Fix duplicate video embed when youtube_url is empty string
- Add .trim() checks to all video source conditions - Prevents rendering empty youtube_url as valid video - Fixes double embed card display issue - Update sidebar icon check to use optional chaining with trim 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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dwindown
162
analyze_transcript2.py
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162
analyze_transcript2.py
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#!/usr/bin/env python3
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"""
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Analyze video transcript to identify topics and create chapter divisions.
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"""
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import json
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import re
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from datetime import timedelta
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def seconds_to_timestamp(seconds):
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"""Convert seconds to readable timestamp."""
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td = timedelta(seconds=float(seconds))
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total_seconds = int(td.total_seconds())
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hours, remainder = divmod(total_seconds, 3600)
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minutes, seconds = divmod(remainder, 60)
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return f"{hours:02d}:{minutes:02d}:{seconds:02d}"
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def load_transcript(file_path):
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"""Load JSON transcript file."""
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with open(file_path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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return data
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def extract_transcript_segments(data):
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"""Extract all transcript segments with timestamps."""
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segments = []
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# The structure has a 'tracks' key
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if 'tracks' in data[0]:
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for track in data[0]['tracks']:
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if track['kind'] == 'asr': # Automatic Speech Recognition
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for event in track['events']:
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start_time = event.get('tStartMs', 0) / 1000
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duration = event.get('dDurationMs', 0) / 1000
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# Extract text from segments
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text_parts = []
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if 'segs' in event:
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for seg in event['segs']:
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if 'utf8' in seg:
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text_parts.append(seg['utf8'])
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text = ' '.join(text_parts)
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if text.strip():
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segments.append({
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'start': start_time,
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'end': start_time + duration,
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'text': text
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})
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return segments
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def group_by_time_window(segments, window_seconds=600):
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"""Group segments into time windows for analysis."""
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groups = []
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current_time = 0
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while current_time < segments[-1]['end']:
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window_end = current_time + window_seconds
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window_segments = [s for s in segments
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if current_time <= s['start'] < window_end]
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if window_segments:
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combined_text = ' '.join([s['text'] for s in window_segments])
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groups.append({
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'start': current_time,
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'end': window_end,
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'segments': window_segments,
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'text': combined_text
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})
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current_time = window_end
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return groups
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def extract_keywords(text):
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"""Extract key topics from text."""
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keywords = {
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'Market & Community': ['market', 'pasar', 'grup', 'komunitas', 'telegram', 'facebook', 'forum'],
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'Problem Finding': ['masalah', 'problem', 'kesulitan', 'permasalahan', 'error'],
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'Exploration': ['explor', 'coba', 'trial', 'nyoba', 'eksplor'],
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'Personal Branding': ['branding', 'personal branding', 'show off', 'image'],
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'AIDA/Funnel': ['aida', 'awareness', 'interest', 'desire', 'action', 'funel', 'funnel'],
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'Trust': ['trust', 'percaya', 'kepercayaan'],
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'Clients': ['klien', 'client', 'pelanggan', 'customer'],
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'Pricing': ['harga', 'price', 'bayar', 'budget', 'rp', 'juta', 'ribu'],
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'Negotiation': ['tawar', 'negosiasi', 'deal'],
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'Services': ['jasa', 'service', 'website', 'plugin', 'elementor', 'instal'],
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'Cold/Warm/Hot Market': ['cold', 'warm', 'hot', 'dingin', 'hangat'],
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'Network': ['network', 'jaringan', 'koneksi', 'hubungan'],
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'Sharing': ['sharing', 'share', 'bagi'],
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'Products': ['produk', 'product', 'template'],
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}
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found = []
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text_lower = text.lower()
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for topic, kw_list in keywords.items():
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count = sum(1 for kw in kw_list if kw.lower() in text_lower)
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if count > 0:
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found.append((topic, count))
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return sorted(found, key=lambda x: x[1], reverse=True)
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def identify_main_topics():
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"""Identify main topics throughout the video."""
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file_path = "/Users/dwindown/CascadeProjects/MeetDwindiCom/access-hub/Live Zoom - Diskusi Cara Jual Jasa via Online.json"
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print("Loading transcript...")
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data = load_transcript(file_path)
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print("Extracting segments...")
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segments = extract_transcript_segments(data)
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print(f"Total segments: {len(segments)}")
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if not segments:
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print("No segments found!")
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return
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total_duration = segments[-1]['end']
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print(f"Total duration: {seconds_to_timestamp(total_duration)} ({total_duration/60:.1f} minutes)")
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print("\n" + "="*80)
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print("ANALYZING CONTENT IN 10-MINUTE INTERVALS")
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print("="*80 + "\n")
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# Group by 10-minute windows
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groups = group_by_time_window(segments, window_seconds=600)
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for i, group in enumerate(groups, 1):
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print(f"\n{'='*80}")
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print(f"SECTION {i}: {seconds_to_timestamp(group['start'])} - {seconds_to_timestamp(group['end'])}")
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print(f"{'='*80}")
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# Get first 500 chars for preview
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preview = group['text'][:500]
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print(f"\nContent Preview:\n{preview}...")
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# Extract keywords
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keywords = extract_keywords(group['text'])
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if keywords:
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print(f"\nMain Topics:")
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for topic, count in keywords[:5]:
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print(f" - {topic}: {count} mentions")
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print("\n" + "="*80)
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print("DETAILED BREAKDOWN (5-minute intervals for first hour)")
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print("="*80 + "\n")
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# More detailed for first hour
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detailed_groups = group_by_time_window(segments[:int(len(segments)*0.4)], window_seconds=300)
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for i, group in enumerate(detailed_groups, 1):
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print(f"\n--- {seconds_to_timestamp(group['start'])} - {seconds_to_timestamp(group['end'])} ---")
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# Get text summary
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text_summary = group['text'][:300]
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print(f"{text_summary}...")
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if __name__ == "__main__":
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identify_main_topics()
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