-- Revert to the correct vector operator for cosine distance
-- Change from <-> (L2 distance) back to <=> (cosine distance)
-- Drop and recreate the semantic search function with the correct operator
DROP FUNCTION IF EXISTS semantic_search(UUID, vector, FLOAT, INTEGER);
-- Recreate the function with the <=> operator
CREATE OR REPLACE FUNCTION semantic_search(
search_book_id UUID,
query_embedding vector(1536),
similarity_threshold FLOAT DEFAULT 0.01,
max_results INTEGER DEFAULT 20
)
RETURNS TABLE(
chunk_id UUID,
file_id UUID,
file_name TEXT,
content TEXT,
similarity FLOAT,
line_start INTEGER,
line_end INTEGER
)
SECURITY DEFINER
SET search_path = public, extensions
AS $$
BEGIN
RETURN QUERY
SELECT
fc.id as chunk_id,
fc.file_id,
fsi.name as file_name,
fc.content,
(1 - (fc.embedding <=> query_embedding)) as similarity,
fc.line_start,
fc.line_end
FROM file_chunks fc
JOIN file_system_items fsi ON fc.file_id = fsi.id
WHERE fc.book_id = search_book_id
AND (1 - (fc.embedding <=> query_embedding)) > similarity_threshold
ORDER BY fc.embedding <=> query_embedding
LIMIT max_results;
END;
$$ LANGUAGE plpgsql;
-- Also update the debug function to use the correct operator
DROP FUNCTION IF EXISTS debug_similarity(UUID, vector);
CREATE OR REPLACE FUNCTION debug_similarity(
search_book_id UUID,
query_embedding vector(1536)
)
RETURNS TABLE (
chunk_id UUID,
file_name TEXT,
content_preview TEXT,
similarity FLOAT,
distance FLOAT
)
SECURITY DEFINER
SET search_path = public, extensions
AS $$
BEGIN
RETURN QUERY
SELECT
fc.id as chunk_id,
fsi.name as file_name,
LEFT(fc.content, 100) as content_preview,
(1 - (fc.embedding <=> query_embedding)) as similarity,
(fc.embedding <=> query_embedding) as distance
FROM file_chunks fc
JOIN file_system_items fsi ON fc.file_id = fsi.id
WHERE fc.book_id = search_book_id
ORDER BY distance ASC;
END;
$$ LANGUAGE plpgsql;