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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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79
libs/partners/fireworks/langchain_fireworks/chat_models.py
View File

@@ -4,20 +4,13 @@ from __future__ import annotations
import json
import logging
from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
from operator import itemgetter
from typing import (
Any,
AsyncIterator,
Callable,
Dict,
Iterator,
List,
Literal,
Mapping,
Optional,
Sequence,
Tuple,
Type,
TypedDict,
Union,
cast,
@@ -109,7 +102,7 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
# Fix for azure
# Also Fireworks returns None for tool invocations
content = _dict.get("content", "") or ""
additional_kwargs: Dict = {}
additional_kwargs: dict = {}
if function_call := _dict.get("function_call"):
additional_kwargs["function_call"] = dict(function_call)
tool_calls = []
@@ -157,7 +150,7 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
Returns:
The dictionary.
"""
message_dict: Dict[str, Any]
message_dict: dict[str, Any]
if isinstance(message, ChatMessage):
message_dict = {"role": message.role, "content": message.content}
elif isinstance(message, HumanMessage):
@@ -205,14 +198,14 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
def _convert_chunk_to_message_chunk(
chunk: Mapping[str, Any], default_class: Type[BaseMessageChunk]
chunk: Mapping[str, Any], default_class: type[BaseMessageChunk]
) -> BaseMessageChunk:
choice = chunk["choices"][0]
_dict = choice["delta"]
role = cast(str, _dict.get("role"))
content = cast(str, _dict.get("content") or "")
additional_kwargs: Dict = {}
tool_call_chunks: List[ToolCallChunk] = []
additional_kwargs: dict = {}
tool_call_chunks: list[ToolCallChunk] = []
if _dict.get("function_call"):
function_call = dict(_dict["function_call"])
if "name" in function_call and function_call["name"] is None:
@@ -290,17 +283,17 @@ class ChatFireworks(BaseChatModel):
"""
@property
def lc_secrets(self) -> Dict[str, str]:
def lc_secrets(self) -> dict[str, str]:
return {"fireworks_api_key": "FIREWORKS_API_KEY"}
@classmethod
def get_lc_namespace(cls) -> List[str]:
def get_lc_namespace(cls) -> list[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "chat_models", "fireworks"]
@property
def lc_attributes(self) -> Dict[str, Any]:
attributes: Dict[str, Any] = {}
def lc_attributes(self) -> dict[str, Any]:
attributes: dict[str, Any] = {}
if self.fireworks_api_base:
attributes["fireworks_api_base"] = self.fireworks_api_base
@@ -319,9 +312,9 @@ class ChatFireworks(BaseChatModel):
"""Model name to use."""
temperature: float = 0.0
"""What sampling temperature to use."""
stop: Optional[Union[str, List[str]]] = Field(default=None, alias="stop_sequences")
stop: Optional[Union[str, list[str]]] = Field(default=None, alias="stop_sequences")
"""Default stop sequences."""
model_kwargs: Dict[str, Any] = Field(default_factory=dict)
model_kwargs: dict[str, Any] = Field(default_factory=dict)
"""Holds any model parameters valid for `create` call not explicitly specified."""
fireworks_api_key: SecretStr = Field(
alias="api_key",
@@ -344,7 +337,7 @@ class ChatFireworks(BaseChatModel):
)
"""Base URL path for API requests, leave blank if not using a proxy or service
emulator."""
request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
request_timeout: Union[float, tuple[float, float], Any, None] = Field(
default=None, alias="timeout"
)
"""Timeout for requests to Fireworks completion API. Can be float, httpx.Timeout or
@@ -364,7 +357,7 @@ class ChatFireworks(BaseChatModel):
@model_validator(mode="before")
@classmethod
def build_extra(cls, values: Dict[str, Any]) -> Any:
def build_extra(cls, values: dict[str, Any]) -> Any:
"""Build extra kwargs from additional params that were passed in."""
all_required_field_names = get_pydantic_field_names(cls)
values = _build_model_kwargs(values, all_required_field_names)
@@ -398,7 +391,7 @@ class ChatFireworks(BaseChatModel):
return self
@property
def _default_params(self) -> Dict[str, Any]:
def _default_params(self) -> dict[str, Any]:
"""Get the default parameters for calling Fireworks API."""
params = {
"model": self.model_name,
@@ -413,7 +406,7 @@ class ChatFireworks(BaseChatModel):
return params
def _get_ls_params(
self, stop: Optional[List[str]] = None, **kwargs: Any
self, stop: Optional[list[str]] = None, **kwargs: Any
) -> LangSmithParams:
"""Get standard params for tracing."""
params = self._get_invocation_params(stop=stop, **kwargs)
@@ -429,7 +422,7 @@ class ChatFireworks(BaseChatModel):
ls_params["ls_stop"] = ls_stop
return ls_params
def _combine_llm_outputs(self, llm_outputs: List[Optional[dict]]) -> dict:
def _combine_llm_outputs(self, llm_outputs: list[Optional[dict]]) -> dict:
overall_token_usage: dict = {}
system_fingerprint = None
for output in llm_outputs:
@@ -452,15 +445,15 @@ class ChatFireworks(BaseChatModel):
def _stream(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
messages: list[BaseMessage],
stop: Optional[list[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> Iterator[ChatGenerationChunk]:
message_dicts, params = self._create_message_dicts(messages, stop)
params = {**params, **kwargs, "stream": True}
default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
default_chunk_class: type[BaseMessageChunk] = AIMessageChunk
for chunk in self.client.create(messages=message_dicts, **params):
if not isinstance(chunk, dict):
chunk = chunk.model_dump()
@@ -487,8 +480,8 @@ class ChatFireworks(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,
stream: Optional[bool] = None,
**kwargs: Any,
@@ -509,8 +502,8 @@ class ChatFireworks(BaseChatModel):
return self._create_chat_result(response)
def _create_message_dicts(
self, messages: List[BaseMessage], stop: Optional[List[str]]
) -> Tuple[List[Dict[str, Any]], Dict[str, Any]]:
self, messages: list[BaseMessage], stop: Optional[list[str]]
) -> tuple[list[dict[str, Any]], dict[str, Any]]:
params = self._default_params
if stop is not None:
params["stop"] = stop
@@ -547,15 +540,15 @@ class ChatFireworks(BaseChatModel):
async def _astream(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
messages: list[BaseMessage],
stop: Optional[list[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> AsyncIterator[ChatGenerationChunk]:
message_dicts, params = self._create_message_dicts(messages, stop)
params = {**params, **kwargs, "stream": True}
default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
default_chunk_class: type[BaseMessageChunk] = AIMessageChunk
async for chunk in self.async_client.acreate(messages=message_dicts, **params):
if not isinstance(chunk, dict):
chunk = chunk.model_dump()
@@ -584,8 +577,8 @@ class ChatFireworks(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,
stream: Optional[bool] = None,
**kwargs: Any,
@@ -607,13 +600,13 @@ class ChatFireworks(BaseChatModel):
return self._create_chat_result(response)
@property
def _identifying_params(self) -> Dict[str, Any]:
def _identifying_params(self) -> dict[str, Any]:
"""Get the identifying parameters."""
return {"model_name": self.model_name, **self._default_params}
def _get_invocation_params(
self, stop: Optional[List[str]] = None, **kwargs: Any
) -> Dict[str, Any]:
self, stop: Optional[list[str]] = None, **kwargs: Any
) -> dict[str, Any]:
"""Get the parameters used to invoke the model."""
return {
"model": self.model_name,
@@ -634,7 +627,7 @@ class ChatFireworks(BaseChatModel):
)
def bind_functions(
self,
functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
functions: Sequence[Union[dict[str, Any], type[BaseModel], Callable, BaseTool]],
function_call: Optional[
Union[_FunctionCall, str, Literal["auto", "none"]]
] = None,
@@ -690,7 +683,7 @@ class ChatFireworks(BaseChatModel):
def bind_tools(
self,
tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
tools: Sequence[Union[dict[str, Any], type[BaseModel], Callable, BaseTool]],
*,
tool_choice: Optional[
Union[dict, str, Literal["auto", "any", "none"], bool]
@@ -738,14 +731,14 @@ class ChatFireworks(BaseChatModel):
def with_structured_output(
self,
schema: Optional[Union[Dict, Type[BaseModel]]] = None,
schema: Optional[Union[dict, type[BaseModel]]] = None,
*,
method: Literal[
"function_calling", "json_mode", "json_schema"
] = "function_calling",
include_raw: bool = False,
**kwargs: Any,
) -> Runnable[LanguageModelInput, Union[Dict, BaseModel]]:
) -> Runnable[LanguageModelInput, Union[dict, BaseModel]]:
"""Model wrapper that returns outputs formatted to match the given schema.
Args:

6
libs/partners/fireworks/langchain_fireworks/embeddings.py
View File

@@ -1,5 +1,3 @@
from typing import List
from langchain_core.embeddings import Embeddings
from langchain_core.utils import secret_from_env
from openai import OpenAI
@@ -96,13 +94,13 @@ class FireworksEmbeddings(BaseModel, Embeddings):
)
return self
def embed_documents(self, texts: List[str]) -> List[List[float]]:
def embed_documents(self, texts: list[str]) -> list[list[float]]:
"""Embed search docs."""
return [
i.embedding
for i in self.client.embeddings.create(input=texts, model=self.model).data
]
def embed_query(self, text: str) -> List[float]:
def embed_query(self, text: str) -> list[float]:
"""Embed query text."""
return self.embed_documents([text])[0]

16
libs/partners/fireworks/langchain_fireworks/llms.py
View File

@@ -1,7 +1,7 @@
"""Wrapper around Fireworks AI's Completion API."""
import logging
from typing import Any, Dict, List, Optional
from typing import Any, Optional
import requests
from aiohttp import ClientSession
@@ -63,7 +63,7 @@ class Fireworks(LLM):
for question answering or summarization. A value greater than 1 introduces more
randomness in the output.
"""
model_kwargs: Dict[str, Any] = Field(default_factory=dict)
model_kwargs: dict[str, Any] = Field(default_factory=dict)
"""Holds any model parameters valid for `create` call not explicitly specified."""
top_k: Optional[int] = None
"""Used to limit the number of choices for the next predicted word or token. It
@@ -90,7 +90,7 @@ class Fireworks(LLM):
@model_validator(mode="before")
@classmethod
def build_extra(cls, values: Dict[str, Any]) -> Any:
def build_extra(cls, values: dict[str, Any]) -> Any:
"""Build extra kwargs from additional params that were passed in."""
all_required_field_names = get_pydantic_field_names(cls)
values = _build_model_kwargs(values, all_required_field_names)
@@ -109,7 +109,7 @@ class Fireworks(LLM):
return f"langchain-fireworks/{__version__}"
@property
def default_params(self) -> Dict[str, Any]:
def default_params(self) -> dict[str, Any]:
return {
"model": self.model,
"temperature": self.temperature,
@@ -122,7 +122,7 @@ class Fireworks(LLM):
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
stop: Optional[list[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
@@ -139,7 +139,7 @@ class Fireworks(LLM):
"Content-Type": "application/json",
}
stop_to_use = stop[0] if stop and len(stop) == 1 else stop
payload: Dict[str, Any] = {
payload: dict[str, Any] = {
**self.default_params,
"prompt": prompt,
"stop": stop_to_use,
@@ -168,7 +168,7 @@ class Fireworks(LLM):
async def _acall(
self,
prompt: str,
stop: Optional[List[str]] = None,
stop: Optional[list[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
@@ -185,7 +185,7 @@ class Fireworks(LLM):
"Content-Type": "application/json",
}
stop_to_use = stop[0] if stop and len(stop) == 1 else stop
payload: Dict[str, Any] = {
payload: dict[str, Any] = {
**self.default_params,
"prompt": prompt,
"stop": stop_to_use,