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partners[lint]: run pyupgrade to get code in line with 3.9 standards (#30781)

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Using `pyupgrade` to get all `partners` code up to 3.9 standards
(mostly, fixing old `typing` imports).
This commit is contained in:
Sydney Runkle
2025-04-11 07:18:44 -04:00
committed by GitHub
parent e72f3c26a0
commit 8c6734325b
123 changed files with 1000 additions and 1109 deletions
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31
libs/partners/huggingface/langchain_huggingface/chat_models/huggingface.py
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@@ -1,16 +1,13 @@
"""Hugging Face Chat Wrapper."""
import json
from collections.abc import Sequence
from dataclasses import dataclass
from typing import (
Any,
Callable,
Dict,
List,
Literal,
Optional,
Sequence,
Type,
Union,
cast,
)
@@ -46,8 +43,8 @@ DEFAULT_SYSTEM_PROMPT = """You are a helpful, respectful, and honest assistant."
class TGI_RESPONSE:
"""Response from the TextGenInference API."""
choices: List[Any]
usage: Dict
choices: list[Any]
usage: dict
@dataclass
@@ -56,12 +53,12 @@ class TGI_MESSAGE:
role: str
content: str
tool_calls: List[Dict]
tool_calls: list[dict]
def _convert_message_to_chat_message(
message: BaseMessage,
) -> Dict:
) -> dict:
if isinstance(message, ChatMessage):
return dict(role=message.role, content=message.content)
elif isinstance(message, HumanMessage):
@@ -104,7 +101,7 @@ def _convert_TGI_message_to_LC_message(
content = cast(str, _message.content)
if content is None:
content = ""
additional_kwargs: Dict = {}
additional_kwargs: dict = {}
if tool_calls := _message.tool_calls:
if "arguments" in tool_calls[0]["function"]:
functions = tool_calls[0]["function"].pop("arguments")
@@ -358,8 +355,8 @@ class ChatHuggingFace(BaseChatModel):
def _generate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
messages: list[BaseMessage],
stop: Optional[list[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> ChatResult:
@@ -380,8 +377,8 @@ class ChatHuggingFace(BaseChatModel):
async def _agenerate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
messages: list[BaseMessage],
stop: Optional[list[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> ChatResult:
@@ -398,7 +395,7 @@ class ChatHuggingFace(BaseChatModel):
def _to_chat_prompt(
self,
messages: List[BaseMessage],
messages: list[BaseMessage],
) -> str:
"""Convert a list of messages into a prompt format expected by wrapped LLM."""
if not messages:
@@ -472,7 +469,7 @@ class ChatHuggingFace(BaseChatModel):
def bind_tools(
self,
tools: Sequence[Union[Dict[str, Any], Type, Callable, BaseTool]],
tools: Sequence[Union[dict[str, Any], type, Callable, BaseTool]],
*,
tool_choice: Optional[
Union[dict, str, Literal["auto", "none", "required"], bool]
@@ -529,8 +526,8 @@ class ChatHuggingFace(BaseChatModel):
return super().bind(tools=formatted_tools, **kwargs)
def _create_message_dicts(
self, messages: List[BaseMessage], stop: Optional[List[str]]
) -> List[Dict[Any, Any]]:
self, messages: list[BaseMessage], stop: Optional[list[str]]
) -> list[dict[Any, Any]]:
message_dicts = [_convert_message_to_chat_message(m) for m in messages]
return message_dicts