app.py

import gradio as gr
import replicate
import os
from PIL import Image
import requests
from io import BytesIO
import time
import tempfile
import base64

# Set up Replicate API key from environment variable
os.environ['REPLICATE_API_TOKEN'] = os.getenv('REPLICATE_API_TOKEN')

def upload_image_to_hosting(image):
    """
    Upload image to multiple hosting services with fallback
    """
    # Method 1: Try imgbb.com (most reliable)
    try:
        buffered = BytesIO()
        image.save(buffered, format="PNG")
        buffered.seek(0)
        img_base64 = base64.b64encode(buffered.getvalue()).decode()
        
        response = requests.post(
            "https://api.imgbb.com/1/upload",
            data={
                'key': '6d207e02198a847aa98d0a2a901485a5',
                'image': img_base64,
            }
        )
        
        if response.status_code == 200:
            data = response.json()
            if data.get('success'):
                return data['data']['url']
    except:
        pass
    
    # Method 2: Try 0x0.st (simple and reliable)
    try:
        buffered = BytesIO()
        image.save(buffered, format="PNG")
        buffered.seek(0)
        
        files = {'file': ('image.png', buffered, 'image/png')}
        response = requests.post("https://0x0.st", files=files)
        
        if response.status_code == 200:
            return response.text.strip()
    except:
        pass
    
    # Method 3: Fallback to base64
    buffered = BytesIO()
    image.save(buffered, format="PNG")
    buffered.seek(0)
    img_base64 = base64.b64encode(buffered.getvalue()).decode()
    return f"data:image/png;base64,{img_base64}"

def process_images(prompt, image1, image2=None):
    """
    Process uploaded images with Replicate API or generate from text
    """
    if not os.getenv('REPLICATE_API_TOKEN'):
        return None, "Please set REPLICATE_API_TOKEN"
    
    try:
        # Check if any images are uploaded
        if not image1 and not image2:
            # Text-to-Image mode (no images uploaded)
            return generate_from_text(prompt)
        
        # Image-to-Image mode (at least one image uploaded)
        image_urls = []
        
        # Upload images
        if image1:
            url1 = upload_image_to_hosting(image1)
            image_urls.append(url1)
        
        if image2:
            url2 = upload_image_to_hosting(image2)
            image_urls.append(url2)
        
        # Run the model with images
        output = replicate.run(
            "google/nano-banana",
            input={
                "prompt": prompt,
                "image_input": image_urls
            }
        )
        
        return process_output(output)
        
    except Exception as e:
        return None, f"Error: {str(e)[:100]}"

def generate_from_text(prompt):
    """
    Generate image from text only using a text-to-image model
    """
    try:
        # Use a text-to-image model when no images are provided
        # Using SDXL-Lightning for fast generation
        output = replicate.run(
            "bytedance/sdxl-lightning-4step:5599ed30703defd1d160a25a63321b4dec97101d98b4674bcc56e41f62f35637",
            input={
                "prompt": prompt,
                "negative_prompt": "worst quality, low quality, blurry, nsfw",
                "width": 1024,
                "height": 1024,
                "num_inference_steps": 4,
                "guidance_scale": 0,
                "scheduler": "K_EULER"
            }
        )
        
        return process_output(output, "✨ Generated from text successfully!")
        
    except Exception as e:
        # Fallback to another model if the first one fails
        try:
            output = replicate.run(
                "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
                input={
                    "prompt": prompt,
                    "negative_prompt": "worst quality, low quality",
                    "width": 1024,
                    "height": 1024,
                    "num_inference_steps": 25,
                    "refine": "expert_ensemble_refiner",
                    "apply_watermark": False
                }
            )
            return process_output(output, "✨ Generated from text successfully!")
        except Exception as e2:
            return None, f"Text generation error: {str(e2)[:100]}"

def process_output(output, success_message="✨ Generated successfully!"):
    """
    Process the output from Replicate API
    """
    if output is None:
        return None, "No output received"
    
    # Get the generated image
    try:
        if hasattr(output, 'read'):
            img_data = output.read()
            img = Image.open(BytesIO(img_data))
            return img, success_message
    except:
        pass
    
    try:
        if hasattr(output, 'url'):
            output_url = output.url()
            response = requests.get(output_url, timeout=30)
            if response.status_code == 200:
                img = Image.open(BytesIO(response.content))
                return img, success_message
    except:
        pass
    
    output_url = None
    if isinstance(output, str):
        output_url = output
    elif isinstance(output, list) and len(output) > 0:
        output_url = output[0]
    
    if output_url:
        response = requests.get(output_url, timeout=30)
        if response.status_code == 200:
            img = Image.open(BytesIO(response.content))
            return img, success_message
    
    return None, "Could not process output"

# Enhanced CSS with modern, minimal design
css = """
.gradio-container {
    background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
    font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
    min-height: 100vh;
}
.header-container {
    background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%);
    padding: 2.5rem;
    border-radius: 24px;
    margin-bottom: 2.5rem;
    box-shadow: 0 20px 60px rgba(255, 179, 71, 0.25);
}
.logo-text {
    font-size: 3.5rem;
    font-weight: 900;
    color: #2d3436;
    text-align: center;
    margin: 0;
    letter-spacing: -2px;
}
.subtitle {
    color: #2d3436;
    text-align: center;
    font-size: 1rem;
    margin-top: 0.5rem;
    opacity: 0.8;
}
.mode-indicator {
    background: rgba(255, 255, 255, 0.3);
    backdrop-filter: blur(10px);
    border-radius: 12px;
    padding: 0.5rem 1rem;
    margin-top: 1rem;
    text-align: center;
    font-weight: 600;
    color: #2d3436;
}
.main-content {
    background: rgba(255, 255, 255, 0.95);
    backdrop-filter: blur(20px);
    border-radius: 24px;
    padding: 2.5rem;
    box-shadow: 0 10px 40px rgba(0, 0, 0, 0.08);
}
.gr-button-primary {
    background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%) !important;
    border: none !important;
    color: #2d3436 !important;
    font-weight: 700 !important;
    font-size: 1.1rem !important;
    padding: 1.2rem 2rem !important;
    border-radius: 14px !important;
    transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
    text-transform: uppercase;
    letter-spacing: 1px;
    width: 100%;
    margin-top: 1rem !important;
}
.gr-button-primary:hover {
    transform: translateY(-3px) !important;
    box-shadow: 0 15px 40px rgba(255, 179, 71, 0.35) !important;
}
.gr-input, .gr-textarea {
    background: #ffffff !important;
    border: 2px solid #e1e8ed !important;
    border-radius: 14px !important;
    color: #2d3436 !important;
    font-size: 1rem !important;
    padding: 0.8rem 1rem !important;
}
.gr-input:focus, .gr-textarea:focus {
    border-color: #ffd93d !important;
    box-shadow: 0 0 0 4px rgba(255, 217, 61, 0.15) !important;
}
.gr-form {
    background: transparent !important;
    border: none !important;
}
.gr-panel {
    background: #ffffff !important;
    border: 2px solid #e1e8ed !important;
    border-radius: 16px !important;
    padding: 1.5rem !important;
}
.gr-box {
    border-radius: 14px !important;
    border-color: #e1e8ed !important;
}
label {
    color: #636e72 !important;
    font-weight: 600 !important;
    font-size: 0.85rem !important;
    text-transform: uppercase;
    letter-spacing: 0.5px;
    margin-bottom: 0.5rem !important;
}
.status-text {
    font-family: 'SF Mono', 'Monaco', monospace;
    color: #00b894;
    font-size: 0.9rem;
}
.image-container {
    border-radius: 14px !important;
    overflow: hidden;
    border: 2px solid #e1e8ed !important;
    background: #fafbfc !important;
}
footer {
    display: none !important;
}
/* Equal sizing for all image containers */
.image-upload {
    min-height: 200px !important;
    max-height: 200px !important;
}
.output-image {
    min-height: 420px !important;
    max-height: 420px !important;
}
/* Ensure consistent spacing */
.gr-row {
    gap: 1rem !important;
}
.gr-column {
    gap: 1rem !important;
}
.info-box {
    background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%);
    border-radius: 12px;
    padding: 1rem;
    margin-bottom: 1rem;
    border-left: 4px solid #2196f3;
}
"""

with gr.Blocks(css=css, theme=gr.themes.Base()) as demo:
    with gr.Column(elem_classes="header-container"):
        gr.HTML("""
            <h1 class="logo-text">🍌 Free Nano Banana</h1>
            <p class="subtitle">AI-Powered Image Generation & Style Transfer</p>
            <div class="mode-indicator">
                💡 Works in two modes: Text-to-Image (no upload) or Style Transfer (with images)
            </div>
            <div style="display: flex; justify-content: center; align-items: center; gap: 10px; margin-top: 20px;">
                <a href="https://huggingface.co/spaces/ginigen/Nano-Banana-PRO" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=NANO%20BANANA&message=PRO&color=%230000ff&labelColor=%23800080&logo=HUGGINGFACE&logoColor=white&style=for-the-badge" alt="badge">
                </a>    
                <a href="https://huggingface.co/spaces/openfree/Nano-Banana-Upscale" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=NANO%20BANANA&message=UPSCALE&color=%230000ff&labelColor=%23800080&logo=GOOGLE&logoColor=white&style=for-the-badge" alt="Nano Banana Upscale">
                </a>                    
                <a href="https://huggingface.co/spaces/aiqtech/Nano-Banana-API" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=NANO%20BANANA&message=API&color=%230000ff&labelColor=%23800080&logo=GOOGLE&logoColor=white&style=for-the-badge" alt="Nano Banana API">
                </a>
                <a href="https://huggingface.co/spaces/ginigen/Nano-Banana-Video" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=NANO%20BANANA&message=VIDEO&color=%230000ff&labelColor=%23800080&logo=GOOGLE&logoColor=white&style=for-the-badge" alt="Nano Banana VIDEO">
                </a>                    
                <a href="https://discord.gg/openfreeai" target="_blank">
                    <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord Openfree AI">
                </a>
            </div>
        """)

    with gr.Column(elem_classes="main-content"):
        # Info box
        gr.HTML("""
            <div class="info-box">
                <strong>How to use:</strong><br>
                • <b>Text-to-Image:</b> Enter a prompt without uploading images<br>
                • <b>Style Transfer:</b> Upload 1-2 images and describe the style you want
            </div>
        """)
        
        with gr.Row(equal_height=True):
            # Left Column - Inputs
            with gr.Column(scale=1):
                prompt = gr.Textbox(
                    label="Prompt / Style Description",
                    placeholder="Describe what you want to generate or the style to apply...",
                    lines=3,
                    value="A beautiful sunset over mountains with golden clouds",
                    elem_classes="prompt-input"
                )
                
                with gr.Row(equal_height=True):
                    image1 = gr.Image(
                        label="Primary Image (Optional)",
                        type="pil",
                        height=200,
                        elem_classes="image-container image-upload"
                    )
                    image2 = gr.Image(
                        label="Secondary Image (Optional)",
                        type="pil",
                        height=200,
                        elem_classes="image-container image-upload"
                    )
                
                generate_btn = gr.Button(
                    "Generate Magic ✨",
                    variant="primary",
                    size="lg"
                )
            
            # Right Column - Output
            with gr.Column(scale=1):
                output_image = gr.Image(
                    label="Generated Result",
                    type="pil",
                    height=420,
                    elem_classes="image-container output-image"
                )
                
                status = gr.Textbox(
                    label="Status",
                    interactive=False,
                    lines=1,
                    elem_classes="status-text",
                    value="Ready to generate..."
                )
    
    # Event handler
    generate_btn.click(
        fn=process_images,
        inputs=[prompt, image1, image2],
        outputs=[output_image, status]
    )
    
    # Examples
    gr.Examples(
        examples=[
            ["A cyberpunk city at night with neon lights and flying cars", None, None],
            ["A magical forest with glowing mushrooms and fireflies", None, None],
            ["Portrait of a robot in renaissance painting style", None, None],
            ["Underwater palace made of coral and pearls", None, None],
        ],
        inputs=[prompt, image1, image2],
        label="Text-to-Image Examples"
    )

# Launch
if __name__ == "__main__":
    demo.launch(
        share=True,
        server_name="0.0.0.0",
        server_port=7860
    )