Delete app-backup1.py

app-backup1.py

@@ -1,1639 +0,0 @@
-import os
-import random
-import base64
-import requests
-import tempfile
-import shutil
-import time
-import numpy as np
-import traceback
-from typing import List, Tuple
-from datetime import datetime, timedelta
-from pathlib import Path
-from io import BytesIO
-from urllib.parse import urljoin
-
-# Selenium 관련
-from selenium import webdriver
-from selenium.webdriver.support.ui import WebDriverWait
-from selenium.webdriver.support import expected_conditions as EC
-from selenium.webdriver.common.by import By
-from selenium.common.exceptions import WebDriverException, TimeoutException
-
-# 이미지 처리
-from PIL import Image, ImageDraw, ImageFont
-
-# Gradio
-import gradio as gr
-
-# HuggingFace
-from huggingface_hub import InferenceClient
-from dotenv import load_dotenv
-
-# HTML 파싱
-from bs4 import BeautifulSoup
-
-# 음성 및 비디오 처리
-from gtts import gTTS
-from moviepy.editor import (
-    VideoFileClip,
-    AudioFileClip,
-    ImageClip,
-    concatenate_videoclips
-)
-
-# .env 파일에서 환경 변수 로드
-load_dotenv()
-
-# HuggingFace 인퍼런스 클라이언트 설정
-hf_client = InferenceClient(
-    "CohereForAI/c4ai-command-r-plus-08-2024",
-    token=os.getenv("HF_TOKEN")
-)
-# 스크린샷 캐시 디렉토리 설정
-CACHE_DIR = Path("screenshot_cache")
-CACHE_DIR.mkdir(exist_ok=True)
-
-# 전역 변수로 스크린샷 캐시 선언
-SCREENSHOT_CACHE = {}
-
-def get_cached_screenshot(url: str) -> str:
-    """캐시된 스크린샷 가져오기 또는 새로 생성"""
-    try:
-        # URL을 안전한 파일명으로 변환
-        safe_filename = base64.urlsafe_b64encode(url.encode()).decode()
-        cache_file = CACHE_DIR / f"{safe_filename[:200]}.jpg"  # PNG 대신 JPG 사용
-        
-        if cache_file.exists():
-            try:
-                with Image.open(cache_file) as img:
-                    buffered = BytesIO()
-                    img.save(buffered, format="JPEG", quality=85, optimize=True)
-                    return base64.b64encode(buffered.getvalue()).decode()
-            except Exception as e:
-                print(f"Cache read error for {url}: {e}")
-                if cache_file.exists():
-                    cache_file.unlink()
-        
-        return take_screenshot(url)
-        
-    except Exception as e:
-        print(f"Screenshot cache error for {url}: {e}")
-        return ""
-
-def take_screenshot(url: str) -> str:
-    """웹사이트 스크린샷 촬영"""
-    if not url.startswith('http'):
-        url = f"https://{url}"
-    
-    options = webdriver.ChromeOptions()
-    options.add_argument('--headless')
-    options.add_argument('--no-sandbox')
-    options.add_argument('--disable-dev-shm-usage')
-    options.add_argument('--window-size=1080,720')
-    
-    driver = None
-    try:
-        driver = webdriver.Chrome(options=options)
-        driver.get(url)
-        
-        # 페이지 로딩 대기
-        WebDriverWait(driver, 15).until(
-            EC.presence_of_element_located((By.TAG_NAME, "body"))
-        )
-        
-        # 추가 대기 시간
-        time.sleep(3)
-        
-        # 스크린샷 촬영 및 최적화
-        screenshot = driver.get_screenshot_as_png()
-        img = Image.open(BytesIO(screenshot))
-        
-        # 이미지 크기 최적화
-        max_size = (800, 600)
-        img.thumbnail(max_size, Image.Resampling.LANCZOS)
-        
-        # JPEG로 변환 및 최적화
-        if img.mode in ('RGBA', 'LA'):
-            background = Image.new('RGB', img.size, (255, 255, 255))
-            background.paste(img, mask=img.split()[-1])
-            img = background
-        
-        # 캐시 저장
-        safe_filename = base64.urlsafe_b64encode(url.encode()).decode()
-        cache_file = CACHE_DIR / f"{safe_filename[:200]}.jpg"
-        img.save(cache_file, format="JPEG", quality=85, optimize=True)
-        
-        # 반환용 이미지 생성
-        buffered = BytesIO()
-        img.save(buffered, format="JPEG", quality=85, optimize=True)
-        return base64.b64encode(buffered.getvalue()).decode()
-        
-    except Exception as e:
-        print(f"Screenshot error for {url}: {e}")
-        return ""
-        
-    finally:
-        if driver:
-            driver.quit()
-
-def cleanup_cache():
-    """캐시 정리"""
-    try:
-        current_time = time.time()
-        for cache_file in CACHE_DIR.glob("*.jpg"):
-            try:
-                # 24시간 이상 된 파일 또는 0바이트 파일 삭제
-                if (current_time - cache_file.stat().st_mtime > 86400) or cache_file.stat().st_size == 0:
-                    cache_file.unlink()
-            except Exception as e:
-                print(f"Error cleaning cache file {cache_file}: {e}")
-                
-    except Exception as e:
-        print(f"Cache cleanup error: {e}")
-
-# 앱 시작 시 캐시 정리
-cleanup_cache()
-
-def calculate_rising_rate(created_date: str, rank: int) -> int:
-    """AI Rising Rate 계산"""
-    # 생성일 기준 점수 계산
-    created = datetime.strptime(created_date.split('T')[0], '%Y-%m-%d')
-    today = datetime.now()
-    days_diff = (today - created).days
-    date_score = max(0, 300 - days_diff)  # 최대 300점
-    
-    # 순위 기준 점수 계산
-    rank_score = max(0, 600 - rank)  # 최대 300점
-    
-    # 총점 계산
-    total_score = date_score + rank_score
-    
-    # 별 개수 계산 (0~5)
-    if total_score <= 200:
-        stars = 1
-    elif total_score <= 400:
-        stars = 2
-    elif total_score <= 600:
-        stars = 3
-    elif total_score <= 800:
-        stars = 4
-    else:
-        stars = 5
-        
-    return stars
-
-def get_popularity_grade(likes: int, stars: int) -> tuple:
-    """AI Popularity Score 등급 계산"""
-    # 기본 점수 (likes)
-    base_score = min(likes, 10000)  # 최대 10000점
-    
-    # 별점 추가 점수 (별 하나당 500점)
-    star_score = stars * 1000
-    
-    # 총점
-    total_score = base_score + star_score
-    
-    # 등급 테이블 (18단계)
-    grades = [
-        (14500, "AAA+"), (14000, "AAA"), (13500, "AAA-"),
-        (13000, "AA+"), (12500, "AA"), (12000, "AA-"),
-        (11500, "A+"), (11000, "A"), (10000, "A-"),
-        (9000, "BBB+"), (8000, "BBB"), (7000, "BBB-"),
-        (6000, "BB+"), (5000, "BB"), (4000, "BB-"),
-        (3000, "B+"), (2000, "B"), (1000, "B-")
-    ]
-    
-    for threshold, grade in grades:
-        if total_score >= threshold:
-            return grade, total_score
-            
-    return "B-", total_score
-
-# get_card 함수 내의 hardware_info 부분을 다음으로 교체:
-def get_rating_info(item: dict, index: int) -> str:
-    """평가 정보 HTML 생성"""
-    created = item.get('createdAt', '').split('T')[0]
-    likes = int(str(item.get('likes', '0')).replace(',', ''))
-    
-    # AI Rising Rate 계산
-    stars = calculate_rising_rate(created, index + 1)
-    star_html = "★" * stars + "☆" * (5 - stars)  # 채워진 별과 빈 별 조합
-    
-    # AI Popularity Score 계산
-    grade, score = get_popularity_grade(likes, stars)
-    
-    # 등급별 색상 설정
-    grade_colors = {
-        'AAA': '#FFD700', 'AA': '#FFA500', 'A': '#FF4500',
-        'BBB': '#4169E1', 'BB': '#1E90FF', 'B': '#00BFFF'
-    }
-    grade_base = grade.rstrip('+-')
-    grade_color = grade_colors.get(grade_base, '#666666')
-    
-    return f"""
-    <div style='
-        margin-top: 15px;
-        padding: 15px;
-        background: rgba(255,255,255,0.4);
-        border-radius: 10px;
-        font-size: 0.9em;
-        box-shadow: 0 2px 10px rgba(0,0,0,0.1);'>
-        <div style='
-            display: grid;
-            grid-template-columns: repeat(2, 1fr);
-            gap: 15px;'>
-            <div style='
-                color: #333;
-                display: flex;
-                flex-direction: column;
-                gap: 5px;'>
-                <span style='font-weight: bold;'>AI Rising Rate:</span>
-                <span style='
-                    color: #FF8C00;
-                    font-size: 1.4em;
-                    letter-spacing: 2px;
-                    text-shadow: 1px 1px 2px rgba(0,0,0,0.1);'>{star_html}</span>
-            </div>
-            <div style='
-                color: #333;
-                display: flex;
-                flex-direction: column;
-                gap: 5px;'>
-                <span style='font-weight: bold;'>AI Popularity Score:</span>
-                <span style='
-                    font-size: 1.2em;
-                    font-weight: bold;
-                    color: {grade_color};
-                    text-shadow: 1px 1px 2px rgba(0,0,0,0.1);'>{grade} ({score:,})</span>
-            </div>
-        </div>
-    </div>
-    """
-
-def get_hardware_info(item: dict) -> tuple:
-    """하드웨어 정보 추출"""
-    try:
-        # runtime 정보 확인
-        runtime = item.get('runtime', {})
-        
-        # CPU 정보 처리
-        cpu_info = runtime.get('cpu', 'Standard')
-        
-        # GPU 정보 처리
-        gpu_info = "None"
-        if runtime.get('accelerator') == "gpu":
-            gpu_type = runtime.get('gpu', {}).get('name', '')
-            gpu_memory = runtime.get('gpu', {}).get('memory', '')
-            if gpu_type:
-                gpu_info = f"{gpu_type}"
-                if gpu_memory:
-                    gpu_info += f" ({gpu_memory}GB)"
-        
-        # spaces decorator 확인
-        if '@spaces.GPU' in str(item.get('sdk_version', '')):
-            if gpu_info == "None":
-                gpu_info = "GPU Enabled"
-        
-        # SDK 정보 처리
-        sdk = item.get('sdk', 'N/A')
-        
-        print(f"Debug - Runtime Info: {runtime}")  # 디버그 출력
-        print(f"Debug - GPU Info: {gpu_info}")    # 디버그 출력
-        
-        return cpu_info, gpu_info, sdk
-        
-    except Exception as e:
-        print(f"Error parsing hardware info: {str(e)}")
-        return 'Standard', 'None', 'N/A'
-
-def get_card(item: dict, index: int, card_type: str = "space") -> str:
-    """통합 카��� HTML 생성"""
-    item_id = item.get('id', '')
-    author, title = item_id.split('/', 1)
-    likes = format(item.get('likes', 0), ',')
-    created = item.get('createdAt', '').split('T')[0]
-    
-    # short_description 가져오기
-    short_description = item.get('cardData', {}).get('short_description', '')
-    
-    # URL 정의
-    if card_type == "space":
-        url = f"https://huggingface.co/spaces/{item_id}"
-    elif card_type == "model":
-        url = f"https://huggingface.co/{item_id}"
-    else:  # dataset
-        url = f"https://huggingface.co/datasets/{item_id}"
-    
-    # 메타데이터 처리
-    tags = item.get('tags', [])
-    pipeline_tag = item.get('pipeline_tag', '')
-    license = item.get('license', '')
-    sdk = item.get('sdk', 'N/A')
-
-    # AI Rating 정보 가져오기
-    rating_info = get_rating_info(item, index)
-
-    # 카드 타입별 그라데이션 설정
-    if card_type == "space":
-        gradient_colors = """
-            rgba(255, 182, 193, 0.7),    /* 파스텔 핑크 */
-            rgba(173, 216, 230, 0.7),    /* 파스텔 블루 */
-            rgba(255, 218, 185, 0.7)     /* 파스텔 피치 */
-        """
-        bg_content = f"""
-            background-image: url(data:image/png;base64,{get_cached_screenshot(url) if get_cached_screenshot(url) else ''});
-            background-size: cover;
-            background-position: center;
-        """
-        type_icon = "🎯"
-        type_label = "SPACE"
-    elif card_type == "model":
-        gradient_colors = """
-            rgba(110, 142, 251, 0.7),    /* 모델 블루 */
-            rgba(130, 158, 251, 0.7),
-            rgba(150, 174, 251, 0.7)
-        """
-        bg_content = f"""
-            background: linear-gradient(135deg, #6e8efb, #4a6cf7);
-            padding: 15px;
-        """
-        type_icon = "🤖"
-        type_label = "MODEL"
-    else:  # dataset
-        gradient_colors = """
-            rgba(255, 107, 107, 0.7),    /* 데이터셋 레드 */
-            rgba(255, 127, 127, 0.7),
-            rgba(255, 147, 147, 0.7)
-        """
-        bg_content = f"""
-            background: linear-gradient(135deg, #ff6b6b, #ff8787);
-            padding: 15px;
-        """
-        type_icon = "📊"
-        type_label = "DATASET"
-
-    content_bg = f"""
-        background: linear-gradient(135deg, {gradient_colors});
-        backdrop-filter: blur(10px);
-    """
-
-    # 태그 표시 (models와 datasets용)
-    tags_html = ""
-    if card_type != "space":
-        tags_html = f"""
-        <div style='
-            position: absolute;
-            top: 50%;
-            left: 50%;
-            transform: translate(-50%, -50%);
-            display: flex;
-            flex-wrap: wrap;
-            gap: 5px;
-            justify-content: center;
-            width: 90%;'>
-            {' '.join([f'''
-                <span style='
-                    background: rgba(255,255,255,0.2);
-                    padding: 5px 10px;
-                    border-radius: 15px;
-                    color: white;
-                    font-size: 0.8em;'>
-                    #{tag}
-                </span>
-            ''' for tag in tags[:5]])}
-        </div>
-        """
-
-    # 카드 HTML 반환
-    return f"""
-    <div class="card" style='
-        position: relative;
-        border: none; 
-        padding: 0;
-        margin: 10px;
-        border-radius: 20px;
-        box-shadow: 0 10px 20px rgba(0,0,0,0.1);
-        background: white;
-        transition: all 0.3s ease;
-        overflow: hidden;
-        min-height: 400px;
-        cursor: pointer;
-        transform-origin: center;'
-        onmouseover="this.style.transform='scale(0.98) translateY(5px)'; this.style.boxShadow='0 5px 15px rgba(0,0,0,0.2)';"
-        onmouseout="this.style.transform='scale(1) translateY(0)'; this.style.boxShadow='0 10px 20px rgba(0,0,0,0.1)';"
-        onclick="window.open('{url}', '_blank')">
-        
-        <!-- 상단 영역 -->
-        <div style='
-            width: 100%;
-            height: 200px;
-            {bg_content}
-            position: relative;'>
-            
-            <!-- 순위 뱃지 -->
-            <div style='
-                position: absolute;
-                top: 10px;
-                left: 10px;
-                background: rgba(0,0,0,0.7);
-                color: white;
-                padding: 5px 15px;
-                border-radius: 20px;
-                font-weight: bold;
-                font-size: 0.9em;
-                backdrop-filter: blur(5px);'>
-                #{index + 1}
-            </div>
-            
-            <!-- 타입 뱃지 -->
-            <div style='
-                position: absolute;
-                top: 10px;
-                right: 10px;
-                background: rgba(255,255,255,0.9);
-                padding: 5px 15px;
-                border-radius: 20px;
-                font-weight: bold;
-                font-size: 0.8em;'>
-                {type_icon} {type_label}
-            </div>
-
-            {tags_html}
-        </div>
-        
-        <!-- 콘텐츠 영역 -->
-        <div style='
-            padding: 20px;
-            {content_bg}
-            border-radius: 0 0 20px 20px;
-            border-top: 1px solid rgba(255,255,255,0.5);'>
-            <h3 style='
-                margin: 0 0 15px 0;
-                color: #333;
-                font-size: 1.3em;
-                line-height: 1.4;
-                display: -webkit-box;
-                -webkit-line-clamp: 2;
-                -webkit-box-orient: vertical;
-                overflow: hidden;
-                text-overflow: ellipsis;
-                text-shadow: 1px 1px 1px rgba(255,255,255,0.8);'>
-                {title}
-            </h3>
-            
-            {f'''
-            <!-- Short Description (Space 카드에만 표시) -->
-            <div style='
-                margin: 0 0 15px 0;
-                color: #444;
-                font-size: 0.9em;
-                line-height: 1.5;
-                display: -webkit-box;
-                -webkit-line-clamp: 3;
-                -webkit-box-orient: vertical;
-                overflow: hidden;
-                text-overflow: ellipsis;
-                background: rgba(255,255,255,0.4);
-                padding: 10px;
-                border-radius: 8px;'>
-                {short_description}
-            </div>
-            ''' if card_type == "space" and short_description else ''}
-            
-            <div style='
-                display: grid;
-                grid-template-columns: repeat(2, 1fr);
-                gap: 10px;
-                font-size: 0.9em;
-                background: rgba(255,255,255,0.3);
-                padding: 10px;
-                border-radius: 10px;'>
-                <div style='color: #444;'>
-                    <span style='margin-right: 5px;'>👤</span> {author}
-                </div>
-                <div style='color: #444;'>
-                    <span style='margin-right: 5px;'>❤️</span> {likes}
-                </div>
-                <div style='color: #444; grid-column: span 2;'>
-                    <span style='margin-right: 5px;'>📅</span> {created}
-                </div>
-            </div>
-
-            {rating_info}
-        </div>
-    </div>
-    """
-
-def get_trending_spaces(search_query="", sort_by="rank", progress=gr.Progress()) -> Tuple[str, str]:
-    """트렌딩 스페이스 가져오기"""
-    url = "https://huggingface.co/api/spaces"
-    
-    try:
-        progress(0, desc="Fetching spaces data...")
-        params = {
-            'full': 'true',
-            'limit': 24
-        }
-
-        response = requests.get(url, params=params)
-        response.raise_for_status()
-        spaces = response.json()
-        
-        # 검색어로 필터링
-        if search_query:
-            spaces = [space for space in spaces if search_query.lower() in 
-                     (space.get('id', '') + ' ' + space.get('title', '')).lower()]
-        
-        # 정렬
-        sort_by = sort_by.lower()
-        if sort_by == "rising_rate":
-            spaces.sort(key=lambda x: calculate_rising_rate(x.get('createdAt', ''), 0), reverse=True)
-        elif sort_by == "popularity":
-            spaces.sort(key=lambda x: get_popularity_grade(
-                int(str(x.get('likes', '0')).replace(',', '')),
-                calculate_rising_rate(x.get('createdAt', ''), 0))[1],
-                reverse=True)
-        
-        progress(0.1, desc="Creating gallery...")
-        html_content = """
-        <div style='padding: 20px; background: #f5f5f5;'>
-            <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
-        """
-        
-        for idx, space in enumerate(spaces):
-            html_content += get_card(space, idx, "space")
-            progress((0.1 + 0.9 * idx/len(spaces)), desc=f"Loading space {idx+1}/{len(spaces)}...")
-            
-        html_content += "</div></div>"
-        
-        progress(1.0, desc="Complete!")
-        return html_content, f"Found {len(spaces)} spaces"
-        
-    except Exception as e:
-        error_html = f'<div style="color: red; padding: 20px;">Error: {str(e)}</div>'
-        return error_html, f"Error: {str(e)}"
-
-def get_models(search_query="", sort_by="rank", progress=gr.Progress()) -> Tuple[str, str]:
-    """인기 모델 가져오기"""
-    url = "https://huggingface.co/api/models"
-    
-    try:
-        progress(0, desc="Fetching models data...")
-        params = {
-            'full': 'true',
-            'limit': 300
-        }
-        response = requests.get(url, params=params)
-        response.raise_for_status()
-        models = response.json()
-        
-        # 검색어로 필터링
-        if search_query:
-            models = [model for model in models if search_query.lower() in 
-                     (model.get('id', '') + ' ' + model.get('title', '')).lower()]
-        
-        # 정렬
-        sort_by = sort_by.lower()
-        if sort_by == "rising_rate":
-            models.sort(key=lambda x: calculate_rising_rate(x.get('createdAt', ''), 0), reverse=True)
-        elif sort_by == "popularity":
-            models.sort(key=lambda x: get_popularity_grade(
-                int(str(x.get('likes', '0')).replace(',', '')),
-                calculate_rising_rate(x.get('createdAt', ''), 0))[1],
-                reverse=True)
-        
-        progress(0.1, desc="Creating gallery...")
-        html_content = """
-        <div style='padding: 20px; background: #f5f5f5;'>
-            <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
-        """
-        
-        for idx, model in enumerate(models):
-            html_content += get_card(model, idx, "model")
-            progress((0.1 + 0.9 * idx/len(models)), desc=f"Loading model {idx+1}/{len(models)}...")
-            
-        html_content += "</div></div>"
-        
-        progress(1.0, desc="Complete!")
-        return html_content, f"Found {len(models)} models"
-        
-    except Exception as e:
-        error_html = f'<div style="color: red; padding: 20px;">Error: {str(e)}</div>'
-        return error_html, f"Error: {str(e)}"
-
-def get_datasets(search_query="", sort_by="rank", progress=gr.Progress()) -> Tuple[str, str]:
-    """인기 데이터셋 가져오기"""
-    url = "https://huggingface.co/api/datasets"
-    
-    try:
-        progress(0, desc="Fetching datasets data...")
-        params = {
-            'full': 'true',
-            'limit': 300
-        }
-        response = requests.get(url, params=params)
-        response.raise_for_status()
-        datasets = response.json()
-        
-        # 검색어로 필터링
-        if search_query:
-            datasets = [dataset for dataset in datasets if search_query.lower() in 
-                       (dataset.get('id', '') + ' ' + dataset.get('title', '')).lower()]
-        
-        # 정렬
-        sort_by = sort_by.lower()
-        if sort_by == "rising_rate":
-            datasets.sort(key=lambda x: calculate_rising_rate(x.get('createdAt', ''), 0), reverse=True)
-        elif sort_by == "popularity":
-            datasets.sort(key=lambda x: get_popularity_grade(
-                int(str(x.get('likes', '0')).replace(',', '')),
-                calculate_rising_rate(x.get('createdAt', ''), 0))[1],
-                reverse=True)
-        
-        progress(0.1, desc="Creating gallery...")
-        html_content = """
-        <div style='padding: 20px; background: #f5f5f5;'>
-            <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
-        """
-        
-        for idx, dataset in enumerate(datasets):
-            html_content += get_card(dataset, idx, "dataset")
-            progress((0.1 + 0.9 * idx/len(datasets)), desc=f"Loading dataset {idx+1}/{len(datasets)}...")
-            
-        html_content += "</div></div>"
-        
-        progress(1.0, desc="Complete!")
-        return html_content, f"Found {len(datasets)} datasets"
-        
-    except Exception as e:
-        error_html = f'<div style="color: red; padding: 20px;">Error: {str(e)}</div>'
-        return error_html, f"Error: {str(e)}"
-
-# 정렬 함수 추가
-def sort_items(items, sort_by):
-    if sort_by == "rank":
-        return items  # 이미 순위대로 정렬되어 있음
-    elif sort_by == "rising_rate":
-        return sorted(items, key=lambda x: calculate_rising_rate(x.get('createdAt', ''), 0), reverse=True)
-    elif sort_by == "popularity":
-        return sorted(items, key=lambda x: get_popularity_grade(int(str(x.get('likes', '0')).replace(',', '')), 
-                     calculate_rising_rate(x.get('createdAt', ''), 0))[1], reverse=True)
-    return items
-
-# API 호출 함수 수정
-def fetch_items(item_type, search_query="", sort_by="rank", limit=1000):
-    """아이템 가져오기 (spaces/models/datasets)"""
-    base_url = f"https://huggingface.co/api/{item_type}"
-    params = {
-        'full': 'true',
-        'limit': limit,
-        'search': search_query
-    }
-    
-    try:
-        response = requests.get(base_url, params=params)
-        response.raise_for_status()
-        items = response.json()
-        
-        # 검색어로 필터링
-        if search_query:
-            items = [item for item in items if search_query.lower() in 
-                    (item.get('id', '') + item.get('title', '')).lower()]
-        
-        # 정렬
-        items = sort_items(items, sort_by)
-        
-        return items[:300]  # 상위 300개만 반환
-    except Exception as e:
-        print(f"Error fetching items: {e}")
-        return []
-
-
-
-def get_space_source(space_id: str) -> dict:
-    """스페이스의 소스코드 가져오기"""
-    try:
-        # HuggingFace API를 통해 소스코드 가져오기
-        headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}
-        
-        # app.py 시도
-        app_url = f"https://huggingface.co/spaces/{space_id}/raw/main/app.py"
-        app_response = requests.get(app_url, headers=headers)
-        
-        # index.html 시도
-        index_url = f"https://huggingface.co/spaces/{space_id}/raw/main/index.html"
-        index_response = requests.get(index_url, headers=headers)
-        
-        source = {
-            "app.py": app_response.text if app_response.status_code == 200 else "",
-            "index.html": index_response.text if index_response.status_code == 200 else ""
-        }
-        
-        return source
-    except Exception as e:
-        print(f"Error fetching source for {space_id}: {str(e)}")
-        return {"app.py": "", "index.html": ""}
-
-def analyze_space(space_info: dict) -> str:
-    """스페이스 분석"""
-    try:
-        space_id = space_info.get('id', '')
-        url = f"https://huggingface.co/spaces/{space_id}"
-        
-        # 소스코드 가져오기
-        source = get_space_source(space_id)
-        source_code = source["app.py"] or source["index.html"]
-        
-        if not source_code:
-            return f"""
-            <div style='
-                padding: 20px;
-                color: #333 !important;
-                background: white !important;
-            '>
-                <h3 style='color: #333 !important; margin-bottom: 10px;'>
-                    #{space_info.get('rank', '0')} {space_id}
-                </h3>
-                <p style='color: red;'>소스코드를 가져올 수 없습니다.</p>
-            </div>
-            """
-        
-        # LLM 분석 프롬프트
-        prompt = f"""
-        다음은 HuggingFace 스페이스({url})의 코드 또는 주석입니다:
-        
-        ```
-        {source_code[:4000]}
-        ```
-        
-        이 내용을 기반으로 다음 항목을 분석해주세요:
-        1. 개요: (한 줄로)
-        2. 요약: (한 줄로)
-        3. 특징 및 장점: (한 줄로)
-        4. 사용 대상: (한 줄로)
-        5. 사용 방법: (한 줄로)
-        6. 유사 서비스와의 차별점: (한 줄로)
-        
-        각 항목은 실제 확인된 내용만 포함하여 한 줄로 작성하세요.
-        코드가 보안처리된 경우 주석을 기반으로 분석하세요.
-        """
-        
-        # LLM 분석 실행
-        messages = [
-            {"role": "system", "content": "소스코드 분석 전문가로서 실제 코드 내용만 기반으로 분석하세요."},
-            {"role": "user", "content": prompt}
-        ]
-        
-        response = hf_client.chat_completion(
-            messages,
-            max_tokens=3900,
-            temperature=0.3
-        )
-        
-        analysis = response.choices[0].message.content
-        
-        return f"""
-        <div style='
-            padding: 20px;
-            color: #333 !important;
-            background: white !important;
-        '>
-            <h3 style='color: #333 !important; margin-bottom: 15px;'>
-                #{space_info.get('rank', '0')} {space_id}
-            </h3>
-            <div style='color: #444 !important; font-size: 0.95em;'>
-                {analysis}
-            </div>
-            <div style='margin-top: 15px;'>
-                <details>
-                    <summary style='cursor: pointer; color: #666 !important;'>
-                        소스코드 미리보기
-                    </summary>
-                    <pre style='
-                        background: #f5f5f5 !important;
-                        padding: 10px;
-                        border-radius: 5px;
-                        font-size: 0.8em;
-                        margin-top: 10px;
-                        white-space: pre-wrap;
-                        word-break: break-all;
-                        color: #333 !important;
-                    '>{source_code[:500]}...</pre>
-                </details>
-            </div>
-        </div>
-        """
-        
-    except Exception as e:
-        return f"<div style='color: red !important; padding: 20px;'>분석 오류: {str(e)}</div>"
-
-
-def analyze_top_spaces(progress=gr.Progress()) -> Tuple[str, str]:
-    """상위 24개 스페이스 분석"""
-    try:
-        progress(0, desc="스페이스 데이터 가져오는 중...")
-        
-        url = "https://huggingface.co/api/spaces"
-        response = requests.get(url, params={'full': 'true', 'limit': 24})
-        response.raise_for_status()
-        spaces = response.json()[:24]
-
-        # 상단 입력 박스와 기본 텍스트를 포함한 HTML 시작
-        html_content = """
-        <div style='padding: 20px; background: #ffffff;'>
-            <div style='margin-bottom: 30px;'>
-                <textarea id='intro_text' rows='4' style='
-                    width: 100%;
-                    padding: 15px;
-                    border: 1px solid #ddd;
-                    border-radius: 10px;
-                    font-size: 1.1em;
-                    line-height: 1.5;
-                    resize: vertical;
-                    background: #f8f9fa;
-                '>안녕하세요. 매일 글로벌 최신 AI 인기 트렌드 서비스를 알아보는 '데일리 AI 트렌딩' 뉴스입니다. 오늘의 허깅페이스 인기 순위 1위부터 24위까지, 분석과 핵심 내용을 살펴보겠습니다.</textarea>
-            </div>
-            <style>
-                .script-card {
-                    background: white !important;
-                    border-radius: 10px;
-                    padding: 20px;
-                    margin-bottom: 20px;
-                    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-                    border: 1px solid #e0e0e0;
-                }
-                .script-content {
-                    color: #444 !important;
-                    font-size: 1.1em;
-                    line-height: 1.6;
-                    white-space: pre-line;
-                }
-            </style>
-        """
-        
-        for idx, space in enumerate(spaces):
-            progress((idx + 1) / 24, desc=f"분석 중... {idx+1}/24")
-            
-            try:
-                source = get_space_source(space['id'])
-                source_code = source["app.py"] or source["index.html"]
-                
-                # 스페이스 ID에서 사용자명 제거하고 프로젝트명만 추출
-                project_name = space['id'].split('/')[-1]
-                
-                prompt = f"""
-                다음 HuggingFace 스페이스를 유튜브 뉴스 리포트 형식으로 설명해주세요.
-                시작은 반드시 "오늘의 인기순위 {idx + 1}위인 {project_name}입니다."로 시작하고,
-                이어서 주요 기능, 특징, 활용방안을 2-3문장으로 자연스럽게 설명해주세요.
-                전체 길이는 3-4문장으로 제한하고, 설명은 뉴스 리포터처럼 명확하고 전문적으로 해주세요.
-
-                소스코드:
-                ```
-                {source_code[:1500]}
-                ```
-                """
-                
-                messages = [
-                    {"role": "system", "content": "AI 기술 전문 뉴스 리포터입니다."},
-                    {"role": "user", "content": prompt}
-                ]
-                
-                response = hf_client.chat_completion(
-                    messages,
-                    max_tokens=2000,
-                    temperature=0.7
-                )
-                
-                script = response.choices[0].message.content.strip()
-                
-                html_content += f"""
-                    <div class='script-card'>
-                        <div class='script-content'>{script}</div>
-                    </div>
-                """
-                
-            except Exception as e:
-                print(f"Error analyzing space {space['id']}: {e}")
-                html_content += f"""
-                    <div class='script-card'>
-                        <div class='script-content' style='color: red !important;'>
-                            순위 {idx + 1}위 분석 중 오류가 발생했습니다.
-                        </div>
-                    </div>
-                """
-        
-        html_content += "</div>"
-        return html_content, f"24개 스페이스 분석 완료"
-        
-    except Exception as e:
-        error_msg = f"Error: {str(e)}"
-        return f"<div style='color: red; padding: 20px;'>{error_msg}</div>", error_msg
-        
-
-def analyze_single_space(space: dict, source_code: str) -> str:
-    """단일 스페이스 분석"""
-    try:
-        if not source_code:
-            return "소스코드를 가져올 수 없습니다."
-            
-        prompt = f"""
-        다음 스페이스의 소스코드를 분석해주세요:
-        
-        ```
-        {source_code[:4000]}
-        ```
-        
-        다음 항목을 각각 한 줄로 요약해주세요:
-        1. 개요:
-        2. 요약:
-        3. 특징 및 장점:
-        4. 사용 대상:
-        5. 사용 방법:
-        6. 유사 서비스와의 차별점:
-        """
-        
-        messages = [
-            {"role": "system", "content": "소스코드 분석 전문가입니다."},
-            {"role": "user", "content": prompt}
-        ]
-        
-        response = hf_client.chat_completion(
-            messages,
-            max_tokens=3900,
-            temperature=0.3
-        )
-        
-        return response.choices[0].message.content
-        
-    except Exception as e:
-        return f"분석 중 오류 발생: {str(e)}"
-
-
-
-def create_editable_space_analysis(progress=gr.Progress()) -> List[str]:
-    """24개 스페이스 분석 텍스트 생성"""
-    try:
-        progress(0, desc="스페이스 데이터 가져오는 중...")
-        
-        url = "https://huggingface.co/api/spaces"
-        response = requests.get(url, params={'full': 'true', 'limit': 24})
-        response.raise_for_status()
-        spaces = response.json()[:24]
-        
-        analysis_texts = []
-        
-        for idx, space in enumerate(spaces):
-            progress((idx + 1) / 24, desc=f"분석 중... {idx+1}/24")
-            try:
-                source = get_space_source(space['id'])
-                source_code = source["app.py"] or source["index.html"]
-                
-                # 프로젝트명만 추출
-                project_name = space['id'].split('/')[-1]
-                
-                prompt = f"""
-                다음 HuggingFace 스페이스를 분석하여 뉴스 리포트 형식으로 설명해주세요:
-                시작은 반드시 "오늘의 인기순위 {idx + 1}위인 {project_name}입니다."로 시작하고,
-                이어서 주요 기능, 특징, 활용방안을 자연스럽게 설명해주세요.
-
-                소스코드:
-                ```
-                {source_code[:1500]}
-                ```
-                """
-                
-                messages = [
-                    {"role": "system", "content": "AI 기술 전문 뉴스 리포터입니다."},
-                    {"role": "user", "content": prompt}
-                ]
-                
-                response = hf_client.chat_completion(
-                    messages,
-                    max_tokens=2000,
-                    temperature=0.7
-                )
-                
-                analysis_texts.append(response.choices[0].message.content.strip())
-                
-            except Exception as e:
-                analysis_texts.append(f"오늘의 인기순위 {idx + 1}위인 {project_name}입니다.")
-        
-        return analysis_texts
-        
-    except Exception as e:
-        return [f"순위 {i+1}위 분석을 준비중입니다." for i in range(24)]
-
-def generate_video(texts: List[str], progress=gr.Progress()) -> str:
-    """영상 생성"""
-    try:
-        from PIL import Image, ImageDraw
-        
-        # 임시 디렉토리 생성
-        temp_dir = tempfile.mkdtemp()
-        output_path = os.path.join(temp_dir, "output_video.mp4")
-        clips = []
-        
-        try:
-            # 인트로 생성
-            intro_text = texts[0]
-            intro_img = Image.new('RGB', (800, 600), (0, 0, 0))
-            draw = ImageDraw.Draw(intro_img)
-            
-            # 인트로 텍스트 그리기
-            margin = 40
-            y_position = margin
-            for line in intro_text.split('\n'):
-                draw.text((margin, y_position), line, fill=(255, 255, 255))
-                y_position += 40
-            
-            # 인트로 클립 생성
-            intro_clip = ImageClip(np.array(intro_img))
-            intro_audio = gTTS(text=intro_text, lang='ko', slow=False)
-            intro_audio_path = os.path.join(temp_dir, "intro.mp3")
-            intro_audio.save(intro_audio_path)
-            intro_audio_clip = AudioFileClip(intro_audio_path)
-            intro_clip = intro_clip.set_duration(intro_audio_clip.duration)
-            intro_clip = intro_clip.set_audio(intro_audio_clip)
-            clips.append(intro_clip)
-            
-            # 각 스페이스별 클립 생성
-            for idx, text in enumerate(texts[1:], 1):
-                progress((idx / len(texts)), desc=f"영상 생성 중... {idx}/{len(texts)}")
-                
-                # 스페이스 URL 구성
-                space_id = text.split("인기순위")[1].split("위인")[0].strip()
-                space_url = f"https://huggingface.co/spaces/{space_id}"
-                
-                # 스크린샷 캡처 (5초 대기)
-                time.sleep(5)  # 충분한 로딩 시간 보장
-                screenshot_base64 = get_cached_screenshot(space_url)
-                
-                if screenshot_base64:
-                    # 스크린샷 이미지 생성
-                    screenshot_data = base64.b64decode(screenshot_base64)
-                    screenshot = Image.open(BytesIO(screenshot_data))
-                    screenshot = screenshot.resize((800, 600), Image.Resampling.LANCZOS)
-                else:
-                    # 스크린샷 실패 시 검은 배경
-                    screenshot = Image.new('RGB', (800, 600), (0, 0, 0))
-                
-                # 텍스트 오버레이
-                draw = ImageDraw.Draw(screenshot)
-                text_lines = text.split('. ')
-                y_position = 500  # 화면 하단에 텍스트 배치
-                for line in text_lines:
-                    if not line.endswith('.'):
-                        line += '.'  # 문장 끝에 마침표 추가
-                    draw.text((20, y_position), line, fill=(255, 255, 255))
-                    y_position += 30
-                
-                # 음성 생성
-                tts = gTTS(text=text, lang='ko', slow=False)
-                audio_path = os.path.join(temp_dir, f"audio_{idx}.mp3")
-                tts.save(audio_path)
-                audio_clip = AudioFileClip(audio_path)
-                
-                # 이미지 클립 생성 및 오디오 결합
-                image_clip = ImageClip(np.array(screenshot))
-                image_clip = image_clip.set_duration(audio_clip.duration)
-                video_clip = image_clip.set_audio(audio_clip)
-                clips.append(video_clip)
-            
-            # 모든 클립 연결
-            final_clip = concatenate_videoclips(clips)
-            
-            # MP4로 저장
-            final_clip.write_videofile(
-                output_path,
-                fps=24,
-                codec='libx264',
-                audio_codec='aac',
-                threads=4
-            )
-            
-            return output_path
-            
-        finally:
-            # 클립 정리
-            for clip in clips:
-                try:
-                    clip.close()
-                except:
-                    pass
-            
-    except Exception as e:
-        print(f"Error generating video: {e}")
-        traceback.print_exc()
-        return ""
-        
-    finally:
-        # 임시 파일 정리
-        try:
-            shutil.rmtree(temp_dir)
-        except Exception as e:
-            print(f"Error cleaning up temp files: {e}")
-
-def create_interface():
-    # 분석용 컴포넌트 리스트 초기화
-    analysis_boxes = []
-    space_images = []
-
-    with gr.Blocks(title="HuggingFace Trending Board", css="""
-        .search-sort-container { 
-            background: linear-gradient(135deg, rgba(255,255,255,0.95), rgba(240,240,255,0.95));
-            border-radius: 15px;
-            padding: 20px;
-            margin: 10px 0;
-            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-            overflow: visible;
-        }
-        .search-box { 
-            border: 2px solid #e1e1e1;
-            border-radius: 10px;
-            padding: 12px;
-            transition: all 0.3s ease;
-            background: linear-gradient(135deg, #ffffff, #f8f9ff);
-            width: 100%;
-        }
-        .search-box:focus { 
-            border-color: #7b61ff;
-            box-shadow: 0 0 0 2px rgba(123,97,255,0.2);
-            background: linear-gradient(135deg, #ffffff, #f0f3ff);
-        }
-        .refresh-btn {
-            background: linear-gradient(135deg, #7b61ff, #6366f1);
-            color: white;
-            border: none;
-            padding: 10px 20px;
-            border-radius: 10px;
-            cursor: pointer;
-            transition: all 0.3s ease;
-            width: 120px;
-            height: 80px !important;
-            display: flex;
-            align-items: center;
-            justify-content: center;
-            margin-left: auto;
-            font-size: 1.2em !important;
-            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-        }
-        .refresh-btn:hover {
-            transform: translateY(-2px);
-            box-shadow: 0 6px 12px rgba(0,0,0,0.2);
-            background: linear-gradient(135deg, #8b71ff, #7376f1);
-        }
-    """) as interface:
-        
-        gr.Markdown("""
-            # 🤗 HuggingFace Trending Board
-            <div style='margin-bottom: 20px; padding: 10px; background: linear-gradient(135deg, rgba(123,97,255,0.1), rgba(99,102,241,0.1)); border-radius: 10px;'>
-                Explore, search, and sort through the Shows Top 300 Trending spaces with AI Ratings
-            </div>
-        """)
-        
-        with gr.Tabs() as tabs:
-            # Spaces 탭
-            with gr.Tab("🎯 Trending Spaces"):
-                with gr.Row(elem_classes="search-sort-container"):
-                    with gr.Column(scale=2):
-                        spaces_search = gr.Textbox(
-                            label="🔍 Search Spaces",
-                            placeholder="Enter keywords to search...",
-                            elem_classes="search-box"
-                        )
-                    with gr.Column(scale=2):
-                        spaces_sort = gr.Radio(
-                            choices=["rank", "rising_rate", "popularity"],
-                            value="rank",
-                            label="Sort by",
-                            interactive=True
-                        )
-                    with gr.Column(scale=1):
-                        spaces_refresh_btn = gr.Button(
-                            "🔄 Refresh",
-                            variant="primary",
-                            elem_classes="refresh-btn"
-                        )
-                spaces_gallery = gr.HTML()
-                spaces_status = gr.Markdown("Loading...")
-            
-            # Models 탭
-            with gr.Tab("🤖 Trending Models"):
-                with gr.Row(elem_classes="search-sort-container"):
-                    with gr.Column(scale=2):
-                        models_search = gr.Textbox(
-                            label="🔍 Search Models",
-                            placeholder="Enter keywords to search...",
-                            elem_classes="search-box"
-                        )
-                    with gr.Column(scale=2):
-                        models_sort = gr.Radio(
-                            choices=["rank", "rising_rate", "popularity"],
-                            value="rank",
-                            label="Sort by",
-                            interactive=True
-                        )
-                    with gr.Column(scale=1):
-                        models_refresh_btn = gr.Button(
-                            "🔄 Refresh",
-                            variant="primary",
-                            elem_classes="refresh-btn"
-                        )
-                models_gallery = gr.HTML()
-                models_status = gr.Markdown("Loading...")
-            
-            # Datasets 탭
-            with gr.Tab("📊 Trending Datasets"):
-                with gr.Row(elem_classes="search-sort-container"):
-                    with gr.Column(scale=2):
-                        datasets_search = gr.Textbox(
-                            label="🔍 Search Datasets",
-                            placeholder="Enter keywords to search...",
-                            elem_classes="search-box"
-                        )
-                    with gr.Column(scale=2):
-                        datasets_sort = gr.Radio(
-                            choices=["rank", "rising_rate", "popularity"],
-                            value="rank",
-                            label="Sort by",
-                            interactive=True
-                        )
-                    with gr.Column(scale=1):
-                        datasets_refresh_btn = gr.Button(
-                            "🔄 Refresh",
-                            variant="primary",
-                            elem_classes="refresh-btn"
-                        )
-                datasets_gallery = gr.HTML()
-                datasets_status = gr.Markdown("Loading...")
-
-        # 분석 탭
-            with gr.Tab("🔍 Top 24 Spaces Analysis"):
-                with gr.Row(elem_classes="search-sort-container"):
-                    analysis_refresh_btn = gr.Button(
-                        "🔄 Analyze All 24 Spaces",
-                        variant="primary",
-                        elem_classes="refresh-btn"
-                    )
-                
-                # 인트로 섹션
-                with gr.Row():
-                    with gr.Column(scale=3):
-                        intro_text = gr.Textbox(
-                            value="안녕하세요. 매일 글로벌 최신 AI 인기 트렌드 서비스를 알아보는 '데일리 AI 트렌딩' 뉴스입니다. 오늘의 허깅페이스 인기 순위 1위부터 24위까지, 분석과 핵심 내용을 살펴보겠습니다.",
-                            label="인트로 텍스트",
-                            lines=4
-                        )
-                    with gr.Column(scale=1):
-    # 인트로 이미지 부분 수정
-                        intro_image = gr.Image(
-                            label="인트로 이미지",
-                            type="filepath",
-                            height=150,
-                            elem_classes="image-upload-box"
-                        )
-    
-                
-                # 24개의 스페이스 분석 섹션
-                for i in range(24):
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            text_box = gr.Textbox(
-                                label=f"Space #{i+1}",
-                                lines=3
-                            )
-                            analysis_boxes.append(text_box)
-                        with gr.Column(scale=1):
-    
-                            img = gr.Image(
-                                label=f"Space #{i+1} Screenshot",
-                                type="filepath", 
-                                height=150,
-                                elem_classes="image-upload-box",
-                                interactive=True
-                            )
-                            space_images.append(img)
-                
-                # 비디오 생성 섹션
-                with gr.Row():
-                    with gr.Column():
-                        generate_btn = gr.Button(
-                            "🎬 영상 생성",
-                            variant="primary",
-                            size="lg"
-                        )
-                        video_output = gr.Video(label="생성된 영상")
-    
-                # 이미지 일괄 업데이트 버튼 추가
-                with gr.Row():
-                    update_images_btn = gr.Button(
-                        "🔄 Update Screenshots",
-                        variant="secondary"
-                    )
-    
-                def update_screenshots():
-                    """스크린샷 일괄 업데이트"""
-                    try:
-                        url = "https://huggingface.co/api/spaces"
-                        response = requests.get(url, params={'full': 'true', 'limit': 24})
-                        spaces = response.json()[:24]
-                        
-                        image_paths = []
-                        temp_dir = Path("temp_screenshots")
-                        temp_dir.mkdir(exist_ok=True)
-                        
-                        for idx, space in enumerate(spaces):
-                            space_url = f"https://huggingface.co/spaces/{space['id']}"
-                            time.sleep(5)  # 충분한 로딩 시간
-                            screenshot_base64 = get_cached_screenshot(space_url)
-                            
-                            if screenshot_base64:
-                                try:
-                                    img_data = base64.b64decode(screenshot_base64)
-                                    screenshot_path = temp_dir / f"screenshot_{idx+1}.jpg"
-                                    with open(screenshot_path, 'wb') as f:
-                                        f.write(img_data)
-                                    image_paths.append(str(screenshot_path))
-                                except Exception as e:
-                                    print(f"Screenshot save error: {e}")
-                                    image_paths.append(None)
-                            else:
-                                image_paths.append(None)
-                        
-                        return image_paths
-                    except Exception as e:
-                        print(f"Update screenshots error: {e}")
-                        return [None] * 24
-    
-            # 이미지 업데이트 버튼 이벤트 핸들러
-        update_images_btn.click(
-            fn=update_screenshots,
-            outputs=space_images
-        )
-
-
-
-        # Event handlers
-        spaces_refresh_btn.click(
-            fn=get_trending_spaces,
-            inputs=[spaces_search, spaces_sort],
-            outputs=[spaces_gallery, spaces_status]
-        )
-        
-        models_refresh_btn.click(
-            fn=get_models,
-            inputs=[models_search, models_sort],
-            outputs=[models_gallery, models_status]
-        )
-        
-        datasets_refresh_btn.click(
-            fn=get_datasets,
-            inputs=[datasets_search, datasets_sort],
-            outputs=[datasets_gallery, datasets_status]
-        )
-        
-        # 검색어 변경 시 자동 새로고침
-        spaces_search.change(
-            fn=get_trending_spaces,
-            inputs=[spaces_search, spaces_sort],
-            outputs=[spaces_gallery, spaces_status]
-        )
-        
-        models_search.change(
-            fn=get_models,
-            inputs=[models_search, models_sort],
-            outputs=[models_gallery, models_status]
-        )
-        
-        datasets_search.change(
-            fn=get_datasets,
-            inputs=[datasets_search, datasets_sort],
-            outputs=[datasets_gallery, datasets_status]
-        )
-        
-        # 정렬 방식 변경 시 자동 새로고침
-        spaces_sort.change(
-            fn=get_trending_spaces,
-            inputs=[spaces_search, spaces_sort],
-            outputs=[spaces_gallery, spaces_status]
-        )
-        
-        models_sort.change(
-            fn=get_models,
-            inputs=[models_search, models_sort],
-            outputs=[models_gallery, models_status]
-        )
-        
-        datasets_sort.change(
-            fn=get_datasets,
-            inputs=[datasets_search, datasets_sort],
-            outputs=[datasets_gallery, datasets_status]
-        )
-
-        # 분석 탭 이벤트 핸들러
-        analysis_refresh_btn.click(
-            fn=on_analyze,
-            outputs=analysis_boxes + space_images
-        )
-        
-        generate_btn.click(
-            fn=on_generate_video,
-            inputs=[intro_text] + analysis_boxes,  # 텍스트 입력만 사용
-            outputs=video_output
-        )
-
-
-        # 초기 데이터 로드
-        interface.load(
-            fn=get_trending_spaces,
-            inputs=[spaces_search, spaces_sort],
-            outputs=[spaces_gallery, spaces_status]
-        )
-        interface.load(
-            fn=get_models,
-            inputs=[models_search, models_sort],
-            outputs=[models_gallery, models_status]
-        )
-        interface.load(
-            fn=get_datasets,
-            inputs=[datasets_search, datasets_sort],
-            outputs=[datasets_gallery, datasets_status]
-        )
-        interface.load(
-            fn=on_analyze,
-            outputs=analysis_boxes + space_images
-        )
-
-    return interface
-
-
-def on_analyze(progress=gr.Progress()):
-    """분석 실행 및 텍스트박스/이미지 업데이트"""
-    try:
-        url = "https://huggingface.co/api/spaces"
-        response = requests.get(url, params={'full': 'true', 'limit': 24})
-        response.raise_for_status()
-        spaces = response.json()[:24]
-        
-        # 결과를 저장할 리스트
-        text_results = []
-        image_results = []
-        
-        # 임시 디렉토리 생성
-        temp_dir = Path("temp_screenshots")
-        temp_dir.mkdir(exist_ok=True)
-        
-        for idx, space in enumerate(spaces):
-            progress((idx + 1) / 24, desc=f"분석 중... {idx+1}/24")
-            try:
-                # 스크린샷 캡처
-                space_url = f"https://huggingface.co/spaces/{space['id']}"
-                project_name = space['id'].split('/')[-1]
-                
-                # 텍스트 분석
-                source = get_space_source(space['id'])
-                source_code = source["app.py"] or source["index.html"]
-                
-                prompt = f"""
-                다음 HuggingFace 스페이스를 뉴스 리포트 형식으로 설명해주세요:
-                시작은 반드시 "오늘의 인기순위 {idx + 1}위인 {project_name}입니다."로 시작하고,
-                이어서 주요 기능과 특징을 자연스럽게 설명해주세요.
-                """
-                
-                messages = [
-                    {"role": "system", "content": "AI 기술 전문 뉴스 리포터입니다."},
-                    {"role": "user", "content": prompt}
-                ]
-                
-                response = hf_client.chat_completion(
-                    messages,
-                    max_tokens=500,
-                    temperature=0.7
-                )
-                
-                analysis = response.choices[0].message.content.strip()
-                text_results.append(analysis)
-                
-                # 스크린샷 처리
-                try:
-                    screenshot_path = temp_dir / f"space_{idx+1}.jpg"
-                    screenshot_base64 = get_cached_screenshot(space_url)
-                    
-                    if screenshot_base64:
-                        img_data = base64.b64decode(screenshot_base64)
-                        with open(screenshot_path, 'wb') as f:
-                            f.write(img_data)
-                        image_results.append(str(screenshot_path))
-                    else:
-                        image_results.append(None)
-                except Exception as e:
-                    print(f"Screenshot error for {space['id']}: {e}")
-                    image_results.append(None)
-                
-            except Exception as e:
-                print(f"Error processing space {space['id']}: {e}")
-                text_results.append(f"순위 {idx + 1}위 분석을 준비중입니다.")
-                image_results.append(None)
-        
-        # 빈 결과 채우기
-        while len(text_results) < 24:
-            text_results.append("분석을 준비중입니다.")
-        while len(image_results) < 24:
-            image_results.append(None)
-        
-        # 모든 결과 합치기
-        all_results = []
-        for text, image in zip(text_results, image_results):
-            all_results.extend([text, image])
-        
-        return all_results
-        
-    except Exception as e:
-        print(f"Analysis error: {e}")
-        return ["분석을 준비중입니다." for _ in range(48)]
-
-# 인터페이스에서 이벤트 핸들러 수정
-analysis_refresh_btn.click(
-    fn=on_analyze,
-    outputs=analysis_boxes + space_images
-)
-
-# 영상 생성 함수 수정
-def on_generate_video(intro_text, *texts):
-    """영상 생성"""
-    try:
-        temp_dir = tempfile.mkdtemp()
-        clips = []
-        
-        # 인트로 처리
-        intro_img = Image.new('RGB', (800, 600), (0, 0, 0))
-        draw = ImageDraw.Draw(intro_img)
-        draw.text((40, 40), intro_text, fill=(255, 255, 255))
-        
-        # 인트로 클립 생성
-        intro_audio = gTTS(text=intro_text, lang='ko', slow=False)
-        intro_audio_path = os.path.join(temp_dir, "intro.mp3")
-        intro_audio.save(intro_audio_path)
-        intro_audio_clip = AudioFileClip(intro_audio_path)
-        
-        intro_clip = ImageClip(np.array(intro_img))
-        intro_clip = intro_clip.set_duration(intro_audio_clip.duration)
-        intro_clip = intro_clip.set_audio(intro_audio_clip)
-        clips.append(intro_clip)
-        
-        # 각 스페이스 처리
-        for idx, text in enumerate(texts):
-            if not text:
-                continue
-                
-            # 이미지 생성
-            img = Image.new('RGB', (800, 600), (0, 0, 0))
-            draw = ImageDraw.Draw(img)
-            draw.text((40, 40), text, fill=(255, 255, 255))
-            
-            # 음성 생성
-            tts = gTTS(text=text, lang='ko', slow=False)
-            audio_path = os.path.join(temp_dir, f"audio_{idx}.mp3")
-            tts.save(audio_path)
-            audio_clip = AudioFileClip(audio_path)
-            
-            # 클립 생성
-            video_clip = ImageClip(np.array(img))
-            video_clip = video_clip.set_duration(audio_clip.duration)
-            video_clip = video_clip.set_audio(audio_clip)
-            clips.append(video_clip)
-        
-        # 최종 영상 생성
-        final_clip = concatenate_videoclips(clips)
-        output_path = "output_video.mp4"
-        final_clip.write_videofile(
-            output_path,
-            fps=24,
-            codec='libx264',
-            audio_codec='aac'
-        )
-        
-        return output_path
-        
-    except Exception as e:
-        print(f"Video generation error: {e}")
-        return None
-    
-    finally:
-        if 'temp_dir' in locals():
-            shutil.rmtree(temp_dir)
-
-if __name__ == "__main__":
-    try:
-        CACHE_DIR.mkdir(exist_ok=True)
-        cleanup_cache()
-        demo = create_interface()
-        demo.launch(
-            share=True,
-            inbrowser=True,
-            show_api=False,
-            max_threads=4
-        )
-    except Exception as e:
-        print(f"Application error: {e}")