Ingest video files into a searchable database with transcription and embeddings.
npx skills add https://github.com/PixelML/av --skill agentic-video-memory
Please help me install this Agent Skill. Skill: agentic-video-memory Source: https://github.com/PixelML/av/tree/main/skills/agentic-video-memory Command: npx skills add https://github.com/PixelML/av --skill agentic-video-memory
This skill solves the problem of information silos within video content by indexing video files, making them as searchable and queryable as text documents.
Use the agentic-video-memory skill to ingest the video file meeting.mp4 and then ask what key decisions were made during the discussion.
High-intent search queries and answers about installing and using this skill.
Video files become searchable through multimodal AI models that generate transcriptions, captions, and embeddings. This process indexes the video archive into a database for semantic search and RAG-based question answering with timestamped citations.
RAG-based question answering for video content uses multimodal AI to index transcriptions and captions. You can ask questions about the video archive and receive answers with precise, timestamped citations pointing to the exact moments in the footage.
Yes, you need ffmpeg and a configured AI provider API key to ingest surveillance video and perform temporal reasoning. These dependencies are required to process the footage and index events like falls or crowd gatherings for intelligence analysis.
Yes, you can use semantic search to locate specific moments in meeting recordings. The skill ingests the video and indexes the content, allowing you to find the exact minute a specific product feature or decision was discussed using natural language.
Multimodal video indexing for surveillance intelligence requires ffmpeg and a configured AI provider API key to process video files. Without these dependencies, the system cannot generate the embeddings or perform the temporal reasoning needed to detect events like falls.
barkleesandersEdit raw video footage into polished final.mp4 files via conversational AI.
zsutxzBuild RAG systems integrating vector stores and retrieval strategies.
Greenmamba29Generate and store vector embeddings for semantic search pipelines.
framerslabTranscribe audio files in batches via the Google Cloud Speech-to-Text API.
