feat(ai): Update AI compute docstring.

gooddata-sdk/gooddata_sdk/compute/service.py

@@ -61,8 +61,8 @@ def retrieve_result_cache_metadata(self, workspace_id: str, result_id: str) -> R
         Gets execution result's metadata from GoodData.CN workspace for given execution result ID.
 
         Args:
-            workspace_id: workspace identifier
-            result_id: execution result ID
+            workspace_id (str): workspace identifier
+            result_id (str): execution result ID
         Returns:
             ResultCacheMetadata: execution result's metadata
         """
@@ -88,8 +88,8 @@ def ai_chat(self, workspace_id: str, question: str) -> ChatResult:
         Chat with AI in GoodData workspace.
 
         Args:
-            workspace_id: workspace identifier
-            question: question to ask AI
+            workspace_id (str): workspace identifier
+            question (str): question for the AI
         Returns:
             ChatResult: Chat response
         """
@@ -113,8 +113,8 @@ def ai_chat_stream(self, workspace_id: str, question: str) -> Iterator[Any]:
         Chat Stream with AI in GoodData workspace.
 
         Args:
-            workspace_id: workspace identifier
-            question: question to ask AI
+            workspace_id (str): workspace identifier
+            question (str): question for the AI
         Returns:
             Iterator[Any]: Yields parsed JSON objects from each SSE event's data field
         """
@@ -143,9 +143,9 @@ def get_ai_chat_history(
         Get chat history with AI in GoodData workspace.
 
         Args:
-            workspace_id: workspace identifier
-            chat_history_interaction_id: collect history starting from this interaction id. If None, complete chat history is returned.
-            thread_id_suffix: suffix to identify a specific chat thread. If provided, chat_history_interaction_id is ignored.
+            workspace_id (str): workspace identifier
+            chat_history_interaction_id (str): collect history starting from this interaction id. If None, complete chat history is returned. Defaults to "".
+            thread_id_suffix (str): suffix to identify a specific chat thread. If provided, chat_history_interaction_id is ignored. Defaults to "".
         Returns:
             ChatHistoryResult: Chat history response containing interactions and other metadata
         """
@@ -160,7 +160,7 @@ def reset_ai_chat_history(self, workspace_id: str) -> None:
         Reset chat history with AI in GoodData workspace.
 
         Args:
-            workspace_id: workspace identifier
+            workspace_id (str): workspace identifier
         """
         chat_history_request = ChatHistoryRequest(reset=True)
         self._actions_api.ai_chat_history(workspace_id, chat_history_request, _check_return_type=False)
@@ -176,10 +176,10 @@ def set_ai_chat_history_feedback(
         Provide feedback for a specific chat history interaction.
 
         Args:
-            workspace_id: workspace identifier
-            user_feedback: feedback to provide ("POSITIVE", "NEGATIVE" or "NONE")
-            chat_history_interaction_id: interaction id to provide feedback for
-            thread_id_suffix: suffix to identify a specific chat thread
+            workspace_id (str): workspace identifier
+            user_feedback (str): feedback to provide ("POSITIVE", "NEGATIVE" or "NONE").
+            chat_history_interaction_id (str): interaction id to provide feedback for.
+            thread_id_suffix (str): suffix to identify a specific chat thread. Defaults to "".
         """
         chat_history_request = ChatHistoryRequest(
             user_feedback=user_feedback,
@@ -203,14 +203,14 @@ def search_ai(
         Search for metadata objects using similarity search.
 
         Args:
-            workspace_id: workspace identifier
-            question: keyword/sentence input for search
-            deep_search: turn on deep search - if true, content of complex objects will be searched as well
-            limit: maximum number of results to return
-            object_types: list of object types to search for. Enum items: "attribute", "metric", "fact",
-                "label", "date", "dataset", "visualization" and "dashboard"
-            relevant_score_threshold: minimum relevance score threshold for results
-            title_to_descriptor_ratio: ratio of title score to descriptor score
+            workspace_id (str): workspace identifier
+            question (str): keyword/sentence input for search
+            deep_search (bool): turn on deep search - if true, content of complex objects will be searched as well
+            limit (Optional[int]): maximum number of results to return. Defaults to None.
+            object_types (Optional[list[str]]): list of object types to search for. Enum items: "attribute", "metric", "fact",
+                "label", "date", "dataset", "visualization" and "dashboard". Defaults to None.
+            relevant_score_threshold (Optional[float]): minimum relevance score threshold for results. Defaults to None.
+            title_to_descriptor_ratio (Optional[float]): ratio of title score to descriptor score. Defaults to None.
 
         Returns:
             SearchResult: Search results
@@ -263,8 +263,8 @@ def sync_metadata(self, workspace_id: str, async_req: bool = False) -> None:
         metadata synchronization becomes automatic.
 
         Args:
-            workspace_id: Workspace identifier
-            async_req: If True, execute request asynchronously. Default is False.
+            workspace_id (str): Workspace identifier
+            async_req (bool): If True, execute request asynchronously. Defaults to False.
 
         Returns:
             None