chore: apply ruff's pyupgrade linter rules to modernize Python code with targeted version (#2419)

This commit is contained in:
Bowen Liang
2024-02-09 15:21:33 +08:00
committed by GitHub
parent 589099a005
commit 063191889d
246 changed files with 912 additions and 937 deletions

View File

@@ -1,5 +1,5 @@
import threading
from typing import List, Optional, Type
from typing import Optional
from flask import Flask, current_app
from langchain.tools import BaseTool
@@ -35,20 +35,20 @@ class DatasetMultiRetrieverToolInput(BaseModel):
class DatasetMultiRetrieverTool(BaseTool):
"""Tool for querying multi dataset."""
name: str = "dataset-"
args_schema: Type[BaseModel] = DatasetMultiRetrieverToolInput
args_schema: type[BaseModel] = DatasetMultiRetrieverToolInput
description: str = "dataset multi retriever and rerank. "
tenant_id: str
dataset_ids: List[str]
dataset_ids: list[str]
top_k: int = 2
score_threshold: Optional[float] = None
reranking_provider_name: str
reranking_model_name: str
return_resource: bool
retriever_from: str
hit_callbacks: List[DatasetIndexToolCallbackHandler] = []
hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
@classmethod
def from_dataset(cls, dataset_ids: List[str], tenant_id: str, **kwargs):
def from_dataset(cls, dataset_ids: list[str], tenant_id: str, **kwargs):
return cls(
name=f'dataset-{tenant_id}',
tenant_id=tenant_id,
@@ -155,8 +155,8 @@ class DatasetMultiRetrieverTool(BaseTool):
async def _arun(self, tool_input: str) -> str:
raise NotImplementedError()
def _retriever(self, flask_app: Flask, dataset_id: str, query: str, all_documents: List,
hit_callbacks: List[DatasetIndexToolCallbackHandler]):
def _retriever(self, flask_app: Flask, dataset_id: str, query: str, all_documents: list,
hit_callbacks: list[DatasetIndexToolCallbackHandler]):
with flask_app.app_context():
dataset = db.session.query(Dataset).filter(
Dataset.tenant_id == self.tenant_id,

View File

@@ -1,5 +1,5 @@
import threading
from typing import List, Optional, Type
from typing import Optional
from flask import current_app
from langchain.tools import BaseTool
@@ -35,14 +35,14 @@ class DatasetRetrieverToolInput(BaseModel):
class DatasetRetrieverTool(BaseTool):
"""Tool for querying a Dataset."""
name: str = "dataset"
args_schema: Type[BaseModel] = DatasetRetrieverToolInput
args_schema: type[BaseModel] = DatasetRetrieverToolInput
description: str = "use this to retrieve a dataset. "
tenant_id: str
dataset_id: str
top_k: int = 2
score_threshold: Optional[float] = None
hit_callbacks: List[DatasetIndexToolCallbackHandler] = []
hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
return_resource: bool
retriever_from: str