implement in core

libs/core/langchain_core/language_models/chat_models.py

@@ -11,10 +11,11 @@ from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Iterator, Sequence
 from functools import cached_property
 from operator import itemgetter
-from typing import (
+from typing import (  # noqa: UP035
     TYPE_CHECKING,
     Any,
     Callable,
+    Dict,
     Literal,
     Optional,
     Union,
@@ -70,11 +71,13 @@ from langchain_core.rate_limiters import BaseRateLimiter
 from langchain_core.runnables import RunnableMap, RunnablePassthrough
 from langchain_core.runnables.config import ensure_config, run_in_executor
 from langchain_core.tracers._streaming import _StreamingCallbackHandler
+from langchain_core.utils import get_pydantic_field_names
 from langchain_core.utils.function_calling import (
     convert_to_json_schema,
     convert_to_openai_tool,
 )
 from langchain_core.utils.pydantic import TypeBaseModel, is_basemodel_subclass
+from langchain_core.utils.utils import _build_model_kwargs
 
 if TYPE_CHECKING:
     import uuid
@@ -302,6 +305,9 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
     - If False (default), will always use streaming case if available.
     """
 
+    model_kwargs: Dict[str, Any] = Field(default_factory=dict)  # noqa: UP006
+    """Holds any model parameters valid for `create` call not explicitly specified."""
+
     @model_validator(mode="before")
     @classmethod
     def raise_deprecation(cls, values: dict) -> Any:
@@ -329,6 +335,13 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
         arbitrary_types_allowed=True,
     )
 
+    @model_validator(mode="before")
+    @classmethod
+    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)
+        return _build_model_kwargs(values, all_required_field_names)
+
     @cached_property
     def _serialized(self) -> dict[str, Any]:
         return dumpd(self)

libs/core/tests/unit_tests/language_models/chat_models/test_base.py

@@ -403,6 +403,40 @@ async def test_disable_streaming_no_streaming_model_async(
         break
 
 
+def test_model_kwargs() -> None:
+    llm = FakeListChatModel(
+        responses=["a", "b", "c"],
+        sleep=0.1,
+        disable_streaming=False,
+        model_kwargs={"foo": "bar"},
+    )
+    assert llm.responses == ["a", "b", "c"]
+    assert llm.sleep == 0.1
+    assert llm.disable_streaming is False
+    assert llm.model_kwargs == {"foo": "bar"}
+
+    with pytest.warns(match="transferred to model_kwargs"):
+        llm = FakeListChatModel(
+            responses=["a", "b", "c"],
+            sleep=0.1,
+            disable_streaming=False,
+            foo="bar",  # type: ignore[call-arg]
+        )
+    assert llm.responses == ["a", "b", "c"]
+    assert llm.sleep == 0.1
+    assert llm.disable_streaming is False
+    assert llm.model_kwargs == {"foo": "bar"}
+
+    # Backward compatibility
+    with pytest.warns(match="should be specified explicitly"):
+        llm = FakeListChatModel(  # type: ignore[call-arg]
+            model_kwargs={"foo": "bar", "responses": ["a", "b", "c"], "sleep": 0.1},
+        )
+    assert llm.responses == ["a", "b", "c"]
+    assert llm.sleep == 0.1
+    assert llm.model_kwargs == {"foo": "bar"}
+
+
 class FakeChatModelStartTracer(FakeTracer):
     def __init__(self) -> None:
         super().__init__()

libs/core/tests/unit_tests/runnables/__snapshots__/test_runnable.ambr

@@ -97,7 +97,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['foo, bar'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['foo, bar'])",
           "name": "FakeListChatModel"
         }
       ],
@@ -227,7 +227,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['baz, qux'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['baz, qux'])",
           "name": "FakeListChatModel"
         }
       ],
@@ -346,7 +346,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['foo, bar'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['foo, bar'])",
           "name": "FakeListChatModel"
         },
         {
@@ -457,7 +457,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['baz, qux'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['baz, qux'])",
           "name": "FakeListChatModel"
         }
       ],
@@ -1009,7 +1009,7 @@
 # name: test_prompt_with_chat_model
   '''
   ChatPromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], input_types={}, partial_variables={}, template='You are a nice assistant.'), additional_kwargs={}), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, template='{question}'), additional_kwargs={})])
-  | FakeListChatModel(responses=['foo'])
+  | FakeListChatModel(model_kwargs={}, responses=['foo'])
   '''
 # ---
 # name: test_prompt_with_chat_model.1
@@ -1109,7 +1109,7 @@
           "fake_chat_models",
           "FakeListChatModel"
         ],
-        "repr": "FakeListChatModel(responses=['foo'])",
+        "repr": "FakeListChatModel(model_kwargs={}, responses=['foo'])",
         "name": "FakeListChatModel"
       }
     },
@@ -1220,7 +1220,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['foo, bar'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['foo, bar'])",
           "name": "FakeListChatModel"
         }
       ],
@@ -1249,7 +1249,7 @@
 # name: test_prompt_with_chat_model_async
   '''
   ChatPromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], input_types={}, partial_variables={}, template='You are a nice assistant.'), additional_kwargs={}), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, template='{question}'), additional_kwargs={})])
-  | FakeListChatModel(responses=['foo'])
+  | FakeListChatModel(model_kwargs={}, responses=['foo'])
   '''
 # ---
 # name: test_prompt_with_chat_model_async.1
@@ -1349,7 +1349,7 @@
           "fake_chat_models",
           "FakeListChatModel"
         ],
-        "repr": "FakeListChatModel(responses=['foo'])",
+        "repr": "FakeListChatModel(model_kwargs={}, responses=['foo'])",
         "name": "FakeListChatModel"
       }
     },
@@ -13535,7 +13535,7 @@
     just_to_test_lambda: RunnableLambda(...)
   }
   | ChatPromptTemplate(input_variables=['documents', 'question'], input_types={}, partial_variables={}, messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], input_types={}, partial_variables={}, template='You are a nice assistant.'), additional_kwargs={}), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['documents', 'question'], input_types={}, partial_variables={}, template='Context:\n{documents}\n\nQuestion:\n{question}'), additional_kwargs={})])
-  | FakeListChatModel(responses=['foo, bar'])
+  | FakeListChatModel(model_kwargs={}, responses=['foo, bar'])
   | CommaSeparatedListOutputParser()
   '''
 # ---
@@ -13738,7 +13738,7 @@
             "fake_chat_models",
             "FakeListChatModel"
           ],
-          "repr": "FakeListChatModel(responses=['foo, bar'])",
+          "repr": "FakeListChatModel(model_kwargs={}, responses=['foo, bar'])",
           "name": "FakeListChatModel"
         }
       ],
@@ -13764,7 +13764,7 @@
   ChatPromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], input_types={}, partial_variables={}, template='You are a nice assistant.'), additional_kwargs={}), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['question'], input_types={}, partial_variables={}, template='{question}'), additional_kwargs={})])
   | RunnableLambda(...)
   | {
-      chat: FakeListChatModel(responses=["i'm a chatbot"]),
+      chat: FakeListChatModel(model_kwargs={}, responses=["i'm a chatbot"]),
       llm: FakeListLLM(responses=["i'm a textbot"])
     }
   '''
@@ -13890,7 +13890,7 @@
                 "fake_chat_models",
                 "FakeListChatModel"
               ],
-              "repr": "FakeListChatModel(responses=[\"i'm a chatbot\"])",
+              "repr": "FakeListChatModel(model_kwargs={}, responses=[\"i'm a chatbot\"])",
               "name": "FakeListChatModel"
             },
             "llm": {
@@ -14045,7 +14045,7 @@
                     "fake_chat_models",
                     "FakeListChatModel"
                   ],
-                  "repr": "FakeListChatModel(responses=[\"i'm a chatbot\"])",
+                  "repr": "FakeListChatModel(model_kwargs={}, responses=[\"i'm a chatbot\"])",
                   "name": "FakeListChatModel"
                 },
                 "kwargs": {