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https://github.com/james-m-jordan/morphik-core.git
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Speed up multivector store
Co-authored-by: Arnav Agrawal <aa779@cornell.edu>
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@ -181,7 +181,8 @@ class MultiVectorStore(BaseVectorStore):
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"""
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"""
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CREATE OR REPLACE FUNCTION max_sim(document bit[], query bit[]) RETURNS double precision AS $$
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CREATE OR REPLACE FUNCTION max_sim(document bit[], query bit[]) RETURNS double precision AS $$
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WITH queries AS (
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WITH queries AS (
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SELECT row_number() OVER () AS query_number, * FROM (SELECT unnest(query) AS query) AS foo
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SELECT row_number() OVER () AS query_number, *
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FROM (SELECT unnest(query) AS query) AS foo
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),
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),
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documents AS (
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documents AS (
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SELECT unnest(document) AS document
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SELECT unnest(document) AS document
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@ -189,7 +190,8 @@ class MultiVectorStore(BaseVectorStore):
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similarities AS (
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similarities AS (
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SELECT
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SELECT
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query_number,
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query_number,
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1.0 - (bit_count(document # query)::float / greatest(bit_length(query), 1)::float) AS similarity
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1.0 - (bit_count(document # query)::float /
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greatest(bit_length(query), 1)::float) AS similarity
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FROM queries CROSS JOIN documents
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FROM queries CROSS JOIN documents
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),
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),
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max_similarities AS (
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max_similarities AS (
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@ -217,10 +219,6 @@ class MultiVectorStore(BaseVectorStore):
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if isinstance(embeddings, list) and not isinstance(embeddings[0], np.ndarray):
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if isinstance(embeddings, list) and not isinstance(embeddings[0], np.ndarray):
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embeddings = np.array(embeddings)
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embeddings = np.array(embeddings)
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# Add this check to ensure pgvector is registered for the connection
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with self.get_connection() as conn:
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register_vector(conn)
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return [Bit(embedding > 0) for embedding in embeddings]
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return [Bit(embedding > 0) for embedding in embeddings]
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async def store_embeddings(self, chunks: List[DocumentChunk]) -> Tuple[bool, List[str]]:
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async def store_embeddings(self, chunks: List[DocumentChunk]) -> Tuple[bool, List[str]]:
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@ -230,7 +228,7 @@ class MultiVectorStore(BaseVectorStore):
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return True, []
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return True, []
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stored_ids = []
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stored_ids = []
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with self.get_connection() as conn:
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for chunk in chunks:
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for chunk in chunks:
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# Ensure embeddings exist
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# Ensure embeddings exist
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if not hasattr(chunk, "embedding") or chunk.embedding is None:
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if not hasattr(chunk, "embedding") or chunk.embedding is None:
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@ -244,7 +242,7 @@ class MultiVectorStore(BaseVectorStore):
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binary_embeddings = self._binary_quantize(embeddings)
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binary_embeddings = self._binary_quantize(embeddings)
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# Insert into database with retry logic
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# Insert into database with retry logic
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with self.get_connection() as conn:
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conn.execute(
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conn.execute(
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"""
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"""
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INSERT INTO multi_vector_embeddings
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INSERT INTO multi_vector_embeddings
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