Update app.py

app.py

@@ -4,88 +4,57 @@ import numpy as np
 import spaces
 import torch
 import random
-from PIL import Image
+from PIL import Image, ImageFilter
 from typing import Iterable
 from gradio.themes import Soft
 from gradio.themes.utils import colors, fonts, sizes
+from deep_translator import GoogleTranslator
+from transformers import pipeline
 
-colors.orange_red = colors.Color(
-    name="orange_red",
-    c50="#FFF0E5",
-    c100="#FFE0CC",
-    c200="#FFC299",
-    c300="#FFA366",
-    c400="#FF8533",
-    c500="#FF4500",
-    c600="#E63E00",
-    c700="#CC3700",
-    c800="#B33000",
-    c900="#992900",
-    c950="#802200",
+# --- تعریف تم ---
+colors.steel_blue = colors.Color(
+    name="steel_blue",
+    c50="#EBF3F8",
+    c100="#D3E5F0",
+    c200="#A8CCE1",
+    c300="#7DB3D2",
+    c400="#529AC3",
+    c500="#4682B4",
+    c600="#3E72A0",
+    c700="#36638C",
+    c800="#2E5378",
+    c900="#264364",
+    c950="#1E3450",
 )
 
-class OrangeRedTheme(Soft):
-    def __init__(
-        self,
-        *,
-        primary_hue: colors.Color | str = colors.gray,
-        secondary_hue: colors.Color | str = colors.orange_red,
-        neutral_hue: colors.Color | str = colors.slate,
-        text_size: sizes.Size | str = sizes.text_lg,
-        font: fonts.Font | str | Iterable[fonts.Font | str] = (
-            fonts.GoogleFont("Outfit"), "Arial", "sans-serif",
-        ),
-        font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
-            fonts.GoogleFont("IBM Plex Mono"), "ui-monospace", "monospace",
-        ),
-    ):
-        super().__init__(
-            primary_hue=primary_hue,
-            secondary_hue=secondary_hue,
-            neutral_hue=neutral_hue,
-            text_size=text_size,
-            font=font,
-            font_mono=font_mono,
-        )
-        super().set(
-            background_fill_primary="*primary_50",
-            background_fill_primary_dark="*primary_900",
-            body_background_fill="linear-gradient(135deg, *primary_200, *primary_100)",
-            body_background_fill_dark="linear-gradient(135deg, *primary_900, *primary_800)",
-            button_primary_text_color="white",
-            button_primary_text_color_hover="white",
-            button_primary_background_fill="linear-gradient(90deg, *secondary_500, *secondary_600)",
-            button_primary_background_fill_hover="linear-gradient(90deg, *secondary_600, *secondary_700)",
-            button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_700)",
-            button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_600)",
-            button_secondary_text_color="black",
-            button_secondary_text_color_hover="white",
-            button_secondary_background_fill="linear-gradient(90deg, *primary_300, *primary_300)",
-            button_secondary_background_fill_hover="linear-gradient(90deg, *primary_400, *primary_400)",
-            button_secondary_background_fill_dark="linear-gradient(90deg, *primary_500, *primary_600)",
-            button_secondary_background_fill_hover_dark="linear-gradient(90deg, *primary_500, *primary_500)",
-            slider_color="*secondary_500",
-            slider_color_dark="*secondary_600",
-            block_title_text_weight="600",
-            block_border_width="3px",
-            block_shadow="*shadow_drop_lg",
-            button_primary_shadow="*shadow_drop_lg",
-            button_large_padding="11px",
-            color_accent_soft="*primary_100",
-            block_label_background_fill="*primary_200",
-        )
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-orange_red_theme = OrangeRedTheme()
+# --- بارگذاری مدل تشخیص محتوای نامناسب (NSFW) ---
+print("Loading Safety Checker...")
+safety_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection", device=-1)
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-dtype = torch.bfloat16
+def is_image_nsfw(image):
+    if image is None: return False
+    try:
+        results = safety_classifier(image)
+        for result in results:
+            if result['label'] == 'nsfw' and result['score'] > 0.75:
+                return True
+        return False
+    except Exception as e:
+        print(f"Safety check error: {e}")
+        return False
 
+# --- بارگذاری مدل اصلی ---
 from diffusers import FlowMatchEulerDiscreteScheduler
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
 from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
 from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
 
-print("Loading Qwen Image Edit Pipeline...")
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+print("Loading pipeline...")
 pipe = QwenImageEditPlusPipeline.from_pretrained(
     "Qwen/Qwen-Image-Edit-2509",
     transformer=QwenImageTransformer2DModel.from_pretrained(
@@ -97,52 +66,74 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     torch_dtype=dtype
 ).to(device)
 
-print("Loading and Fusing Lightning LoRA...")
-pipe.load_lora_weights("lightx2v/Qwen-Image-Lightning",
-                       weight_name="Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors",
-                       adapter_name="lightning")
-pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
-
-print("Loading Task Adapters...")
-
-pipe.load_lora_weights("tarn59/apply_texture_qwen_image_edit_2509", 
-                       weight_name="apply_texture_v2_qwen_image_edit_2509.safetensors", 
-                       adapter_name="texture")
+# بارگذاری LoRA ها
+pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime", weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors", adapter_name="anime")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles", weight_name="镜头转换.safetensors", adapter_name="multiple-angles")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration", weight_name="移除光影.safetensors", adapter_name="light-restoration")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight", weight_name="Qwen-Edit-Relight.safetensors", adapter_name="relight")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multi-Angle-Lighting", weight_name="多角度灯光-251116.safetensors", adapter_name="multi-angle-lighting")
+pipe.load_lora_weights("tlennon-ie/qwen-edit-skin", weight_name="qwen-edit-skin_1.1_000002750.safetensors", adapter_name="edit-skin")
+pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509", weight_name="next-scene_lora-v2-3000.safetensors", adapter_name="next-scene")
+pipe.load_lora_weights("vafipas663/Qwen-Edit-2509-Upscale-LoRA", weight_name="qwen-edit-enhance_64-v3_000001000.safetensors", adapter_name="upscale-image")
 
-pipe.load_lora_weights("ostris/qwen_image_edit_inpainting", 
-                       weight_name="qwen_image_edit_inpainting.safetensors", 
-                       adapter_name="fusion")
+pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
+MAX_SEED = np.iinfo(np.int32).max
 
-pipe.load_lora_weights("ostris/qwen_image_edit_2509_shirt_design", 
-                       weight_name="qwen_image_edit_2509_shirt_design.safetensors", 
-                       adapter_name="shirt_design")
+LORA_MAPPING = {
+    "تبدیل عکس به انیمه": "anime",
+    "تغییر زاویه دید": "multiple-angles",
+    "اصلاح نور و سایه": "light-restoration",
+    "نورپردازی مجدد (Relight)": "relight",
+    "نورپردازی چند زاویه‌ای": "multi-angle-lighting",
+    "روتوش پوست": "edit-skin",
+    "صحنه بعدی (سینمایی)": "next-scene",
+    "افزایش کیفیت (Upscale)": "upscale-image"
+}
 
-pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Fusion", 
-                       weight_name="溶图.safetensors", 
-                       adapter_name="fusion-x")
+ASPECT_RATIOS_LIST = [
+    "خودکار (پیش‌فرض)",
+    "۱:۱ (مربع - 1024x1024)",
+    "۱۶:۹ (افقی - 1344x768)",
+    "۹:۱۶ (عمودی - 768x1344)",
+    "شخصی‌سازی (Custom)"
+]
 
-pipe.load_lora_weights("oumoumad/Qwen-Edit-2509-Material-transfer", 
-                       weight_name="material-transfer_000004769.safetensors", 
-                       adapter_name="material-transfer")
+ASPECT_RATIOS_MAP = {
+    "خودکار (پیش‌فرض)": "Auto",
+    "۱:۱ (مربع - 1024x1024)": (1024, 1024),
+    "۱۶:۹ (افقی - 1344x768)": (1344, 768),
+    "۹:۱۶ (عمودی - 768x1344)": (768, 1344),
+    "شخصی‌سازی (Custom)": "Custom"
+}
 
-pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Light-Migration", 
-                       weight_name="参考色调.safetensors", 
-                       adapter_name="light-migration")
+BANNED_WORDS = [
+    "nude", "naked", "sex", "porn", "undressed", "nsfw", "erotic", "xxx", 
+    "breast", "nipple", "genital", "vagina", "penis", "ass", "butt", "sexual",
+    "lingerie", "bikini", "swimwear", "underwear", "fetish", "topless",
+    "exhibitionism", "hentai", "ecchi", "18+"
+]
 
-try:
-    pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
-    print("Flash Attention 3 Processor set successfully.")
-except Exception as e:
-    print(f"Could not set FA3 processor (likely hardware mismatch): {e}. using default attention.")
+def check_text_safety(text):
+    text_lower = text.lower()
+    for word in BANNED_WORDS:
+        if f" {word} " in f" {text_lower} ": 
+            return False
+    return True
 
-MAX_SEED = np.iinfo(np.int32).max
+def translate_prompt(text):
+    if not text:
+        return ""
+    try:
+        translated = GoogleTranslator(source='auto', target='en').translate(text)
+        return translated
+    except Exception as e:
+        print(f"Translation Error: {e}")
+        return text
 
 def update_dimensions_on_upload(image):
     if image is None:
         return 1024, 1024
-    
     original_width, original_height = image.size
-    
     if original_width > original_height:
         new_width = 1024
         aspect_ratio = original_height / original_width
@@ -151,166 +142,560 @@ def update_dimensions_on_upload(image):
         new_height = 1024
         aspect_ratio = original_width / original_height
         new_width = int(new_height * aspect_ratio)
-        
-    # Ensure dimensions are multiples of 16
-    new_width = (new_width // 16) * 16
-    new_height = (new_height // 16) * 16
-    
+    new_width = (new_width // 8) * 8
+    new_height = (new_height // 8) * 8
     return new_width, new_height
 
+def get_error_html(message):
+    return f"""
+    <div style="background-color: #fee2e2; border: 1px solid #ef4444; color: #b91c1c; padding: 12px; border-radius: 8px; text-align: center; margin-bottom: 10px; font-weight: bold; display: flex; align-items: center; justify-content: center; gap: 8px;">
+        <span style="font-size: 1.2em;">⛔</span>
+        {message}
+    </div>
+    """
+
+def get_success_html(message):
+    return f"""
+    <div style="background-color: #dcfce7; border: 1px solid #22c55e; color: #15803d; padding: 12px; border-radius: 8px; text-align: center; margin-bottom: 10px; font-weight: bold; display: flex; align-items: center; justify-content: center; gap: 8px;">
+        <span style="font-size: 1.2em;">✅</span>
+        {message}
+    </div>
+    """
+
 @spaces.GPU(duration=30)
 def infer(
-    image_1,
-    image_2,
+    input_image,
     prompt,
-    lora_adapter,
+    lora_adapter_persian,
     seed,
     randomize_seed,
     guidance_scale,
     steps,
+    aspect_ratio_selection,
+    custom_width,
+    custom_height,
     progress=gr.Progress(track_tqdm=True)
 ):
-    if image_1 is None or image_2 is None:
-        raise gr.Error("Please upload both images for Fusion/Texture/FaceSwap tasks.")
-    
-    if not prompt:
-        if lora_adapter == "Cloth-Design-Fuse":
-            prompt = "Put this design on their shirt."
-        elif lora_adapter == "Texture Edit":
-            prompt = "Apply texture to object."
-        elif lora_adapter == "Fuse-Objects":
-            prompt = "Fuse object into background."
-        elif lora_adapter == "Super-Fusion":
-            prompt = "Blend the product into the background, correct its perspective and lighting, and make it naturally integrated with the scene."
-        elif lora_adapter == "Material-Transfer":
-            prompt = "change materials of image1 to match the reference in image2"
-        elif lora_adapter == "Light-Migration":
-            prompt = "Refer to the color tone, remove the original lighting from Image 1, and relight Image 1 based on the lighting and color tone of Image 2."
-            
-    adapters_map = {
-        "Texture Edit": "texture",
-        "Fuse-Objects": "fusion",
-        "Cloth-Design-Fuse": "shirt_design",
-        "Super-Fusion": "fusion-x",
-        "Material-Transfer": "material-transfer",
-        "Light-Migration": "light-migration",
-    }
-    
-    active_adapter = adapters_map.get(lora_adapter)
-    
-    if active_adapter:
-        pipe.set_adapters([active_adapter], adapter_weights=[1.0])
-    else:
-        pipe.set_adapters([], adapter_weights=[])
+    if input_image is None:
+        return None, seed, get_error_html("لطفاً ابتدا یک تصویر بارگذاری کنید.")
+
+    if is_image_nsfw(input_image):
+        return None, seed, get_error_html("تصویر ورودی دارای محتوای نامناسب است و پردازش نمی‌شود.")
 
+    english_prompt = translate_prompt(prompt)
+    if not check_text_safety(english_prompt):
+        return None, seed, get_error_html("متن درخواست شامل کلمات غیرمجاز یا غیراخلاقی است.")
+
+    adapter_internal_name = LORA_MAPPING.get(lora_adapter_persian)
+    if adapter_internal_name:
+        pipe.set_adapters([adapter_internal_name], adapter_weights=[1.0])
+    
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator(device=device).manual_seed(seed)
-    negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
+    
+    safety_negative = "nsfw, nude, naked, porn, sexual, xxx, breast, nipple, genital, vagina, penis, ass, lingerie, bikini, swimwear, underwear, fetish, topless, gore, violence, blood"
+    base_negative = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
+    final_negative_prompt = f"{safety_negative}, {base_negative}"
 
-    img1_pil = image_1.convert("RGB")
-    img2_pil = image_2.convert("RGB")
+    original_image = input_image.convert("RGB")
+    
+    selection_value = ASPECT_RATIOS_MAP.get(aspect_ratio_selection)
     
-    width, height = update_dimensions_on_upload(img1_pil)
+    if selection_value == "Custom":
+        width = (int(custom_width) // 8) * 8
+        height = (int(custom_height) // 8) * 8
+    elif selection_value == "Auto" or selection_value is None:
+        width, height = update_dimensions_on_upload(original_image)
+    else:
+        width, height = selection_value
+
+    try:
+        result = pipe(
+            image=original_image,
+            prompt=english_prompt,
+            negative_prompt=final_negative_prompt,
+            height=height,
+            width=width,
+            num_inference_steps=steps,
+            generator=generator,
+            true_cfg_scale=guidance_scale,
+        ).images[0]
 
-    result = pipe(
-        image=[img1_pil, img2_pil],
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        height=height,
-        width=width,
-        num_inference_steps=steps,
-        generator=generator,
-        true_cfg_scale=guidance_scale,
-    ).images[0]
+        if is_image_nsfw(result):
+            return None, seed, get_error_html("تصویر تولید شده حاوی محتوای نامناسب بود و حذف شد.")
+        
+        return result, seed, get_success_html("تصویر با موفقیت ویرایش شد.")
 
-    return result, seed
+    except Exception as e:
+        return None, seed, get_error_html(f"خطا در پردازش: {str(e)}")
 
 @spaces.GPU(duration=30)
-def infer_example(image_1, image_2, prompt, lora_adapter):
-    if image_1 is None or image_2 is None:
-        return None, 0
-    result, seed = infer(
-        image_1.convert("RGB"), 
-        image_2.convert("RGB"), 
-        prompt, 
-        lora_adapter, 
-        0,
-        True,
-        1.0,
-        4
-    )
-    return result, seed
+def infer_example(input_image, prompt, lora_adapter):
+    res, s, status = infer(input_image, prompt, lora_adapter, 0, True, 1.0, 4, "خودکار (پیش‌فرض)", 1024, 1024)
+    return res, s, status
+
+# --- جاوااسکریپت (اصلاح شده و قدرتمند) ---
+js_code = """
+<script>
+// تابع فورس کردن تم روشن
+function forceLightMode() {
+    const body = document.querySelector('body');
+    if (body) {
+        body.classList.remove('dark');
+        body.style.backgroundColor = '#f5f7fa';
+        body.style.color = '#333333';
+    }
+    document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
+}
+
+// تابع بستن مودال
+function closeQuotaModal() {
+    const modal = document.getElementById('custom-quota-modal');
+    if (modal) modal.style.display = 'none';
+    
+    // حذف پیام‌های خطا از صفحه تا دوباره نمایش داده نشوند
+    document.querySelectorAll('.toast-wrap').forEach(el => {
+        if (el.innerText.includes('GPU quota')) el.remove();
+    });
+}
+
+// آبزرور قدرتمند برای شکار و جایگزینی خطا
+const observer = new MutationObserver((mutations) => {
+    let quotaErrorFound = false;
+    
+    // جستجو در تمام المان‌های اضافه شده
+    mutations.forEach((mutation) => {
+        mutation.addedNodes.forEach((node) => {
+            if (node.nodeType === 1) { // Element node
+                const text = node.innerText || node.textContent;
+                // بررسی متن‌های مربوط به Quota
+                if (text && (text.includes('exceeded your GPU quota') || text.includes('GPU quota'))) {
+                    // مخفی کردن المان اصلی
+                    node.style.display = 'none';
+                    node.style.visibility = 'hidden';
+                    node.style.opacity = '0';
+                    quotaErrorFound = true;
+                }
+            }
+        });
+    });
+
+    // بررسی المان‌های موجود (برای اطمینان)
+    document.querySelectorAll('.toast-wrap, .error').forEach(el => {
+        if (el.innerText.includes('GPU quota')) {
+            el.style.display = 'none';
+            quotaErrorFound = true;
+        }
+    });
+
+    if (quotaErrorFound) {
+        const modal = document.getElementById('custom-quota-modal');
+        if (modal && modal.style.display !== 'flex') {
+            modal.style.display = 'flex';
+        }
+    }
+});
+
+document.addEventListener('DOMContentLoaded', () => {
+    forceLightMode();
+    setInterval(forceLightMode, 1000);
+    
+    // شروع مانیتور کردن
+    observer.observe(document.body, {
+        childList: true,
+        subtree: true,
+        characterData: true
+    });
+});
+</script>
+"""
+
+# جاوااسکریپت دانلود
+js_dl = """
+async (image) => {
+    if (!image) { alert("لطفاً ابتدا تصویر را تولید کنید."); return; }
+    let fileUrl = image.url;
+    if (fileUrl && !fileUrl.startsWith('http')) {
+       fileUrl = window.location.origin + fileUrl;
+    } else if (!fileUrl && image.path) {
+       fileUrl = window.location.origin + "/file=" + image.path;
+    }
+    console.log("Sending download request for:", fileUrl);
+    window.parent.postMessage({ type: 'DOWNLOAD_REQUEST', url: fileUrl }, '*');
+}
+"""
+
+# --- تنظیمات HTML و CSS ---
+html_code = """
+<style>
+@import url('https://fonts.googleapis.com/css2?family=Vazirmatn:wght@300;400;500;700&display=swap');
+
+/* تنظیمات کلی */
+:root, .dark, body, .gradio-container {
+    --body-background-fill: #f5f7fa !important;
+    --body-text-color: #1f2937 !important;
+    --background-fill-primary: #ffffff !important;
+    --background-fill-secondary: #f3f4f6 !important;
+    --border-color-primary: #e5e7eb !important;
+    --block-background-fill: #ffffff !important;
+    --block-label-text-color: #374151 !important;
+    --block-title-text-color: #111827 !important;
+    --input-background-fill: #ffffff !important;
+    color-scheme: light !important;
+}
+
+body {
+    font-family: 'Vazirmatn', sans-serif !important;
+    background-color: #f5f7fa !important;
+    margin: 0;
+    padding: 10px;
+}
+
+/* استایل مودال سفارشی */
+#custom-quota-modal {
+    position: fixed;
+    top: 0;
+    left: 0;
+    width: 100vw;
+    height: 100vh;
+    background-color: rgba(0, 0, 0, 0.85); /* تیره‌تر برای تمرکز بیشتر */
+    backdrop-filter: blur(8px);
+    z-index: 2147483647; /* بالاترین لایه ممکن */
+    display: none;
+    justify-content: center;
+    align-items: center;
+    direction: rtl;
+}
+
+.quota-modal-content {
+    background-color: white;
+    padding: 40px;
+    border-radius: 24px;
+    width: 90%;
+    max-width: 450px;
+    text-align: center;
+    box-shadow: 0 20px 60px rgba(0,0,0,0.4);
+    animation: slideIn 0.4s cubic-bezier(0.175, 0.885, 0.32, 1.275);
+    border: 1px solid rgba(255,255,255,0.2);
+}
+
+.quota-icon {
+    font-size: 72px;
+    margin-bottom: 25px;
+    display: block;
+    animation: float 3s ease-in-out infinite;
+}
+
+.quota-title {
+    font-size: 1.6em;
+    font-weight: 900;
+    color: #e11d48;
+    margin-bottom: 15px;
+}
+
+.quota-text {
+    font-size: 1.15em;
+    color: #374151;
+    line-height: 1.8;
+    margin-bottom: 30px;
+}
+
+.quota-btn {
+    background: linear-gradient(135deg, #e11d48 0%, #be123c 100%);
+    color: white;
+    border: none;
+    padding: 14px 35px;
+    border-radius: 14px;
+    font-weight: bold;
+    font-family: 'Vazirmatn', sans-serif;
+    font-size: 1.1em;
+    cursor: pointer;
+    box-shadow: 0 4px 15px rgba(225, 29, 72, 0.4);
+    transition: transform 0.2s;
+    width: 100%;
+}
+
+.quota-btn:hover {
+    transform: scale(1.02);
+}
+
+@keyframes slideIn {
+    from { opacity: 0; transform: translateY(30px) scale(0.9); }
+    to { opacity: 1; transform: translateY(0) scale(1); }
+}
+
+@keyframes float {
+    0% { transform: translateY(0px); }
+    50% { transform: translateY(-10px); }
+    100% { transform: translateY(0px); }
+}
 
-css="""
+/* مخفی کردن پیام‌های خطای پیش‌فرض Gradio */
+.toast-wrap, .toast-error, .error {
+    display: none !important;
+    opacity: 0 !important;
+    visibility: hidden !important;
+    pointer-events: none !important;
+}
+
+/* سایر استایل‌ها */
 #col-container {
     margin: 0 auto;
-    max-width: 1100px;
+    max-width: 980px;
+    direction: rtl;
+    text-align: right;
+    padding: 30px;
+    background: #ffffff !important;
+    border-radius: 24px;
+    box-shadow: 0 10px 40px -10px rgba(0,0,0,0.08); 
+    border: 1px solid rgba(255,255,255,0.8);
+}
+
+#main-title h1 {
+    font-size: 2.4em !important;
+    text-align: center;
+    color: #1a202c !important;
+    margin-bottom: 15px;
+    font-weight: 800;
+    background: -webkit-linear-gradient(45deg, #2563eb, #1e40af);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+}
+
+#main-description {
+    text-align: center;
+    font-size: 1.15em;
+    color: #4b5563 !important;
+    margin-bottom: 40px;
+    line-height: 1.6;
+}
+
+.gr-input-label, span.label-wrap, label span {
+    font-weight: 700 !important;
+    color: #374151 !important;
+    font-size: 0.95em !important;
+    margin-bottom: 8px !important;
 }
-#main-title h1 {font-size: 2.1em !important;}
+
+textarea, input[type="text"] {
+    border: 2px solid #e2e8f0 !important;
+    border-radius: 12px !important;
+    background-color: #ffffff !important;
+    color: #111827 !important;
+    padding: 12px !important;
+    font-family: 'Vazirmatn', sans-serif !important;
+}
+
+textarea:focus, input[type="text"]:focus {
+    border-color: #3b82f6 !important;
+    box-shadow: 0 0 0 4px rgba(59, 130, 246, 0.1) !important;
+    outline: none;
+}
+
+.gr-dropdown {
+    background: #ffffff !important;
+    border-radius: 12px !important;
+}
+
+.primary-btn, button.primary {
+    background: linear-gradient(135deg, #10b981 0%, #059669 100%) !important;
+    border: none !important;
+    color: white !important;
+    font-weight: 700 !important;
+    font-size: 1.1em !important;
+    padding: 14px 28px !important;
+    border-radius: 14px !important;
+    box-shadow: 0 4px 15px rgba(16, 185, 129, 0.3) !important;
+    transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
+    cursor: pointer !important;
+    width: 100%;
+    margin-top: 15px;
+}
+
+.primary-btn:hover, button.primary:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 8px 25px rgba(16, 185, 129, 0.45) !important;
+}
+
+#download-btn {
+    background: linear-gradient(135deg, #3b82f6 0%, #2563eb 100%) !important;
+    box-shadow: 0 4px 15px rgba(59, 130, 246, 0.3) !important;
+}
+#download-btn:hover {
+    box-shadow: 0 8px 25px rgba(59, 130, 246, 0.45) !important;
+}
+
+.gradio-container .prose table, 
+.gradio-container table {
+    background-color: #ffffff !important;
+    color: #111827 !important;
+    border: 1px solid #e5e7eb !important;
+    border-radius: 12px !important;
+    overflow: hidden !important;
+    width: 100% !important;
+    margin-top: 20px !important;
+}
+
+.gradio-container thead th {
+    background-color: #f3f4f6 !important;
+    color: #374151 !important;
+    font-weight: 700 !important;
+    border-bottom: 2px solid #e5e7eb !important;
+    padding: 12px !important;
+    text-align: right !important;
+}
+
+.gradio-container tbody tr {
+    background-color: #ffffff !important;
+    border-bottom: 1px solid #f3f4f6 !important;
+}
+
+.gradio-container tbody tr:hover {
+    background-color: #f9fafb !important;
+}
+
+.gradio-container tbody td {
+    background-color: #ffffff !important;
+    color: #374151 !important;
+    padding: 10px !important;
+}
+
+footer { display: none !important; }
+.flagging { display: none !important; }
+
+@media (prefers-color-scheme: dark) {
+    body, .gradio-container, .prose, table, tr, td, th {
+        background-color: #ffffff !important;
+        color: #333333 !important;
+    }
+}
+</style>
+"""
+
+modal_html = """
+<div id="custom-quota-modal">
+    <div class="quota-modal-content">
+        <span class="quota-icon">✈️</span>
+        <div class="quota-title">محدودیت استفاده</div>
+        <div class="quota-text">
+            سهمیه استفاده از گرافیک پر شده است.
+            <br><br>
+            برای ادامه، لطفاً <b>حالت هواپیما (Airplane Mode)</b> گوشی خود را یکبار روشن و خاموش کنید تا IP شما تغییر کند و سپس مجدد تلاش کنید.
+        </div>
+        <button class="quota-btn" onclick="closeQuotaModal()">متوجه شدم</button>
+    </div>
+</div>
 """
 
 with gr.Blocks() as demo:
+    # تزریق کدها به ترتیب
+    gr.HTML(html_code + modal_html + js_code)
+    
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("# **Qwen-Image-Edit-2509-LoRAs-Fast-Fusion**", elem_id="main-title")
-        gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) model.")
-        with gr.Row(equal_height=True):
-          
-            with gr.Column(scale=1):
-                with gr.Row():
-                    image_1 = gr.Image(label="Base Image", type="pil", height=290)
-                    image_2 = gr.Image(label="Reference Image", type="pil", height=290)
+        gr.Markdown("# **ویرایشگر هوشمند آلفا**", elem_id="main-title")
+        gr.Markdown(
+            "با هوش مصنوعی آلفا تصاویر تونو به مدل های مختلف ویرایش کنید.", 
+            elem_id="main-description"
+        )
 
+        with gr.Row(equal_height=True):
+            with gr.Column():
+                input_image = gr.Image(label="بارگذاری تصویر", type="pil", height=320)
+                
                 prompt = gr.Text(
-                    label="Edit Prompt",
+                    label="دستور ویرایش (به فارسی)",
                     show_label=True,
-                    placeholder="e.g., Apply wood texture to the mug...",
+                    placeholder="مثال: تصویر را به سبک انیمه تبدیل کن...",
+                    rtl=True,
+                    lines=3
                 )
                 
-                run_button = gr.Button("Edit Image", variant="primary")
-
-                with gr.Accordion("Advanced Settings", open=False, visible=False):
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
-                    randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-                    guidance_scale = gr.Slider(label="True Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
-                    steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
+                status_box = gr.HTML(label="وضعیت")
+                
+                run_button = gr.Button("✨ شروع پردازش و ساخت تصویر", variant="primary", elem_classes="primary-btn")
 
-            with gr.Column(scale=1):
-                output_image = gr.Image(label="Output Image", interactive=False, format="png", height=350)
+            with gr.Column():
+                output_image = gr.Image(label="تصویر نهایی", interactive=False, format="png", height=380)
+                
+                download_button = gr.Button("📥 دانلود و ذخیره تصویر", variant="secondary", elem_id="download-btn", elem_classes="primary-btn")
                 
                 with gr.Row():
                     lora_adapter = gr.Dropdown(
-                        label="Choose Editing Style",
-                        choices=["Texture Edit", "Cloth-Design-Fuse", "Fuse-Objects", "Super-Fusion", "Light-Migration", "Material-Transfer"],
-                        value="Texture Edit",
-                    )        
- 
+                        label="انتخاب سبک ویرایش (LoRA)",
+                        choices=list(LORA_MAPPING.keys()),
+                        value="تبدیل عکس به انیمه"
+                    )
+                
+                with gr.Accordion("تنظیمات پیشرفته", open=False, visible=True):
+                    aspect_ratio_selection = gr.Dropdown(
+                        label="ابعاد تصویر خروجی",
+                        choices=ASPECT_RATIOS_LIST,
+                        value="خودکار (پیش‌فرض)",
+                        interactive=True
+                    )
+                    
+                    with gr.Row(visible=False) as custom_dims_row:
+                        custom_width = gr.Slider(
+                            label="عرض دلخواه (Width)",
+                            minimum=256, maximum=2048, step=8, value=1024
+                        )
+                        custom_height = gr.Slider(
+                            label="ارتفاع دلخواه (Height)",
+                            minimum=256, maximum=2048, step=8, value=1024
+                        )
+                    
+                    seed = gr.Slider(label="دانه تصادفی (Seed)", minimum=0, maximum=MAX_SEED, step=1, value=0)
+                    randomize_seed = gr.Checkbox(label="استفاده از Seed تصادفی", value=True)
+                    guidance_scale = gr.Slider(label="میزان وفاداری به متن (Guidance Scale)", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
+                    steps = gr.Slider(label="تعداد مراحل پردازش (Steps)", minimum=1, maximum=50, step=1, value=4)
+        
+        def toggle_row(choice):
+            if choice == "شخصی‌سازی (Custom)":
+                return gr.update(visible=True)
+            return gr.update(visible=False)
+
+        aspect_ratio_selection.change(
+            fn=toggle_row,
+            inputs=aspect_ratio_selection,
+            outputs=custom_dims_row
+        )
+
         gr.Examples(
             examples=[
-                ["examples/M1.jpg", "examples/M2.jpg", "Refer to the color tone, remove the original lighting from Image 1, and relight Image 1 based on the lighting and color tone of Image 2.", "Light-Migration"],
-                ["examples/Cloth2.jpg", "examples/Design2.png", "Put this design on their shirt.", "Cloth-Design-Fuse"],
-                ["examples/Cup1.png", "examples/Wood1.png", "Apply wood texture to mug.", "Texture Edit"],
-                ["examples/Cloth1.jpg", "examples/Design1.png", "Put this design on their shirt.", "Cloth-Design-Fuse"],
-                ["examples/F3.jpg", "examples/F4.jpg", "Replace her glasses with the new glasses from image 1.", "Super-Fusion"],
-                ["examples/Chair.jpg", "examples/Material.jpg", "Change materials of image1 to match the reference in image2.", "Material-Transfer"],
-                ["examples/F1.jpg", "examples/F2.jpg", "Put the small bottle on the table.", "Super-Fusion"],
-                ["examples/Mug1.jpg", "examples/Texture1.jpg", "Apply the design from image 2 to the mug.", "Texture Edit"],
-                ["examples/Cat1.jpg", "examples/Glass1.webp", "A cat wearing glasses in image 2.", "Fuse-Objects"],
-
+                ["examples/1.jpg", "تبدیل به انیمه کن.", "تبدیل عکس به انیمه"],
+                ["examples/5.jpg", "سایه‌ها را حذف کن و نورپردازی نرم به تصویر بده.", "اصلاح نور و سایه"],
+                ["examples/4.jpg", "از فیلتر ساعت طلایی با پخش نور ملایم استفاده کن.", "نورپردازی مجدد (Relight)"],
+                ["examples/2.jpeg", "دوربین را ۴۵ درجه به سمت چپ بچرخان.", "تغییر زاویه دید"],
+                ["examples/7.jpg", "منبع نور را از سمت راست عقب قرار بده.", "نورپردازی چند زاویه‌ای"],
+                ["examples/10.jpeg", "کیفیت تصویر را افزایش بده (Upscale).", "افزایش کیفیت (Upscale)"],
+                ["examples/7.jpg", "منبع نور را از پایین بتابان.", "نورپردازی چند زاویه‌ای"],
+                ["examples/2.jpeg", "زاویه دوربین را به نمای بالا گوشه راست تغییر بده.", "تغییر زاویه دید"],
+                ["examples/9.jpg", "دوربین کمی به جلو حرکت می‌کند در حالی که نور خورشید از میان ابرها می‌تابد و درخششی نرم اطراف شبح شخصیت در مه ایجاد می‌کند. سبک سینمایی واقعی.", "صحنه بعدی (سینمایی)"],
+                ["examples/8.jpg", "جزئیات پوست سوژه را برجسته‌تر و طبیعی‌تر کن.", "روتوش پوست"],
+                ["examples/6.jpg", "دوربین را به نمای پایین به بالا تغییر بده.", "تغییر زاویه دید"],
             ],
-            inputs=[image_1, image_2, prompt, lora_adapter],
-            outputs=[output_image, seed],
+            inputs=[input_image, prompt, lora_adapter],
+            outputs=[output_image, seed, status_box],
             fn=infer_example,
             cache_examples=False,
-            label="Examples"
+            label="نمونه‌ها (برای تست کلیک کنید)"
         )
 
     run_button.click(
         fn=infer,
-        inputs=[image_1, image_2, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
-        outputs=[output_image, seed]
+        inputs=[input_image, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps, aspect_ratio_selection, custom_width, custom_height],
+        outputs=[output_image, seed, status_box],
+        api_name="predict"
     )
-    
+
+    download_button.click(
+        fn=None,
+        inputs=[output_image],
+        outputs=None,
+        js=js_dl
+    )
+
 if __name__ == "__main__":
-    demo.queue(max_size=50).launch(css=css, theme=orange_red_theme, mcp_server=True, ssr_mode=False, show_error=True)
+    demo.queue(max_size=30).launch(show_error=True)