VideoIQ packages transcripts, summaries, and chat into one video workspace
VideoIQ is an open-source, AI-powered video workspace designed to convert long-form video into transcripts, summaries, and interactive chat-enabled knowledge bases. It features a Django backend, React frontend, and a Chrome extension, supporting local video uploads, YouTube ingestion, and screen recording. The system processes video content to generate timestamped transcripts, clean summaries, and enables chatbot interactions grounded in the video's information.
Key Takeaways
- The repo supports local video upload, YouTube URL ingestion, and frontend screen recording.
- VideoIQ generates timestamped transcripts, cleaned summaries, and chatbot workflows grounded in processed video content.
- The stack uses Python 3.12, Django REST Framework, Celery, Redis, React 18, Vite, and FFmpeg.
- The system tracks video states from pending and processing through transcript_ready, summarizing, indexing_chat, completed, and failed.
- The Chrome extension is a Manifest V3 side panel wrapper that points to http://127.0.0.1:8000 by default.
Why It Matters
VideoIQ bundles transcription, summarization, and chat into one workflow for long-form video, which lowers the friction of turning raw media into searchable text artifacts. It also spans the browser and app layers with a Django backend, React frontend, and Chrome side panel extension, showing a single codebase approach across web and extension surfaces. The clearest signal to watch is how the project evolves its processing states — pending through indexing_chat to completed — because that reveals how much of the workflow is automated and observable in the UI.
Read full article at github.com
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