core: Add ruff rules RET

libs/core/langchain_core/_api/deprecation.py

@@ -443,8 +443,7 @@ def warn_deprecated(
                 f"{removal}"
             )
             raise NotImplementedError(msg)
-        else:
-            removal = f"in {removal}"
+        removal = f"in {removal}"
 
     if not message:
         message = ""

libs/core/langchain_core/agents.py

@@ -172,8 +172,7 @@ def _convert_agent_action_to_messages(
     """
     if isinstance(agent_action, AgentActionMessageLog):
         return agent_action.message_log
-    else:
-        return [AIMessage(content=agent_action.log)]
+    return [AIMessage(content=agent_action.log)]
 
 
 def _convert_agent_observation_to_messages(
@@ -192,14 +191,13 @@ def _convert_agent_observation_to_messages(
     """
     if isinstance(agent_action, AgentActionMessageLog):
         return [_create_function_message(agent_action, observation)]
-    else:
-        content = observation
-        if not isinstance(observation, str):
-            try:
-                content = json.dumps(observation, ensure_ascii=False)
-            except Exception:
-                content = str(observation)
-        return [HumanMessage(content=content)]
+    content = observation
+    if not isinstance(observation, str):
+        try:
+            content = json.dumps(observation, ensure_ascii=False)
+        except Exception:
+            content = str(observation)
+    return [HumanMessage(content=content)]
 
 
 def _create_function_message(

libs/core/langchain_core/beta/runnables/context.py

@@ -56,11 +56,10 @@ def _key_from_id(id_: str) -> str:
     wout_prefix = id_.split(CONTEXT_CONFIG_PREFIX, maxsplit=1)[1]
     if wout_prefix.endswith(CONTEXT_CONFIG_SUFFIX_GET):
         return wout_prefix[: -len(CONTEXT_CONFIG_SUFFIX_GET)]
-    elif wout_prefix.endswith(CONTEXT_CONFIG_SUFFIX_SET):
+    if wout_prefix.endswith(CONTEXT_CONFIG_SUFFIX_SET):
         return wout_prefix[: -len(CONTEXT_CONFIG_SUFFIX_SET)]
-    else:
-        msg = f"Invalid context config id {id_}"
-        raise ValueError(msg)
+    msg = f"Invalid context config id {id_}"
+    raise ValueError(msg)
 
 
 def _config_with_context(
@@ -190,8 +189,7 @@ def invoke(
         configurable = config.get("configurable", {})
         if isinstance(self.key, list):
             return {key: configurable[id_]() for key, id_ in zip(self.key, self.ids)}
-        else:
-            return configurable[self.ids[0]]()
+        return configurable[self.ids[0]]()
 
     async def ainvoke(
         self, input: Any, config: Optional[RunnableConfig] = None, **kwargs: Any
@@ -201,8 +199,7 @@ async def ainvoke(
         if isinstance(self.key, list):
             values = await asyncio.gather(*(configurable[id_]() for id_ in self.ids))
             return dict(zip(self.key, values))
-        else:
-            return await configurable[self.ids[0]]()
+        return await configurable[self.ids[0]]()
 
 
 SetValue = Union[
@@ -397,5 +394,4 @@ def setter(
 def _print_keys(keys: Union[str, Sequence[str]]) -> str:
     if isinstance(keys, str):
         return f"'{keys}'"
-    else:
-        return ", ".join(f"'{k}'" for k in keys)
+    return ", ".join(f"'{k}'" for k in keys)

libs/core/langchain_core/document_loaders/langsmith.py

@@ -122,8 +122,7 @@ def lazy_load(self) -> Iterator[Document]:
 def _stringify(x: Union[str, dict]) -> str:
     if isinstance(x, str):
         return x
-    else:
-        try:
-            return json.dumps(x, indent=2)
-        except Exception:
-            return str(x)
+    try:
+        return json.dumps(x, indent=2)
+    except Exception:
+        return str(x)

libs/core/langchain_core/documents/base.py

@@ -45,8 +45,7 @@ class BaseMedia(Serializable):
     def cast_id_to_str(cls, id_value: Any) -> Optional[str]:
         if id_value is not None:
             return str(id_value)
-        else:
-            return id_value
+        return id_value
 
 
 class Blob(BaseMedia):
@@ -163,9 +162,9 @@ def as_bytes(self) -> bytes:
         """Read data as bytes."""
         if isinstance(self.data, bytes):
             return self.data
-        elif isinstance(self.data, str):
+        if isinstance(self.data, str):
             return self.data.encode(self.encoding)
-        elif self.data is None and self.path:
+        if self.data is None and self.path:
             with open(str(self.path), "rb") as f:
                 return f.read()
         else:
@@ -306,5 +305,4 @@ def __str__(self) -> str:
         # a more general solution of formatting content directly inside the prompts.
         if self.metadata:
             return f"page_content='{self.page_content}' metadata={self.metadata}"
-        else:
-            return f"page_content='{self.page_content}'"
+        return f"page_content='{self.page_content}'"

libs/core/langchain_core/example_selectors/length_based.py

@@ -79,9 +79,8 @@ def select_examples(self, input_variables: dict[str, str]) -> list[dict]:
             new_length = remaining_length - self.example_text_lengths[i]
             if new_length < 0:
                 break
-            else:
-                examples.append(self.examples[i])
-                remaining_length = new_length
+            examples.append(self.examples[i])
+            remaining_length = new_length
             i += 1
         return examples
 

libs/core/langchain_core/example_selectors/semantic_similarity.py

@@ -54,8 +54,7 @@ def _example_to_text(
     ) -> str:
         if input_keys:
             return " ".join(sorted_values({key: example[key] for key in input_keys}))
-        else:
-            return " ".join(sorted_values(example))
+        return " ".join(sorted_values(example))
 
     def _documents_to_examples(self, documents: list[Document]) -> list[dict]:
         # Get the examples from the metadata.

libs/core/langchain_core/indexing/api.py

@@ -152,16 +152,15 @@ def _get_source_id_assigner(
     """Get the source id from the document."""
     if source_id_key is None:
         return lambda doc: None
-    elif isinstance(source_id_key, str):
+    if isinstance(source_id_key, str):
         return lambda doc: doc.metadata[source_id_key]
-    elif callable(source_id_key):
+    if callable(source_id_key):
         return source_id_key
-    else:
-        msg = (
-            f"source_id_key should be either None, a string or a callable. "
-            f"Got {source_id_key} of type {type(source_id_key)}."
-        )
-        raise ValueError(msg)
+    msg = (
+        f"source_id_key should be either None, a string or a callable. "
+        f"Got {source_id_key} of type {type(source_id_key)}."
+    )
+    raise ValueError(msg)
 
 
 def _deduplicate_in_order(

libs/core/langchain_core/language_models/base.py

@@ -141,8 +141,7 @@ def set_verbose(cls, verbose: Optional[bool]) -> bool:
         """
         if verbose is None:
             return _get_verbosity()
-        else:
-            return verbose
+        return verbose
 
     @property
     @override
@@ -349,8 +348,7 @@ def get_token_ids(self, text: str) -> list[int]:
         """
         if self.custom_get_token_ids is not None:
             return self.custom_get_token_ids(text)
-        else:
-            return _get_token_ids_default_method(text)
+        return _get_token_ids_default_method(text)
 
     def get_num_tokens(self, text: str) -> int:
         """Get the number of tokens present in the text.

libs/core/langchain_core/language_models/chat_models.py

@@ -259,16 +259,15 @@ def OutputType(self) -> Any:
     def _convert_input(self, input: LanguageModelInput) -> PromptValue:
         if isinstance(input, PromptValue):
             return input
-        elif isinstance(input, str):
+        if isinstance(input, str):
             return StringPromptValue(text=input)
-        elif isinstance(input, Sequence):
+        if isinstance(input, Sequence):
             return ChatPromptValue(messages=convert_to_messages(input))
-        else:
-            msg = (
-                f"Invalid input type {type(input)}. "
-                "Must be a PromptValue, str, or list of BaseMessages."
-            )
-            raise ValueError(msg)  # noqa: TRY004
+        msg = (
+            f"Invalid input type {type(input)}. "
+            "Must be a PromptValue, str, or list of BaseMessages."
+        )
+        raise ValueError(msg)  # noqa: TRY004
 
     def invoke(
         self,
@@ -565,10 +564,9 @@ def _get_llm_string(self, stop: Optional[list[str]] = None, **kwargs: Any) -> st
             _cleanup_llm_representation(serialized_repr, 1)
             llm_string = json.dumps(serialized_repr, sort_keys=True)
             return llm_string + "---" + param_string
-        else:
-            params = self._get_invocation_params(stop=stop, **kwargs)
-            params = {**params, **kwargs}
-            return str(sorted(params.items()))
+        params = self._get_invocation_params(stop=stop, **kwargs)
+        params = {**params, **kwargs}
+        return str(sorted(params.items()))
 
     def generate(
         self,
@@ -1024,9 +1022,8 @@ def __call__(
         ).generations[0][0]
         if isinstance(generation, ChatGeneration):
             return generation.message
-        else:
-            msg = "Unexpected generation type"
-            raise ValueError(msg)  # noqa: TRY004
+        msg = "Unexpected generation type"
+        raise ValueError(msg)  # noqa: TRY004
 
     async def _call_async(
         self,
@@ -1041,9 +1038,8 @@ async def _call_async(
         generation = result.generations[0][0]
         if isinstance(generation, ChatGeneration):
             return generation.message
-        else:
-            msg = "Unexpected generation type"
-            raise ValueError(msg)  # noqa: TRY004
+        msg = "Unexpected generation type"
+        raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="invoke", removal="1.0")
     def call_as_llm(
@@ -1059,9 +1055,8 @@ def predict(
         result = self([HumanMessage(content=text)], stop=_stop, **kwargs)
         if isinstance(result.content, str):
             return result.content
-        else:
-            msg = "Cannot use predict when output is not a string."
-            raise ValueError(msg)  # noqa: TRY004
+        msg = "Cannot use predict when output is not a string."
+        raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="invoke", removal="1.0")
     def predict_messages(
@@ -1084,9 +1079,8 @@ async def apredict(
         )
         if isinstance(result.content, str):
             return result.content
-        else:
-            msg = "Cannot use predict when output is not a string."
-            raise ValueError(msg)  # noqa: TRY004
+        msg = "Cannot use predict when output is not a string."
+        raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
     async def apredict_messages(
@@ -1259,8 +1253,7 @@ class AnswerWithJustification(BaseModel):
                 [parser_none], exception_key="parsing_error"
             )
             return RunnableMap(raw=llm) | parser_with_fallback
-        else:
-            return llm | output_parser
+        return llm | output_parser
 
 
 class SimpleChatModel(BaseChatModel):

libs/core/langchain_core/language_models/llms.py

@@ -249,8 +249,7 @@ def update_cache(
         prompt = prompts[missing_prompt_idxs[i]]
         if llm_cache is not None:
             llm_cache.update(prompt, llm_string, result)
-    llm_output = new_results.llm_output
-    return llm_output
+    return new_results.llm_output
 
 
 async def aupdate_cache(
@@ -283,8 +282,7 @@ async def aupdate_cache(
         prompt = prompts[missing_prompt_idxs[i]]
         if llm_cache:
             await llm_cache.aupdate(prompt, llm_string, result)
-    llm_output = new_results.llm_output
-    return llm_output
+    return new_results.llm_output
 
 
 class BaseLLM(BaseLanguageModel[str], ABC):
@@ -328,16 +326,15 @@ def OutputType(self) -> type[str]:
     def _convert_input(self, input: LanguageModelInput) -> PromptValue:
         if isinstance(input, PromptValue):
             return input
-        elif isinstance(input, str):
+        if isinstance(input, str):
             return StringPromptValue(text=input)
-        elif isinstance(input, Sequence):
+        if isinstance(input, Sequence):
             return ChatPromptValue(messages=convert_to_messages(input))
-        else:
-            msg = (
-                f"Invalid input type {type(input)}. "
-                "Must be a PromptValue, str, or list of BaseMessages."
-            )
-            raise ValueError(msg)  # noqa: TRY004
+        msg = (
+            f"Invalid input type {type(input)}. "
+            "Must be a PromptValue, str, or list of BaseMessages."
+        )
+        raise ValueError(msg)  # noqa: TRY004
 
     def _get_ls_params(
         self,
@@ -447,8 +444,7 @@ def batch(
             except Exception as e:
                 if return_exceptions:
                     return cast(list[str], [e for _ in inputs])
-                else:
-                    raise
+                raise
         else:
             batches = [
                 inputs[i : i + max_concurrency]
@@ -493,8 +489,7 @@ async def abatch(
             except Exception as e:
                 if return_exceptions:
                     return cast(list[str], [e for _ in inputs])
-                else:
-                    raise
+                raise
         else:
             batches = [
                 inputs[i : i + max_concurrency]
@@ -960,10 +955,9 @@ def generate(
                     callback_managers, prompts, run_name_list, run_ids_list
                 )
             ]
-            output = self._generate_helper(
+            return self._generate_helper(
                 prompts, stop, run_managers, bool(new_arg_supported), **kwargs
             )
-            return output
         if len(missing_prompts) > 0:
             run_managers = [
                 callback_managers[idx].on_llm_start(
@@ -1208,14 +1202,13 @@ async def agenerate(
                 ]
             )
             run_managers = [r[0] for r in run_managers]  # type: ignore[misc]
-            output = await self._agenerate_helper(
+            return await self._agenerate_helper(
                 prompts,
                 stop,
                 run_managers,  # type: ignore[arg-type]
                 bool(new_arg_supported),
                 **kwargs,  # type: ignore[arg-type]
             )
-            return output
         if len(missing_prompts) > 0:
             run_managers = await asyncio.gather(
                 *[