fastvideogen

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fantaxy commited on Jun 10

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baf7ca7

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1 Parent(s): 3a578db

Update app.py

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@@ -1,402 +1,824 @@
-import spaces
-from functools import lru_cache
-import gradio as gr
-from gradio_toggle import Toggle
-import torch
-from huggingface_hub import snapshot_download
-from transformers import CLIPProcessor, CLIPModel, pipeline
-import random
-from xora.models.autoencoders.causal_video_autoencoder import CausalVideoAutoencoder
-from xora.models.transformers.transformer3d import Transformer3DModel
-from xora.models.transformers.symmetric_patchifier import SymmetricPatchifier
-from xora.schedulers.rf import RectifiedFlowScheduler
-from xora.pipelines.pipeline_xora_video import XoraVideoPipeline
-from transformers import T5EncoderModel, T5Tokenizer
-from xora.utils.conditioning_method import ConditioningMethod
-from pathlib import Path
-import safetensors.torch
-import json
-import numpy as np
-import cv2
-from PIL import Image
-import tempfile
-import os
-import gc
-import csv
-from datetime import datetime
-from openai import OpenAI
-# 한글-영어 번역기 초기화
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
-torch.backends.cuda.matmul.allow_tf32 = False
-torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
-torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
-torch.backends.cudnn.allow_tf32 = False
-torch.backends.cudnn.deterministic = False
-torch.backends.cuda.preferred_blas_library="cublas"
-torch.set_float32_matmul_precision("highest")
-MAX_SEED = np.iinfo(np.int32).max
-# Load Hugging Face token if needed
-hf_token = os.getenv("HF_TOKEN")
-openai_api_key = os.getenv("OPENAI_API_KEY")
-client = OpenAI(api_key=openai_api_key)
-system_prompt_t2v_path = "assets/system_prompt_t2v.txt"
-with open(system_prompt_t2v_path, "r") as f:
-    system_prompt_t2v = f.read()
-# Set model download directory within Hugging Face Spaces
-model_path = "asset"
-commit_hash='c7c8ad4c2ddba847b94e8bfaefbd30bd8669fafc'
-if not os.path.exists(model_path):
-    snapshot_download("Lightricks/LTX-Video", revision=commit_hash, local_dir=model_path, repo_type="model", token=hf_token)
-# Global variables to load components
-vae_dir = Path(model_path) / "vae"
-unet_dir = Path(model_path) / "unet"
-scheduler_dir = Path(model_path) / "scheduler"
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-clip_model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32", cache_dir=model_path).to(torch.device("cuda:0"))
-clip_processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32", cache_dir=model_path)
-def process_prompt(prompt):
-    # 한글이 포함되어 있는지 확인
-    if any(ord('가') <= ord(char) <= ord('힣') for char in prompt):
-        # 한글을 영어로 번역
-        translated = translator(prompt)[0]['translation_text']
-        return translated
-    return prompt
-def compute_clip_embedding(text=None):
-    inputs = clip_processor(text=text, return_tensors="pt", padding=True).to(device)
-    outputs = clip_model.get_text_features(**inputs)
-    embedding = outputs.detach().cpu().numpy().flatten().tolist()
-    return embedding
-def load_vae(vae_dir):
-    vae_ckpt_path = vae_dir / "vae_diffusion_pytorch_model.safetensors"
-    vae_config_path = vae_dir / "config.json"
-    with open(vae_config_path, "r") as f:
-        vae_config = json.load(f)
-    vae = CausalVideoAutoencoder.from_config(vae_config)
-    vae_state_dict = safetensors.torch.load_file(vae_ckpt_path)
-    vae.load_state_dict(vae_state_dict)
-    return vae.to(device).to(torch.bfloat16)
-def load_unet(unet_dir):
-    unet_ckpt_path = unet_dir / "unet_diffusion_pytorch_model.safetensors"
-    unet_config_path = unet_dir / "config.json"
-    transformer_config = Transformer3DModel.load_config(unet_config_path)
-    transformer = Transformer3DModel.from_config(transformer_config)
-    unet_state_dict = safetensors.torch.load_file(unet_ckpt_path)
-    transformer.load_state_dict(unet_state_dict, strict=True)
-    return transformer.to(device).to(torch.bfloat16)
-def load_scheduler(scheduler_dir):
-    scheduler_config_path = scheduler_dir / "scheduler_config.json"
-    scheduler_config = RectifiedFlowScheduler.load_config(scheduler_config_path)
-    return RectifiedFlowScheduler.from_config(scheduler_config)
-# Preset options for resolution and frame configuration
-preset_options = [
-    {"label": "1216x704, 41 frames", "width": 1216, "height": 704, "num_frames": 41},
-    {"label": "1088x704, 49 frames", "width": 1088, "height": 704, "num_frames": 49},
-    {"label": "1056x640, 57 frames", "width": 1056, "height": 640, "num_frames": 57},
-    {"label": "448x448, 100 frames", "width": 448, "height": 448, "num_frames": 100},
-    {"label": "448x448, 200 frames", "width": 448, "height": 448, "num_frames": 200},
-    {"label": "448x448, 300 frames", "width": 448, "height": 448, "num_frames": 300},
-    {"label": "640x640, 80 frames", "width": 640, "height": 640, "num_frames": 80},
-    {"label": "640x640, 120 frames", "width": 640, "height": 640, "num_frames": 120},
-    {"label": "768x768, 64 frames", "width": 768, "height": 768, "num_frames": 64},
-    {"label": "768x768, 90 frames", "width": 768, "height": 768, "num_frames": 90},
-    {"label": "720x720, 64 frames", "width": 768, "height": 768, "num_frames": 64},
-    {"label": "720x720, 100 frames", "width": 768, "height": 768, "num_frames": 100},
-    {"label": "768x512, 97 frames", "width": 768, "height": 512, "num_frames": 97},
-    {"label": "512x512, 160 frames", "width": 512, "height": 512, "num_frames": 160},
-    {"label": "512x512, 200 frames", "width": 512, "height": 512, "num_frames": 200},
 ]
-def preset_changed(preset):
-    if preset != "Custom":
-        selected = next(item for item in preset_options if item["label"] == preset)
-        return (
-            selected["height"],
-            selected["width"],
-            selected["num_frames"],
-            gr.update(visible=False),
-            gr.update(visible=False),
-            gr.update(visible=False),
-        )
-    else:
-        return (
-            None,
-            None,
-            None,
-            gr.update(visible=True),
-            gr.update(visible=True),
-            gr.update(visible=True),
-        )
-# Load models
-vae = load_vae(vae_dir)
-unet = load_unet(unet_dir)
-scheduler = load_scheduler(scheduler_dir)
-patchifier = SymmetricPatchifier(patch_size=1)
-text_encoder = T5EncoderModel.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", subfolder="text_encoder").to(torch.device("cuda:0"))
-tokenizer = T5Tokenizer.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", subfolder="tokenizer")
-pipeline = XoraVideoPipeline(
-    transformer=unet,
-    patchifier=patchifier,
-    text_encoder=text_encoder,
-    tokenizer=tokenizer,
-    scheduler=scheduler,
-    vae=vae,
-).to(torch.device("cuda:0"))
-def enhance_prompt_if_enabled(prompt, enhance_toggle):
-    if not enhance_toggle:
-        print("Enhance toggle is off, Prompt: ", prompt)
-        return prompt
-    messages = [
-        {"role": "system", "content": system_prompt_t2v},
-        {"role": "user", "content": prompt},
-    ]
     try:
-        response = client.chat.completions.create(
-            model="gpt-4-mini",
-            messages=messages,
-            max_tokens=200,
-        )
-        print("Enhanced Prompt: ", response.choices[0].message.content.strip())
-        return response.choices[0].message.content.strip()
-    except Exception as e:
-        print(f"Error: {e}")
-        return prompt
-@spaces.GPU(duration=90)
-def generate_video_from_text_90(
-    prompt="",
-    enhance_prompt_toggle=False,
-    negative_prompt="",
-    frame_rate=25,
-    seed=random.randint(0, MAX_SEED),
-    num_inference_steps=30,
-    guidance_scale=3.2,
-    height=768,
-    width=768,
-    num_frames=60,
-    progress=gr.Progress(),
-):
-    # 프롬프트 전처리 (한글 -> 영어)
-    prompt = process_prompt(prompt)
-    negative_prompt = process_prompt(negative_prompt)
-    if len(prompt.strip()) < 50:
-        raise gr.Error(
-            "Prompt must be at least 50 characters long. Please provide more details for the best results.",
-            duration=5,
-        )
-    prompt = enhance_prompt_if_enabled(prompt, enhance_prompt_toggle)
-    sample = {
-        "prompt": prompt,
-        "prompt_attention_mask": None,
-        "negative_prompt": negative_prompt,
-        "negative_prompt_attention_mask": None,
-        "media_items": None,
-    }
-    generator = torch.Generator(device="cuda").manual_seed(seed)
-    def gradio_progress_callback(self, step, timestep, kwargs):
-        progress((step + 1) / num_inference_steps)
     try:
-        with torch.no_grad():
-            images = pipeline(
-                num_inference_steps=num_inference_steps,
-                num_images_per_prompt=1,
-                guidance_scale=guidance_scale,
-                generator=generator,
-                output_type="pt",
-                height=height,
-                width=width,
-                num_frames=num_frames,
-                frame_rate=frame_rate,
-                **sample,
-                is_video=True,
-                vae_per_channel_normalize=True,
-                conditioning_method=ConditioningMethod.UNCONDITIONAL,
-                mixed_precision=True,
-                callback_on_step_end=gradio_progress_callback,
-            ).images
     except Exception as e:
-        raise gr.Error(
-            f"An error occurred while generating the video. Please try again. Error: {e}",
-            duration=5,
-        )
     finally:
-        torch.cuda.empty_cache()
-        gc.collect()
-    output_path = tempfile.mktemp(suffix=".mp4")
-    video_np = images.squeeze(0).permute(1, 2, 3, 0).cpu().float().numpy()
-    video_np = (video_np * 255).astype(np.uint8)
-    height, width = video_np.shape[1:3]
-    out = cv2.VideoWriter(output_path, cv2.VideoWriter_fourcc(*"mp4v"), frame_rate, (width, height))
-    for frame in video_np[..., ::-1]:
-        out.write(frame)
-    out.release()
-    del images
-    del video_np
-    torch.cuda.empty_cache()
-    return output_path
-def create_advanced_options():
-    with gr.Accordion("Step 4: Advanced Options (Optional)", open=False):
-        seed = gr.Slider(label="4.1 Seed", minimum=0, maximum=1000000, step=1, value=646373)
-        inference_steps = gr.Slider(label="4.2 Inference Steps", minimum=5, maximum=150, step=5, value=40)
-        guidance_scale = gr.Slider(label="4.3 Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=4.2)
-        height_slider = gr.Slider(
-            label="4.4 Height",
-            minimum=256,
-            maximum=1024,
-            step=64,
-            value=768,
-            visible=False,
-        )
-        width_slider = gr.Slider(
-            label="4.5 Width",
-            minimum=256,
-            maximum=1024,
-            step=64,
-            value=768,
-            visible=False,
-        )
-        num_frames_slider = gr.Slider(
-            label="4.5 Number of Frames",
-            minimum=1,
-            maximum=500,
-            step=1,
-            value=60,
-            visible=False,
-        )
-        return [
-            seed,
-            inference_steps,
-            guidance_scale,
-            height_slider,
-            width_slider,
-            num_frames_slider,
-        ]
-css = """
-footer {
-    visibility: hidden;
 }
-/* 비디오 출력 컨테이너 크기 조정 */
-.video-output-container {
-    max-width: 50%;
-    margin-left: auto;
-    margin-right: auto;
 }
-/* 비디오 플레이어 크기 조정 */
-.video-player {
-    width: 100%;
-    max-height: 50vh;
-    object-fit: contain;
 }
-"""
-with gr.Blocks(theme="soft", css=css) as iface:
-    with gr.Row():
-        # 입력 섹션 (왼쪽)
-        with gr.Column(scale=1):
-            txt2vid_prompt = gr.Textbox(
-                label="Step 1: Enter Your Prompt (한글 또는 영어)",
-                placeholder="Describe the video you want to create (at least 50 characters)...",
-                value="A sleek vintage classic car is driving along a Hawaiian coastal road, seen from a low-angle front bumper camera view, with the ocean waves and palm trees rolling by in the background.",
-                lines=5,
-            )
-            txt2vid_enhance_toggle = Toggle(
-                label="Enhance Prompt",
-                value=False,
-                interactive=True,
-            )
-            txt2vid_negative_prompt = gr.Textbox(
-                label="Step 2: Enter Negative Prompt",
-                placeholder="Describe the elements you do not want in the video...",
-                value="low quality, worst quality, deformed, distorted, damaged, motion blur, motion artifacts, fused fingers, incorrect anatomy, strange hands, ugly",
-                lines=2,
-            )
-            txt2vid_preset = gr.Dropdown(
-                choices=[p["label"] for p in preset_options],
-                value="512x512, 160 frames",
-                label="Step 3.1: Choose Resolution Preset",
-            )
-            txt2vid_frame_rate = gr.Slider(
-                label="Step 3.2: Frame Rate",
-                minimum=6,
-                maximum=60,
-                step=1,
-                value=20,
-            )
-            txt2vid_advanced = create_advanced_options()
-            txt2vid_generate = gr.Button(
-                "Step 5: Generate Video",
-                variant="primary",
-                size="lg",
-            )
-        # 출력 섹션 (오른쪽)
-        with gr.Column(scale=1):
-            txt2vid_output = gr.Video(
-                label="Generated Output",
-                elem_classes=["video-output-container", "video-player"]
-            )
-    txt2vid_preset.change(
-        fn=preset_changed,
-        inputs=[txt2vid_preset],
-        outputs=txt2vid_advanced[3:],
-    )
-    txt2vid_generate.click(
-        fn=generate_video_from_text_90,
-        inputs=[
-            txt2vid_prompt,
-            txt2vid_enhance_toggle,
-            txt2vid_negative_prompt,
-            txt2vid_frame_rate,
-            *txt2vid_advanced,
-        ],
-        outputs=txt2vid_output,
-        concurrency_limit=1,
-        concurrency_id="generate_video",
-        queue=True,
-    )
-iface.queue(max_size=64, default_concurrency_limit=1, api_open=False).launch(share=True, show_api=False)

+from flask import Flask, render_template, request, jsonify
+import os, re, json, sqlite3
+app = Flask(__name__)
+# ────────────────────────── 1. CONFIGURATION ──────────────────────────
+DB_FILE = "favorite_sites.json"  # JSON file for backward compatibility
+SQLITE_DB = "favorite_sites.db"  # SQLite database for persistence
+# Domains that commonly block iframes
+BLOCKED_DOMAINS = [
+    "naver.com", "daum.net", "google.com",
+    "facebook.com", "instagram.com", "kakao.com",
+    "ycombinator.com"
 ]
+# ────────────────────────── 2. CURATED CATEGORIES ──────────────────────────
+CATEGORIES = {
+    "Productivity": [
+        "https://huggingface.co/spaces/openfree/Chart-GPT",
+        "https://huggingface.co/spaces/ginipick/AI-BOOK",
+        "https://huggingface.co/spaces/VIDraft/Voice-Clone-Podcast",
+        "https://huggingface.co/spaces/ginipick/PDF-EXAM",
+        "https://huggingface.co/spaces/ginigen/perflexity-clone",
+        "https://huggingface.co/spaces/ginipick/IDEA-DESIGN",
+        "https://huggingface.co/spaces/ginipick/10m-marketing",
+        "https://huggingface.co/spaces/openfree/Live-Podcast",
+        "https://huggingface.co/spaces/openfree/AI-Podcast",
+        "https://huggingface.co/spaces/ginipick/QR-Canvas-plus",
+        "https://huggingface.co/spaces/openfree/Badge",
+        "https://huggingface.co/spaces/VIDraft/mouse-webgen",
+        "https://huggingface.co/spaces/openfree/Vibe-Game",
+        "https://huggingface.co/spaces/VIDraft/NH-Prediction",
+        "https://huggingface.co/spaces/ginipick/NH-Korea",
+        "https://huggingface.co/spaces/openfree/Naming",
+        "https://huggingface.co/spaces/ginipick/Change-Hair",
+    ],
+    "Multimodal": [
+        "https://huggingface.co/spaces/Heartsync/adult",
+        "https://huggingface.co/spaces/Heartsync/NSFW-Uncensored",
+        "https://huggingface.co/spaces/Heartsync/NSFW-Uncensored-video2",
+        "https://huggingface.co/spaces/Heartsync/NSFW-Uncensored-video",
+        "https://huggingface.co/spaces/Heartsync/WAN-VIDEO-AUDIO",
+        "https://huggingface.co/spaces/Heartsync/wan2-1-fast-security",
+        "https://huggingface.co/spaces/ginigen/Flux-VIDEO",
+        "https://huggingface.co/spaces/ginigen/3D-LLAMA-V1",
+        "https://huggingface.co/spaces/ginigen/Flux-VIDEO",
+        "https://huggingface.co/spaces/openfree/Multilingual-TTS",
+        "https://huggingface.co/spaces/VIDraft/ACE-Singer",
+        "https://huggingface.co/spaces/openfree/DreamO-video",
+        "https://huggingface.co/spaces/fantaxy/Sound-AI-SFX",
+        "https://huggingface.co/spaces/ginigen/SFX-Sound-magic",
+        "https://huggingface.co/spaces/ginigen/VoiceClone-TTS",
+        "https://huggingface.co/spaces/aiqcamp/ENGLISH-Speaking-Scoring",
+        "https://huggingface.co/spaces/fantaxy/Remove-Video-Background",
+    ],
+    "Professional": [
+        "https://huggingface.co/spaces/Heartsync/Novel-NSFW",
+        "https://huggingface.co/spaces/fantaxy/fantasy-novel",
+        "https://huggingface.co/spaces/VIDraft/money-radar",
+        "https://huggingface.co/spaces/immunobiotech/drug-discovery",
+        "https://huggingface.co/spaces/immunobiotech/Gemini-MICHELIN",
+        "https://huggingface.co/spaces/openfree/Cycle-Navigator",
+        "https://huggingface.co/spaces/VIDraft/Fashion-Fit",
+        "https://huggingface.co/spaces/openfree/Stock-Trading-Analysis",
+        "https://huggingface.co/spaces/ginipick/AgentX-Papers",
+        "https://huggingface.co/spaces/Heartsync/Papers-Leaderboard",
+        "https://huggingface.co/spaces/VIDraft/PapersImpact",
+        "https://huggingface.co/spaces/ginigen/multimodal-chat-mbti-korea",
+    ],
+    "Image": [
+        "https://huggingface.co/spaces/ginigen/FLUX-Ghibli-LoRA2",
+        "https://huggingface.co/spaces/aiqcamp/REMOVAL-TEXT-IMAGE",
+        "https://huggingface.co/spaces/VIDraft/BAGEL-Websearch",
+        "https://huggingface.co/spaces/ginigen/Every-Text",
+        "https://huggingface.co/spaces/ginigen/text3d-r1",
+        "https://huggingface.co/spaces/ginipick/FLUXllama",
+        "https://huggingface.co/spaces/ginigen/Workflow-Canvas",
+        "https://huggingface.co/spaces/ginigen/canvas-studio",
+        "https://huggingface.co/spaces/VIDraft/ReSize-Image-Outpainting",
+        "https://huggingface.co/spaces/Heartsync/FLUX-Vision",
+        "https://huggingface.co/spaces/fantos/textcutobject",
+        "https://huggingface.co/spaces/aiqtech/imaginpaint",
+        "https://huggingface.co/spaces/openfree/ColorRevive",
+        "https://huggingface.co/spaces/openfree/ultpixgen",
+        "https://huggingface.co/spaces/VIDraft/Polaroid-Style",
+        "https://huggingface.co/spaces/ginigen/VisualCloze",
+        "https://huggingface.co/spaces/fantaxy/ofai-flx-logo",
+        "https://huggingface.co/spaces/ginigen/interior-design",
+        "https://huggingface.co/spaces/ginigen/MagicFace-V3",
+        "https://huggingface.co/spaces/fantaxy/flx-pulid",
+        "https://huggingface.co/spaces/seawolf2357/Ghibli-Multilingual-Text-rendering",
+        "https://huggingface.co/spaces/VIDraft/Open-Meme-Studio",
+        "https://huggingface.co/spaces/VIDraft/stable-diffusion-3.5-large-turboX",
+        "https://huggingface.co/spaces/aiqtech/flxgif",
+        "https://huggingface.co/spaces/openfree/VectorFlow",
+#        "https://huggingface.co/spaces/ginigen/3D-LLAMA",
+#         "https://huggingface.co/spaces/ginigen/Multi-LoRAgen",
+    ],
+    "LLM / VLM": [
+        "https://huggingface.co/spaces/ginigen/deepseek-r1-0528-API",
+        "https://huggingface.co/spaces/aiqcamp/Mistral-Devstral-API"
+        "https://huggingface.co/spaces/aiqcamp/deepseek-r1-0528",
+        "https://huggingface.co/spaces/aiqcamp/deepseek-r1-0528-qwen3-8b",
+        "https://huggingface.co/spaces/aiqcamp/deepseek-r1-0528",
+        "https://huggingface.co/spaces/aiqcamp/Mistral-Devstral-API",
+        "https://huggingface.co/spaces/VIDraft/Mistral-RAG-BitSix",
+        "https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-4B",
+        "https://huggingface.co/spaces/VIDraft/Gemma-3-R1984-12B",
+        "https://huggingface.co/spaces/ginigen/Mistral-Perflexity",
+        "https://huggingface.co/spaces/aiqcamp/gemini-2.5-flash-preview",
+        "https://huggingface.co/spaces/openfree/qwen3-30b-a3b-research",
+        "https://huggingface.co/spaces/openfree/qwen3-235b-a22b-research",
+        "https://huggingface.co/spaces/openfree/Llama-4-Maverick-17B-Research",
+    ],
+}
+# ────────────────────────── 3. DATABASE FUNCTIONS ──────────────────────────
+def init_db():
+    # Initialize JSON file if it doesn't exist
+    if not os.path.exists(DB_FILE):
+        with open(DB_FILE, "w", encoding="utf-8") as f:
+            json.dump([], f, ensure_ascii=False)
+    # Initialize SQLite database
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    cursor.execute('''
+    CREATE TABLE IF NOT EXISTS urls (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        url TEXT UNIQUE NOT NULL,
+        date_added TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+    )
+    ''')
+    conn.commit()
+    # If we have data in JSON but not in SQLite (first run with new SQLite DB),
+    # migrate the data from JSON to SQLite
+    json_urls = load_json()
+    if json_urls:
+        db_urls = load_db_sqlite()
+        for url in json_urls:
+            if url not in db_urls:
+                add_url_to_sqlite(url)
+    conn.close()
+def load_json():
+    """Load URLs from JSON file (for backward compatibility)"""
     try:
+        with open(DB_FILE, "r", encoding="utf-8") as f:
+            raw = json.load(f)
+        return raw if isinstance(raw, list) else []
+    except Exception:
+        return []
+def save_json(lst):
+    """Save URLs to JSON file (for backward compatibility)"""
+    try:
+        with open(DB_FILE, "w", encoding="utf-8") as f:
+            json.dump(lst, f, ensure_ascii=False, indent=2)
+        return True
+    except Exception:
+        return False
+def load_db_sqlite():
+    """Load URLs from SQLite database"""
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    cursor.execute("SELECT url FROM urls ORDER BY date_added DESC")
+    urls = [row[0] for row in cursor.fetchall()]
+    conn.close()
+    return urls
+def add_url_to_sqlite(url):
+    """Add a URL to SQLite database"""
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    try:
+        cursor.execute("INSERT INTO urls (url) VALUES (?)", (url,))
+        conn.commit()
+        success = True
+    except sqlite3.IntegrityError:
+        # URL already exists
+        success = False
+    conn.close()
+    return success
+def update_url_in_sqlite(old_url, new_url):
+    """Update a URL in SQLite database"""
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    try:
+        cursor.execute("UPDATE urls SET url = ? WHERE url = ?", (new_url, old_url))
+        if cursor.rowcount > 0:
+            conn.commit()
+            success = True
+        else:
+            success = False
+    except sqlite3.IntegrityError:
+        # New URL already exists
+        success = False
+    conn.close()
+    return success
+def delete_url_from_sqlite(url):
+    """Delete a URL from SQLite database"""
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    cursor.execute("DELETE FROM urls WHERE url = ?", (url,))
+    if cursor.rowcount > 0:
+        conn.commit()
+        success = True
+    else:
+        success = False
+    conn.close()
+    return success
+def load_db():
+    """Primary function to load URLs - prioritizes SQLite DB but falls back to JSON"""
+    urls = load_db_sqlite()
+    if not urls:
+        # If SQLite DB is empty, try loading from JSON
+        urls = load_json()
+        # If we found URLs in JSON, migrate them to SQLite
+        for url in urls:
+            add_url_to_sqlite(url)
+    return urls
+def save_db(lst):
+    """Save URLs to both SQLite and JSON"""
+    # Get existing URLs from SQLite for comparison
+    existing_urls = load_db_sqlite()
+    # Clear all URLs from SQLite and add the new list
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
+    cursor.execute("DELETE FROM urls")
+    for url in lst:
+        cursor.execute("INSERT INTO urls (url) VALUES (?)", (url,))
+    conn.commit()
+    conn.close()
+    # Also save to JSON for backward compatibility
+    return save_json(lst)
+# ────────────────────────── 4. URL HELPERS ──────────────────────────
+def direct_url(hf_url):
+    m = re.match(r"https?://huggingface\.co/spaces/([^/]+)/([^/?#]+)", hf_url)
+    if not m:
+        return hf_url
+    owner, name = m.groups()
+    owner = owner.lower()
+    name = name.replace('.', '-').replace('_', '-').lower()
+    return f"https://{owner}-{name}.hf.space"
+def screenshot_url(url):
+    return f"https://image.thum.io/get/fullpage/{url}"
+def process_url_for_preview(url):
+    """Returns (preview_url, mode)"""
+    # Handle blocked domains first
+    if any(d for d in BLOCKED_DOMAINS if d in url):
+        return screenshot_url(url), "snapshot"
+    # Special case handling for problematic URLs
+    if "vibe-coding-tetris" in url or "World-of-Tank-GAME" in url or "Minesweeper-Game" in url:
+        return screenshot_url(url), "snapshot"
+    # General HF space handling
+    try:
+        if "huggingface.co/spaces" in url:
+            parts = url.rstrip("/").split("/")
+            if len(parts) >= 5:
+                owner = parts[-2]
+                name = parts[-1]
+                embed_url = f"https://huggingface.co/spaces/{owner}/{name}/embed"
+                return embed_url, "iframe"
+    except Exception:
+        return screenshot_url(url), "snapshot"
+    # Default handling
+    return url, "iframe"
+# ────────────────────────── 5. API ROUTES ──────────────────────────
+@app.route('/api/category')
+def api_category():
+    cat = request.args.get('name', '')
+    urls = CATEGORIES.get(cat, [])
+    # Add pagination for categories as well
+    page = int(request.args.get('page', 1))
+    per_page = int(request.args.get('per_page', 4))  # Changed to 4 per page
+    total_pages = max(1, (len(urls) + per_page - 1) // per_page)
+    start = (page - 1) * per_page
+    end = min(start + per_page, len(urls))
+    urls_page = urls[start:end]
+    items = [
+        {
+            "title": url.split('/')[-1],
+            "owner": url.split('/')[-2] if '/spaces/' in url else '',
+            "iframe": direct_url(url),
+            "shot": screenshot_url(url),
+            "hf": url
+        } for url in urls_page
+    ]
+    return jsonify({
+        "items": items,
+        "page": page,
+        "total_pages": total_pages
+    })
+@app.route('/api/favorites')
+def api_favorites():
+    # Load URLs from SQLite database
+    urls = load_db()
+    page = int(request.args.get('page', 1))
+    per_page = int(request.args.get('per_page', 4))  # Changed to 4 per page
+    total_pages = max(1, (len(urls) + per_page - 1) // per_page)
+    start = (page - 1) * per_page
+    end = min(start + per_page, len(urls))
+    urls_page = urls[start:end]
+    result = []
+    for url in urls_page:
+        try:
+            preview_url, mode = process_url_for_preview(url)
+            result.append({
+                "title": url.split('/')[-1],
+                "url": url,
+                "preview_url": preview_url,
+                "mode": mode
+            })
+        except Exception:
+            # Fallback to screenshot mode
+            result.append({
+                "title": url.split('/')[-1],
+                "url": url,
+                "preview_url": screenshot_url(url),
+                "mode": "snapshot"
+            })
+    return jsonify({
+        "items": result,
+        "page": page,
+        "total_pages": total_pages
+    })
+@app.route('/api/url/add', methods=['POST'])
+def add_url():
+    url = request.form.get('url', '').strip()
+    if not url:
+        return jsonify({"success": False, "message": "URL is required"})
+    # SQLite에 추가 시도
+    conn = sqlite3.connect(SQLITE_DB)
+    cursor = conn.cursor()
     try:
+        cursor.execute("INSERT INTO urls (url) VALUES (?)", (url,))
+        conn.commit()
+        success = True
+    except sqlite3.IntegrityError:
+        # URL이 이미 존재하는 경우
+        success = False
     except Exception as e:
+        print(f"SQLite error: {str(e)}")
+        success = False
     finally:
+        conn.close()
+    if not success:
+        return jsonify({"success": False, "message": "URL already exists or could not be added"})
+    # JSON 파일에도 추가 (백업용)
+    data = load_json()
+    if url not in data:
+        data.insert(0, url)
+        save_json(data)
+    return jsonify({"success": True, "message": "URL added successfully"})
+@app.route('/api/url/update', methods=['POST'])
+def update_url():
+    old = request.form.get('old', '')
+    new = request.form.get('new', '').strip()
+    if not new:
+        return jsonify({"success": False, "message": "New URL is required"})
+    # Update in SQLite DB
+    if not update_url_in_sqlite(old, new):
+        return jsonify({"success": False, "message": "URL not found or new URL already exists"})
+    # Also update JSON file for backward compatibility
+    data = load_json()
+    try:
+        idx = data.index(old)
+        data[idx] = new
+        save_json(data)
+    except ValueError:
+        # If URL not in JSON, add it
+        data.append(new)
+        save_json(data)
+    return jsonify({"success": True, "message": "URL updated successfully"})
+@app.route('/api/url/delete', methods=['POST'])
+def delete_url():
+    url = request.form.get('url', '')
+    # Delete from SQLite DB
+    if not delete_url_from_sqlite(url):
+        return jsonify({"success": False, "message": "URL not found"})
+    # Also update JSON file for backward compatibility
+    data = load_json()
+    try:
+        data.remove(url)
+        save_json(data)
+    except ValueError:
+        pass
+    return jsonify({"success": True, "message": "URL deleted successfully"})
+# ────────────────────────── 6. MAIN ROUTES ──────────────────────────
+@app.route('/')
+def home():
+    os.makedirs('templates', exist_ok=True)
+    with open('templates/index.html', 'w', encoding='utf-8') as fp:
+        fp.write(r'''<!DOCTYPE html>
+<html>
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<title>Web Gallery</title>
+<style>
+@import url('https://fonts.googleapis.com/css2?family=Nunito:wght@300;600&display=swap');
+body{margin:0;font-family:Nunito,sans-serif;background:#f6f8fb;}
+.tabs{display:flex;flex-wrap:wrap;gap:8px;padding:16px;}
+.tab{padding:6px 14px;border:none;border-radius:18px;background:#e2e8f0;font-weight:600;cursor:pointer;}
+.tab.active{background:#a78bfa;color:#1a202c;}
+.tab.manage{background:#ff6e91;color:white;}
+.tab.manage.active{background:#ff2d62;color:white;}
+/* Updated grid to show 2x2 layout */
+.grid{display:grid;grid-template-columns:repeat(2,1fr);gap:20px;padding:0 16px 60px;max-width:1200px;margin:0 auto;}
+@media(max-width:800px){.grid{grid-template-columns:1fr;}}
+/* Increased card height for larger display */
+.card{background:#fff;border-radius:12px;box-shadow:0 2px 8px rgba(0,0,0,.08);overflow:hidden;height:540px;display:flex;flex-direction:column;position:relative;}
+.frame{flex:1;position:relative;overflow:hidden;}
+.frame iframe{position:absolute;width:166.667%;height:166.667%;transform:scale(.6);transform-origin:top left;border:0;}
+.frame img{width:100%;height:100%;object-fit:cover;}
+.card-label{position:absolute;top:10px;left:10px;padding:4px 8px;border-radius:4px;font-size:11px;font-weight:bold;z-index:100;text-transform:uppercase;letter-spacing:0.5px;box-shadow:0 2px 4px rgba(0,0,0,0.2);}
+.label-live{background:linear-gradient(135deg, #00c6ff, #0072ff);color:white;}
+.label-static{background:linear-gradient(135deg, #ff9a9e, #fad0c4);color:#333;}
+.foot{height:44px;background:#fafafa;display:flex;align-items:center;justify-content:center;border-top:1px solid #eee;}
+.foot a{font-size:.82rem;font-weight:700;color:#4a6dd8;text-decoration:none;}
+.pagination{display:flex;justify-content:center;margin:20px 0;gap:10px;}
+.pagination button{padding:5px 15px;border:none;border-radius:20px;background:#e2e8f0;cursor:pointer;}
+.pagination button:disabled{opacity:0.5;cursor:not-allowed;}
+.manage-panel{background:white;border-radius:12px;box-shadow:0 2px 8px rgba(0,0,0,.08);margin:16px;padding:20px;}
+.form-group{margin-bottom:15px;}
+.form-group label{display:block;margin-bottom:5px;font-weight:600;}
+.form-control{width:100%;padding:8px;border:1px solid #ddd;border-radius:4px;box-sizing:border-box;}
+.btn{padding:8px 15px;border:none;border-radius:4px;cursor:pointer;font-weight:600;}
+.btn-primary{background:#4a6dd8;color:white;}
+.btn-danger{background:#e53e3e;color:white;}
+.btn-success{background:#38a169;color:white;}
+.status{padding:10px;margin:10px 0;border-radius:4px;display:none;}
+.status.success{display:block;background:#c6f6d5;color:#22543d;}
+.status.error{display:block;background:#fed7d7;color:#822727;}
+.url-list{margin:20px 0;border:1px solid #eee;border-radius:4px;max-height:300px;overflow-y:auto;}
+.url-item{padding:10px;border-bottom:1px solid #eee;display:flex;justify-content:space-between;align-items:center;}
+.url-item:last-child{border-bottom:none;}
+.url-controls{display:flex;gap:5px;}
+</style>
+</head>
+<body>
+<header style="text-align: center; padding: 20px; background: linear-gradient(135deg, #f6f8fb, #e2e8f0); border-bottom: 1px solid #ddd;">
+  <h1 style="margin-bottom: 10px;">🌟Open Free AI Playground</h1>
+  <p>
+    <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="badge"></a>
+  </p>
+</header>
+<div class="tabs" id="tabs"></div>
+<div id="content"></div>
+<script>
+// Basic configuration
+const cats = {{cats|tojson}};
+const tabs = document.getElementById('tabs');
+const content = document.getElementById('content');
+let active = "";
+let currentPage = 1;
+// Simple utility functions
+function loadHTML(url, callback) {
+  const xhr = new XMLHttpRequest();
+  xhr.open('GET', url, true);
+  xhr.onreadystatechange = function() {
+    if (xhr.readyState === 4 && xhr.status === 200) {
+      callback(xhr.responseText);
+    }
+  };
+  xhr.send();
 }
+function makeRequest(url, method, data, callback) {
+  const xhr = new XMLHttpRequest();
+  xhr.open(method, url, true);
+  xhr.onreadystatechange = function() {
+    if (xhr.readyState === 4 && xhr.status === 200) {
+      callback(JSON.parse(xhr.responseText));
+    }
+  };
+  if (method === 'POST') {
+    xhr.send(data);
+  } else {
+    xhr.send();
+  }
 }
+function updateTabs() {
+  Array.from(tabs.children).forEach(b => {
+    b.classList.toggle('active', b.dataset.c === active);
+  });
 }
+// Tab handlers
+function loadCategory(cat, page) {
+  if(cat === active && currentPage === page) return;
+  active = cat;
+  currentPage = page || 1;
+  updateTabs();
+  content.innerHTML = '<p style="text-align:center;padding:40px">Loading…</p>';
+  makeRequest('/api/category?name=' + encodeURIComponent(cat) + '&page=' + currentPage + '&per_page=4', 'GET', null, function(data) {
+    let html = '<div class="grid">';
+    if(data.items.length === 0) {
+      html += '<p style="grid-column:1/-1;text-align:center;padding:40px">No items in this category.</p>';
+    } else {
+      data.items.forEach(item => {
+        html += `
+          <div class="card">
+            <div class="card-label label-live">LIVE</div>
+            <div class="frame">
+              <iframe src="${item.iframe}" loading="lazy" sandbox="allow-forms allow-modals allow-popups allow-same-origin allow-scripts allow-downloads"></iframe>
+            </div>
+            <div class="foot">
+              <a href="${item.hf}" target="_blank">${item.title}</a>
+            </div>
+          </div>
+        `;
+      });
+    }
+    html += '</div>';
+    // Add pagination
+    html += `
+      <div class="pagination">
+        <button ${currentPage <= 1 ? 'disabled' : ''} onclick="loadCategory('${cat}', ${currentPage-1})">« Previous</button>
+        <span>Page ${currentPage} of ${data.total_pages}</span>
+        <button ${currentPage >= data.total_pages ? 'disabled' : ''} onclick="loadCategory('${cat}', ${currentPage+1})">Next »</button>
+      </div>
+    `;
+    content.innerHTML = html;
+  });
+}
+function loadFavorites(page) {
+  if(active === 'Favorites' && currentPage === page) return;
+  active = 'Favorites';
+  currentPage = page || 1;
+  updateTabs();
+  content.innerHTML = '<p style="text-align:center;padding:40px">Loading…</p>';
+  makeRequest('/api/favorites?page=' + currentPage + '&per_page=4', 'GET', null, function(data) {
+    let html = '<div class="grid">';
+    if(data.items.length === 0) {
+      html += '<p style="grid-column:1/-1;text-align:center;padding:40px">No favorites saved yet.</p>';
+    } else {
+      data.items.forEach(item => {
+        if(item.mode === 'snapshot') {
+          html += `
+            <div class="card">
+              <div class="card-label label-static">Static</div>
+              <div class="frame">
+                <img src="${item.preview_url}" loading="lazy">
+              </div>
+              <div class="foot">
+                <a href="${item.url}" target="_blank">${item.title}</a>
+              </div>
+            </div>
+          `;
+        } else {
+          html += `
+            <div class="card">
+              <div class="card-label label-live">LIVE</div>
+              <div class="frame">
+                <iframe src="${item.preview_url}" loading="lazy" sandbox="allow-forms allow-modals allow-popups allow-same-origin allow-scripts allow-downloads"></iframe>
+              </div>
+              <div class="foot">
+                <a href="${item.url}" target="_blank">${item.title}</a>
+              </div>
+            </div>
+          `;
+        }
+      });
+    }
+    html += '</div>';
+    // Add pagination
+    html += `
+      <div class="pagination">
+        <button ${currentPage <= 1 ? 'disabled' : ''} onclick="loadFavorites(${currentPage-1})">« Previous</button>
+        <span>Page ${currentPage} of ${data.total_pages}</span>
+        <button ${currentPage >= data.total_pages ? 'disabled' : ''} onclick="loadFavorites(${currentPage+1})">Next »</button>
+      </div>
+    `;
+    content.innerHTML = html;
+  });
+}
+function loadManage() {
+  if(active === 'Manage') return;
+  active = 'Manage';
+  updateTabs();
+  content.innerHTML = `
+    <div class="manage-panel">
+      <h2>Add New URL</h2>
+      <div class="form-group">
+        <label for="new-url">URL</label>
+        <input type="text" id="new-url" class="form-control" placeholder="https://example.com">
+      </div>
+      <button onclick="addUrl()" class="btn btn-primary">Add URL</button>
+      <div id="add-status" class="status"></div>
+      <h2>Manage Saved URLs</h2>
+      <div id="url-list" class="url-list">Loading...</div>
+    </div>
+  `;
+  loadUrlList();
+}
+// URL management functions
+function loadUrlList() {
+  makeRequest('/api/favorites?per_page=100', 'GET', null, function(data) {
+    const urlList = document.getElementById('url-list');
+    if(data.items.length === 0) {
+      urlList.innerHTML = '<p style="text-align:center;padding:20px">No URLs saved yet.</p>';
+      return;
+    }
+    let html = '';
+    data.items.forEach(item => {
+      // Escape the URL to prevent JavaScript injection when used in onclick handlers
+      const escapedUrl = item.url.replace(/'/g, "\\'");
+      html += `
+        <div class="url-item">
+          <div>${item.url}</div>
+          <div class="url-controls">
+            <button class="btn" onclick="editUrl('${escapedUrl}')">Edit</button>
+            <button class="btn btn-danger" onclick="deleteUrl('${escapedUrl}')">Delete</button>
+          </div>
+        </div>
+      `;
+    });
+    urlList.innerHTML = html;
+  });
+}
+function addUrl() {
+  const url = document.getElementById('new-url').value.trim();
+  if(!url) {
+    showStatus('add-status', 'Please enter a URL', false);
+    return;
+  }
+  const formData = new FormData();
+  formData.append('url', url);
+  makeRequest('/api/url/add', 'POST', formData, function(data) {
+    showStatus('add-status', data.message, data.success);
+    if(data.success) {
+      document.getElementById('new-url').value = '';
+      loadUrlList();
+      // If currently in Favorites tab, reload to see changes immediately
+      if(active === 'Favorites') {
+        loadFavorites(currentPage);
+      }
+    }
+  });
+}
+function editUrl(url) {
+  // Decode URL if it was previously escaped
+  const decodedUrl = url.replace(/\\'/g, "'");
+  const newUrl = prompt('Edit URL:', decodedUrl);
+  if(!newUrl || newUrl === decodedUrl) return;
+  const formData = new FormData();
+  formData.append('old', decodedUrl);
+  formData.append('new', newUrl);
+  makeRequest('/api/url/update', 'POST', formData, function(data) {
+    if(data.success) {
+      loadUrlList();
+      // If currently in Favorites tab, reload to see changes immediately
+      if(active === 'Favorites') {
+        loadFavorites(currentPage);
+      }
+    } else {
+      alert(data.message);
+    }
+  });
+}
+function deleteUrl(url) {
+  // Decode URL if it was previously escaped
+  const decodedUrl = url.replace(/\\'/g, "'");
+  if(!confirm('Are you sure you want to delete this URL?')) return;
+  const formData = new FormData();
+  formData.append('url', decodedUrl);
+  makeRequest('/api/url/delete', 'POST', formData, function(data) {
+    if(data.success) {
+      loadUrlList();
+      // If currently in Favorites tab, reload to see changes immediately
+      if(active === 'Favorites') {
+        loadFavorites(currentPage);
+      }
+    } else {
+      alert(data.message);
+    }
+  });
+}
+function showStatus(id, message, success) {
+  const status = document.getElementById(id);
+  status.textContent = message;
+  status.className = success ? 'status success' : 'status error';
+  setTimeout(() => {
+    status.className = 'status';
+  }, 3000);
+}
+// Create tabs
+// Favorites tab first
+const favTab = document.createElement('button');
+favTab.className = 'tab';
+favTab.textContent = 'Favorites';
+favTab.dataset.c = 'Favorites';
+favTab.onclick = function() { loadFavorites(1); };
+tabs.appendChild(favTab);
+// Category tabs
+cats.forEach(c => {
+  const b = document.createElement('button');
+  b.className = 'tab';
+  b.textContent = c;
+  b.dataset.c = c;
+  b.onclick = function() { loadCategory(c, 1); };
+  tabs.appendChild(b);
+});
+// Manage tab last
+const manageTab = document.createElement('button');
+manageTab.className = 'tab manage';
+manageTab.textContent = 'Manage';
+manageTab.dataset.c = 'Manage';
+manageTab.onclick = function() { loadManage(); };
+tabs.appendChild(manageTab);
+// Start with Favorites tab
+loadFavorites(1);
+</script>
+</body>
+</html>''')
+    # Return the rendered template
+    return render_template('index.html', cats=list(CATEGORIES.keys()))
+# Initialize database on startup
+init_db()
+# Define a function to ensure database consistency
+def ensure_db_consistency():
+    # Make sure we have the latest data in both JSON and SQLite
+    urls = load_db_sqlite()
+    save_json(urls)
+# For Flask 2.0+ compatibility
+@app.before_request
+def before_request_func():
+    # Use a flag to run this only once
+    if not hasattr(app, '_got_first_request'):
+        ensure_db_consistency()
+        app._got_first_request = True
+if __name__ == '__main__':
+    # 앱 시작 전에 명시적으로 DB 초기화
+    print("Initializing database...")
+    init_db()
+    # 데이터베이스 파일 경로 및 존재 여부 확인
+    db_path = os.path.abspath(SQLITE_DB)
+    print(f"SQLite DB path: {db_path}")
+    if os.path.exists(SQLITE_DB):
+        print(f"Database file exists, size: {os.path.getsize(SQLITE_DB)} bytes")
+    else:
+        print("Warning: Database file does not exist after initialization!")
+    app.run(host='0.0.0.0', port=7860)