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refactor: replace bare dict with dict[str, Any] in model_manager and … (#35083)

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wdeveloper16 2026-04-13 19:14:08 +02:00 committed by GitHub
parent 3d4ddf4a6f
commit 9ed8a5ed73
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2 changed files with 14 additions and 10 deletions
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10
api/core/model_manager.py
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@ -115,7 +115,7 @@ class ModelInstance:
def invoke_llm( def invoke_llm(
self, self,
prompt_messages: Sequence[PromptMessage], prompt_messages: Sequence[PromptMessage],
model_parameters: dict | None = None, model_parameters: dict[str, Any] | None = None,
tools: Sequence[PromptMessageTool] | None = None, tools: Sequence[PromptMessageTool] | None = None,
stop: list[str] | None = None, stop: list[str] | None = None,
stream: Literal[True] = True, stream: Literal[True] = True,
@ -126,7 +126,7 @@ class ModelInstance:
def invoke_llm( def invoke_llm(
self, self,
prompt_messages: list[PromptMessage], prompt_messages: list[PromptMessage],
model_parameters: dict | None = None, model_parameters: dict[str, Any] | None = None,
tools: Sequence[PromptMessageTool] | None = None, tools: Sequence[PromptMessageTool] | None = None,
stop: list[str] | None = None, stop: list[str] | None = None,
stream: Literal[False] = False, stream: Literal[False] = False,
@ -137,7 +137,7 @@ class ModelInstance:
def invoke_llm( def invoke_llm(
self, self,
prompt_messages: list[PromptMessage], prompt_messages: list[PromptMessage],
model_parameters: dict | None = None, model_parameters: dict[str, Any] | None = None,
tools: Sequence[PromptMessageTool] | None = None, tools: Sequence[PromptMessageTool] | None = None,
stop: list[str] | None = None, stop: list[str] | None = None,
stream: bool = True, stream: bool = True,
@ -147,7 +147,7 @@ class ModelInstance:
def invoke_llm( def invoke_llm(
self, self,
prompt_messages: Sequence[PromptMessage], prompt_messages: Sequence[PromptMessage],
model_parameters: dict | None = None, model_parameters: dict[str, Any] | None = None,
tools: Sequence[PromptMessageTool] | None = None, tools: Sequence[PromptMessageTool] | None = None,
stop: Sequence[str] | None = None, stop: Sequence[str] | None = None,
stream: bool = True, stream: bool = True,
@ -528,7 +528,7 @@ class LBModelManager:
model_type: ModelType, model_type: ModelType,
model: str, model: str,
load_balancing_configs: list[ModelLoadBalancingConfiguration], load_balancing_configs: list[ModelLoadBalancingConfiguration],
managed_credentials: dict | None = None, managed_credentials: dict[str, Any] | None = None,
): ):
""" """
Load balancing model manager Load balancing model manager

14
api/core/rag/retrieval/dataset_retrieval.py
View File

@ -875,7 +875,11 @@ class DatasetRetrieval:
return retrieval_resource_list return retrieval_resource_list
def _on_retrieval_end( def _on_retrieval_end(
self, flask_app: Flask, documents: list[Document], message_id: str | None = None, timer: dict | None = None self,
flask_app: Flask,
documents: list[Document],
message_id: str | None = None,
timer: dict[str, Any] | None = None,
): ):
"""Handle retrieval end.""" """Handle retrieval end."""
with flask_app.app_context(): with flask_app.app_context():
@ -980,7 +984,7 @@ class DatasetRetrieval:
self._send_trace_task(message_id, documents, timer) self._send_trace_task(message_id, documents, timer)
def _send_trace_task(self, message_id: str | None, documents: list[Document], timer: dict | None): def _send_trace_task(self, message_id: str | None, documents: list[Document], timer: dict[str, Any] | None):
"""Send trace task if trace manager is available.""" """Send trace task if trace manager is available."""
trace_manager: TraceQueueManager | None = ( trace_manager: TraceQueueManager | None = (
self.application_generate_entity.trace_manager if self.application_generate_entity else None self.application_generate_entity.trace_manager if self.application_generate_entity else None
@ -1142,7 +1146,7 @@ class DatasetRetrieval:
invoke_from: InvokeFrom, invoke_from: InvokeFrom,
hit_callback: DatasetIndexToolCallbackHandler, hit_callback: DatasetIndexToolCallbackHandler,
user_id: str, user_id: str,
inputs: dict, inputs: dict[str, Any],
) -> list[DatasetRetrieverBaseTool] | None: ) -> list[DatasetRetrieverBaseTool] | None:
""" """
A dataset tool is a tool that can be used to retrieve information from a dataset A dataset tool is a tool that can be used to retrieve information from a dataset
@ -1337,7 +1341,7 @@ class DatasetRetrieval:
metadata_filtering_mode: str, metadata_filtering_mode: str,
metadata_model_config: ModelConfig, metadata_model_config: ModelConfig,
metadata_filtering_conditions: MetadataFilteringCondition | None, metadata_filtering_conditions: MetadataFilteringCondition | None,
inputs: dict, inputs: dict[str, Any],
) -> tuple[dict[str, list[str]] | None, MetadataFilteringCondition | None]: ) -> tuple[dict[str, list[str]] | None, MetadataFilteringCondition | None]:
document_query = select(DatasetDocument).where( document_query = select(DatasetDocument).where(
DatasetDocument.dataset_id.in_(dataset_ids), DatasetDocument.dataset_id.in_(dataset_ids),
@ -1417,7 +1421,7 @@ class DatasetRetrieval:
metadata_filter_document_ids[document.dataset_id].append(document.id) # type: ignore metadata_filter_document_ids[document.dataset_id].append(document.id) # type: ignore
return metadata_filter_document_ids, metadata_condition return metadata_filter_document_ids, metadata_condition
def _replace_metadata_filter_value(self, text: str, inputs: dict) -> str: def _replace_metadata_filter_value(self, text: str, inputs: dict[str, Any]) -> str:
if not inputs: if not inputs:
return text return text