style(core): fix mypy no-any-return violations (#34204)

* FIxed where possible
* Used `cast` when not possible to fix

---------

Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>

libs/core/langchain_core/prompts/base.py

@@ -9,12 +9,7 @@ from abc import ABC, abstractmethod
 from collections.abc import Mapping  # noqa: TC003
 from functools import cached_property
 from pathlib import Path
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Generic,
-    TypeVar,
-)
+from typing import TYPE_CHECKING, Any, Generic, TypeVar, cast
 
 import yaml
 from pydantic import BaseModel, ConfigDict, Field, model_validator
@@ -122,7 +117,10 @@ class BasePromptTemplate(
 
     @cached_property
     def _serialized(self) -> dict[str, Any]:
-        return dumpd(self)
+        # self is always a Serializable object in this case, thus the result is
+        # guaranteed to be a dict since dumpd uses the default callback, which uses
+        # obj.to_json which always returns TypedDict subclasses
+        return cast("dict[str, Any]", dumpd(self))
 
     @property
     @override
@@ -156,7 +154,7 @@ class BasePromptTemplate(
         if not isinstance(inner_input, dict):
             if len(self.input_variables) == 1:
                 var_name = self.input_variables[0]
-                inner_input = {var_name: inner_input}
+                inner_input_ = {var_name: inner_input}
 
             else:
                 msg = (
@@ -168,12 +166,14 @@ class BasePromptTemplate(
                         message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT
                     )
                 )
-        missing = set(self.input_variables).difference(inner_input)
+        else:
+            inner_input_ = inner_input
+        missing = set(self.input_variables).difference(inner_input_)
         if missing:
             msg = (
                 f"Input to {self.__class__.__name__} is missing variables {missing}. "
                 f" Expected: {self.input_variables}"
-                f" Received: {list(inner_input.keys())}"
+                f" Received: {list(inner_input_.keys())}"
             )
             example_key = missing.pop()
             msg += (
@@ -184,7 +184,7 @@ class BasePromptTemplate(
             raise KeyError(
                 create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
             )
-        return inner_input
+        return inner_input_
 
     def _format_prompt_with_error_handling(self, inner_input: dict) -> PromptValue:
         inner_input_ = self._validate_input(inner_input)

libs/core/langchain_core/prompts/dict.py

@@ -2,7 +2,7 @@
 
 import warnings
 from functools import cached_property
-from typing import Any, Literal
+from typing import Any, Literal, cast
 
 from typing_extensions import override
 
@@ -65,7 +65,10 @@ class DictPromptTemplate(RunnableSerializable[dict, dict]):
 
     @cached_property
     def _serialized(self) -> dict[str, Any]:
-        return dumpd(self)
+        # self is always a Serializable object in this case, thus the result is
+        # guaranteed to be a dict since dumpd uses the default callback, which uses
+        # obj.to_json which always returns TypedDict subclasses
+        return cast("dict[str, Any]", dumpd(self))
 
     @classmethod
     def is_lc_serializable(cls) -> bool:
@@ -116,7 +119,7 @@ def _insert_input_variables(
     inputs: dict[str, Any],
     template_format: Literal["f-string", "mustache"],
 ) -> dict[str, Any]:
-    formatted = {}
+    formatted: dict[str, Any] = {}
     formatter = DEFAULT_FORMATTER_MAPPING[template_format]
     for k, v in template.items():
         if isinstance(v, str):
@@ -132,7 +135,7 @@ def _insert_input_variables(
                 warnings.warn(msg, stacklevel=2)
             formatted[k] = _insert_input_variables(v, inputs, template_format)
         elif isinstance(v, (list, tuple)):
-            formatted_v = []
+            formatted_v: list[str | dict[str, Any]] = []
             for x in v:
                 if isinstance(x, str):
                     formatted_v.append(formatter(x, **inputs))

libs/core/langchain_core/prompts/few_shot_with_templates.py

@@ -6,6 +6,7 @@ from typing import Any
 from pydantic import ConfigDict, model_validator
 from typing_extensions import Self
 
+from langchain_core.example_selectors import BaseExampleSelector
 from langchain_core.prompts.prompt import PromptTemplate
 from langchain_core.prompts.string import (
     DEFAULT_FORMATTER_MAPPING,
@@ -21,7 +22,7 @@ class FewShotPromptWithTemplates(StringPromptTemplate):
     """Examples to format into the prompt.
     Either this or example_selector should be provided."""
 
-    example_selector: Any = None
+    example_selector: BaseExampleSelector | None = None
     """ExampleSelector to choose the examples to format into the prompt.
     Either this or examples should be provided."""
 

libs/core/langchain_core/prompts/image.py

@@ -1,6 +1,6 @@
 """Image prompt template for a multimodal model."""
 
-from typing import Any
+from typing import Any, Literal, cast
 
 from pydantic import Field
 
@@ -125,7 +125,7 @@ class ImagePromptTemplate(BasePromptTemplate[ImageURL]):
         output: ImageURL = {"url": url}
         if detail:
             # Don't check literal values here: let the API check them
-            output["detail"] = detail
+            output["detail"] = cast("Literal['auto', 'low', 'high']", detail)
         return output
 
     async def aformat(self, **kwargs: Any) -> ImageURL:

libs/core/langchain_core/prompts/message.py

@@ -92,4 +92,4 @@ class BaseMessagePromptTemplate(Serializable, ABC):
         from langchain_core.prompts.chat import ChatPromptTemplate  # noqa: PLC0415
 
         prompt = ChatPromptTemplate(messages=[self])
-        return prompt + other
+        return prompt.__add__(other)

libs/core/langchain_core/prompts/string.py

@@ -3,11 +3,12 @@
 from __future__ import annotations
 
 import warnings
-from abc import ABC
+from abc import ABC, abstractmethod
 from string import Formatter
-from typing import TYPE_CHECKING, Any, Literal
+from typing import TYPE_CHECKING, Any, Literal, cast
 
 from pydantic import BaseModel, create_model
+from typing_extensions import override
 
 from langchain_core.prompt_values import PromptValue, StringPromptValue
 from langchain_core.prompts.base import BasePromptTemplate
@@ -189,17 +190,20 @@ def mustache_schema(template: str) -> type[BaseModel]:
     return _create_model_recursive("PromptInput", defs)
 
 
-def _create_model_recursive(name: str, defs: Defs) -> type:
-    return create_model(  # type: ignore[call-overload]
-        name,
-        **{
-            k: (_create_model_recursive(k, v), None) if v else (type(v), None)
-            for k, v in defs.items()
-        },
+def _create_model_recursive(name: str, defs: Defs) -> type[BaseModel]:
+    return cast(
+        "type[BaseModel]",
+        create_model(  # type: ignore[call-overload]
+            name,
+            **{
+                k: (_create_model_recursive(k, v), None) if v else (type(v), None)
+                for k, v in defs.items()
+            },
+        ),
     )
 
 
-DEFAULT_FORMATTER_MAPPING: dict[str, Callable] = {
+DEFAULT_FORMATTER_MAPPING: dict[str, Callable[..., str]] = {
     "f-string": formatter.format,
     "mustache": mustache_formatter,
     "jinja2": jinja2_formatter,
@@ -330,6 +334,10 @@ class StringPromptTemplate(BasePromptTemplate, ABC):
         """
         return StringPromptValue(text=await self.aformat(**kwargs))
 
+    @override
+    @abstractmethod
+    def format(self, **kwargs: Any) -> str: ...
+
     def pretty_repr(
         self,
         html: bool = False,  # noqa: FBT001,FBT002