diff --git a/docs-website/reference/integrations-api/qdrant.md b/docs-website/reference/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference/integrations-api/qdrant.md
+++ b/docs-website/reference/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.18/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.19/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.20/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.21/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.22/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.23/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.24/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.25/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.26/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.27/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.28/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.29/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.30/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-2.31/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-3.0/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-3.0/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-3.0/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-3.0/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-3.1/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-3.1/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-3.1/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-3.1/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python
diff --git a/docs-website/reference_versioned_docs/version-3.2-unstable/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-3.2-unstable/integrations-api/qdrant.md
new file mode 100644
index 0000000000..7a61da3c50
--- /dev/null
+++ b/docs-website/reference_versioned_docs/version-3.2-unstable/integrations-api/qdrant.md
@@ -0,0 +1,1453 @@
+---
+title: "Qdrant"
+id: integrations-qdrant
+description: "Qdrant integration for Haystack"
+slug: "/integrations-qdrant"
+---
+
+
+## haystack_integrations.components.retrievers.qdrant.retriever
+
+### QdrantEmbeddingRetriever
+
+A component for retrieving documents from an QdrantDocumentStore using dense vectors.
+
+Usage example:
+
+```python
+from haystack.dataclasses import Document
+from haystack_integrations.components.retrievers.qdrant import QdrantEmbeddingRetriever
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+
+document_store = QdrantDocumentStore(
+    ":memory:",
+    recreate_index=True,
+    return_embedding=True,
+)
+
+document_store.write_documents([Document(content="test", embedding=[0.5]*768)])
+
+retriever = QdrantEmbeddingRetriever(document_store=document_store)
+
+# using a fake vector to keep the example simple
+retriever.run(query_embedding=[0.1]*768)
+```
+
+#### __init__
+
+```python
+__init__(
+    document_store: QdrantDocumentStore,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int = 10,
+    scale_score: bool = False,
+    return_embedding: bool = False,
+    filter_policy: str | FilterPolicy = FilterPolicy.REPLACE,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> None
+```
+
+Create a QdrantEmbeddingRetriever component.
+
+**Parameters:**
+
+- **document_store** (<code>QdrantDocumentStore</code>) – An instance of QdrantDocumentStore.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – A dictionary with filters to narrow down the search space.
+- **top_k** (<code>int</code>) – The maximum number of documents to retrieve. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool</code>) – Whether to return the embedding of the retrieved Documents.
+- **filter_policy** (<code>str | FilterPolicy</code>) – Policy to determine how filters are applied.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the `similarity` function specified in the Document Store.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Raises:**
+
+- <code>ValueError</code> – If `document_store` is not an instance of `QdrantDocumentStore`.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> QdrantEmbeddingRetriever
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>QdrantEmbeddingRetriever</code> – Deserialized component.
+
+#### close
+
+```python
+close() -> None
+```
+
+Release the synchronous resources of the underlying Document Store.
+
+#### close_async
+
+```python
+close_async() -> None
+```
+
+Release the asynchronous resources of the underlying Document Store.
+
+#### run
+
+```python
+run(
+    query_embedding: list[float],
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    scale_score: bool | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Run the Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_embedding** (<code>list\[float\]</code>) – Embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – A dictionary with filters to narrow down the search space.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool | None</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+#### run_async
+
+```python
+run_async(
+    query_embedding: list[float],
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    scale_score: bool | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Asynchronously run the Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_embedding** (<code>list\[float\]</code>) – Embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – A dictionary with filters to narrow down the search space.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool | None</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+### QdrantSparseEmbeddingRetriever
+
+A component for retrieving documents from an QdrantDocumentStore using sparse vectors.
+
+Usage example:
+
+```python
+from haystack_integrations.components.retrievers.qdrant import QdrantSparseEmbeddingRetriever
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+from haystack.dataclasses import Document, SparseEmbedding
+
+document_store = QdrantDocumentStore(
+    ":memory:",
+    use_sparse_embeddings=True,
+    recreate_index=True,
+    return_embedding=True,
+)
+
+doc = Document(content="test", sparse_embedding=SparseEmbedding(indices=[0, 3, 5], values=[0.1, 0.5, 0.12]))
+document_store.write_documents([doc])
+
+retriever = QdrantSparseEmbeddingRetriever(document_store=document_store)
+sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
+retriever.run(query_sparse_embedding=sparse_embedding)
+```
+
+#### __init__
+
+```python
+__init__(
+    document_store: QdrantDocumentStore,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int = 10,
+    scale_score: bool = False,
+    return_embedding: bool = False,
+    filter_policy: str | FilterPolicy = FilterPolicy.REPLACE,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> None
+```
+
+Create a QdrantSparseEmbeddingRetriever component.
+
+**Parameters:**
+
+- **document_store** (<code>QdrantDocumentStore</code>) – An instance of QdrantDocumentStore.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – A dictionary with filters to narrow down the search space.
+- **top_k** (<code>int</code>) – The maximum number of documents to retrieve. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool</code>) – Whether to return the sparse embedding of the retrieved Documents.
+- **filter_policy** (<code>str | FilterPolicy</code>) – Policy to determine how filters are applied. Defaults to "replace".
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Raises:**
+
+- <code>ValueError</code> – If `document_store` is not an instance of `QdrantDocumentStore`.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> QdrantSparseEmbeddingRetriever
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>QdrantSparseEmbeddingRetriever</code> – Deserialized component.
+
+#### close
+
+```python
+close() -> None
+```
+
+Release the synchronous resources of the underlying Document Store.
+
+#### close_async
+
+```python
+close_async() -> None
+```
+
+Release the asynchronous resources of the underlying Document Store.
+
+#### run
+
+```python
+run(
+    query_sparse_embedding: SparseEmbedding,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    scale_score: bool | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Run the Sparse Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_sparse_embedding** (<code>SparseEmbedding</code>) – Sparse Embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+  the `filter_policy` chosen at retriever initialization. See init method docstring for more
+  details.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool | None</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+#### run_async
+
+```python
+run_async(
+    query_sparse_embedding: SparseEmbedding,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    scale_score: bool | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+) -> dict[str, list[Document]]
+```
+
+Asynchronously run the Sparse Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_sparse_embedding** (<code>SparseEmbedding</code>) – Sparse Embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+  the `filter_policy` chosen at retriever initialization. See init method docstring for more
+  details.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **scale_score** (<code>bool | None</code>) – Whether to scale the scores of the retrieved documents or not.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+### QdrantHybridRetriever
+
+A component for retrieving documents from a QdrantDocumentStore using both dense and sparse vectors.
+
+Fuses the results using Reciprocal Rank Fusion.
+
+Usage example:
+
+```python
+from haystack_integrations.components.retrievers.qdrant import QdrantHybridRetriever
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+from haystack.dataclasses import Document, SparseEmbedding
+
+document_store = QdrantDocumentStore(
+    ":memory:",
+    use_sparse_embeddings=True,
+    recreate_index=True,
+    return_embedding=True,
+    wait_result_from_api=True,
+)
+
+doc = Document(content="test",
+               embedding=[0.5]*768,
+               sparse_embedding=SparseEmbedding(indices=[0, 3, 5], values=[0.1, 0.5, 0.12]))
+
+document_store.write_documents([doc])
+
+retriever = QdrantHybridRetriever(document_store=document_store)
+embedding = [0.1]*768
+sparse_embedding = SparseEmbedding(indices=[0, 1, 2, 3], values=[0.1, 0.8, 0.05, 0.33])
+retriever.run(query_embedding=embedding, query_sparse_embedding=sparse_embedding)
+```
+
+#### __init__
+
+```python
+__init__(
+    document_store: QdrantDocumentStore,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int = 10,
+    return_embedding: bool = False,
+    filter_policy: str | FilterPolicy = FilterPolicy.REPLACE,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+    rrf_k: int | None = None,
+    rrf_weights: list[float] | None = None,
+) -> None
+```
+
+Create a QdrantHybridRetriever component.
+
+**Parameters:**
+
+- **document_store** (<code>QdrantDocumentStore</code>) – An instance of QdrantDocumentStore.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – A dictionary with filters to narrow down the search space.
+- **top_k** (<code>int</code>) – The maximum number of documents to retrieve. If using `group_by` parameters, maximum number of
+  groups to return.
+- **return_embedding** (<code>bool</code>) – Whether to return the embeddings of the retrieved Documents.
+- **filter_policy** (<code>str | FilterPolicy</code>) – Policy to determine how filters are applied.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+- **rrf_k** (<code>int | None</code>) – The `k` constant for Reciprocal Rank Fusion. Controls ranking formula smoothing.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-constant-k.
+  Requires Qdrant server >= 1.16.0.
+- **rrf_weights** (<code>list\[float\] | None</code>) – Per-prefetch weights for RRF fusion — `[sparse_weight, dense_weight]`.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-weights.
+  Requires Qdrant server >= 1.17.0.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'document_store' is not an instance of QdrantDocumentStore.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> QdrantHybridRetriever
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – Dictionary to deserialize from.
+
+**Returns:**
+
+- <code>QdrantHybridRetriever</code> – Deserialized component.
+
+#### close
+
+```python
+close() -> None
+```
+
+Release the synchronous resources of the underlying Document Store.
+
+#### close_async
+
+```python
+close_async() -> None
+```
+
+Release the asynchronous resources of the underlying Document Store.
+
+#### run
+
+```python
+run(
+    query_embedding: list[float],
+    query_sparse_embedding: SparseEmbedding,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+    rrf_k: int | None = None,
+    rrf_weights: list[float] | None = None,
+) -> dict[str, list[Document]]
+```
+
+Run the Sparse Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_embedding** (<code>list\[float\]</code>) – Dense embedding of the query.
+- **query_sparse_embedding** (<code>SparseEmbedding</code>) – Sparse embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+  the `filter_policy` chosen at retriever initialization. See init method docstring for more
+  details.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+- **rrf_k** (<code>int | None</code>) – Override the init-time `rrf_k` for this run.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-constant-k.
+  Requires Qdrant server >= 1.16.0.
+- **rrf_weights** (<code>list\[float\] | None</code>) – Override the init-time `rrf_weights` for this run.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-weights.
+  Requires Qdrant server >= 1.17.0.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+#### run_async
+
+```python
+run_async(
+    query_embedding: list[float],
+    query_sparse_embedding: SparseEmbedding,
+    filters: dict[str, Any] | models.Filter | None = None,
+    top_k: int | None = None,
+    return_embedding: bool | None = None,
+    score_threshold: float | None = None,
+    group_by: str | None = None,
+    group_size: int | None = None,
+    rrf_k: int | None = None,
+    rrf_weights: list[float] | None = None,
+) -> dict[str, list[Document]]
+```
+
+Asynchronously run the Sparse Embedding Retriever on the given input data.
+
+**Parameters:**
+
+- **query_embedding** (<code>list\[float\]</code>) – Dense embedding of the query.
+- **query_sparse_embedding** (<code>SparseEmbedding</code>) – Sparse embedding of the query.
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+  the `filter_policy` chosen at retriever initialization. See init method docstring for more
+  details.
+- **top_k** (<code>int | None</code>) – The maximum number of documents to return. If using `group_by` parameters, maximum number of
+  groups to return.
+- **return_embedding** (<code>bool | None</code>) – Whether to return the embedding of the retrieved Documents.
+- **score_threshold** (<code>float | None</code>) – A minimal score threshold for the result.
+  Score of the returned result might be higher or smaller than the threshold
+  depending on the Distance function used.
+  E.g. for cosine similarity only higher scores will be returned.
+- **group_by** (<code>str | None</code>) – Payload field to group by, must be a string or number field. If the field contains more than 1
+  value, all values will be used for grouping. One point can be in multiple groups.
+- **group_size** (<code>int | None</code>) – Maximum amount of points to return per group. Default is 3.
+- **rrf_k** (<code>int | None</code>) – Override the init-time `rrf_k` for this run.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-constant-k.
+  Requires Qdrant server >= 1.16.0.
+- **rrf_weights** (<code>list\[float\] | None</code>) – Override the init-time `rrf_weights` for this run.
+  See https://qdrant.tech/documentation/search/hybrid-queries/#setting-rrf-weights.
+  Requires Qdrant server >= 1.17.0.
+
+**Returns:**
+
+- <code>dict\[str, list\[Document\]\]</code> – The retrieved documents.
+
+**Raises:**
+
+- <code>ValueError</code> – If 'filter_policy' is set to 'MERGE' and 'filters' is a native Qdrant filter.
+
+## haystack_integrations.document_stores.qdrant.document_store
+
+### get_batches_from_generator
+
+```python
+get_batches_from_generator(iterable: list, n: int) -> Generator
+```
+
+Batch elements of an iterable into fixed-length chunks or blocks.
+
+### QdrantDocumentStore
+
+A QdrantDocumentStore implementation that you can use with any Qdrant instance.
+
+Supports in-memory, disk-persisted, Docker-based, and Qdrant Cloud Cluster deployments.
+
+Usage example by creating an in-memory instance:
+
+```python
+from haystack.dataclasses.document import Document
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+
+document_store = QdrantDocumentStore(
+    ":memory:",
+    recreate_index=True,
+    embedding_dim=5
+)
+document_store.write_documents([
+    Document(content="This is first", embedding=[0.0]*5),
+    Document(content="This is second", embedding=[0.1, 0.2, 0.3, 0.4, 0.5])
+])
+```
+
+Usage example with Qdrant Cloud:
+
+```python
+from haystack.dataclasses.document import Document
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+
+document_store = QdrantDocumentStore(
+        url="https://xxxxxx-xxxxx-xxxxx-xxxx-xxxxxxxxx.us-east.aws.cloud.qdrant.io:6333",
+    api_key="<your-api-key>",
+)
+document_store.write_documents([
+    Document(content="This is first", embedding=[0.0]*5),
+    Document(content="This is second", embedding=[0.1, 0.2, 0.3, 0.4, 0.5])
+])
+```
+
+#### __init__
+
+```python
+__init__(
+    location: str | None = None,
+    url: str | None = None,
+    port: int = 6333,
+    grpc_port: int = 6334,
+    prefer_grpc: bool = False,
+    https: bool | None = None,
+    api_key: Secret | None = None,
+    prefix: str | None = None,
+    timeout: int | None = None,
+    host: str | None = None,
+    path: str | None = None,
+    force_disable_check_same_thread: bool = False,
+    index: str = "Document",
+    embedding_dim: int = 768,
+    on_disk: bool = False,
+    use_sparse_embeddings: bool = False,
+    sparse_idf: bool = False,
+    similarity: str = "cosine",
+    return_embedding: bool = False,
+    progress_bar: bool = True,
+    recreate_index: bool = False,
+    shard_number: int | None = None,
+    replication_factor: int | None = None,
+    write_consistency_factor: int | None = None,
+    on_disk_payload: bool | None = None,
+    hnsw_config: dict | None = None,
+    optimizers_config: dict | None = None,
+    wal_config: dict | None = None,
+    quantization_config: dict | None = None,
+    wait_result_from_api: bool = True,
+    metadata: dict | None = None,
+    write_batch_size: int = 100,
+    scroll_size: int = 10000,
+    payload_fields_to_index: list[dict] | None = None,
+) -> None
+```
+
+Initializes a QdrantDocumentStore.
+
+**Parameters:**
+
+- **location** (<code>str | None</code>) – If `":memory:"` - use in-memory Qdrant instance.
+  If `str` - use it as a URL parameter.
+  If `None` - use default values for host and port.
+- **url** (<code>str | None</code>) – Either host or str of `Optional[scheme], host, Optional[port], Optional[prefix]`.
+- **port** (<code>int</code>) – Port of the REST API interface.
+- **grpc_port** (<code>int</code>) – Port of the gRPC interface.
+- **prefer_grpc** (<code>bool</code>) – If `True` - use gRPC interface whenever possible in custom methods.
+- **https** (<code>bool | None</code>) – If `True` - use HTTPS(SSL) protocol.
+- **api_key** (<code>Secret | None</code>) – API key for authentication in Qdrant Cloud.
+- **prefix** (<code>str | None</code>) – If not `None` - add prefix to the REST URL path.
+  Example: service/v1 will result in http://localhost:6333/service/v1/{qdrant-endpoint}
+  for REST API.
+- **timeout** (<code>int | None</code>) – Timeout for REST and gRPC API requests.
+- **host** (<code>str | None</code>) – Host name of Qdrant service. If ùrl`and`host`are`None`, set to `localhost\`.
+- **path** (<code>str | None</code>) – Persistence path for QdrantLocal.
+- **force_disable_check_same_thread** (<code>bool</code>) – For QdrantLocal, force disable check_same_thread.
+  Only use this if you can guarantee that you can resolve the thread safety outside QdrantClient.
+- **index** (<code>str</code>) – Name of the index.
+- **embedding_dim** (<code>int</code>) – Dimension of the embeddings.
+- **on_disk** (<code>bool</code>) – Whether to store the collection on disk.
+- **use_sparse_embeddings** (<code>bool</code>) – If set to `True`, enables support for sparse embeddings.
+- **sparse_idf** (<code>bool</code>) – If set to `True`, computes the Inverse Document Frequency (IDF) when using sparse embeddings.
+  It is required to use techniques like BM42. It is ignored if `use_sparse_embeddings` is `False`.
+- **similarity** (<code>str</code>) – The similarity metric to use.
+- **return_embedding** (<code>bool</code>) – Whether to return embeddings in the search results.
+- **progress_bar** (<code>bool</code>) – Whether to show a progress bar or not.
+- **recreate_index** (<code>bool</code>) – Whether to recreate the index.
+- **shard_number** (<code>int | None</code>) – Number of shards in the collection.
+- **replication_factor** (<code>int | None</code>) – Replication factor for the collection.
+  Defines how many copies of each shard will be created. Effective only in distributed mode.
+- **write_consistency_factor** (<code>int | None</code>) – Write consistency factor for the collection. Minimum value is 1.
+  Defines how many replicas should apply to the operation for it to be considered successful.
+  Increasing this number makes the collection more resilient to inconsistencies
+  but will cause failures if not enough replicas are available.
+  Effective only in distributed mode.
+- **on_disk_payload** (<code>bool | None</code>) – If `True`, the point's payload will not be stored in memory and
+  will be read from the disk every time it is requested.
+  This setting saves RAM by slightly increasing response time.
+  Note: indexed payload values remain in RAM.
+- **hnsw_config** (<code>dict | None</code>) – Params for HNSW index.
+- **optimizers_config** (<code>dict | None</code>) – Params for optimizer.
+- **wal_config** (<code>dict | None</code>) – Params for Write-Ahead-Log.
+- **quantization_config** (<code>dict | None</code>) – Params for quantization. If `None`, quantization will be disabled.
+- **wait_result_from_api** (<code>bool</code>) – Whether to wait for the result from the API after each request.
+- **metadata** (<code>dict | None</code>) – Additional metadata to include with the documents.
+- **write_batch_size** (<code>int</code>) – The batch size for writing documents.
+- **scroll_size** (<code>int</code>) – The scroll size for reading documents.
+- **payload_fields_to_index** (<code>list\[dict\] | None</code>) – List of payload fields to index.
+
+#### close
+
+```python
+close() -> None
+```
+
+Release the associated synchronous resources.
+
+#### close_async
+
+```python
+close_async() -> None
+```
+
+Release the associated asynchronous resources.
+
+#### count_documents
+
+```python
+count_documents() -> int
+```
+
+Returns the number of documents present in the Document Store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
+#### count_documents_async
+
+```python
+count_documents_async() -> int
+```
+
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
+#### filter_documents
+
+```python
+filter_documents(
+    filters: dict[str, Any] | rest.Filter | None = None,
+) -> list[Document]
+```
+
+Returns the documents that match the provided filters.
+
+For a detailed specification of the filters, refer to the
+[documentation](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\] | Filter | None</code>) – The filters to apply to the document list.
+
+**Returns:**
+
+- <code>list\[Document\]</code> – A list of documents that match the given filters.
+
+#### filter_documents_async
+
+```python
+filter_documents_async(
+    filters: dict[str, Any] | rest.Filter | None = None,
+) -> list[Document]
+```
+
+Asynchronously returns the documents that match the provided filters.
+
+#### write_documents
+
+```python
+write_documents(
+    documents: list[Document], policy: DuplicatePolicy = DuplicatePolicy.FAIL
+) -> int
+```
+
+Writes documents to Qdrant using the specified policy.
+
+The QdrantDocumentStore can handle duplicate documents based on the given policy.
+The available policies are:
+
+- `FAIL`: The operation will raise an error if any document already exists.
+- `OVERWRITE`: Existing documents will be overwritten with the new ones.
+- `SKIP`: Existing documents will be skipped, and only new documents will be added.
+
+**Parameters:**
+
+- **documents** (<code>list\[Document\]</code>) – A list of Document objects to write to Qdrant.
+- **policy** (<code>DuplicatePolicy</code>) – The policy for handling duplicate documents.
+
+**Returns:**
+
+- <code>int</code> – The number of documents written to the document store.
+
+#### write_documents_async
+
+```python
+write_documents_async(
+    documents: list[Document], policy: DuplicatePolicy = DuplicatePolicy.FAIL
+) -> int
+```
+
+Asynchronously writes documents to Qdrant using the specified policy.
+
+The QdrantDocumentStore can handle duplicate documents based on the given policy.
+The available policies are:
+
+- `FAIL`: The operation will raise an error if any document already exists.
+- `OVERWRITE`: Existing documents will be overwritten with the new ones.
+- `SKIP`: Existing documents will be skipped, and only new documents will be added.
+
+**Parameters:**
+
+- **documents** (<code>list\[Document\]</code>) – A list of Document objects to write to Qdrant.
+- **policy** (<code>DuplicatePolicy</code>) – The policy for handling duplicate documents.
+
+**Returns:**
+
+- <code>int</code> – The number of documents written to the document store.
+
+#### delete_documents
+
+```python
+delete_documents(document_ids: list[str]) -> None
+```
+
+Deletes documents that match the provided `document_ids` from the document store.
+
+**Parameters:**
+
+- **document_ids** (<code>list\[str\]</code>) – the document ids to delete
+
+#### delete_documents_async
+
+```python
+delete_documents_async(document_ids: list[str]) -> None
+```
+
+Asynchronously deletes documents that match the provided `document_ids` from the document store.
+
+**Parameters:**
+
+- **document_ids** (<code>list\[str\]</code>) – the document ids to delete
+
+#### delete_by_filter
+
+```python
+delete_by_filter(filters: dict[str, Any]) -> int
+```
+
+Deletes all documents that match the provided filters.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to select documents for deletion.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>int</code> – The number of documents deleted.
+
+#### delete_by_filter_async
+
+```python
+delete_by_filter_async(filters: dict[str, Any]) -> int
+```
+
+Asynchronously deletes all documents that match the provided filters.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to select documents for deletion.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>int</code> – The number of documents deleted.
+
+#### update_by_filter
+
+```python
+update_by_filter(filters: dict[str, Any], meta: dict[str, Any]) -> int
+```
+
+Updates the metadata of all documents that match the provided filters.
+
+**Note**: This operation is not atomic. Documents matching the filter are fetched first,
+then updated. If documents are modified between the fetch and update operations,
+those changes may be lost.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to select documents for updating.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+- **meta** (<code>dict\[str, Any\]</code>) – The metadata fields to update. This will be merged with existing metadata.
+
+**Returns:**
+
+- <code>int</code> – The number of documents updated.
+
+#### update_by_filter_async
+
+```python
+update_by_filter_async(filters: dict[str, Any], meta: dict[str, Any]) -> int
+```
+
+Asynchronously updates the metadata of all documents that match the provided filters.
+
+**Note**: This operation is not atomic. Documents matching the filter are fetched first,
+then updated. If documents are modified between the fetch and update operations,
+those changes may be lost.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to select documents for updating.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+- **meta** (<code>dict\[str, Any\]</code>) – The metadata fields to update. This will be merged with existing metadata.
+
+**Returns:**
+
+- <code>int</code> – The number of documents updated.
+
+#### delete_all_documents
+
+```python
+delete_all_documents(recreate_index: bool = False) -> None
+```
+
+Deletes all documents from the document store.
+
+**Parameters:**
+
+- **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
+#### delete_all_documents_async
+
+```python
+delete_all_documents_async(recreate_index: bool = False) -> None
+```
+
+Asynchronously deletes all documents from the document store.
+
+**Parameters:**
+
+- **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
+#### count_documents_by_filter
+
+```python
+count_documents_by_filter(filters: dict[str, Any]) -> int
+```
+
+Returns the number of documents that match the provided filters.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to count documents.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>int</code> – The number of documents that match the filters.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
+#### count_documents_by_filter_async
+
+```python
+count_documents_by_filter_async(filters: dict[str, Any]) -> int
+```
+
+Asynchronously returns the number of documents that match the provided filters.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to apply to select documents for counting.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>int</code> – The number of documents that match the filters.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
+#### get_metadata_fields_info
+
+```python
+get_metadata_fields_info() -> dict[str, dict[str, str]]
+```
+
+Returns the information about the metadata fields in the collection.
+
+Since Qdrant may not have a payload schema for unindexed metadata,
+this method scrolls through documents to infer field types from
+payload["meta"].
+
+**Returns:**
+
+- <code>dict\[str, dict\[str, str\]\]</code> – A dictionary mapping field names to their type information e.g.:
+
+```python
+{"category": {"type": "keyword"}, "priority": {"type": "long"}}
+```
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
+#### get_metadata_fields_info_async
+
+```python
+get_metadata_fields_info_async() -> dict[str, dict[str, str]]
+```
+
+Asynchronously returns the information about the metadata fields in the collection.
+
+Since Qdrant may not have a payload schema for unindexed metadata,
+this method scrolls through documents to infer field types from
+payload["meta"].
+
+**Returns:**
+
+- <code>dict\[str, dict\[str, str\]\]</code> – A dictionary mapping field names to their type information e.g.:
+
+```python
+{"category": {"type": "keyword"}, "priority": {"type": "long"}}
+```
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
+#### get_metadata_field_min_max
+
+```python
+get_metadata_field_min_max(metadata_field: str) -> dict[str, Any]
+```
+
+Returns the minimum and maximum values for the given metadata field.
+
+**Parameters:**
+
+- **metadata_field** (<code>str</code>) – The metadata field key (inside `meta`) to get the minimum and maximum values for.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – A dictionary with the keys "min" and "max", where each value is the minimum or maximum value of the
+  metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
+  the field.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
+#### get_metadata_field_min_max_async
+
+```python
+get_metadata_field_min_max_async(metadata_field: str) -> dict[str, Any]
+```
+
+Asynchronously returns the minimum and maximum values for the given metadata field.
+
+**Parameters:**
+
+- **metadata_field** (<code>str</code>) – The metadata field key (inside `meta`) to get the minimum and maximum values for.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – A dictionary with the keys "min" and "max", where each value is the minimum or maximum value of the
+  metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
+  the field.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
+#### count_unique_metadata_by_filter
+
+```python
+count_unique_metadata_by_filter(
+    filters: dict[str, Any], metadata_fields: list[str]
+) -> dict[str, int]
+```
+
+Returns the number of unique values for each specified metadata field among documents that match the filters.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to restrict the documents considered.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+- **metadata_fields** (<code>list\[str\]</code>) – List of metadata field keys (inside `meta`) to count unique values for.
+
+**Returns:**
+
+- <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
+  documents.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
+#### count_unique_metadata_by_filter_async
+
+```python
+count_unique_metadata_by_filter_async(
+    filters: dict[str, Any], metadata_fields: list[str]
+) -> dict[str, int]
+```
+
+Asynchronously returns the number of unique values for each specified metadata field among documents.
+
+Only documents that match the filters are considered.
+
+**Parameters:**
+
+- **filters** (<code>dict\[str, Any\]</code>) – The filters to restrict the documents considered.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+- **metadata_fields** (<code>list\[str\]</code>) – List of metadata field keys (inside `meta`) to count unique values for.
+
+**Returns:**
+
+- <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
+  documents.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
+#### get_metadata_field_unique_values
+
+```python
+get_metadata_field_unique_values(
+    metadata_field: str,
+    search_term: str | None = None,
+    from_: int = 0,
+    size: int = 10,
+    filters: dict[str, Any] | None = None,
+) -> tuple[list[Any], int]
+```
+
+Returns unique values for a metadata field, with optional filters, search term and pagination.
+
+Unique values are sorted by string representation, then by type name, before pagination is applied.
+
+**Note**: This operation can be expensive for metadata fields with many unique values, since all
+matching documents must be scrolled through to compute the total count.
+
+**Parameters:**
+
+- **metadata_field** (<code>str</code>) – The metadata field key (inside `meta`) to get unique values for.
+- **search_term** (<code>str | None</code>) – Optional case-insensitive substring filter applied to the metadata field's own value.
+- **from\_** (<code>int</code>) – The offset for pagination (0-based). Defaults to 0.
+- **size** (<code>int</code>) – The maximum number of unique values to return. Defaults to 10.
+- **filters** (<code>dict\[str, Any\] | None</code>) – Optional filters to restrict the documents considered.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
+#### get_metadata_field_unique_values_async
+
+```python
+get_metadata_field_unique_values_async(
+    metadata_field: str,
+    search_term: str | None = None,
+    from_: int = 0,
+    size: int = 10,
+    filters: dict[str, Any] | None = None,
+) -> tuple[list[Any], int]
+```
+
+Asynchronously returns unique values for a metadata field, with optional filters, search term and pagination.
+
+Unique values are sorted by string representation, then by type name, before pagination is applied.
+
+**Note**: This operation can be expensive for metadata fields with many unique values, since all
+matching documents must be scrolled through to compute the total count.
+
+**Parameters:**
+
+- **metadata_field** (<code>str</code>) – The metadata field key (inside `meta`) to get unique values for.
+- **search_term** (<code>str | None</code>) – Optional case-insensitive substring filter applied to the metadata field's own value.
+- **from\_** (<code>int</code>) – The offset for pagination (0-based). Defaults to 0.
+- **size** (<code>int</code>) – The maximum number of unique values to return. Defaults to 10.
+- **filters** (<code>dict\[str, Any\] | None</code>) – Optional filters to restrict the documents considered.
+  For filter syntax, see [Haystack metadata filtering](https://docs.haystack.deepset.ai/docs/metadata-filtering)
+
+**Returns:**
+
+- <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> QdrantDocumentStore
+```
+
+Deserializes the component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – The dictionary to deserialize from.
+
+**Returns:**
+
+- <code>QdrantDocumentStore</code> – The deserialized component.
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – Dictionary with serialized data.
+
+#### get_documents_by_id
+
+```python
+get_documents_by_id(ids: list[str]) -> list[Document]
+```
+
+Retrieves documents from Qdrant by their IDs.
+
+**Parameters:**
+
+- **ids** (<code>list\[str\]</code>) – A list of document IDs to retrieve.
+
+**Returns:**
+
+- <code>list\[Document\]</code> – A list of documents.
+
+#### get_documents_by_id_async
+
+```python
+get_documents_by_id_async(ids: list[str]) -> list[Document]
+```
+
+Retrieves documents from Qdrant by their IDs.
+
+**Parameters:**
+
+- **ids** (<code>list\[str\]</code>) – A list of document IDs to retrieve.
+
+**Returns:**
+
+- <code>list\[Document\]</code> – A list of documents.
+
+#### get_distance
+
+```python
+get_distance(similarity: str) -> rest.Distance
+```
+
+Retrieves the distance metric for the specified similarity measure.
+
+**Parameters:**
+
+- **similarity** (<code>str</code>) – The similarity measure to retrieve the distance.
+
+**Returns:**
+
+- <code>Distance</code> – The corresponding rest.Distance object.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – If the provided similarity measure is not supported.
+
+#### recreate_collection
+
+```python
+recreate_collection(
+    collection_name: str,
+    distance: rest.Distance,
+    embedding_dim: int,
+    on_disk: bool | None = None,
+    use_sparse_embeddings: bool | None = None,
+    sparse_idf: bool = False,
+) -> None
+```
+
+Recreates the Qdrant collection with the specified parameters.
+
+**Parameters:**
+
+- **collection_name** (<code>str</code>) – The name of the collection to recreate.
+- **distance** (<code>Distance</code>) – The distance metric to use for the collection.
+- **embedding_dim** (<code>int</code>) – The dimension of the embeddings.
+- **on_disk** (<code>bool | None</code>) – Whether to store the collection on disk.
+- **use_sparse_embeddings** (<code>bool | None</code>) – Whether to use sparse embeddings.
+- **sparse_idf** (<code>bool</code>) – Whether to compute the Inverse Document Frequency (IDF) when using sparse embeddings. Required for BM42.
+
+#### recreate_collection_async
+
+```python
+recreate_collection_async(
+    collection_name: str,
+    distance: rest.Distance,
+    embedding_dim: int,
+    on_disk: bool | None = None,
+    use_sparse_embeddings: bool | None = None,
+    sparse_idf: bool = False,
+) -> None
+```
+
+Asynchronously recreates the Qdrant collection with the specified parameters.
+
+**Parameters:**
+
+- **collection_name** (<code>str</code>) – The name of the collection to recreate.
+- **distance** (<code>Distance</code>) – The distance metric to use for the collection.
+- **embedding_dim** (<code>int</code>) – The dimension of the embeddings.
+- **on_disk** (<code>bool | None</code>) – Whether to store the collection on disk.
+- **use_sparse_embeddings** (<code>bool | None</code>) – Whether to use sparse embeddings.
+- **sparse_idf** (<code>bool</code>) – Whether to compute the Inverse Document Frequency (IDF) when using sparse embeddings. Required for BM42.
+
+## haystack_integrations.document_stores.qdrant.migrate_to_sparse
+
+### migrate_to_sparse_embeddings_support
+
+```python
+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.
+
+With qdrant-hasytack v3.3.0, support for sparse embeddings has been added to `QdrantDocumentStore`.
+This feature is disabled by default and can be enabled by setting `use_sparse_embeddings=True` in the init
+parameters. To store sparse embeddings, Document stores/collections created with this feature disabled must be
+migrated to a new collection with the feature enabled.
+
+This utility function applies to on-premise and cloud instances of Qdrant.
+It does not work for local in-memory/disk-persisted instances.
+
+The utility function merely migrates the existing documents so that they are ready to store sparse embeddings.
+It does not compute sparse embeddings. To do this, you need to use a Sparse Embedder component.
+
+Example usage:
+
+```python
+from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
+from haystack_integrations.document_stores.qdrant import migrate_to_sparse_embeddings_support
+
+old_document_store = QdrantDocumentStore(url="http://localhost:6333",
+                                         index="Document",
+                                         use_sparse_embeddings=False)
+new_index = "Document_sparse"
+
+migrate_to_sparse_embeddings_support(old_document_store, new_index)
+
+# now you can use the new document store with sparse embeddings support
+new_document_store = QdrantDocumentStore(url="http://localhost:6333",
+                                         index=new_index,
+                                         use_sparse_embeddings=True)
+```
+
+**Parameters:**
+
+- **old_document_store** (<code>QdrantDocumentStore</code>) – The existing QdrantDocumentStore instance to migrate from.
+- **new_index** (<code>str</code>) – The name of the new index/collection to create with sparse embeddings support.
diff --git a/docs-website/reference_versioned_docs/version-3.2/integrations-api/qdrant.md b/docs-website/reference_versioned_docs/version-3.2/integrations-api/qdrant.md
index 174ff310f4..7a61da3c50 100644
--- a/docs-website/reference_versioned_docs/version-3.2/integrations-api/qdrant.md
+++ b/docs-website/reference_versioned_docs/version-3.2/integrations-api/qdrant.md
@@ -778,13 +778,29 @@ count_documents() -> int
 
 Returns the number of documents present in the Document Store.
 
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
+
 #### count_documents_async
 
 ```python
 count_documents_async() -> int
 ```
 
-Asynchronously returns the number of documents present in the document dtore.
+Asynchronously returns the number of documents present in the document store.
+
+**Returns:**
+
+- <code>int</code> – The number of documents in the collection.
+
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents fails.
 
 #### filter_documents
 
@@ -983,6 +999,10 @@ Deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### delete_all_documents_async
 
 ```python
@@ -995,6 +1015,10 @@ Asynchronously deletes all documents from the document store.
 
 - **recreate_index** (<code>bool</code>) – Whether to recreate the index after deleting all documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Deleting documents or recreating the collection fails.
+
 #### count_documents_by_filter
 
 ```python
@@ -1012,6 +1036,10 @@ Returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### count_documents_by_filter_async
 
 ```python
@@ -1029,6 +1057,10 @@ Asynchronously returns the number of documents that match the provided filters.
 
 - <code>int</code> – The number of documents that match the filters.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Counting documents matching the filters fails.
+
 #### get_metadata_fields_info
 
 ```python
@@ -1049,6 +1081,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_fields_info_async
 
 ```python
@@ -1069,6 +1105,10 @@ payload["meta"].
 {"category": {"type": "keyword"}, "priority": {"type": "long"}}
 ```
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing metadata field information fails.
+
 #### get_metadata_field_min_max
 
 ```python
@@ -1087,6 +1127,10 @@ Returns the minimum and maximum values for the given metadata field.
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### get_metadata_field_min_max_async
 
 ```python
@@ -1105,6 +1149,10 @@ Asynchronously returns the minimum and maximum values for the given metadata fie
   metadata field across all documents. Returns `{"min": None, "max": None}` if no documents have
   the field.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or computing the metadata bounds fails.
+
 #### count_unique_metadata_by_filter
 
 ```python
@@ -1126,6 +1174,10 @@ Returns the number of unique values for each specified metadata field among docu
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### count_unique_metadata_by_filter_async
 
 ```python
@@ -1149,6 +1201,10 @@ Only documents that match the filters are considered.
 - <code>dict\[str, int\]</code> – A dictionary mapping each metadata field name to the count of its unique values among the filtered
   documents.
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or counting unique metadata values fails.
+
 #### get_metadata_field_unique_values
 
 ```python
@@ -1181,6 +1237,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### get_metadata_field_unique_values_async
 
 ```python
@@ -1213,6 +1273,10 @@ matching documents must be scrolled through to compute the total count.
 
 - <code>tuple\[list\[Any\], int\]</code> – A tuple containing (list of unique values, total count of unique matching values).
 
+**Raises:**
+
+- <code>QdrantStoreError</code> – Retrieving or processing unique metadata values fails.
+
 #### from_dict
 
 ```python