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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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8
api/core/agent/base_agent_runner.py
View file

@ -1,7 +1,7 @@
import json
import logging
import uuid
from typing import Optional, Union, cast
from typing import Union, cast
from sqlalchemy import select
@ -60,8 +60,8 @@ class BaseAgentRunner(AppRunner):
message: Message,
user_id: str,
model_instance: ModelInstance,
memory: Optional[TokenBufferMemory] = None,
prompt_messages: Optional[list[PromptMessage]] = None,
memory: TokenBufferMemory | None = None,
prompt_messages: list[PromptMessage] | None = None,
):
self.tenant_id = tenant_id
self.application_generate_entity = application_generate_entity
@ -112,7 +112,7 @@ class BaseAgentRunner(AppRunner):
features = model_schema.features if model_schema and model_schema.features else []
self.stream_tool_call = ModelFeature.STREAM_TOOL_CALL in features
self.files = application_generate_entity.files if ModelFeature.VISION in features else []
self.query: Optional[str] = ""
self.query: str | None = ""
self._current_thoughts: list[PromptMessage] = []
def _repack_app_generate_entity(

10
api/core/agent/cot_agent_runner.py
View file

@ -1,7 +1,7 @@
import json
from abc import ABC, abstractmethod
from collections.abc import Generator, Mapping, Sequence
from typing import Any, Optional
from typing import Any
from core.agent.base_agent_runner import BaseAgentRunner
from core.agent.entities import AgentScratchpadUnit
@ -70,12 +70,12 @@ class CotAgentRunner(BaseAgentRunner, ABC):
self._prompt_messages_tools = prompt_messages_tools
function_call_state = True
llm_usage: dict[str, Optional[LLMUsage]] = {"usage": None}
llm_usage: dict[str, LLMUsage | None] = {"usage": None}
final_answer = ""
prompt_messages: list = [] # Initialize prompt_messages
agent_thought_id = "" # Initialize agent_thought_id
def increase_usage(final_llm_usage_dict: dict[str, Optional[LLMUsage]], usage: LLMUsage):
def increase_usage(final_llm_usage_dict: dict[str, LLMUsage | None], usage: LLMUsage):
if not final_llm_usage_dict["usage"]:
final_llm_usage_dict["usage"] = usage
else:
@ -122,7 +122,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
callbacks=[],
)
usage_dict: dict[str, Optional[LLMUsage]] = {}
usage_dict: dict[str, LLMUsage | None] = {}
react_chunks = CotAgentOutputParser.handle_react_stream_output(chunks, usage_dict)
scratchpad = AgentScratchpadUnit(
agent_response="",
@ -274,7 +274,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
action: AgentScratchpadUnit.Action,
tool_instances: Mapping[str, Tool],
message_file_ids: list[str],
trace_manager: Optional[TraceQueueManager] = None,
trace_manager: TraceQueueManager | None = None,
) -> tuple[str, ToolInvokeMeta]:
"""
handle invoke action

3
api/core/agent/cot_completion_agent_runner.py
View file

@ -1,5 +1,4 @@
import json
from typing import Optional
from core.agent.cot_agent_runner import CotAgentRunner
from core.model_runtime.entities.message_entities import (
@ -31,7 +30,7 @@ class CotCompletionAgentRunner(CotAgentRunner):
return system_prompt
def _organize_historic_prompt(self, current_session_messages: Optional[list[PromptMessage]] = None) -> str:
def _organize_historic_prompt(self, current_session_messages: list[PromptMessage] | None = None) -> str:
"""
Organize historic prompt
"""

16
api/core/agent/entities.py
View file

@ -1,5 +1,5 @@
from enum import StrEnum
from typing import Any, Optional, Union
from typing import Any, Union
from pydantic import BaseModel, Field
@ -50,11 +50,11 @@ class AgentScratchpadUnit(BaseModel):
"action_input": self.action_input,
}
agent_response: Optional[str] = None
thought: Optional[str] = None
action_str: Optional[str] = None
observation: Optional[str] = None
action: Optional[Action] = None
agent_response: str | None = None
thought: str | None = None
action_str: str | None = None
observation: str | None = None
action: Action | None = None
def is_final(self) -> bool:
"""
@ -81,8 +81,8 @@ class AgentEntity(BaseModel):
provider: str
model: str
strategy: Strategy
prompt: Optional[AgentPromptEntity] = None
tools: Optional[list[AgentToolEntity]] = None
prompt: AgentPromptEntity | None = None
tools: list[AgentToolEntity] | None = None
max_iteration: int = 10

6
api/core/agent/fc_agent_runner.py
View file

@ -2,7 +2,7 @@ import json
import logging
from collections.abc import Generator
from copy import deepcopy
from typing import Any, Optional, Union
from typing import Any, Union
from core.agent.base_agent_runner import BaseAgentRunner
from core.app.apps.base_app_queue_manager import PublishFrom
@ -52,14 +52,14 @@ class FunctionCallAgentRunner(BaseAgentRunner):
# continue to run until there is not any tool call
function_call_state = True
llm_usage: dict[str, Optional[LLMUsage]] = {"usage": None}
llm_usage: dict[str, LLMUsage | None] = {"usage": None}
final_answer = ""
prompt_messages: list = [] # Initialize prompt_messages
# get tracing instance
trace_manager = app_generate_entity.trace_manager
def increase_usage(final_llm_usage_dict: dict[str, Optional[LLMUsage]], usage: LLMUsage):
def increase_usage(final_llm_usage_dict: dict[str, LLMUsage | None], usage: LLMUsage):
if not final_llm_usage_dict["usage"]:
final_llm_usage_dict["usage"] = usage
else:

12
api/core/agent/plugin_entities.py
View file

@ -1,5 +1,5 @@
from enum import StrEnum
from typing import Any, Optional
from typing import Any
from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_validator
@ -53,7 +53,7 @@ class AgentStrategyParameter(PluginParameter):
return cast_parameter_value(self, value)
type: AgentStrategyParameterType = Field(..., description="The type of the parameter")
help: Optional[I18nObject] = None
help: I18nObject | None = None
def init_frontend_parameter(self, value: Any):
return init_frontend_parameter(self, self.type, value)
@ -61,7 +61,7 @@ class AgentStrategyParameter(PluginParameter):
class AgentStrategyProviderEntity(BaseModel):
identity: AgentStrategyProviderIdentity
plugin_id: Optional[str] = Field(None, description="The id of the plugin")
plugin_id: str | None = Field(None, description="The id of the plugin")
class AgentStrategyIdentity(ToolIdentity):
@ -84,9 +84,9 @@ class AgentStrategyEntity(BaseModel):
identity: AgentStrategyIdentity
parameters: list[AgentStrategyParameter] = Field(default_factory=list)
description: I18nObject = Field(..., description="The description of the agent strategy")
output_schema: Optional[dict] = None
features: Optional[list[AgentFeature]] = None
meta_version: Optional[str] = None
output_schema: dict | None = None
features: list[AgentFeature] | None = None
meta_version: str | None = None
# pydantic configs
model_config = ConfigDict(protected_namespaces=())

18
api/core/agent/strategy/base.py
View file

@ -1,6 +1,6 @@
from abc import ABC, abstractmethod
from collections.abc import Generator, Sequence
from typing import Any, Optional
from typing import Any
from core.agent.entities import AgentInvokeMessage
from core.agent.plugin_entities import AgentStrategyParameter
@ -16,10 +16,10 @@ class BaseAgentStrategy(ABC):
self,
params: dict[str, Any],
user_id: str,
conversation_id: Optional[str] = None,
app_id: Optional[str] = None,
message_id: Optional[str] = None,
credentials: Optional[InvokeCredentials] = None,
conversation_id: str | None = None,
app_id: str | None = None,
message_id: str | None = None,
credentials: InvokeCredentials | None = None,
) -> Generator[AgentInvokeMessage, None, None]:
"""
Invoke the agent strategy.
@ -37,9 +37,9 @@ class BaseAgentStrategy(ABC):
self,
params: dict[str, Any],
user_id: str,
conversation_id: Optional[str] = None,
app_id: Optional[str] = None,
message_id: Optional[str] = None,
credentials: Optional[InvokeCredentials] = None,
conversation_id: str | None = None,
app_id: str | None = None,
message_id: str | None = None,
credentials: InvokeCredentials | None = None,
) -> Generator[AgentInvokeMessage, None, None]:
pass

10
api/core/agent/strategy/plugin.py
View file

@ -1,5 +1,5 @@
from collections.abc import Generator, Sequence
from typing import Any, Optional
from typing import Any
from core.agent.entities import AgentInvokeMessage
from core.agent.plugin_entities import AgentStrategyEntity, AgentStrategyParameter
@ -38,10 +38,10 @@ class PluginAgentStrategy(BaseAgentStrategy):
self,
params: dict[str, Any],
user_id: str,
conversation_id: Optional[str] = None,
app_id: Optional[str] = None,
message_id: Optional[str] = None,
credentials: Optional[InvokeCredentials] = None,
conversation_id: str | None = None,
app_id: str | None = None,
message_id: str | None = None,
credentials: InvokeCredentials | None = None,
) -> Generator[AgentInvokeMessage, None, None]:
"""
Invoke the agent strategy.