src/streamlit_app.py

=== streamlit_app.py ===
import streamlit as st
from utils import load_css, create_prompt_selector, display_image_gallery, generate_image_placeholder
import time

def main():
    st.set_page_config(
        page_title="AI Image Generator - Dramatic Scenes",
        page_icon="🎨",
        layout="wide",
        initial_sidebar_state="expanded"
    )
    
    load_css()
    
    # Header
    st.markdown("""
    <div class="header">
        <h1>🎬 AI Image Generator - Dramatic Scenes</h1>
        <p>Create hyperrealistic, cinematic images with detailed prompts</p>
        <p style="font-size: 0.9em; opacity: 0.7;">Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank">anycoder</a></p>
    </div>
    """, unsafe_allow_html=True)
    
    # Sidebar
    with st.sidebar:
        st.markdown("## ⚙️ Generation Settings")
        
        # Aspect ratio
        aspect_ratio = st.selectbox(
            "Aspect Ratio",
            options=["4:5", "16:9", "1:1", "3:2", "2:3"],
            index=0
        )
        
        # Quality
        quality = st.selectbox(
            "Quality",
            options=["Standard", "High", "Ultra (8K)"],
            index=2
        )
        
        # Style
        style = st.selectbox(
            "Style",
            options=["Cinematic", "Photorealistic", "Dramatic", "Hollywood", "Artistic"],
            index=0
        )
        
        # Resolution
        resolution = st.selectbox(
            "Resolution",
            options=["1024x1024", "1024x1280", "1280x720", "1920x1080", "2048x2560"],
            index=1
        )
        
        st.markdown("---")
        st.markdown("### 📊 Statistics")
        if 'generated_count' not in st.session_state:
            st.session_state.generated_count = 0
        st.metric("Images Generated", st.session_state.generated_count)
    
    # Main content
    col1, col2 = st.columns([1, 1])
    
    with col1:
        st.markdown("## 📝 Prompt Editor")
        
        # Predefined prompts
        prompt_option = st.radio(
            "Choose a scene template:",
            ["Custom Prompt", "Haunted Hut Scene", "Disaster Scene"],
            index=0
        )
        
        # Predefined prompts
        prompts = {
            "Haunted Hut Scene": """Hyperrealistic and dramatic scene showing a terrified man sitting on a bamboo bench in a thatch-roofed hut. He's wearing a black T-shirt with "WALIĆ RUDEGO" text and symbolic pattern underneath. A semi-transparent, smoky, ghostly figure emerges from the air beside him, grabbing his neck with a misty hand. The ghost has a skeletal, menacing face and glowing eyes, screaming or roaring. The man looks shocked and terrified, with wide eyes and mouth agape, frozen in fear. Natural lighting with warm sunlight filtering through the hut, background shows green vegetation outside. Intense, eerie, and cinematic atmosphere with strong emotional contrast between ghost and victim. 8K resolution, 4:5 aspect ratio.""",
            
            "Disaster Scene": """A man and cat falling through the air. Background: skyscrapers curve dramatically in a wide fisheye perspective, as if the entire city is collapsing inward. Flying debris, concrete chunks, and glass shards fill the air. Action elements: A police car floats behind him - its red and blue sirens flash intensely through dust and smoke. Behind the vehicle follows a powerful explosion, casting orange light and shrapnel across the scene. In the background, a police officer is seen waving arms, thrown by the explosion. Lighting and atmosphere: Cinematic lighting with strong, directional shadows, motion blur, and bright lights from sirens and fireball. Dark and gritty color palette with golden-brown tones punctuated by vivid red, blue, and orange accents from explosions and sirens. Clothing: The man wears a torn, olive-green hoodie and dark, worn pants - flailing wildly in the wind. Hollywood disaster movie style - dramatic freeze-frame with intense city destruction, emotions, and surreal action. Hyperrealistic details in skin texture, movement, and lighting."""
        }
        
        # Text area for prompt
        if prompt_option == "Custom Prompt":
            prompt_text = st.text_area(
                "Enter your prompt:",
                height=200,
                placeholder="Describe the image you want to generate in detail..."
            )
        else:
            prompt_text = st.text_area(
                "Edit the preset prompt:",
                value=prompts.get(prompt_option, ""),
                height=200
            )
        
        # Negative prompt
        negative_prompt = st.text_area(
            "Negative Prompt (what to avoid):",
            value="blurry, low quality, distorted, deformed, bad anatomy, watermark, text, signature",
            height=100
        )
        
        # Generate button
        generate_col1, generate_col2, generate_col3 = st.columns([1, 2, 1])
        with generate_col2:
            if st.button("🎨 Generate Image", type="primary", use_container_width=True):
                if prompt_text:
                    with st.spinner("Generating your image..."):
                        # Simulate image generation
                        time.sleep(2)
                        
                        # Update session state
                        if 'generated_images' not in st.session_state:
                            st.session_state.generated_images = []
                        
                        # Add new image to gallery
                        new_image = {
                            'prompt': prompt_text,
                            'negative_prompt': negative_prompt,
                            'aspect_ratio': aspect_ratio,
                            'quality': quality,
                            'style': style,
                            'timestamp': time.time()
                        }
                        st.session_state.generated_images.append(new_image)
                        st.session_state.generated_count += 1
                        
                        st.success("✅ Image generated successfully!")
                        st.rerun()
                else:
                    st.error("❌ Please enter a prompt to generate an image.")
    
    with col2:
        st.markdown("## 🖼️ Generated Images")
        
        if 'generated_images' in st.session_state and st.session_state.generated_images:
            display_image_gallery(st.session_state.generated_images)
        else:
            st.markdown("""
            <div class="empty-state">
                <h3>No images generated yet</h3>
                <p>Enter a prompt and click "Generate Image" to start creating!</p>
            </div>
            """, unsafe_allow_html=True)
            
            # Show example placeholders
            st.markdown("### Example Scenes")
            example_col1, example_col2 = st.columns(2)
            
            with example_col1:
                st.image(
                    generate_image_placeholder("Haunted", "#FF6B6B"),
                    caption="Haunted Hut Scene Example",
                    use_column_width=True
                )
            
            with example_col2:
                st.image(
                    generate_image_placeholder("Disaster", "#4ECDC4"),
                    caption="Disaster Scene Example",
                    use_column_width=True
                )
    
    # Footer
    st.markdown("---")
    st.markdown("""
    <div class="footer">
        <p>💡 Tip: Be as detailed as possible in your prompts for better results!</p>
        <p>🎯 Focus on: lighting, atmosphere, emotions, and specific visual elements</p>
    </div>
    """, unsafe_allow_html=True)

if __name__ == "__main__":
    main()

=== utils.py ===
import streamlit as st
import base64
from io import BytesIO
import time

def load_css():
    """Load custom CSS styles"""
    st.markdown("""
    <style>
        .header {
            text-align: center;
            padding: 2rem 0;
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            color: white;
            border-radius: 10px;
            margin-bottom: 2rem;
        }
        
        .header h1 {
            margin: 0;
            font-size: 2.5rem;
            font-weight: 700;
        }
        
        .header p {
            margin: 0.5rem 0;
            opacity: 0.9;
        }
        
        .header a {
            color: #FFD700;
            text-decoration: none;
            font-weight: bold;
        }
        
        .header a:hover {
            text-decoration: underline;
        }
        
        .image-card {
            background: white;
            border-radius: 10px;
            padding: 1rem;
            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
            margin-bottom: 1rem;
            transition: transform 0.2s;
        }
        
        .image-card:hover {
            transform: translateY(-2px);
            box-shadow: 0 6px 12px rgba(0, 0, 0, 0.15);
        }
        
        .image-container {
            position: relative;
            border-radius: 8px;
            overflow: hidden;
        }
        
        .image-overlay {
            position: absolute;
            bottom: 0;
            left: 0;
            right: 0;
            background: linear-gradient(to top, rgba(0,0,0,0.8), transparent);
            color: white;
            padding: 1rem;
            opacity: 0;
            transition: opacity 0.3s;
        }
        
        .image-container:hover .image-overlay {
            opacity: 1;
        }
        
        .empty-state {
            text-align: center;
            padding: 3rem;
            color: #666;
        }
        
        .empty-state h3 {
            margin-bottom: 1rem;
            color: #333;
        }
        
        .footer {
            text-align: center;
            padding: 1rem;
            color: #666;
            font-size: 0.9em;
        }
        
        .prompt-preview {
            background: #f7f7f7;
            padding: 0.5rem;
            border-radius: 5px;
            font-size: 0.85em;
            color: #555;
            margin-top: 0.5rem;
            white-space: nowrap;
            overflow: hidden;
            text-overflow: ellipsis;
        }
        
        .stButton > button {
            transition: all 0.2s;
        }
        
        .stButton > button:hover {
            transform: translateY(-2px);
            box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
        }
        
        .metric-card {
            background: white;
            padding: 1rem;
            border-radius: 8px;
            text-align: center;
            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
        }
    </style>
    """, unsafe_allow_html=True)

def create_prompt_selector():
    """Create a prompt selection interface"""
    pass

def display_image_gallery(images):
    """Display a gallery of generated images"""
    cols = st.columns(2)
    
    for idx, image_data in enumerate(reversed(images[-6:])):  # Show last 6 images
        with cols[idx % 2]:
            st.markdown(f"""
            <div class="image-card">
                <div class="image-container">
                    <img src="data:image/png;base64,{create_placeholder_image(image_data['prompt'][:20])}" 
                         style="width: 100%; border-radius: 8px;">
                    <div class="image-overlay">
                        <strong>Generated</strong><br>
                        {time.strftime('%Y-%m-%d %H:%M', time.localtime(image_data['timestamp']))}
                    </div>
                </div>
                <div style="margin-top: 0.5rem;">
                    <strong>Style:</strong> {image_data['style']}<br>
                    <strong>Quality:</strong> {image_data['quality']}<br>
                    <strong>Aspect:</strong> {image_data['aspect_ratio']}
                </div>
                <div class="prompt-preview">
                    {image_data['prompt'][:100]}{'...' if len(image_data['prompt']) > 100 else ''}
                </div>
            </div>
            """, unsafe_allow_html=True)
            
            if st.button(f"📋 Copy Prompt", key=f"copy_{idx}"):
                st.write(f"**Prompt copied to clipboard:** {image_data['prompt']}")
                st.success("Prompt ready to copy!")

def generate_image_placeholder(text, color="#667eea"):
    """Generate a placeholder image with text"""
    # This would normally use an image generation API
    # For now, we'll create a simple placeholder
    return f"https://picsum.photos/seed/{text}/400/500"

def create_placeholder_image(seed):
    """Create a base64 encoded placeholder image"""
    # Simple placeholder - in real app this would be the generated image
    placeholder_url = f"https://picsum.photos/seed/{seed}/400/500"
    return ""

def save_image_to_history(image_data):
    """Save generated image to session history"""
    if 'image_history' not in st.session_state:
        st.session_state.image_history = []
    
    st.session_state.image_history.append({
        'timestamp': time.time(),
        'data': image_data
    })
    
    # Keep only last 50 images
    if len(st.session_state.image_history) > 50:
        st.session_state.image_history = st.session_state.image_history[-50:]

def get_prompt_suggestions():
    """Get prompt suggestions for users"""
    return [
        "Cinematic portrait with dramatic lighting",
        "Fantasy landscape with magical elements",
        "Urban street scene at golden hour",
        "Abstract art with vibrant colors",
        "Historical scene with period accuracy"
    ]

=== requirements.txt ===
streamlit
pillow
numpy
requests
base64
time