core[patch]: move some attr/methods to BaseLanguageModel (#18936)

Cleans up some shared code between `BaseLLM` and `BaseChatModel`. One
functional difference to make it more consistent (see comment)

libs/core/langchain_core/language_models/base.py

@@ -7,6 +7,7 @@ from typing import (
     Any,
     Dict,
     List,
+    Mapping,
     Optional,
     Sequence,
     Set,
@@ -25,7 +26,7 @@ from langchain_core.messages import (
     get_buffer_string,
 )
 from langchain_core.prompt_values import PromptValue
-from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.pydantic_v1 import BaseModel, Field, validator
 from langchain_core.runnables import Runnable, RunnableSerializable
 from langchain_core.utils import get_pydantic_field_names
 
@@ -63,6 +64,12 @@ LanguageModelLike = Runnable[LanguageModelInput, LanguageModelOutput]
 LanguageModelOutputVar = TypeVar("LanguageModelOutputVar", BaseMessage, str)
 
 
+def _get_verbosity() -> bool:
+    from langchain_core.globals import get_verbose
+
+    return get_verbose()
+
+
 class BaseLanguageModel(
     RunnableSerializable[LanguageModelInput, LanguageModelOutputVar], ABC
 ):
@@ -71,6 +78,28 @@ class BaseLanguageModel(
     All language model wrappers inherit from BaseLanguageModel.
     """
 
+    cache: Optional[bool] = None
+    """Whether to cache the response."""
+    verbose: bool = Field(default_factory=_get_verbosity)
+    """Whether to print out response text."""
+    callbacks: Callbacks = Field(default=None, exclude=True)
+    """Callbacks to add to the run trace."""
+    tags: Optional[List[str]] = Field(default=None, exclude=True)
+    """Tags to add to the run trace."""
+    metadata: Optional[Dict[str, Any]] = Field(default=None, exclude=True)
+    """Metadata to add to the run trace."""
+
+    @validator("verbose", pre=True, always=True)
+    def set_verbose(cls, verbose: Optional[bool]) -> bool:
+        """If verbose is None, set it.
+
+        This allows users to pass in None as verbose to access the global setting.
+        """
+        if verbose is None:
+            return _get_verbosity()
+        else:
+            return verbose
+
     @property
     def InputType(self) -> TypeAlias:
         """Get the input type for this runnable."""
@@ -257,6 +286,11 @@ class BaseLanguageModel(
             Top model prediction as a message.
         """
 
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        """Get the identifying parameters."""
+        return {}
+
     def get_token_ids(self, text: str) -> List[int]:
         """Return the ordered ids of the tokens in a text.
 

libs/core/langchain_core/language_models/chat_models.py

@@ -54,12 +54,6 @@ if TYPE_CHECKING:
     from langchain_core.runnables import RunnableConfig
 
 
-def _get_verbosity() -> bool:
-    from langchain_core.globals import get_verbose
-
-    return get_verbose()
-
-
 def generate_from_stream(stream: Iterator[ChatGenerationChunk]) -> ChatResult:
     """Generate from a stream."""
 
@@ -125,18 +119,8 @@ def _as_async_iterator(sync_iterator: Callable) -> Callable:
 class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
     """Base class for Chat models."""
 
-    cache: Optional[bool] = None
-    """Whether to cache the response."""
-    verbose: bool = Field(default_factory=_get_verbosity)
-    """Whether to print out response text."""
-    callbacks: Callbacks = Field(default=None, exclude=True)
-    """Callbacks to add to the run trace."""
     callback_manager: Optional[BaseCallbackManager] = Field(default=None, exclude=True)
     """[DEPRECATED] Callback manager to add to the run trace."""
-    tags: Optional[List[str]] = Field(default=None, exclude=True)
-    """Tags to add to the run trace."""
-    metadata: Optional[Dict[str, Any]] = Field(default=None, exclude=True)
-    """Metadata to add to the run trace."""
 
     @root_validator()
     def raise_deprecation(cls, values: Dict) -> Dict:
@@ -816,11 +800,6 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             _stop = list(stop)
         return await self._call_async(messages, stop=_stop, **kwargs)
 
-    @property
-    def _identifying_params(self) -> Dict[str, Any]:
-        """Get the identifying parameters."""
-        return {}
-
     @property
     @abstractmethod
     def _llm_type(self) -> str:

libs/core/langchain_core/language_models/llms.py

@@ -1,4 +1,5 @@
 """Base interface for large language models to expose."""
+
 from __future__ import annotations
 
 import asyncio
@@ -16,7 +17,6 @@ from typing import (
     Dict,
     Iterator,
     List,
-    Mapping,
     Optional,
     Sequence,
     Tuple,
@@ -56,19 +56,13 @@ from langchain_core.messages import (
 )
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult, RunInfo
 from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPromptValue
-from langchain_core.pydantic_v1 import Field, root_validator, validator
+from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.runnables import RunnableConfig, ensure_config, get_config_list
 from langchain_core.runnables.config import run_in_executor
 
 logger = logging.getLogger(__name__)
 
 
-def _get_verbosity() -> bool:
-    from langchain_core.globals import get_verbose
-
-    return get_verbose()
-
-
 @functools.lru_cache
 def _log_error_once(msg: str) -> None:
     """Log an error once."""
@@ -200,16 +194,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
 
     It should take in a prompt and return a string."""
 
-    cache: Optional[bool] = None
-    """Whether to cache the response."""
-    verbose: bool = Field(default_factory=_get_verbosity)
-    """Whether to print out response text."""
-    callbacks: Callbacks = Field(default=None, exclude=True)
-    """Callbacks to add to the run trace."""
-    tags: Optional[List[str]] = Field(default=None, exclude=True)
-    """Tags to add to the run trace."""
-    metadata: Optional[Dict[str, Any]] = Field(default=None, exclude=True)
-    """Metadata to add to the run trace."""
     callback_manager: Optional[BaseCallbackManager] = Field(default=None, exclude=True)
     """[DEPRECATED]"""
 
@@ -229,17 +213,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             values["callbacks"] = values.pop("callback_manager", None)
         return values
 
-    @validator("verbose", pre=True, always=True)
-    def set_verbose(cls, verbose: Optional[bool]) -> bool:
-        """If verbose is None, set it.
-
-        This allows users to pass in None as verbose to access the global setting.
-        """
-        if verbose is None:
-            return _get_verbosity()
-        else:
-            return verbose
-
     # --- Runnable methods ---
 
     @property
@@ -1081,11 +1054,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         content = await self._call_async(text, stop=_stop, **kwargs)
         return AIMessage(content=content)
 
-    @property
-    def _identifying_params(self) -> Mapping[str, Any]:
-        """Get the identifying parameters."""
-        return {}
-
     def __str__(self) -> str:
         """Get a string representation of the object for printing."""
         cls_name = f"\033[1m{self.__class__.__name__}\033[0m"