anthropic[patch]: ruff fixes and rules (#31899)

* bump ruff deps
* add more thorough ruff rules
* fix said rules

libs/partners/anthropic/langchain_anthropic/llms.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import re
 import warnings
 from collections.abc import AsyncIterator, Iterator, Mapping
@@ -85,8 +87,7 @@ class _AnthropicCommon(BaseLanguageModel):
     @classmethod
     def build_extra(cls, values: dict) -> Any:
         all_required_field_names = get_pydantic_field_names(cls)
-        values = _build_model_kwargs(values, all_required_field_names)
-        return values
+        return _build_model_kwargs(values, all_required_field_names)
 
     @model_validator(mode="after")
     def validate_environment(self) -> Self:
@@ -125,11 +126,12 @@ class _AnthropicCommon(BaseLanguageModel):
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""
-        return {**{}, **self._default_params}
+        return {**self._default_params}
 
     def _get_anthropic_stop(self, stop: Optional[list[str]] = None) -> list[str]:
         if not self.HUMAN_PROMPT or not self.AI_PROMPT:
-            raise NameError("Please ensure the anthropic package is loaded")
+            msg = "Please ensure the anthropic package is loaded"
+            raise NameError(msg)
 
         if stop is None:
             stop = []
@@ -152,6 +154,7 @@ class AnthropicLLM(LLM, _AnthropicCommon):
             from langchain_anthropic import AnthropicLLM
 
             model = AnthropicLLM()
+
     """
 
     model_config = ConfigDict(
@@ -166,7 +169,7 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         warnings.warn(
             "This Anthropic LLM is deprecated. "
             "Please use `from langchain_anthropic import ChatAnthropic` "
-            "instead"
+            "instead",
         )
         return values
 
@@ -199,7 +202,9 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         }
 
     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 = super()._get_ls_params(stop=stop, **kwargs)
@@ -213,7 +218,8 @@ class AnthropicLLM(LLM, _AnthropicCommon):
 
     def _wrap_prompt(self, prompt: str) -> str:
         if not self.HUMAN_PROMPT or not self.AI_PROMPT:
-            raise NameError("Please ensure the anthropic package is loaded")
+            msg = "Please ensure the anthropic package is loaded"
+            raise NameError(msg)
 
         if prompt.startswith(self.HUMAN_PROMPT):
             return prompt  # Already wrapped.
@@ -238,6 +244,8 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         Args:
             prompt: The prompt to pass into the model.
             stop: Optional list of stop words to use when generating.
+            run_manager: Optional callback manager for LLM run.
+            kwargs: Additional keyword arguments to pass to the model.
 
         Returns:
             The string generated by the model.
@@ -253,7 +261,10 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         if self.streaming:
             completion = ""
             for chunk in self._stream(
-                prompt=prompt, stop=stop, run_manager=run_manager, **kwargs
+                prompt=prompt,
+                stop=stop,
+                run_manager=run_manager,
+                **kwargs,
             ):
                 completion += chunk.text
             return completion
@@ -281,7 +292,10 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         if self.streaming:
             completion = ""
             async for chunk in self._astream(
-                prompt=prompt, stop=stop, run_manager=run_manager, **kwargs
+                prompt=prompt,
+                stop=stop,
+                run_manager=run_manager,
+                **kwargs,
             ):
                 completion += chunk.text
             return completion
@@ -308,8 +322,12 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         Args:
             prompt: The prompt to pass into the model.
             stop: Optional list of stop words to use when generating.
+            run_manager: Optional callback manager for LLM run.
+            kwargs: Additional keyword arguments to pass to the model.
+
         Returns:
             A generator representing the stream of tokens from Anthropic.
+
         Example:
 
             .. code-block:: python
@@ -319,12 +337,16 @@ class AnthropicLLM(LLM, _AnthropicCommon):
                 generator = anthropic.stream(prompt)
                 for token in generator:
                     yield token
+
         """
         stop = self._get_anthropic_stop(stop)
         params = {**self._default_params, **kwargs}
 
         for token in self.client.completions.create(
-            prompt=self._wrap_prompt(prompt), stop_sequences=stop, stream=True, **params
+            prompt=self._wrap_prompt(prompt),
+            stop_sequences=stop,
+            stream=True,
+            **params,
         ):
             chunk = GenerationChunk(text=token.completion)
 
@@ -344,8 +366,12 @@ class AnthropicLLM(LLM, _AnthropicCommon):
         Args:
             prompt: The prompt to pass into the model.
             stop: Optional list of stop words to use when generating.
+            run_manager: Optional callback manager for LLM run.
+            kwargs: Additional keyword arguments to pass to the model.
+
         Returns:
             A generator representing the stream of tokens from Anthropic.
+
         Example:
             .. code-block:: python
 
@@ -354,6 +380,7 @@ class AnthropicLLM(LLM, _AnthropicCommon):
                 generator = anthropic.stream(prompt)
                 for token in generator:
                     yield token
+
         """
         stop = self._get_anthropic_stop(stop)
         params = {**self._default_params, **kwargs}
@@ -372,15 +399,16 @@ class AnthropicLLM(LLM, _AnthropicCommon):
 
     def get_num_tokens(self, text: str) -> int:
         """Calculate number of tokens."""
-        raise NotImplementedError(
+        msg = (
             "Anthropic's legacy count_tokens method was removed in anthropic 0.39.0 "
             "and langchain-anthropic 0.3.0. Please use "
             "ChatAnthropic.get_num_tokens_from_messages instead."
         )
+        raise NotImplementedError(
+            msg,
+        )
 
 
 @deprecated(since="0.1.0", removal="1.0.0", alternative="AnthropicLLM")
 class Anthropic(AnthropicLLM):
     """Anthropic large language model."""
-
-    pass