ContentIQ turns YouTube videos into summaries and Q&A
ContentIQ offers an instant video analysis tool that converts YouTube links or uploaded video files into summaries, chapter timestamps, and AI-powered Q&A. The system employs a multi-tiered transcription fallback, adaptive summarization using Groq's LLaMA, and semantic indexing in ChromaDB to generate structured insights from video content.
Key Takeaways
- Dual input supports YouTube URLs plus direct uploads in MP4, MOV, MP3, WAV, and FLAC.
- The transcription fallback runs YT Transcript API first, then Supadata API, then yt-dlp plus Groq Whisper-large-v3-turbo.
- Adaptive summarization uses tiktoken to route under 8,000 tokens to one Groq LLaMA 3.1 call and over 8,000 tokens to map-reduce.
- Segments are chunked into 2-minute windows, embedded with ONNX MiniLM-L6-v2, and stored in ChromaDB keyed by video_id.
- Contextual chat uses MMR retrieval with k=5 and fetch_k=15 plus session memory for timestamp-aware answers.
Why It Matters
ContentIQ packages transcription, summarization, and retrieval into a single video-analysis flow, which lowers the number of tools needed to turn a clip into structured notes. The architecture is notable for its tiered fallback path, token-aware LLaMA routing, and ChromaDB indexing of 2-minute segments, all of which point to a system built around video-specific search and Q&A rather than plain transcription. Watch whether the product keeps the same one-screen workflow across both YouTube URLs and uploaded files, since both inputs are part of the launch.
Read full article at contentiq-h3yi.onrender.com
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