More type hints

Author: sjrl

integrations/qdrant/src/haystack_integrations/components/retrievers/qdrant/retriever.py

@@ -46,7 +46,7 @@ def __init__(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> None:
         """
         Create a QdrantEmbeddingRetriever component.
 
@@ -136,7 +136,7 @@ def run(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Run the Embedding Retriever on the given input data.
 
@@ -180,7 +180,7 @@ async def run_async(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Asynchronously run the Embedding Retriever on the given input data.
 
@@ -252,7 +252,7 @@ def __init__(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> None:
         """
         Create a QdrantSparseEmbeddingRetriever component.
 
@@ -342,7 +342,7 @@ def run(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Run the Sparse Embedding Retriever on the given input data.
 
@@ -391,7 +391,7 @@ async def run_async(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Asynchronously run the Sparse Embedding Retriever on the given input data.
 
@@ -473,7 +473,7 @@ def __init__(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> None:
         """
         Create a QdrantHybridRetriever component.
 
@@ -557,7 +557,7 @@ def run(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Run the Sparse Embedding Retriever on the given input data.
 
@@ -606,7 +606,7 @@ async def run_async(
         score_threshold: Optional[float] = None,
         group_by: Optional[str] = None,
         group_size: Optional[int] = None,
-    ):
+    ) -> Dict[str, List[Document]]:
         """
         Asynchronously run the Sparse Embedding Retriever on the given input data.
 

integrations/qdrant/src/haystack_integrations/document_stores/qdrant/filters.py

@@ -138,10 +138,10 @@ def convert_filters_to_qdrant(
 
 
 def build_filters_for_repeated_operators(
-    must_clauses,
-    should_clauses,
-    must_not_clauses,
-    qdrant_filter,
+    must_clauses: List,
+    should_clauses: List,
+    must_not_clauses: List,
+    qdrant_filter: List[models.Filter],
 ) -> List[models.Filter]:
     """
     Flattens the nested lists of clauses by creating separate Filters for each clause of a logical operator.

integrations/qdrant/src/haystack_integrations/document_stores/qdrant/migrate_to_sparse.py

@@ -11,7 +11,7 @@
 logger.setLevel(python_logging.INFO)
 
 
-def migrate_to_sparse_embeddings_support(old_document_store: QdrantDocumentStore, new_index: str):
+def migrate_to_sparse_embeddings_support(old_document_store: QdrantDocumentStore, new_index: str) -> None:
     """
     Utility function to migrate an existing `QdrantDocumentStore` to a new one with support for sparse embeddings.