{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/e4a08ca76e0a4667b6d4d0297385be1d\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/e4a08ca76e0a4667b6d4d0297385be1d-00001.gif","duration":215.148,"title":"Exploring Video Chunking and Semantic Search","description":"In this video, I, Manti Kargi, from Tumkongas, demonstrate the process of video chunking and semantic search. I explain how the video is loaded, chunks are stored in the vector database, and relevant metadata is stored in the Postgres database. I also showcase the use of Gemini API for answering questions about the video content. Watch this video to understand the working of video chunking and semantic search and how it can be applied to enhance video editing and retrieval. Action: Watch the video to gain insights into video chunking and semantic search techniques."}