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developer28 commited on Jun 21, 2025

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1 Parent(s): f25e87e

Update app.py

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app.py +26 -693

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@@ -1,703 +1,36 @@
 import gradio as gr
-import yt_dlp
 import os
-import tempfile
-import shutil
-from pathlib import Path
-import re
 import uuid
-import json
-from datetime import datetime
-import google.generativeai as genai
-class YouTubeDownloader:
-    def __init__(self):
-        self.download_dir = tempfile.mkdtemp()
-        # Use temp directory for Gradio compatibility
-        self.temp_downloads = tempfile.mkdtemp(prefix="youtube_downloads_")
-        # Also create user downloads folder for copying
-        self.downloads_folder = os.path.join(os.path.expanduser("~"), "Downloads", "YouTube_Downloads")
-        os.makedirs(self.downloads_folder, exist_ok=True)
-        self.gemini_model = None
-    def configure_gemini(self, api_key):
-        """Configure Gemini API with the provided key"""
-        try:
-            genai.configure(api_key=api_key)
-            self.gemini_model = genai.GenerativeModel(model_name="gemini-1.5-flash-latest")
-            return True, "✅ Gemini API configured successfully!"
-        except Exception as e:
-            return False, f"❌ Failed to configure Gemini API: {str(e)}"
-    def cleanup(self):
-        """Clean up temporary directories and files"""
-        try:
-            if hasattr(self, 'download_dir') and os.path.exists(self.download_dir):
-                shutil.rmtree(self.download_dir)
-                print(f"✅ Cleaned up temporary directory: {self.download_dir}")
-            if hasattr(self, 'temp_downloads') and os.path.exists(self.temp_downloads):
-                shutil.rmtree(self.temp_downloads)
-                print(f"✅ Cleaned up temp downloads directory: {self.temp_downloads}")
-        except Exception as e:
-            print(f"⚠️ Warning: Could not clean up temporary directory: {e}")
-    def is_valid_youtube_url(self, url):
-        youtube_regex = re.compile(
-            r'(https?://)?(www\.)?(youtube|youtu|youtube-nocookie)\.(com|be)/'
-            r'(watch\?v=|embed/|v/|.+\?v=)?([^&=%\?]{11})'
-        )
-        return youtube_regex.match(url) is not None
-    def generate_scene_breakdown_gemini(self, video_info):
-        """Generate AI-powered scene breakdown using Gemini"""
-        if not self.gemini_model:
-            return self.generate_scene_breakdown_fallback(video_info)
-        try:
-            duration = video_info.get('duration', 0)
-            title = video_info.get('title', '')
-            description = video_info.get('description', '')[:1500]  # Increased limit for better context
-            if not duration:
-                return ["**[Duration Unknown]**: Unable to generate timestamped breakdown - video duration not available"]
-            # Create enhanced prompt for Gemini
-            prompt = f"""
-            Analyze this YouTube video and create a highly detailed, scene-by-scene breakdown with precise timestamps and specific descriptions:
-            Title: {title}
-            Duration: {duration} seconds
-            Description: {description}
-            IMPORTANT INSTRUCTIONS:
-            1. Create detailed scene descriptions that include:
-               - Physical appearance of people (age, gender, clothing, hair, etc.)
-               - Exact actions being performed
-               - Dialogue or speech (include actual lines if audible, or infer probable spoken lines based on actions and setting; format them as "Character: line...")
-               - Setting and environment details
-               - Props, objects, or products being shown
-               - Visual effects, text overlays, or graphics
-               - Mood, tone, and atmosphere
-               - Camera movements or angles (if apparent)
-            2. Dialogue Emphasis:
-               - Include short dialogue lines in **every scene** wherever plausible.
-               - Write lines like: Character: "Actual or inferred line..."
-               - If dialogue is not available, intelligently infer probable phrases (e.g., "Welcome!", "Try this now!", "It feels amazing!").
-               - Do NOT skip dialogue unless it’s clearly impossible.
-            3. Timestamp Guidelines:
-               - For videos under 1 minute: 2-3 second segments
-               - For videos 1-5 minutes: 3-5 second segments
-               - For videos 5-15 minutes: 5-10 second segments
-               - For videos over 15 minutes: 10-15 second segments
-               - Maximum 20 scenes total for longer videos
-            4. Format each scene EXACTLY like this:
-               **[MM:SS-MM:SS]**: Detailed description including who is visible, what they're wearing, what they're doing, what they're saying (if applicable), setting details, objects shown, and any visual elements.
-            5. Write descriptions as if you're watching the video in real-time, noting everything visible and audible.
-            Based on the title and description, intelligently infer what would likely happen in each time segment. Consider the video type and create contextually appropriate, detailed descriptions.
-            """
-            response = self.gemini_model.generate_content(prompt)
-            # Parse the response into individual scenes
-            if response and response.text:
-                scenes = []
-                lines = response.text.split('\n')
-                current_scene = ""
-                for line in lines:
-                    line = line.strip()
-                    if line.strip().startswith("**[") and "]**:" in line:
-                        # This is a new scene timestamp line
-                        if current_scene:
-                            scenes.append(current_scene.strip())
-                        current_scene = line.strip()
-                    elif current_scene:
-                        # This is continuation of the current scene description
-                        current_scene += "\n" + line.strip()
-                # Add the last scene if exists
-                if current_scene:
-                    scenes.append(current_scene.strip())
-                return scenes if scenes else self.generate_scene_breakdown_fallback(video_info)
-            else:
-                return self.generate_scene_breakdown_fallback(video_info)
-        except Exception as e:
-            print(f"Gemini API error: {e}")
-            return self.generate_scene_breakdown_fallback(video_info)
-    def generate_scene_breakdown_fallback(self, video_info):
-        """Enhanced fallback scene generation when Gemini is not available"""
-        duration = video_info.get('duration', 0)
-        title = video_info.get('title', '').lower()
-        description = video_info.get('description', '').lower()
-        uploader = video_info.get('uploader', 'Content creator')
-        if not duration:
-            return ["**[Duration Unknown]**: Unable to generate timestamped breakdown"]
-        # Determine segment length based on duration
-        if duration <= 60:
-            segment_length = 3
-        elif duration <= 300:
-            segment_length = 5
-        elif duration <= 900:
-            segment_length = 10
-        else:
-            segment_length = 15
-        scenes = []
-        num_segments = min(duration // segment_length + 1, 20)
-        # Detect video type for better descriptions
-        video_type = self.detect_video_type_detailed(title, description)
-        for i in range(num_segments):
-            start_time = i * segment_length
-            end_time = min(start_time + segment_length - 1, duration)
-            start_formatted = f"{start_time//60}:{start_time%60:02d}"
-            end_formatted = f"{end_time//60}:{end_time%60:02d}"
-            # Generate contextual descriptions based on video type and timing
-            desc = self.generate_contextual_description(i, num_segments, video_type, uploader, title)
-            scenes.append(f"**[{start_formatted}-{end_formatted}]**: {desc}")
-        return scenes
-    def detect_video_type_detailed(self, title, description):
-        """Detect video type with more detail for better fallback descriptions"""
-        text = (title + " " + description).lower()
-        if any(word in text for word in ['tutorial', 'how to', 'guide', 'learn', 'diy', 'step by step']):
-            return 'tutorial'
-        elif any(word in text for word in ['review', 'unboxing', 'test', 'comparison', 'vs']):
-            return 'review'
-        elif any(word in text for word in ['vlog', 'daily', 'routine', 'day in', 'morning', 'skincare']):
-            return 'vlog'
-        elif any(word in text for word in ['music', 'song', 'cover', 'lyrics', 'dance']):
-            return 'music'
-        elif any(word in text for word in ['comedy', 'funny', 'prank', 'challenge', 'reaction']):
-            return 'entertainment'
-        elif any(word in text for word in ['news', 'breaking', 'update', 'report']):
-            return 'news'
-        elif any(word in text for word in ['cooking', 'recipe', 'food', 'kitchen']):
-            return 'cooking'
-        elif any(word in text for word in ['workout', 'fitness', 'exercise', 'yoga']):
-            return 'fitness'
-        else:
-            return 'general'
-    def generate_contextual_description(self, scene_index, total_scenes, video_type, uploader, title):
-        """Generate contextual descriptions based on video type and scene position"""
-        # Common elements
-        presenter_desc = f"The content creator"
-        if 'woman' in title.lower() or 'girl' in title.lower():
-            presenter_desc = "A woman"
-        elif 'man' in title.lower() or 'guy' in title.lower():
-            presenter_desc = "A man"
-        # Position-based descriptions
-        if scene_index == 0:
-            # Opening scene
-            if video_type == 'tutorial':
-                return f"{presenter_desc} appears on screen, likely introducing themselves and the topic. They may be in a well-lit indoor setting, wearing casual clothing, and addressing the camera directly with a welcoming gesture."
-            elif video_type == 'vlog':
-                return f"{presenter_desc} greets the camera with a smile, possibly waving. They appear to be in their usual filming location, wearing their typical style, and beginning their introduction to today's content."
-            elif video_type == 'review':
-                return f"{presenter_desc} introduces the product or topic they'll be reviewing, likely holding or displaying the item. The setting appears organized, possibly with the product prominently featured."
-            else:
-                return f"{presenter_desc} appears on screen to begin the video, introducing the topic with engaging body language and clear speech directed at the audience."
-        elif scene_index == total_scenes - 1:
-            # Closing scene
-            if video_type == 'tutorial':
-                return f"{presenter_desc} concludes the tutorial, possibly showing the final result. They may be thanking viewers, asking for engagement (likes/comments), and suggesting related content."
-            elif video_type == 'vlog':
-                return f"{presenter_desc} wraps up their vlog, possibly reflecting on the day's events. They appear relaxed and are likely saying goodbye to viewers with a friendly gesture."
-            else:
-                return f"{presenter_desc} concludes the video with final thoughts, thanking viewers for watching, and encouraging engagement through likes, comments, and subscriptions."
-        else:
-            # Middle scenes - content-specific
-            if video_type == 'tutorial':
-                step_num = scene_index
-                return f"{presenter_desc} demonstrates step {step_num} of the process, showing specific techniques and explaining the procedure. They may be using tools or materials, with close-up shots of their hands working."
-            elif video_type == 'review':
-                return f"{presenter_desc} examines different aspects of the product, pointing out features and sharing their opinions. They may be holding, using, or demonstrating the item while speaking to the camera."
-            elif video_type == 'vlog':
-                return f"{presenter_desc} continues sharing their experience, possibly showing different locations or activities. The scene captures candid moments with natural lighting and casual interactions."
-            elif video_type == 'cooking':
-                return f"{presenter_desc} works in the kitchen, preparing ingredients or cooking. They demonstrate techniques while explaining each step, with kitchen tools and ingredients visible on the counter."
-            elif video_type == 'fitness':
-                return f"{presenter_desc} demonstrates exercise movements, likely in workout attire in a gym or home setting. They show proper form while providing instruction and motivation."
-            else:
-                return f"{presenter_desc} continues with the main content, engaging with the audience through clear explanations and demonstrations. The setting remains consistent with good lighting and clear audio."
-    def detect_video_type(self, title, description):
-        """Detect video type based on title and description"""
-        text = (title + " " + description).lower()
-        if any(word in text for word in ['music', 'song', 'album', 'artist', 'band', 'lyrics']):
-            return "🎵 Music Video"
-        elif any(word in text for word in ['tutorial', 'how to', 'guide', 'learn', 'teaching']):
-            return "📚 Tutorial/Educational"
-        elif any(word in text for word in ['funny', 'comedy', 'entertainment', 'vlog', 'challenge']):
-            return "🎭 Entertainment/Comedy"
-        elif any(word in text for word in ['news', 'breaking', 'report', 'update']):
-            return "📰 News/Information"
-        elif any(word in text for word in ['review', 'unboxing', 'test', 'comparison']):
-            return "⭐ Review/Unboxing"
-        elif any(word in text for word in ['commercial', 'ad', 'brand', 'product']):
-            return "📺 Commercial/Advertisement"
-        else:
-            return "🎬 General Content"
-    def detect_background_music(self, video_info):
-        """Detect background music style"""
-        title = video_info.get('title', '').lower()
-        description = video_info.get('description', '').lower()
-        if any(word in title for word in ['music', 'song', 'soundtrack']):
-            return "🎵 Original Music/Soundtrack - Primary audio content"
-        elif any(word in title for word in ['commercial', 'ad', 'brand']):
-            return "🎶 Upbeat Commercial Music - Designed to enhance brand appeal"
-        elif any(word in title for word in ['tutorial', 'how to', 'guide']):
-            return "🔇 Minimal/No Background Music - Focus on instruction"
-        elif any(word in title for word in ['vlog', 'daily', 'life']):
-            return "🎼 Ambient Background Music - Complementary to narration"
-        else:
-            return "🎵 Background Music - Complementing video mood and pacing"
-    def detect_influencer_status(self, video_info):
-        """Detect influencer status"""
-        subscriber_count = video_info.get('channel_followers', 0)
-        view_count = video_info.get('view_count', 0)
-        if subscriber_count > 10000000:
-            return "🌟 Mega Influencer (10M+ subscribers)"
-        elif subscriber_count > 1000000:
-            return "⭐ Major Influencer (1M+ subscribers)"
-        elif subscriber_count > 100000:
-            return "🎯 Mid-tier Influencer (100K+ subscribers)"
-        elif subscriber_count > 10000:
-            return "📈 Micro Influencer (10K+ subscribers)"
-        elif view_count > 100000:
-            return "🔥 Viral Content Creator"
-        else:
-            return "👤 Regular Content Creator"
-    def format_number(self, num):
-        if num is None or num == 0:
-            return "0"
-        if num >= 1_000_000_000:
-            return f"{num/1_000_000_000:.1f}B"
-        elif num >= 1_000_000:
-            return f"{num/1_000_000:.1f}M"
-        elif num >= 1_000:
-            return f"{num/1_000:.1f}K"
-        return str(num)
-    def format_video_info(self, video_info):
-        """Streamlined video information formatting"""
-        if not video_info:
-            return "❌ No video information available."
-        # Basic information
-        title = video_info.get("title", "Unknown")
-        uploader = video_info.get("uploader", "Unknown")
-        duration = video_info.get("duration", 0)
-        duration_str = f"{duration//60}:{duration%60:02d}" if duration else "Unknown"
-        view_count = video_info.get("view_count", 0)
-        like_count = video_info.get("like_count", 0)
-        comment_count = video_info.get("comment_count", 0)
-        upload_date = video_info.get("upload_date", "Unknown")
-        # Format upload date
-        if len(upload_date) == 8:
-            formatted_date = f"{upload_date[:4]}-{upload_date[4:6]}-{upload_date[6:8]}"
-        else:
-            formatted_date = upload_date
-        # Generate enhanced analysis
-        scene_descriptions = self.generate_scene_breakdown_gemini(video_info)
-        video_type = self.detect_video_type(title, video_info.get('description', ''))
-        background_music = self.detect_background_music(video_info)
-        influencer_status = self.detect_influencer_status(video_info)
-        # Calculate engagement metrics
-        engagement_rate = (like_count / view_count) * 100 if view_count > 0 else 0
-        # Generate streamlined report
-        report = f"""
-🎬 YOUTUBE VIDEO ANALYSIS REPORT
-{'='*50}
-📋 BASIC INFORMATION
-{'─'*25}
-📹 **Title:** {title}
-👤 **Uploader:** {uploader}
-📅 **Upload Date:** {formatted_date}
-⏱️ **Duration:** {duration_str}
-🆔 **Video ID:** {video_info.get('id', 'Unknown')}
-📊 PERFORMANCE METRICS
-{'─'*25}
-👀 **Views:** {self.format_number(view_count)} ({view_count:,})
-👍 **Likes:** {self.format_number(like_count)} ({like_count:,})
-💬 **Comments:** {self.format_number(comment_count)} ({comment_count:,})
-📈 **Engagement Rate:** {engagement_rate:.2f}%
-🎯 CONTENT ANALYSIS
-{'─'*25}
-📂 **Video Type:** {video_type}
-🎵 **Background Music:** {background_music}
-👑 **Creator Status:** {influencer_status}
-🎬 DETAILED SCENE BREAKDOWN
-{'─'*30}
-{chr(10).join(scene_descriptions)}
-📝 DESCRIPTION PREVIEW
-{'─'*25}
-{video_info.get('description', 'No description available')[:500]}
-{'...(truncated)' if len(video_info.get('description', '')) > 500 else ''}
-{'='*50}
-📊 **Analysis completed:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
-🤖 **AI Enhancement:** {'Gemini AI' if self.gemini_model else 'Standard Analysis'}
-"""
-        return report.strip()
-    def get_video_info(self, url, progress=gr.Progress(), cookiefile=None):
-        """Extract video information"""
-        if not url or not url.strip():
-            return None, "❌ Please enter a YouTube URL"
-        if not self.is_valid_youtube_url(url):
-            return None, "❌ Invalid YouTube URL format"
-        try:
-            progress(0.1, desc="Initializing YouTube extractor...")
-            ydl_opts = {
-                'noplaylist': True,
-                'extract_flat': False,
-            }
-            if cookiefile and os.path.exists(cookiefile):
-                ydl_opts['cookiefile'] = cookiefile
-            progress(0.5, desc="Extracting video metadata...")
-            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-                info = ydl.extract_info(url, download=False)
-            progress(1.0, desc="✅ Analysis complete!")
-            return info, "✅ Video information extracted successfully"
-        except Exception as e:
-            return None, f"❌ Error: {str(e)}"
-    def download_video(self, url, quality="best", audio_only=False, progress=gr.Progress(), cookiefile=None):
-        """Download video with progress tracking"""
-        if not url or not url.strip():
-            return None, "❌ Please enter a YouTube URL"
-        if not self.is_valid_youtube_url(url):
-            return None, "❌ Invalid YouTube URL format"
-        try:
-            progress(0.1, desc="Preparing download...")
-            # Create unique filename
-            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-            # Download to temp directory first (Gradio compatible)
-            ydl_opts = {
-                'outtmpl': os.path.join(self.temp_downloads, f'%(title)s_{timestamp}.%(ext)s'),
-                'noplaylist': True,
-            }
-            if audio_only:
-                ydl_opts['format'] = 'bestaudio/best'
-                ydl_opts['postprocessors'] = [{
-                    'key': 'FFmpegExtractAudio',
-                    'preferredcodec': 'mp3',
-                    'preferredquality': '192',
-                }]
-            else:
-                if quality == "best":
-                    ydl_opts['format'] = 'best[height<=1080]'
-                elif quality == "720p":
-                    ydl_opts['format'] = 'best[height<=720]'
-                elif quality == "480p":
-                    ydl_opts['format'] = 'best[height<=480]'
-                else:
-                    ydl_opts['format'] = 'best'
-            if cookiefile and os.path.exists(cookiefile):
-                ydl_opts['cookiefile'] = cookiefile
-            # Progress hook
-            def progress_hook(d):
-                if d['status'] == 'downloading':
-                    if 'total_bytes' in d:
-                        percent = (d['downloaded_bytes'] / d['total_bytes']) * 100
-                        progress(0.1 + (percent / 100) * 0.7, desc=f"Downloading... {percent:.1f}%")
-                    else:
-                        progress(0.5, desc="Downloading...")
-                elif d['status'] == 'finished':
-                    progress(0.8, desc="Processing download...")
-            ydl_opts['progress_hooks'] = [progress_hook]
-            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-                info = ydl.extract_info(url, download=True)
-            progress(0.9, desc="Copying to Downloads folder...")
-            # Find the downloaded file in temp directory
-            downloaded_file_temp = None
-            for file in os.listdir(self.temp_downloads):
-                if timestamp in file:
-                    downloaded_file_temp = os.path.join(self.temp_downloads, file)
-                    break
-            if not downloaded_file_temp:
-                return None, "❌ Downloaded file not found in temp directory"
-            # Copy to user's Downloads folder
-            final_filename = os.path.basename(downloaded_file_temp)
-            final_path = os.path.join(self.downloads_folder, final_filename)
-            try:
-                shutil.copy2(downloaded_file_temp, final_path)
-                copy_success = True
-            except Exception as e:
-                print(f"Warning: Could not copy to Downloads folder: {e}")
-                copy_success = False
-                final_path = "File downloaded to temp location only"
-            progress(1.0, desc="✅ Download complete!")
-            success_msg = f"""✅ Download successful!
-📁 Temp file (for download): {os.path.basename(downloaded_file_temp)}
-📁 Permanent location: {final_path if copy_success else 'Copy failed'}
-🎯 File size: {os.path.getsize(downloaded_file_temp) / (1024*1024):.1f} MB"""
-            return downloaded_file_temp, success_msg
-        except Exception as e:
-            return None, f"❌ Download failed: {str(e)}"
-# Initialize global downloader
-downloader = YouTubeDownloader()
-def configure_api_key(api_key):
-    """Configure Gemini API key"""
-    if not api_key or not api_key.strip():
-        return "❌ Please enter a valid Google API key", gr.update(visible=False)
-    success, message = downloader.configure_gemini(api_key.strip())
-    if success:
-        return message, gr.update(visible=True)
-    else:
-        return message, gr.update(visible=False)
-def analyze_with_cookies(url, cookies_file, progress=gr.Progress()):
-    """Main analysis function"""
-    try:
-        progress(0.05, desc="Starting analysis...")
-        cookiefile = None
-        if cookies_file and os.path.exists(cookies_file):
-            cookiefile = cookies_file
-        info, msg = downloader.get_video_info(url, progress=progress, cookiefile=cookiefile)
-        if info:
-            progress(0.95, desc="Generating comprehensive report...")
-            formatted_info = downloader.format_video_info(info)
-            progress(1.0, desc="✅ Complete!")
-            return formatted_info
-        else:
-            return f"❌ Analysis Failed: {msg}"
-    except Exception as e:
-        return f"❌ System Error: {str(e)}"
-def download_with_cookies(url, quality, audio_only, cookies_file, progress=gr.Progress()):
-    """Main download function"""
-    try:
-        progress(0.05, desc="Preparing download...")
-        cookiefile = None
-        if cookies_file and os.path.exists(cookies_file):
-            cookiefile = cookies_file
-        file_path, msg = downloader.download_video(url, quality, audio_only, progress=progress, cookiefile=cookiefile)
-        if file_path:
-            return file_path, msg
-        else:
-            return None, msg
-    except Exception as e:
-        return None, f"❌ System Error: {str(e)}"
-def create_interface():
-    """Create and configure the Gradio interface"""
-    with gr.Blocks(theme=gr.themes.Soft(), title="🎥 YouTube Video Analyzer & Downloader Pro") as interface:
-        gr.HTML("<h1>🎥 YouTube Video Analyzer & Downloader Pro</h1>")
-        # API Key Configuration Section
-        with gr.Group():
-            gr.HTML("<h3>🔑 Google Gemini API Configuration</h3>")
-            with gr.Row():
-                api_key_input = gr.Textbox(
-                    label="🔑 Google API Key",
-                    placeholder="Enter your Google API Key for enhanced AI analysis...",
-                    type="password",
-                    value=""
-                )
-                configure_btn = gr.Button("🔧 Configure API", variant="secondary")
-            api_status = gr.Textbox(
-                label="API Status",
-                value="❌ Gemini API not configured - Using fallback analysis",
-                interactive=False,
-                lines=1
-            )
-        # Main Interface (initially hidden until API is configured)
-        main_interface = gr.Group(visible=False)
-        with main_interface:
-            with gr.Row():
-                url_input = gr.Textbox(
-                    label="🔗 YouTube URL",
-                    placeholder="Paste your YouTube video URL here...",
-                    value=""
-                )
-                cookies_input = gr.File(
-                    label="🍪 Upload cookies.txt (Optional)",
-                    file_types=[".txt"],
-                    type="filepath"
-                )
-            with gr.Tabs():
-                with gr.TabItem("📊 Video Analysis"):
-                    analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")
-                    analysis_output = gr.Textbox(
-                        label="📊 Analysis Report",
-                        lines=25,
-                        show_copy_button=True
-                    )
-                    analyze_btn.click(
-                        fn=analyze_with_cookies,
-                        inputs=[url_input, cookies_input],
-                        outputs=analysis_output,
-                        show_progress=True
-                    )
-                with gr.TabItem("⬇️ Video Download"):
-                    with gr.Row():
-                        quality_dropdown = gr.Dropdown(
-                            choices=["best", "720p", "480p"],
-                            value="best",
-                            label="📺 Video Quality"
-                        )
-                        audio_only_checkbox = gr.Checkbox(
-                            label="🎵 Audio Only (MP3)",
-                            value=False
-                        )
-                    download_btn = gr.Button("⬇️ Download Video", variant="primary")
-                    download_status = gr.Textbox(
-                        label="📥 Download Status",
-                        lines=5,
-                        show_copy_button=True
-                    )
-                    download_file = gr.File(
-                        label="📁 Downloaded File",
-                        visible=False
-                    )
-                    def download_and_update(url, quality, audio_only, cookies_file, progress=gr.Progress()):
-                        file_path, status = download_with_cookies(url, quality, audio_only, cookies_file, progress)
-                        if file_path and os.path.exists(file_path):
-                            return status, gr.update(value=file_path, visible=True)
-                        else:
-                            return status, gr.update(visible=False)
-                    download_btn.click(
-                        fn=download_and_update,
-                        inputs=[url_input, quality_dropdown, audio_only_checkbox, cookies_input],
-                        outputs=[download_status, download_file],
-                        show_progress=True
-                    )
-        # Configure API key button action
-        configure_btn.click(
-            fn=configure_api_key,
-            inputs=[api_key_input],
-            outputs=[api_status, main_interface]
-        )
-        # Always show interface option (for fallback mode)
-        with gr.Row():
-            show_interface_btn = gr.Button("🚀 Use Without Gemini API (Fallback Mode)", variant="secondary")
-            def show_fallback_interface():
-                return "⚠️ Using fallback analysis mode", gr.update(visible=True)
-            show_interface_btn.click(
-                fn=show_fallback_interface,
-                outputs=[api_status, main_interface]
-            )
-        gr.HTML("""
-        <div style="margin-top: 20px; padding: 15px; background-color: #f0f8ff; border-radius: 10px; border-left: 5px solid #4285f4;">
-            <h3>🔑 How to Get Google API Key:</h3>
-            <ol>
-                <li>Go to <a href="https://console.cloud.google.com/" target="_blank">Google Cloud Console</a></li>
-                <li>Create a new project or select an existing one</li>
-                <li>Enable the "Generative Language API"</li>
-                <li>Go to "Credentials" and create an API key</li>
-                <li>Copy the API key and paste it above</li>
-            </ol>
-            <p><strong>✨ Benefits of using Gemini API:</strong></p>
-            <ul>
-                <li>🤖 AI-powered scene descriptions with contextual understanding</li>
-                <li>🎯 More accurate content type detection</li>
-                <li>📊 Enhanced analysis based on video content</li>
-                <li>⏰ Intelligent timestamp segmentation</li>
-            </ul>
-        </div>
-        """)
-    return interface
-if __name__ == "__main__":
-    demo = create_interface()
-    import atexit
-    atexit.register(downloader.cleanup)
-    demo.launch(debug=True, show_error=True)

 import gradio as gr
+from xhtml2pdf import pisa
+from io import BytesIO
 import os
 import uuid
+def generate_dummy_pdf():
+    html = """
+    <html>
+    <body>
+    <h1>Hello, PDF!</h1>
+    <p>This is a test PDF file.</p>
+    </body>
+    </html>
+    """
+    result = BytesIO()
+    pisa_status = pisa.CreatePDF(html, dest=result)
+    if pisa_status.err:
+        print("PDF generation failed")
+        return None
+    pdf_path = os.path.join(os.path.expanduser("~"), "Downloads", f"test_pdf_{uuid.uuid4().hex}.pdf")
+    with open(pdf_path, "wb") as f:
+        f.write(result.getvalue())
+    print("✅ PDF saved at:", pdf_path)
+    return pdf_path
+with gr.Blocks() as demo:
+    btn = gr.Button("📄 Generate PDF")
+    output = gr.File(label="📥 Download PDF")
+    btn.click(fn=generate_dummy_pdf, inputs=[], outputs=output)
+demo.launch()