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import spaces
import os
import re
import json
import time
import torch
import tempfile
import io
import random
import string
import logging
from typing import Tuple, Optional, List, Dict, Any, Union

from PIL import Image, ImageDraw, ImageFont
from tqdm import tqdm
import gradio as gr

from safetensors.torch import save_file
from src.pipeline import FluxPipeline
from src.transformer_flux import FluxTransformer2DModel
from src.lora_helper import set_single_lora, set_multi_lora, unset_lora

# Google Gemini API ์ถ”๊ฐ€
from google import genai
from google.genai import types

# Initialize the image processor
base_path = "black-forest-labs/FLUX.1-dev"    
lora_base_path = "./models"

# System prompt that will be hidden from users but automatically added to their input
SYSTEM_PROMPT = "Ghibli Studio style, Charming hand-drawn anime-style illustration"

# ๋กœ๊น… ์„ค์ •
logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(levelname)s - %(message)s'
)

# Load the model
pipe = FluxPipeline.from_pretrained(base_path, torch_dtype=torch.bfloat16)
transformer = FluxTransformer2DModel.from_pretrained(base_path, subfolder="transformer", torch_dtype=torch.bfloat16)
pipe.transformer = transformer
pipe.to("cuda")

def clear_cache(transformer):
    for name, attn_processor in transformer.attn_processors.items():
        attn_processor.bank_kv.clear()

#######################################
# Utility Functions
#######################################

# Simple Timer Class
class timer:
    def __init__(self, method_name="timed process"):
        self.method = method_name
    def __enter__(self):
        self.start = time.time()
        print(f"[TIMER] {self.method} starts")
    def __exit__(self, exc_type, exc_val, exc_tb):
        end = time.time()
        print(f"[TIMER] {self.method} took {round(end - self.start, 2)}s")

# ๊ฐ„๋‹จํ•œ ๋ฒˆ์—ญ ๊ธฐ๋Šฅ (ํ•œ๊ธ€ -> ์˜์–ด)
def maybe_translate_to_english(text: str) -> str:
    """
    ํ…์ŠคํŠธ์— ํ•œ๊ธ€์ด ํฌํ•จ๋˜์–ด ์žˆ์œผ๋ฉด ์˜์–ด๋กœ ๋ฒˆ์—ญ, ์•„๋‹ˆ๋ฉด ๊ทธ๋Œ€๋กœ ๋ฐ˜ํ™˜
    """
    if not text or not re.search("[๊ฐ€-ํžฃ]", text):
        return text
    
    try:
        # ๊ฐ„๋‹จํ•œ ๋ฒˆ์—ญ ๊ทœ์น™ (์‹ค์ œ ํ”„๋กœ๋•์…˜์—์„œ๋Š” API ์‚ฌ์šฉ ๊ถŒ์žฅ)
        translations = {
            "์•ˆ๋…•ํ•˜์„ธ์š”": "Hello",
            "ํ™˜์˜ํ•ฉ๋‹ˆ๋‹ค": "Welcome",
            "์•„๋ฆ„๋‹ค์šด ๋‹น์‹ ": "Beautiful You",
            "์•ˆ๋…•": "Hello",
            "๊ณ ์–‘์ด": "Cat",
            "๋ฐฐ๋„ˆ": "Banner",
            "์ฌ๊ธ€๋ผ์Šค": "Sunglasses",
            "์ฐฉ์šฉํ•œ": "wearing",
            "ํฐ์ƒ‰": "white"
        }
        
        # ์ „์ฒด ๋ฌธ์žฅ์— ๋Œ€ํ•œ ๋Œ€๋žต์ ์ธ ๋ฒˆ์—ญ
        for kr, en in translations.items():
            if kr in text:
                text = text.replace(kr, en)
                
        print(f"[TRANSLATE] Translated Korean text: '{text}'")
        return text
    except Exception as e:
        print(f"[WARNING] Translation failed: {e}")
        return text

def save_binary_file(file_name, data):
    with open(file_name, "wb") as f:
        f.write(data)

#######################################
# Gemini API Functions
#######################################

def generate_by_google_genai(text, file_name, model="gemini-2.0-flash-exp"):
    """
    - ์ถ”๊ฐ€ ์ง€์‹œ์‚ฌํ•ญ(AIP)์„ ์ „๋‹ฌํ•ด ์ด๋ฏธ์ง€ ๊ธฐ๋ฐ˜ ํŽธ์ง‘์„ ์ˆ˜ํ–‰.
    - ์‘๋‹ต์ด '์ด๋ฏธ์ง€'๋ฉด ์ €์žฅ, 'ํ…์ŠคํŠธ'๋ฉด ๋ˆ„์ ํ•˜์—ฌ ๋ฐ˜ํ™˜.
    """
    # API ํ‚ค ๊ฐ€์ ธ์˜ค๊ธฐ (ํ™˜๊ฒฝ ๋ณ€์ˆ˜ GAPI_TOKEN ์‚ฌ์šฉ)
    api_key = os.getenv("GAPI_TOKEN", None)
    if not api_key:
        raise ValueError("GAPI_TOKEN is missing. Please set an API key.")

    client = genai.Client(api_key=api_key)
    files = [client.files.upload(file=file_name)]
    
    contents = [
        types.Content(
            role="user",
            parts=[
                types.Part.from_uri(
                    file_uri=files[0].uri,
                    mime_type=files[0].mime_type,
                ),
                types.Part.from_text(text=text),
            ],
        ),
    ]

    generate_content_config = types.GenerateContentConfig(
        temperature=1,
        top_p=0.95,
        top_k=40,
        max_output_tokens=8192,
        response_modalities=["image", "text"],
        response_mime_type="text/plain",
    )

    text_response = ""
    image_path = None

    # ์ž„์‹œ ํŒŒ์ผ์— ์ด๋ฏธ์ง€ ์ €์žฅ ๊ฐ€๋Šฅํ•˜๋„๋ก ์ค€๋น„
    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
        temp_path = tmp.name
        for chunk in client.models.generate_content_stream(
            model=model,
            contents=contents,
            config=generate_content_config,
        ):
            if not chunk.candidates or not chunk.candidates[0].content or not chunk.candidates[0].content.parts:
                continue

            candidate = chunk.candidates[0].content.parts[0]
            # ๋งŒ์•ฝ inline_data(์ด๋ฏธ์ง€ ๋ฐ์ดํ„ฐ)๊ฐ€ ์žˆ๋‹ค๋ฉด -> ์‹ค์ œ ์ด๋ฏธ์ง€ ํŽธ์ง‘ ๊ฒฐ๊ณผ
            if candidate.inline_data:
                save_binary_file(temp_path, candidate.inline_data.data)
                print(f"File of mime type {candidate.inline_data.mime_type} saved to: {temp_path}")
                image_path = temp_path
                # ์ด๋ฏธ์ง€ ํ•œ ์žฅ๋งŒ ํ™•๋ณดํ•˜๋ฉด ์ค‘๋‹จ
                break
            else:
                # inline_data๊ฐ€ ์—†์œผ๋ฉด ํ…์ŠคํŠธ ๋ฐ์ดํ„ฐ์ด๋ฏ€๋กœ ๋ˆ„์ 
                text_response += chunk.text + "\n"
    
    del files
    return image_path, text_response

def change_text_in_image_two_times(original_image, instruction):
    """
    Call the text-modification API twice (Google Gemini), returning 2 final variations.
    """
    if original_image is None:
        raise gr.Error("์ฒ˜๋ฆฌํ•  ์ด๋ฏธ์ง€๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค. ๋จผ์ € ์ด๋ฏธ์ง€๋ฅผ ์ƒ์„ฑํ•ด์ฃผ์„ธ์š”.")
        
    results = []
    for version_tag in ["(A)", "(B)"]:
        mod_instruction = f"{instruction} {version_tag}"
        try:
            # ์ด๋ฏธ์ง€ ์ €์žฅ์šฉ ์ž„์‹œ ํŒŒ์ผ ์ƒ์„ฑ
            with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
                original_path = tmp.name
                
                # PIL ์ด๋ฏธ์ง€ ๊ฐ์ฒด์ธ ๊ฒฝ์šฐ ์ €์žฅ
                print(f"[DEBUG] Saving image of type {type(original_image)} to temporary file")
                if isinstance(original_image, Image.Image):
                    original_image.save(original_path, format="PNG")
                    print(f"[DEBUG] Saved image to temporary file: {original_path}")
                else:
                    raise gr.Error(f"์˜ˆ์ƒ๋œ PIL Image๊ฐ€ ์•„๋‹Œ {type(original_image)} ํƒ€์ž…์ด ์ œ๊ณต๋˜์—ˆ์Šต๋‹ˆ๋‹ค.")

            print(f"[DEBUG] Google Gemini API์— ๋ณด๋‚ด๋Š” ์ง€์‹œ์‚ฌํ•ญ: {mod_instruction}")
            image_path, text_response = generate_by_google_genai(
                text=mod_instruction,
                file_name=original_path
            )
            
            if image_path:
                print(f"[DEBUG] Received image from Gemini API: {image_path}")
                try:
                    with open(image_path, "rb") as f:
                        image_data = f.read()
                    new_img = Image.open(io.BytesIO(image_data))
                    results.append(new_img)
                except Exception as img_err:
                    print(f"[ERROR] Failed to process Gemini image: {img_err}")
                    results.append(original_image)
            else:
                # ๋งŒ์•ฝ ์ด๋ฏธ์ง€ ์‘๋‹ต์ด ์—†๊ณ , ํ…์ŠคํŠธ๋งŒ ์˜จ ๊ฒฝ์šฐ
                print(f"[WARNING] ์ด๋ฏธ์ง€๊ฐ€ ๋ฐ˜ํ™˜๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ํ…์ŠคํŠธ ์‘๋‹ต: {text_response}")
                results.append(original_image)
                
        except Exception as e:
            logging.exception(f"Text modification error: {e}")
            # ์˜ค๋ฅ˜๊ฐ€ ๋‚˜๋„ ์›๋ณธ ์ด๋ฏธ์ง€๋ผ๋„ ๋ฐ˜ํ™˜
            print(f"[ERROR] ํ…์ŠคํŠธ ์ˆ˜์ • ์ค‘ ์˜ค๋ฅ˜ ๋ฐœ์ƒ: {e}")
            results.append(original_image)
            
    return results

#######################################
# Image Generation Functions
#######################################

@spaces.GPU()
def single_condition_generate_image(user_prompt, spatial_img, height, width, seed):
    # Combine the system prompt with user prompt
    full_prompt = f"{SYSTEM_PROMPT}, {user_prompt}" if user_prompt else SYSTEM_PROMPT
    
    # Set the Ghibli LoRA
    lora_path = os.path.join(lora_base_path, "Ghibli.safetensors")
    set_single_lora(pipe.transformer, lora_path, lora_weights=[1], cond_size=512)
    
    # Process the image
    spatial_imgs = [spatial_img] if spatial_img else []
    image = pipe(
        full_prompt,
        height=int(height),
        width=int(width),
        guidance_scale=3.5,
        num_inference_steps=25,
        max_sequence_length=512,
        generator=torch.Generator("cpu").manual_seed(seed), 
        subject_images=[],
        spatial_images=spatial_imgs,
        cond_size=512,
    ).images[0]
    clear_cache(pipe.transformer)
    return image

@spaces.GPU()
def text_rendering_generate_image(user_prompt, input_text, text_color, text_size, text_position, spatial_img, height, width, seed):
    """
    Generate image with Ghibli style and then send to Gemini API for multilingual text rendering
    """
    try:
        # Step 1: Generate the base image using FLUX
        print(f"[DEBUG] Generating base image with FLUX")
        full_prompt = f"{SYSTEM_PROMPT}, {user_prompt}" if user_prompt else SYSTEM_PROMPT
        
        # Set the Ghibli LoRA
        lora_path = os.path.join(lora_base_path, "Ghibli.safetensors")
        set_single_lora(pipe.transformer, lora_path, lora_weights=[1], cond_size=512)
        
        # Process the image
        spatial_imgs = [spatial_img] if spatial_img else []
        base_image = pipe(
            full_prompt,
            height=int(height),
            width=int(width),
            guidance_scale=3.5,
            num_inference_steps=25,
            max_sequence_length=512,
            generator=torch.Generator("cpu").manual_seed(seed), 
            subject_images=[],
            spatial_images=spatial_imgs,
            cond_size=512,
        ).images[0]
        clear_cache(pipe.transformer)
        
        # If no text is provided, return the base image
        if not input_text or not input_text.strip():
            return [base_image, base_image]
            
        # Step 2: Build the instruction for Gemini API
        instruction = f"Add the text '{input_text}' to this image in {text_color} color"
        
        # Add position information
        if text_position == "top":
            instruction += " at the top of the image"
        elif text_position == "bottom":
            instruction += " at the bottom of the image"
        else:  # center
            instruction += " at the center of the image"
            
        # Add size information
        if text_size <= 40:
            instruction += " in small size"
        elif text_size <= 120:
            instruction += " in medium size"
        else:
            instruction += " in large size"
            
        instruction += ". Make sure the text is clearly visible and readable."
        
        # Step 3: Call Gemini API to generate two variations
        print(f"[DEBUG] Sending to Gemini API with instruction: {instruction}")
        return change_text_in_image_two_times(base_image, instruction)
        
    except Exception as e:
        logging.exception(f"Text rendering error: {e}")
        # Create a dummy image in case of error
        dummy_img = Image.new('RGB', (width, height), color=(255, 200, 200))
        draw = ImageDraw.Draw(dummy_img)
        draw.text((width//2, height//2), f"Error: {str(e)}", fill="black", anchor="mm")
        return [dummy_img, dummy_img]

# Load example images
def load_examples():
    examples = []
    test_img_dir = "./test_imgs"
    example_prompts = [
        " ",
        "saying 'HELLO' in 'speech bubble'",
        "background 'alps'"
    ]
    
    for i, filename in enumerate(["00.jpg", "02.jpg", "03.jpg"]):
        img_path = os.path.join(test_img_dir, filename)
        if os.path.exists(img_path):
            # Use dimensions from original code for each specific example
            if filename == "00.jpg":
                height, width = 680, 1024
            elif filename == "02.jpg":
                height, width = 560, 1024
            elif filename == "03.jpg":
                height, width = 1024, 768
            else:
                height, width = 768, 768
                
            examples.append([
                example_prompts[i % len(example_prompts)],  # User prompt (without system prompt)
                Image.open(img_path),                       # Reference image
                height,                                     # Height
                width,                                      # Width
                i + 1                                       # Seed
            ])
    
    return examples

# Load examples for text rendering tab
def load_text_examples():
    examples = []
    test_img_dir = "./test_imgs"
    
    example_data = [
        {
            "prompt": "cute character with speech bubble",
            "text": "Hello World!",
            "color": "#ffffff",
            "size": 72,
            "position": "center",
            "filename": "00.jpg",
            "height": 680,
            "width": 1024,
            "seed": 123
        },
        {
            "prompt": "landscape with message",
            "text": "์•ˆ๋…•ํ•˜์„ธ์š”!",
            "color": "#ffff00",
            "size": 100,
            "position": "top",
            "filename": "03.jpg",
            "height": 1024,
            "width": 768,
            "seed": 456
        },
        {
            "prompt": "character with subtitles",
            "text": "ใ“ใ‚“ใซใกใฏไธ–็•Œ!",
            "color": "#00ffff",
            "size": 90,
            "position": "bottom",
            "filename": "02.jpg",
            "height": 560,
            "width": 1024,
            "seed": 789
        }
    ]
    
    for example in example_data:
        img_path = os.path.join(test_img_dir, example["filename"])
        if os.path.exists(img_path):
            examples.append([
                example["prompt"],
                example["text"],
                example["color"],
                example["size"],
                example["position"],
                Image.open(img_path),
                example["height"],
                example["width"],
                example["seed"]
            ])
    
    return examples

# Function to check API availability - modified to work directly
def check_api_status():
    # Check Gemini API availability
    api_key = os.getenv("GAPI_TOKEN")
    gemini_available = api_key is not None
    
    if gemini_available:
        return """<div class="api-status api-connected">โœ“ Connected to FLUX.1 and Gemini API</div>"""
    else:
        return """<div class="api-status api-disconnected">โœ— Gemini API connection issue. Please check GAPI_TOKEN environment variable.</div>"""

# CSS for improved UI
css = """
:root {
    --primary-color: #4a6670;
    --accent-color: #ff8a65;
    --background-color: #f5f5f5;
    --card-background: #ffffff;
    --text-color: #333333;
    --border-radius: 10px;
    --shadow: 0 4px 6px rgba(0,0,0,0.1);
}

body {
    background-color: var(--background-color);
    color: var(--text-color);
    font-family: 'Helvetica Neue', Arial, sans-serif;
}

.container {
    max-width: 1200px;
    margin: 0 auto;
    padding: 20px;
}

.gr-header {
    background: linear-gradient(135deg, #668796 0%, #4a6670 100%);
    padding: 24px;
    border-radius: var(--border-radius);
    margin-bottom: 24px;
    box-shadow: var(--shadow);
    text-align: center;
}

.gr-header h1 {
    color: white;
    font-size: 2.5rem;
    margin: 0;
    font-weight: 700;
}

.gr-header p {
    color: rgba(255, 255, 255, 0.9);
    font-size: 1.1rem;
    margin-top: 8px;
}

.gr-panel {
    background-color: var(--card-background);
    border-radius: var(--border-radius);
    padding: 16px;
    box-shadow: var(--shadow);
}

.gr-button {
    background-color: var(--accent-color);
    border: none;
    color: white;
    padding: 10px 20px;
    border-radius: 5px;
    font-size: 16px;
    font-weight: bold;
    cursor: pointer;
    transition: transform 0.1s, background-color 0.3s;
}

.gr-button:hover {
    background-color: #ff7043;
    transform: translateY(-2px);
}

.gr-input, .gr-select {
    border-radius: 5px;
    border: 1px solid #ddd;
    padding: 10px;
    width: 100%;
}

.gr-form {
    display: grid;
    gap: 16px;
}

.gr-box {
    background-color: var(--card-background);
    border-radius: var(--border-radius);
    padding: 20px;
    box-shadow: var(--shadow);
    margin-bottom: 20px;
}

.gr-gallery {
    display: grid;
    grid-template-columns: repeat(auto-fill, minmax(200px, 1fr));
    gap: 16px;
}

.gr-gallery-item {
    overflow: hidden;
    border-radius: var(--border-radius);
    box-shadow: var(--shadow);
    transition: transform 0.3s;
}

.gr-gallery-item:hover {
    transform: scale(1.02);
}

.gr-image {
    width: 100%;
    height: auto;
    object-fit: cover;
}

.gr-footer {
    text-align: center;
    margin-top: 40px;
    padding: 20px;
    color: #666;
    font-size: 14px;
}

.gr-examples-gallery {
    margin-top: 20px;
}

/* Responsive adjustments */
@media (max-width: 768px) {
    .gr-header h1 {
        font-size: 1.8rem;
    }
    
    .gr-panel {
        padding: 12px;
    }
}

/* Ghibli-inspired accent colors */
.gr-accent-1 {
    background-color: #95ccd9;
}

.gr-accent-2 {
    background-color: #74ad8c;
}

.gr-accent-3 {
    background-color: #f9c06b;
}

.text-rendering-options {
    background-color: #f0f8ff;
    padding: 16px;
    border-radius: var(--border-radius);
    margin-top: 16px;
}

.api-status {
    font-size: 14px;
    color: #666;
    text-align: center;
    margin-bottom: 10px;
}

.api-connected {
    color: green;
}

.api-disconnected {
    color: red;
}
"""

# Create the Gradio Blocks interface
with gr.Blocks(css=css) as demo:
    gr.HTML("""
    <div class="gr-header">
        <h1>โœจ Ghibli Multilingual Text-Rendering โœจ</h1>
        <p>Transform your ideas into magical Ghibli-inspired artwork with multilingual text</p>
    </div>
    """)
    
    # API Status - ์ง์ ‘ ํ˜ธ์ถœํ•ด์„œ ์ดˆ๊ธฐ ์ƒํƒœ ์„ค์ •
    api_status = gr.Markdown(check_api_status(), visible=True)
    
    with gr.Tabs():
        with gr.Tab("Create Ghibli Art"):
            with gr.Row():
                with gr.Column(scale=1):
                    gr.HTML("""
                    <div class="gr-box">
                        <h3>๐ŸŽจ Your Creative Input</h3>
                        <p>Describe what you want to see in your Ghibli-inspired image</p>
                    </div>
                    """)
                    
                    user_prompt = gr.Textbox(
                        label="Your description", 
                        placeholder="Describe what you want to see (e.g., a cat sitting by the window)",
                        lines=2
                    )
                    
                    spatial_img = gr.Image(
                        label="Reference Image (Optional)", 
                        type="pil",
                        elem_classes="gr-image-upload"
                    )
                    
                    with gr.Group():
                        with gr.Row():
                            height = gr.Slider(minimum=256, maximum=1024, step=64, label="Height", value=768)
                            width = gr.Slider(minimum=256, maximum=1024, step=64, label="Width", value=768)
                        
                        seed = gr.Slider(minimum=1, maximum=9999, step=1, label="Seed", value=42, 
                                        info="Change for different variations")
                    
                    generate_btn = gr.Button("โœจ Generate Ghibli Art", variant="primary", elem_classes=["generate-btn"])
                
                with gr.Column(scale=1):
                    gr.HTML("""
                    <div class="gr-box">
                        <h3>โœจ Your Magical Creation</h3>
                        <p>Your Ghibli-inspired artwork will appear here</p>
                    </div>
                    """)
                    output_image = gr.Image(label="Generated Image", elem_classes="gr-output-image")
            
            gr.HTML("""
            <div class="gr-box gr-examples-gallery">
                <h3>โœจ Inspiration Gallery</h3>
                <p>Click on any example to try it out</p>
            </div>
            """)
            
            # Add examples
            examples = load_examples()
            gr.Examples(
                examples=examples,
                inputs=[user_prompt, spatial_img, height, width, seed],
                outputs=output_image,
                fn=single_condition_generate_image,
                cache_examples=False,
                examples_per_page=4
            )
            
            # Link the button to the function
            generate_btn.click(
                single_condition_generate_image,
                inputs=[user_prompt, spatial_img, height, width, seed],
                outputs=output_image
            )
        
        # Second tab for Image & Multilingual Text Rendering with Gemini API
        with gr.Tab("Image & Multilingual Text Rendering"):
            with gr.Row():
                with gr.Column(scale=1):
                    gr.HTML("""
                    <div class="gr-box">
                        <h3>๐ŸŒˆ Art with Multilingual Text</h3>
                        <p>Create Ghibli-style images with beautiful text in any language using Gemini AI</p>
                    </div>
                    """)
                    
                    text_user_prompt = gr.Textbox(
                        label="Image Description", 
                        placeholder="Describe what you want to see (e.g., a character with speech bubble)",
                        lines=2
                    )
                    
                    with gr.Group(elem_classes="text-rendering-options"):
                        input_text = gr.Textbox(
                            label="Multilingual Text to Add", 
                            placeholder="Enter text in any language (Korean, Japanese, English, etc.)",
                            lines=1
                        )
                        
                        with gr.Row():
                            text_color = gr.ColorPicker(
                                label="Text Color", 
                                value="#FFFFFF"
                            )
                            
                            text_size = gr.Slider(
                                minimum=24, 
                                maximum=200, 
                                step=4, 
                                label="Text Size", 
                                value=72
                            )
                        
                        text_position = gr.Radio(
                            ["top", "center", "bottom"], 
                            label="Text Position", 
                            value="center"
                        )
                    
                    text_spatial_img = gr.Image(
                        label="Reference Image (Optional)", 
                        type="pil",
                        elem_classes="gr-image-upload"
                    )
                    
                    with gr.Group():
                        with gr.Row():
                            text_height = gr.Slider(minimum=256, maximum=1024, step=64, label="Height", value=768)
                            text_width = gr.Slider(minimum=256, maximum=1024, step=64, label="Width", value=768)
                        
                        text_seed = gr.Slider(minimum=1, maximum=9999, step=1, label="Seed", value=42, 
                                           info="Change for different variations")
                    
                    text_generate_btn = gr.Button("โœจ Generate Art with Multilingual Text", variant="primary", elem_classes=["generate-btn"])
                
                with gr.Column(scale=1):
                    gr.HTML("""
                    <div class="gr-box">
                        <h3>โœจ Your Text Creations (Two Variations)</h3>
                        <p>Two versions of your Ghibli-inspired artwork with text will appear here</p>
                    </div>
                    """)
                    
                    with gr.Row():
                        text_output_image1 = gr.Image(
                            label="Variation A", 
                            type="pil",
                            elem_classes="gr-output-image"
                        )
                        text_output_image2 = gr.Image(
                            label="Variation B", 
                            type="pil",
                            elem_classes="gr-output-image"
                        )
            
            gr.HTML("""
            <div class="gr-box gr-examples-gallery">
                <h3>โœจ Multilingual Text Examples</h3>
                <p>Click on any example to try it out</p>
            </div>
            """)
            
            # Add text rendering examples
            text_examples = load_text_examples()
            gr.Examples(
                examples=text_examples,
                inputs=[text_user_prompt, input_text, text_color, text_size, text_position, 
                        text_spatial_img, text_height, text_width, text_seed],
                outputs=[text_output_image1, text_output_image2],
                fn=text_rendering_generate_image,
                cache_examples=False,
                examples_per_page=3
            )
            
            # Link the text render button to the function
            text_generate_btn.click(
                text_rendering_generate_image,
                inputs=[text_user_prompt, input_text, text_color, text_size, text_position, 
                        text_spatial_img, text_height, text_width, text_seed],
                outputs=[text_output_image1, text_output_image2]
            )
    
    gr.HTML("""
    <div class="gr-footer">
        <p>Powered by FLUX.1, Ghibli LoRA, and Google Gemini API โ€ข Created with โค๏ธ</p>
    </div>
    """)

# Launch the Gradio app
demo.queue().launch()