-- Drop old function
drop function if exists match_documents (vector(1536), int);

-- Create a table to store your documents
    create table documents (
        id bigserial primary key,
        content text, -- corresponds to Document.pageContent
        metadata jsonb, -- corresponds to Document.metadata
        embedding vector(768) -- 768 works for Gemini embeddings, change if needed
    );

-- Create a function to search for documents
    create function match_documents (
            query_embedding vector(768),
            match_count int DEFAULT null,
            filter jsonb DEFAULT '{}'
        ) returns table (
            id bigint,
            content text,
            metadata jsonb,
            similarity float
        )
        language plpgsql
        as $$
        #variable_conflict use_column
        begin
        return query
        select
            id,
            content,
            metadata,
            1 - (documents.embedding <=> query_embedding) as similarity
        from documents
        where metadata @> filter
        order by documents.embedding <=> query_embedding
        limit match_count;
        end;
        $$;