Implementing semantic image search with Amazon Titan and Supabase Vector

Amazon Bedrock is a fully managed service that offers high-performing foundation models for generative AI applications with security and privacy features. Amazon Titan is a family of foundation models for text and image generation. The authors create a Python application using Poetry to get started with Amazon Bedrock and Supabase Vector, which enables image search and reverse image search using the Amazon Titan multimodal model. They demonstrate how to create embeddings for images, create a vector store client, generate embeddings, upsert them into a database, query the collection, and perform an image search from a text query. The application showcases the capabilities of Amazon Bedrock and Supabase Vector in implementing image search with just a few lines of Python code.

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