On the Subject of Neural V RAG
• Developed an AI-powered video search platform using React.js and Python Flask API that enables users to search videos based on scenes, objects, or specific content.
• Built the core AI system using AI Agent architecture combined with RAG (Retrieval-Augmented Generation) techniques for intelligent and context-aware video retrieval.
• Implemented vector embedding search with PGVector to analyze video content and return relevant videos with accurate timestamps/timeframes.
• Designed and optimized backend APIs for video indexing, semantic search, and fast retrieval of large-scale video data.
• Created a scalable embedding-based database system capable of efficiently storing, processing, and searching high-dimensional video embeddings.
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Technologies Used