CheeYung's picture
Update basic agent framework
7d88664
-- 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 $$
#variable_conflict use_column
begin
return query
select
id,
content,
metadata,
1 - (documents.embedding <=> query_embedding) as similarity
from documents
where metadata @> filter
order by documents.embedding <=> query_embedding
limit match_count;
end;
$$;