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chore: add ast-grep rule to convert Optional[T] to T | None (#25560)

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-LAN- 2025-09-15 13:06:33 +08:00 • committed by GitHub
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394 changed files with 2555 additions and 2792 deletions
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54
api/core/model_manager.py
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@ -103,47 +103,47 @@ class ModelInstance:
def invoke_llm(
self,
prompt_messages: Sequence[PromptMessage],
model_parameters: Optional[dict] = None,
model_parameters: dict | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stop: list[str] | None = None,
stream: Literal[True] = True,
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> Generator: ...
@overload
def invoke_llm(
self,
prompt_messages: list[PromptMessage],
model_parameters: Optional[dict] = None,
model_parameters: dict | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stop: list[str] | None = None,
stream: Literal[False] = False,
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> LLMResult: ...
@overload
def invoke_llm(
self,
prompt_messages: list[PromptMessage],
model_parameters: Optional[dict] = None,
model_parameters: dict | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stop: list[str] | None = None,
stream: bool = True,
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> Union[LLMResult, Generator]: ...
def invoke_llm(
self,
prompt_messages: Sequence[PromptMessage],
model_parameters: Optional[dict] = None,
model_parameters: dict | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[Sequence[str]] = None,
stop: Sequence[str] | None = None,
stream: bool = True,
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> Union[LLMResult, Generator]:
"""
Invoke large language model
@ -176,7 +176,7 @@ class ModelInstance:
)
def get_llm_num_tokens(
self, prompt_messages: Sequence[PromptMessage], tools: Optional[Sequence[PromptMessageTool]] = None
self, prompt_messages: Sequence[PromptMessage], tools: Sequence[PromptMessageTool] | None = None
) -> int:
"""
Get number of tokens for llm
@ -199,7 +199,7 @@ class ModelInstance:
)
def invoke_text_embedding(
self, texts: list[str], user: Optional[str] = None, input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT
self, texts: list[str], user: str | None = None, input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT
) -> TextEmbeddingResult:
"""
Invoke large language model
@ -246,9 +246,9 @@ class ModelInstance:
self,
query: str,
docs: list[str],
score_threshold: Optional[float] = None,
top_n: Optional[int] = None,
user: Optional[str] = None,
score_threshold: float | None = None,
top_n: int | None = None,
user: str | None = None,
) -> RerankResult:
"""
Invoke rerank model
@ -276,7 +276,7 @@ class ModelInstance:
),
)
def invoke_moderation(self, text: str, user: Optional[str] = None) -> bool:
def invoke_moderation(self, text: str, user: str | None = None) -> bool:
"""
Invoke moderation model
@ -297,7 +297,7 @@ class ModelInstance:
),
)
def invoke_speech2text(self, file: IO[bytes], user: Optional[str] = None) -> str:
def invoke_speech2text(self, file: IO[bytes], user: str | None = None) -> str:
"""
Invoke large language model
@ -318,7 +318,7 @@ class ModelInstance:
),
)
def invoke_tts(self, content_text: str, tenant_id: str, voice: str, user: Optional[str] = None) -> Iterable[bytes]:
def invoke_tts(self, content_text: str, tenant_id: str, voice: str, user: str | None = None) -> Iterable[bytes]:
"""
Invoke large language tts model
@ -397,7 +397,7 @@ class ModelInstance:
except Exception as e:
raise e
def get_tts_voices(self, language: Optional[str] = None):
def get_tts_voices(self, language: str | None = None):
"""
Invoke large language tts model voices
@ -470,7 +470,7 @@ class LBModelManager:
model_type: ModelType,
model: str,
load_balancing_configs: list[ModelLoadBalancingConfiguration],
managed_credentials: Optional[dict] = None,
managed_credentials: dict | None = None,
):
"""
Load balancing model manager
@ -495,7 +495,7 @@ class LBModelManager:
else:
load_balancing_config.credentials = managed_credentials
def fetch_next(self) -> Optional[ModelLoadBalancingConfiguration]:
def fetch_next(self) -> ModelLoadBalancingConfiguration | None:
"""
Get next model load balancing config
Strategy: Round Robin