A library for interfacing with pg_vector for RAG
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Project description
pgvector-rag
A simple library for working with RAG documents using pg_vector in PostgreSQL.
Documents will pass through an optimization stage where the content is converted to markdown, submitted to Anthropic's Sonet 3.5 to optimize the content, and the response is used to a store a conside revision of the document.
OpenAI's text-embedding-3-small is used to generate the embeddings for the
for the document and used to generate the embeddings to compare against in
the database.
Schema is contained in the postgres directory.
Install with pip install pgvector-rag.
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