe lighting, atmosphere, and mood
-4. Include specific visual style and artistic technique references
-5. Add technical quality terms (8K, detailed, masterful, etc.)
-
-FORMAT YOUR RESPONSE AS A SINGLE PARAGRAPH with no additional comments, explanations, or bullet points. Use natural language without awkward comma separations. Aim for 75-150 words.
-
-AVOID:
-- Do not include quotation marks in your response
-- Do not preface with "here's a prompt" or similar text
-- Do not use placeholders
-- Do not add negative prompts
-- Do not write in list format or use bullet points
-
-Respond only with the enhanced prompt and nothing else."""
+# Set up logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[logging.StreamHandler(sys.stdout)]
+)
+logger = logging.getLogger("nostalgia_nexus")
 
-        # Creation type description
-        creation_description = CREATION_TYPES.get(creation_type, "Create a detailed image")
-        
-        # Art style description
-        style_description = ART_STYLES.get(art_style, "with detailed and professional quality")
-        
-        # Prepare the user prompt for Llama
-        user_prompt = f"""Description: {user_input}
-Creation Type: {creation_type} - {creation_description}
-Art Style: {art_style} - {style_description}
-Mood: {mood}
+# Setup client function
+def setup_client(api_key, provider=None):
+    try:
+        if provider:
+            client = InferenceClient(provider=provider, api_key=api_key)
+            logger.info(f"{provider} client initialized successfully")
+        else:
+            client = InferenceClient(api_key=api_key)
+            logger.info("Hugging Face client initialized successfully")
+        return client
+    except Exception as e:
+        logger.error(f"Error initializing client: {str(e)}")
+        return None
 
-Please create a comprehensive, detailed image generation prompt that combines all these elements."""
+# Initialize clients
+hf_api_key = os.getenv("HF_API_KEY1") or "your_hf_api_key_here"
+hf_client = setup_client(hf_api_key)
+logger.info("Hugging Face client created successfully")
 
-        try:
-            completion = llama_client.chat.completions.create(
-                model="meta-llama/Llama-4-Scout-17B-16E-Instruct",
-                messages=[
-                    {"role": "system", "content": system_prompt},
-                    {"role": "user", "content": user_prompt}
-                ],
-                max_tokens=500,
-            )
-            enhanced = completion.choices[0].message.content
-            logger.info(f"Llama 4 enhanced prompt: {enhanced[:100]}...")
-            return enhanced if enhanced else user_input
-        except Exception as e:
-            logger.error(f"Error during Llama enhancement: {str(e)}")
-            return enhance_prompt_fallback(user_input, creation_type, art_style, mood)
-    except Exception as e:
-        logger.error(f"Error in Llama enhancement: {str(e)}")
-        return enhance_prompt_fallback(user_input, creation_type, art_style, mood)
+# (Optional) Setup Llama client if available
+llama_api_key = os.getenv("HF_API_KEY2") or "your_llama_api_key_here"
+try:
+    llama_client = setup_client(llama_api_key, "sambanova")
+    use_llama = True
+    logger.info("Llama client created successfully")
+except Exception as e:
+    logger.warning(f"Llama client not available: {str(e)}. Will use fallback enhancement.")
+    llama_client = None
+    use_llama = False
 
-# Fallback prompt enhancement without Llama
+# Fallback prompt enhancement function
 def enhance_prompt_fallback(user_input, creation_type, art_style, mood):
     logger.info(f"Using fallback enhancement for: {user_input[:50]}...")
-    
-    # Quality terms by creation type
     quality_terms = {
-        "Realistic Photo": [
-            "photorealistic", "high resolution", "detailed", 
-            "natural lighting", "sharp focus", "professional photography"
-        ],
-        "Digital Art": [
-            "vibrant colors", "clean lines", "digital illustration", 
-            "polished", "professional digital art", "detailed rendering"
-        ],
-        "Fantasy Illustration": [
-            "magical atmosphere", "fantasy art", "detailed illustration", 
-            "epic", "otherworldly", "imaginative scene"
-        ],
-        "Concept Art": [
-            "professional concept art", "detailed design", "conceptual illustration", 
-            "industry standard", "visual development", "production artwork"
-        ],
-        "Anime/Manga": [
-            "anime style", "manga illustration", "cel shaded", 
-            "Japanese animation", "2D character art", "anime aesthetic"
-        ],
-        "Oil Painting": [
-            "oil on canvas", "textured brushwork", "rich colors", 
-            "traditional painting", "artistic brushstrokes", "gallery quality"
-        ],
-        "Watercolor": [
-            "watercolor painting", "soft color bleeding", "delicate washes", 
-            "transparent layers", "loose brushwork", "gentle transitions"
-        ],
-        "Sketch": [
-            "detailed sketch", "pencil drawing", "line art", 
-            "hand-drawn", "fine details", "shading techniques"
-        ],
-        "3D Rendering": [
-            "3D render", "volumetric lighting", "ray tracing", 
-            "3D modeling", "realistic textures", "computer graphics"
-        ],
-        "Pixel Art": [
-            "pixel art", "8-bit style", "retro game aesthetic", 
-            "limited color palette", "pixelated", "nostalgic game art"
-        ]
+        "Realistic Photo": ["photorealistic", "high resolution", "detailed", "natural lighting", "sharp focus", "professional photography"],
+        "Digital Art": ["vibrant colors", "clean lines", "digital illustration", "polished", "professional digital art", "detailed rendering"],
+        "Fantasy Illustration": ["magical atmosphere", "fantasy art", "detailed illustration", "epic", "otherworldly", "imaginative scene"],
+        "Concept Art": ["professional concept art", "detailed design", "conceptual illustration", "industry standard", "visual development", "production artwork"],
+        "Anime/Manga": ["anime style", "manga illustration", "cel shaded", "Japanese animation", "2D character art", "anime aesthetic"],
+        "Oil Painting": ["oil on canvas", "textured brushwork", "rich colors", "traditional painting", "artistic brushstrokes", "gallery quality"],
+        "Watercolor": ["watercolor painting", "soft color bleeding", "delicate washes", "transparent layers", "loose brushwork", "gentle transitions"],
+        "Sketch": ["detailed sketch", "pencil drawing", "line art", "hand-drawn", "fine details", "shading techniques"],
+        "3D Rendering": ["3D render", "volumetric lighting", "ray tracing", "3D modeling", "realistic textures", "computer graphics"],
+        "Pixel Art": ["pixel art", "8-bit style", "retro game aesthetic", "limited color palette", "pixelated", "nostalgic game art"]
     }
-    
-    # Style modifiers for different art styles
     style_modifiers = {
         "Photorealistic": "highly detailed photorealistic style with perfect lighting",
         "Impressionist": "impressionist style with visible brushstrokes capturing light and atmosphere",
@@ -243,8 +125,6 @@ def enhance_prompt_fallback(user_input, creation_type, art_style, mood):
         "Studio Ghibli": "Studio Ghibli anime style with whimsical detailed environments",
         "Hyperrealism": "hyperrealistic style with extreme detail beyond photography"
     }
-    
-    # Mood modifiers for different moods
     mood_modifiers = {
         "Happy": "bright cheerful atmosphere with warm colors",
         "Sad": "melancholic atmosphere with muted colors",
@@ -257,184 +137,209 @@ def enhance_prompt_fallback(user_input, creation_type, art_style, mood):
         "Romantic": "soft romantic atmosphere with dreamy lighting",
         "Epic": "grand epic atmosphere with dramatic scale"
     }
-    
-    # Get terms for the specific creation type, or use generic terms
-    type_terms = quality_terms.get(creation_type, [
-        "high quality", "detailed", "professional", "masterful"
-    ])
-    
-    # Common quality terms
-    common_terms = [
-        "8K resolution", "highly detailed", "professional",
-        "trending on artstation", "masterpiece"
-    ]
-    
-    # Get style modifier
+    type_terms = quality_terms.get(creation_type, ["high quality", "detailed", "professional", "masterful"])
+    common_terms = ["8K resolution", "highly detailed", "professional", "trending on artstation", "masterpiece"]
     style_modifier = style_modifiers.get(art_style, "detailed style")
-    
-    # Get mood modifier
     mood_modifier = mood_modifiers.get(mood, "atmospheric")
-    
-    # Basic prompt structure
-    prompt_parts = [
-        user_input,
-        style_modifier,
-        mood_modifier
-    ]
-    
-    # Add randomly selected quality terms
+    prompt_parts = [user_input, style_modifier, mood_modifier]
     selected_type_terms = random.sample(type_terms, min(3, len(type_terms)))
     selected_common_terms = random.sample(common_terms, min(2, len(common_terms)))
-    
-    # Combine terms
     quality_description = ", ".join(selected_type_terms + selected_common_terms)
-    
-    # Final enhanced prompt
     enhanced_prompt = f"{', '.join(prompt_parts)}, {quality_description}"
-    
     logger.info(f"Fallback enhanced prompt: {enhanced_prompt[:100]}...")
     return enhanced_prompt
 
+# Llama prompt enhancement function
+def enhance_prompt_with_llama(user_input, creation_type, art_style, mood):
+    try:
+        if not use_llama or llama_client is None:
+            logger.warning("Llama enhancement not available, using fallback")
+            return enhance_prompt_fallback(user_input, creation_type, art_style, mood)
+        logger.info(f"Enhancing prompt with Llama 4 for creation type: {creation_type}, art style: {art_style}")
+        system_prompt = """You are a world-class prompt engineer who specializes in creating detailed, effective prompts for text-to-image AI models.
+
+Your task is to transform a user's simple description into a comprehensive, detailed image generation prompt that will create stunning visuals. Consider all the provided elements (description, creation type, art style, mood) and combine them into a cohesive, detailed prompt.
+
+MOST IMPORTANTLY - ADD LOGICAL DETAILS:
+- Analyze what the user wants and add logical details that would make the scene realistic or coherent
+- If describing something fantastical (e.g., "flying cat"), add logical details about how this could work (e.g., "a cat with majestic feathered wings spread wide")
+- Think about environment, lighting, perspective, time of day, weather, and other contextual elements
+- Create a vivid, imaginable scene with spatial relationships clearly defined
+
+PROMPT STRUCTURE GUIDELINES:
+1. Start with the core subject and its primary characteristics
+2. Add environment and setting details
+3. Describe lighting, atmosphere, and mood
+4. Include specific visual style and artistic technique references
+5. Add technical quality terms (8K, detailed, masterful, etc.)
+
+FORMAT YOUR RESPONSE AS A SINGLE PARAGRAPH with no additional comments, explanations, or bullet points. Use natural language without awkward comma separations. Aim for 75-150 words.
+
+AVOID:
+- Do not include quotation marks in your response
+- Do not preface with "here's a prompt" or similar text
+- Do not use placeholders
+- Do not add negative prompts
+- Do not write in list format or use bullet points
+
+Respond only with the enhanced prompt and nothing else."""
+        creation_description = CREATION_TYPES.get(creation_type, "Create a detailed image")
+        style_description = ART_STYLES.get(art_style, "with detailed and professional quality")
+        user_prompt = f"Description: {user_input}\nCreation Type: {creation_type} - {creation_description}\nArt Style: {art_style} - {style_description}\nMood: {mood}\n\nPlease create a comprehensive, detailed image generation prompt that combines all these elements."
+        completion = llama_client.chat.completions.create(
+            model="meta-llama/Llama-4-Scout-17B-16E-Instruct",
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_prompt}
+            ],
+            max_tokens=500,
+        )
+        enhanced = completion.choices[0].message.content
+        logger.info(f"Llama 4 enhanced prompt: {enhanced[:100]}...")
+        return enhanced if enhanced else user_input
+    except Exception as e:
+        logger.error(f"Error during Llama enhancement: {str(e)}")
+        return enhance_prompt_fallback(user_input, creation_type, art_style, mood)
+
 # Generate image function
 def generate_image(description, creation_type, art_style, mood, model_name):
     try:
         logger.info(f"Generating image with model: {model_name}")
-        
-        # Use Llama 4 for prompt enhancement with all inputs
         enhanced_prompt = enhance_prompt_with_llama(description, creation_type, art_style, mood)
-        
-        # Check if client is available
         if hf_client is None:
             logger.error("Hugging Face client not available")
             return None, "Error: Hugging Face client not available", enhanced_prompt
-        
-        # Generate image
         logger.info(f"Sending request to model {model_name} with prompt: {enhanced_prompt[:100]}...")
         image = hf_client.text_to_image(
             prompt=enhanced_prompt,
             model=model_name,
             negative_prompt="low quality, blurry, distorted, deformed, disfigured, bad anatomy, watermark, signature, text"
         )
-        
         logger.info("Image generated successfully")
-        
-        # Analysis information
-        analysis = f"Image generated using model: {model_name}\n"
+        analysis = f"Image generated using model: <b style='color:#FF6F61;'>{IMAGE_MODELS.get(model_name, model_name)}</b>\n"
         if use_llama:
-            analysis += "Prompt enhanced with Llama 4"
+            analysis += "Prompt enhanced with <b style='color:#FF6F61;'>Llama 4</b>"
         else:
             analysis += "Prompt enhanced with fallback method"
-        
         return image, analysis, enhanced_prompt
     except Exception as e:
         logger.error(f"Error generating image: {str(e)}")
         return None, f"Error generating image: {str(e)}", enhanced_prompt
 
-# Create Gradio interface
-with gr.Blocks(title="AI Image Creator") as interface:
-    gr.Markdown("# 🎨 AI Image Creator")
-    gr.Markdown("### Transform your ideas into stunning images with AI")
-    
+# Build Gradio Interface with enhanced UI and highlighting names
+with gr.Blocks(title="Nostalgia Nexus") as interface:
+    # Add custom CSS for additional styling
+    gr.HTML(
+        """
+        <style>
+            body { background-color: #fdfdfd; }
+            .gradio-container { font-family: 'Arial', sans-serif; }
+            .header-title { text-align: center; color: #FF6F61; font-size: 2.5em; font-weight: bold; }
+            .header-subtitle { text-align: center; color: #6B5B95; font-size: 1.5em; margin-bottom: 20px; }
+        </style>
+        """
+    )
+
+    # Header with highlighted project name and subtitle
+    gr.Markdown(
+        """
+        <h1 class="header-title">🎨 Nostalgia Nexus</h1>
+        <h3 class="header-subtitle">Transform your childhood memories into stunning images with AI</h3>
+        """
+    )
+
     with gr.Row():
         with gr.Column():
-            # Core inputs - streamlined for simplicity
+            # Core input: description
             description_input = gr.Textbox(
                 label="Describe what you want to see",
                 placeholder="Be detailed and specific about what you want in the image...",
                 lines=4
             )
-            
             with gr.Row():
                 creation_type = gr.Dropdown(
                     choices=list(CREATION_TYPES.keys()),
                     value="Digital Art",
                     label="Creation Type"
                 )
-                
                 model_selector = gr.Dropdown(
                     choices=list(IMAGE_MODELS.keys()),
                     value="stabilityai/stable-diffusion-xl-base-1.0",
                     label="Image Model"
                 )
-            
             with gr.Row():
                 art_style = gr.Dropdown(
                     choices=list(ART_STYLES.keys()),
                     value="Photorealistic",
                     label="Art Style"
                 )
-                
                 mood_dropdown = gr.Dropdown(
-                    choices=["Happy", "Sad", "Mysterious", "Peaceful", "Tense", 
+                    choices=["Happy", "Sad", "Mysterious", "Peaceful", "Tense",
                              "Whimsical", "Dark", "Energetic", "Romantic", "Epic"],
                     value="Peaceful",
                     label="Mood"
                 )
-            
-            # Generate button
             generate_button = gr.Button("✨ Generate Image", variant="primary", size="lg")
-            
-            # Display model names in a more user-friendly way
+            # Display model names in a highlighted, user-friendly way
             def format_model_name(model_key):
                 return IMAGE_MODELS.get(model_key, model_key)
-            
             model_label = gr.HTML(value="")
             model_selector.change(
-                fn=lambda x: f"<p>Selected model: <b>{format_model_name(x)}</b></p>",
+                fn=lambda x: f"<p style='color: #FF6F61; font-weight: bold;'>Selected model: {format_model_name(x)}</p>",
                 inputs=model_selector,
                 outputs=model_label
             )
-        
         with gr.Column():
-            # Output areas
+            # Output areas: image and enhanced prompt
             image_output = gr.Image(label="Generated Image")
-            
             with gr.Accordion("Enhanced Prompt", open=False):
                 prompt_output = gr.Textbox(label="AI-Enhanced Prompt Used", lines=6)
-    
-    # Connect generate button
+    # Connect generate button click event to image generation function
     generate_button.click(
         fn=generate_image,
         inputs=[description_input, creation_type, art_style, mood_dropdown, model_selector],
         outputs=[image_output, model_label, prompt_output]
     )
-    
-    # Tips
-    with gr.Accordion("Tips for better results", open=True):
-        gr.Markdown("""
-        ### 💡 Tips for better results:
-        
-        - **Be specific** about what you want to see - include details about subjects, actions, setting
-        - **Mention colors, textures, lighting** if they're important to your vision
-        - **Try different art styles** to dramatically change the look and feel
-        - **The mood selection** influences the overall atmosphere and color palette
-        - **SDXL model** generally produces the highest quality images but takes longer
-        
-        #### Examples of good descriptions:
-        
-        - *"A serene lake at sunset with mountains in the background and a small wooden boat floating nearby"*
-        - *"A futuristic cityscape with flying cars, neon lights, and tall skyscrapers under a night sky with two moons"*
-        - *"A close-up portrait of an elderly craftsman with weathered hands working on an intricate wooden carving in his workshop"*
-        """)
 
-    # Troubleshooting
+    # Tips section with enhanced styling
+    with gr.Accordion("Tips for better results", open=True):
+        gr.Markdown(
+            """
+            <div style="background-color: #FFF3E0; padding: 10px; border-radius: 5px;">
+            <h4 style="color: #FF6F61;">💡 Tips for better results:</h4>
+            <ul>
+                <li><b>Be specific</b>: include details about subjects, actions, and settings.</li>
+                <li><b>Mention colors, textures, and lighting</b> to enhance your vision.</li>
+                <li><b>Try different art styles</b> to change the overall mood.</li>
+                <li><b>Select the mood</b> to influence the final atmosphere.</li>
+                <li><b>SDXL model</b> generally yields the highest quality images, albeit slower.</li>
+            </ul>
+            <p><i>Examples:</i></p>
+            <ul>
+                <li>"A serene lake at sunset with mountains in the background and a small wooden boat floating nearby"</li>
+                <li>"A futuristic cityscape with flying cars, neon lights, and skyscrapers under a dual-moon night sky"</li>
+                <li>"An elderly craftsman with weathered hands meticulously carving a detailed wooden sculpture"</li>
+            </ul>
+            </div>
+            """
+        )
+    # Troubleshooting section with enhanced styling
     with gr.Accordion("Troubleshooting", open=False):
-        gr.Markdown("""
-        ### Troubleshooting Tips
-        
-        If you encounter errors:
-        
-        1. **Check the console/terminal** where you're running this code for detailed logs
-        2. **Verify your Hugging Face API key** is correct and has the right permissions
-        3. **Try a different model** if you get access restriction errors
-        4. **Simplify your prompt** if it's very long or complex
-        5. **Restart the app** if you've been running it for a long time
-        
-        Common errors:
-        - 401/403 errors: API key issues or model access restrictions
-        - 429 errors: Rate limiting (too many requests)
-        - 503 errors: Service temporarily unavailable
-        """)
+        gr.Markdown(
+            """
+            <div style="background-color: #F8D7DA; padding: 10px; border-radius: 5px;">
+            <h4 style="color: #C82333;">Troubleshooting Tips</h4>
+            <ol>
+                <li>Check the console/terminal for detailed logs.</li>
+                <li>Verify your Hugging Face API key and its permissions.</li>
+                <li>Try a different model if access errors occur.</li>
+                <li>Simplify your prompt if it is overly long or complex.</li>
+                <li>Restart the app if it has been running for a long time.</li>
+            </ol>
+            <p>Common errors include 401/403 (authentication/model access issues), 429 (rate limiting), and 503 (service unavailability).</p>
+            </div>
+            """
+        )
 
-# Launch the interface
-interface.launch()
+# Launch the Gradio interface
+interface.launch()