feat: remove fllter argument never used

custom_pgvector.py

@@ -292,7 +292,6 @@ class CustomPGVector(VectorStore):
         return self.similarity_search_by_vector(
             embedding=embedding,
             k=k,
-            filter=filter,
         )
 
     def similarity_search_with_score(
@@ -313,7 +312,7 @@ class CustomPGVector(VectorStore):
         """
         embedding = self.embedding_function.embed_query(query)
         docs = self.similarity_search_with_score_by_vector(
-            embedding=embedding, k=k, filter=filter
+            embedding=embedding, k=k
         )
         return docs
 
@@ -335,9 +334,8 @@ class CustomPGVector(VectorStore):
         self,
         embedding: List[float],
         k: int = 4,
-        filter: Optional[dict] = None,
     ) -> List[Tuple[Document, float]]:
-        results = self.__query_collection(embedding=embedding, k=k, filter=filter)
+        results = self.__query_collection(embedding=embedding, k=k)
 
         return self._results_to_docs_and_scores(results)
 
@@ -366,7 +364,6 @@ class CustomPGVector(VectorStore):
         self,
         embedding: List[float],
         k: int = 4,
-        filter: Optional[Dict[str, str]] = None,
     ) -> List[Any]:
         """Query the collection."""
         with Session(self._conn) as session:
@@ -401,7 +398,6 @@ class CustomPGVector(VectorStore):
         self,
         embedding: List[float],
         k: int = 4,
-        filter: Optional[dict] = None,
         **kwargs: Any,
     ) -> List[Document]:
         """Return docs most similar to embedding vector.
@@ -415,7 +411,7 @@ class CustomPGVector(VectorStore):
             List of Documents most similar to the query vector.
         """
         docs_and_scores = self.similarity_search_with_score_by_vector(
-            embedding=embedding, k=k, filter=filter
+            embedding=embedding, k=k
         )
         return _results_to_docs(docs_and_scores)