This blog outlines the development of a live image search functionality capable of querying via natural language. By leveraging CocoIndex for indexing and CLIP ViT-L/14 for generating image embeddings, the system enables effective semantic searches. New files can be added dynamically, ensuring quick processing and indexing. Qdrant is utilized for managing the vectorized data, while FastAPI facilitates the creation of a high-performance API. The flow involves reading images, embedding them, and storing them for efficient retrieval, providing users with an intuitive search experience.
CocoIndex is an ultra performant real-time data transformation framework for AI, enabling seamless indexing of changed files within minutes.
By employing CLIP ViT-L/14, we can effectively understand both images and text, facilitating advanced semantic image searches.
Utilizing Qdrant as a vector database allows us to efficiently store and retrieve embeddings generated from images and search queries.
FastAPI serves as a robust web framework for creating APIs, enhancing the performance of our image search application.
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