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Fix basedpyright type errors (#25435)

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Signed-off-by: -LAN- <laipz8200@outlook.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
-LAN-
2025-09-10 01:54:26 +08:00
committed by GitHub
parent 2ac7a9c8fc
commit 08dd3f7b50
100 changed files with 847 additions and 497 deletions
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12
api/core/llm_generator/llm_generator.py
View File

@@ -20,7 +20,7 @@ from core.llm_generator.prompts import (
)
from core.model_manager import ModelManager
from core.model_runtime.entities.llm_entities import LLMResult
from core.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage
from core.model_runtime.entities.message_entities import PromptMessage, SystemPromptMessage, UserPromptMessage
from core.model_runtime.entities.model_entities import ModelType
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
from core.ops.entities.trace_entity import TraceTaskName
@@ -313,14 +313,20 @@ class LLMGenerator:
model_type=ModelType.LLM,
)
prompt_messages = [SystemPromptMessage(content=prompt), UserPromptMessage(content=query)]
prompt_messages: list[PromptMessage] = [SystemPromptMessage(content=prompt), UserPromptMessage(content=query)]
response: LLMResult = model_instance.invoke_llm(
# Explicitly use the non-streaming overload
result = model_instance.invoke_llm(
prompt_messages=prompt_messages,
model_parameters={"temperature": 0.01, "max_tokens": 2000},
stream=False,
)
# Runtime type check since pyright has issues with the overload
if not isinstance(result, LLMResult):
raise TypeError("Expected LLMResult when stream=False")
response = result
answer = cast(str, response.message.content)
return answer.strip()

14
api/core/llm_generator/output_parser/structured_output.py
View File

@@ -45,6 +45,7 @@ class SpecialModelType(StrEnum):
@overload
def invoke_llm_with_structured_output(
*,
provider: str,
model_schema: AIModelEntity,
model_instance: ModelInstance,
@@ -53,14 +54,13 @@ def invoke_llm_with_structured_output(
model_parameters: Optional[Mapping] = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stream: Literal[True] = True,
stream: Literal[True],
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
) -> Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
@overload
def invoke_llm_with_structured_output(
*,
provider: str,
model_schema: AIModelEntity,
model_instance: ModelInstance,
@@ -69,14 +69,13 @@ def invoke_llm_with_structured_output(
model_parameters: Optional[Mapping] = None,
tools: Sequence[PromptMessageTool] | None = None,
stop: Optional[list[str]] = None,
stream: Literal[False] = False,
stream: Literal[False],
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
) -> LLMResultWithStructuredOutput: ...
@overload
def invoke_llm_with_structured_output(
*,
provider: str,
model_schema: AIModelEntity,
model_instance: ModelInstance,
@@ -89,9 +88,8 @@ def invoke_llm_with_structured_output(
user: Optional[str] = None,
callbacks: Optional[list[Callback]] = None,
) -> LLMResultWithStructuredOutput | Generator[LLMResultChunkWithStructuredOutput, None, None]: ...
def invoke_llm_with_structured_output(
*,
provider: str,
model_schema: AIModelEntity,
model_instance: ModelInstance,