import gradio as gr
import yt_dlp
import os
import tempfile
import shutil
from pathlib import Path
import re
import uuid

session_data = {}

class YouTubeDownloader:
    def __init__(self):
        self.download_dir = tempfile.mkdtemp()

    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 format_video_info(self, video_info):
        if not video_info:
            return "❌ No video information available."

        duration = video_info.get('duration', 0)
        duration_str = f"{duration//3600}:{(duration%3600)//60:02d}:{duration%60:02d}" if duration else "Unknown"
        upload_date = video_info.get('upload_date', '')
        formatted_date = f"{upload_date[:4]}-{upload_date[4:6]}-{upload_date[6:8]}" if len(upload_date) == 8 else upload_date or "Unknown"

        def format_number(num):
            if 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)

        scene_descriptions = []
        if duration:
            chunk = 3
            for start in range(0, duration, chunk):
                end = min(start + chunk - 1, duration)
                description = f"Visual segment from {start}s to {end}s. (e.g., close-up, presenter talks, etc.)"
                scene_descriptions.append(f"* **[{start//60}:{start%60:02d}-{end//60}:{end%60:02d}]**: {description}")
        else:
            scene_descriptions.append("* No timestamped breakdown available.")

        tags = ' '.join(video_info.get('tags', [])).lower()
        title = video_info.get('title', '').lower()
        description_text = video_info.get('description', '').lower()
        channel = video_info.get('channel', '').lower()

        if any(word in description_text for word in ['calm music', 'soft', 'soothing']):
            music_style = "Calm"
        elif any(word in description_text for word in ['energetic', 'upbeat', 'lively']):
            music_style = "Upbeat"
        elif "music" not in description_text:
            music_style = "No music"
        else:
            music_style = "Unknown"

        known_names = [
            "Kartik Aaryan", "Virat Kohli", "Deepika Padukone", "Alia Bhatt", "Ranveer Singh",
            "MrBeast", "PewDiePie", "CarryMinati", "Prajakta Koli", "Bhuvan Bam",
            "Amitabh Bachchan", "Katrina Kaif", "Salman Khan", "Kiara Advani",
            "Kylie Jenner", "Shahrukh Khan", "Ananya Pandey", "Ashish Chanchlani",
            "Sundar Pichai", "Elon Musk", "Taylor Swift", "Janhvi Kapoor"
        ]

        metadata = " ".join([
            video_info.get('title', ''),
            video_info.get('description', ''),
            video_info.get('uploader', ''),
            video_info.get('channel', ''),
            ' '.join(video_info.get('tags', []))
        ]).lower()

        matched = [name for name in known_names if any(part in metadata for part in name.lower().split())]

        if matched:
            influencer_note = f"Yes, known influencer/celebrity detected: {', '.join(matched)}"
        else:
            influencer_note = "No known influencer or celebrity detected."

        if any(word in metadata for word in ["actor", "brand ambassador", "featured", "with", "hosted by"]):
            influencer_note += " (Someone might be featured — check visually)"

        if "review" in title or "demo" in title or "how to" in title:
            video_type = "Educational"
        elif "ad" in title or "promo" in title or "launch" in title:
            video_type = "Promotional"
        elif "funny" in title or "challenge" in title:
            video_type = "Entertainment"
        else:
            video_type = "Informational"

        if any(word in description_text for word in ['excited', 'amazing', 'love']):
            emotion = "Positive"
        elif any(word in description_text for word in ['calm', 'soothing']):
            emotion = "Neutral"
        elif any(word in description_text for word in ['warning', 'serious']):
            emotion = "Serious"
        else:
            emotion = "Neutral"

        report = f"""📹 VIDEO ANALYSIS REPORT
{'='*50}

📝 BASIC INFORMATION:
• Title: {video_info.get('title', 'Unknown')}
• Channel: {video_info.get('channel', 'Unknown')}
• Uploader: {video_info.get('uploader', 'Unknown')}
• Upload Date: {formatted_date}
• Duration: {duration_str}

📊 STATISTICS:
• Views: {format_number(video_info.get('view_count', 0))}
• Likes: {format_number(video_info.get('like_count', 0))}
• Comments: {format_number(video_info.get('comment_count', 0))}
• Channel Followers: {format_number(video_info.get('channel_followers', 0))}

🏷️ CATEGORIES & TAGS:
• Categories: {', '.join(video_info.get('categories', [])) or 'None'}
• Tags: {', '.join(video_info.get('tags', [])[:10]) or 'None'}
{('• More tags...' if len(video_info.get('tags', [])) > 10 else '')}

📖 DESCRIPTION (first 500 chars):
{video_info.get('description', 'No description available')[:500]}
{'...' if len(video_info.get('description', '')) > 500 else ''}

🎬 SCENE-BY-SCENE BREAKDOWN:
{chr(10).join(scene_descriptions)}

🎵 BACKGROUND MUSIC STYLE: {music_style}
👤 INFLUENCER PRESENT: {influencer_note}
🎥 VIDEO TYPE: {video_type}
🎭 OVERALL EMOTION: {emotion}

🔗 VIDEO URL:
{video_info.get('webpage_url', 'Unknown')}
"""
        return report.strip()

    def get_video_info(self, url):
        ydl_opts = {
            'noplaylist': True,
            'extract_flat': False,
        }
        try:
            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
                info = ydl.extract_info(url, download=False)
                return info, "✅ Info retrieved"
        except Exception as e:
            return None, f"❌ {str(e)}"

downloader = YouTubeDownloader()

def analyze(url):
    info, msg = downloader.get_video_info(url)
    if info:
        return downloader.format_video_info(info)
    else:
        return msg

demo = gr.Interface(fn=analyze, inputs=gr.Textbox(label="YouTube URL"), outputs="text", title="YouTube Analyzer with Scene Breakdown")

if __name__ == "__main__":
    demo.launch()