A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store
What is the aws-samples/text-embeddings-pipeline-for-rag GitHub project? Description: "A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store". Written in TypeScript. Explain what it does, its main use cases, key features, and who would benefit from using it.
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