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

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Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
-LAN-
2025-09-15 13:06:33 +08:00
committed by GitHub
parent 2e44ebe98d
commit bab4975809
394 changed files with 2555 additions and 2792 deletions
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4
api/core/llm_generator/llm_generator.py
View File

@@ -2,7 +2,7 @@ import json
import logging
import re
from collections.abc import Sequence
from typing import Optional, cast
from typing import cast
import json_repair
@@ -37,7 +37,7 @@ logger = logging.getLogger(__name__)
class LLMGenerator:
@classmethod
def generate_conversation_name(
cls, tenant_id: str, query, conversation_id: Optional[str] = None, app_id: Optional[str] = None
cls, tenant_id: str, query, conversation_id: str | None = None, app_id: str | None = None
):
prompt = CONVERSATION_TITLE_PROMPT

36
api/core/llm_generator/output_parser/structured_output.py
View File

@@ -2,7 +2,7 @@ import json
from collections.abc import Generator, Mapping, Sequence
from copy import deepcopy
from enum import StrEnum
from typing import Any, Literal, Optional, cast, overload
from typing import Any, Literal, cast, overload
import json_repair
from pydantic import TypeAdapter, ValidationError
@@ -51,12 +51,12 @@ def invoke_llm_with_structured_output(
model_instance: ModelInstance,
prompt_messages: Sequence[PromptMessage],
json_schema: Mapping[str, Any],
model_parameters: Optional[Mapping] = None,
model_parameters: Mapping | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stop: list[str] | None = None,
stream: Literal[True],
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
@overload
def invoke_llm_with_structured_output(
@@ -66,12 +66,12 @@ def invoke_llm_with_structured_output(
model_instance: ModelInstance,
prompt_messages: Sequence[PromptMessage],
json_schema: Mapping[str, Any],
model_parameters: Optional[Mapping] = None,
model_parameters: Mapping | None = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stop: list[str] | None = None,
stream: Literal[False],
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
user: str | None = None,
callbacks: list[Callback] | None = None,
) -> LLMResultWithStructuredOutput: ...
@overload
def invoke_llm_with_structured_output(
@@ -81,12 +81,12 @@ def invoke_llm_with_structured_output(
model_instance: ModelInstance,
prompt_messages: Sequence[PromptMessage],
json_schema: Mapping[str, Any],
model_parameters: Optional[Mapping] = None,
model_parameters: Mapping | 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,
) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
def invoke_llm_with_structured_output(
*,
@@ -95,12 +95,12 @@ def invoke_llm_with_structured_output(
model_instance: ModelInstance,
prompt_messages: Sequence[PromptMessage],
json_schema: Mapping[str, Any],
model_parameters: Optional[Mapping] = None,
model_parameters: Mapping | 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,
) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]:
"""
Invoke large language model with structured output
@@ -166,7 +166,7 @@ def invoke_llm_with_structured_output(
def generator() -> Generator[LLMResultChunkWithStructuredOutput, None, None]:
result_text: str = ""
prompt_messages: Sequence[PromptMessage] = []
system_fingerprint: Optional[str] = None
system_fingerprint: str | None = None
for event in llm_result:
if isinstance(event, LLMResultChunk):
prompt_messages = event.prompt_messages