{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/1a8af684822a43e9b4b2518c406addc6\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/1a8af684822a43e9b4b2518c406addc6-a62aeb08bd78ba86.gif","duration":272.056,"title":"DocuMind AI: End-to-End GenAI Document Chatbot Using LLMs &amp; Vector Search","description":"In this video, I walk you through my project, Document AI, which uses FastAPI for the backend. We handle file uploads and convert documents into text using a document loader. The chat functionality allows users to query relevant information from these documents using a query engine and LLM. The front end features a user-friendly landing page with options for document uploads and voice queries. I encourage viewers to explore the application and provide feedback."}