{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/9b112343b0104392b47bd8c1c85b1826\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/9b112343b0104392b47bd8c1c85b1826-b38086d9b825f366.gif","duration":115.998,"title":"Setting Up VectorDBQ: A Guide to the Semantic Search Engine","description":"Hi, I'm Ace, and in this video, I walk you through setting up VectorDBQ, a semantic search engine I built for a technical task requested by Stack.ai. You can find the project on GitHub, where I recommend checking out the documentation to get started. After signing up and configuring your environment variables, including the cohere API key, you can build and run the Docker container. I also added a simple UI for you to experiment with, allowing you to search and add chunks in real time. Please follow the steps I outlined to successfully set up the project."}