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PostgreSQL Vector Database implementation for LangChain Go

langchaingo extension to use pgvector as a vector database for your Go applications. It uses the pgvector-go library along with pgx driver.

You can use this in your LangChain applications as a standalone vector database or more likely, as part of a chain. For example, in a RAG implementation:

    import(
        "github.com/abhirockzz/langchain-go-postgresql-vectorstore/pgvector"
         //...
    )
    func ragToRiches(){
        
        bedrockClaudeLLM, err := claude.New("us-east-1")

        tableName := "test_table"
        textColumnName := "text_data"
        embeddingStoreColumnName := "embedding_data"

        amazonTitanEmbedder, err := titan_embedding.New("us-east-1")

        pgVectorStore, err := pgvector.New(pgConnString, 
                                        tableName, 
                                        embeddingStoreColumnName, 
                                        textColumnName, 
                                        false, 
                                        amazonTitanEmbedder)

        result, err := chains.Run(
            context.Background(),
            chains.NewRetrievalQAFromLLM(
                bedrockClaudeLLM,
                vectorstores.ToRetriever(pgVectorStore, numOfResults),
            ),
            question,
            chains.WithMaxTokens(8091),
        )
    }

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langchain Vector Store implementation based for PostgreSQL pgvector

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