multiple: enforce standards on tool_choice (#30372)

- Test if models support forcing tool calls via `tool_choice`. If they
do, they should support
  - `"any"` to specify any tool
  - the tool name as a string to force calling a particular tool
- Add `tool_choice` to signature of `BaseChatModel.bind_tools` in core
- Deprecate `tool_choice_value` in standard tests in favor of a boolean
`has_tool_choice`

Will follow up with PRs in external repos (tested in AWS and Google
already).

libs/partners/groq/tests/integration_tests/test_standard.py

@@ -1,6 +1,6 @@
 """Standard LangChain interface tests"""
 
-from typing import Optional, Type
+from typing import Type
 
 import pytest
 from langchain_core.language_models import BaseChatModel
@@ -40,11 +40,6 @@ class TestGroqLlama(BaseTestGroq):
             "rate_limiter": rate_limiter,
         }
 
-    @property
-    def tool_choice_value(self) -> Optional[str]:
-        """Value to use for tool choice when used in tests."""
-        return "any"
-
     @property
     def supports_json_mode(self) -> bool:
         return True

libs/partners/mistralai/langchain_mistralai/chat_models.py

@@ -685,6 +685,7 @@ class ChatMistralAI(BaseChatModel):
     def bind_tools(
         self,
         tools: Sequence[Union[Dict[str, Any], Type, Callable, BaseTool]],
+        tool_choice: Optional[Union[dict, str, Literal["auto", "any"]]] = None,
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, BaseMessage]:
         """Bind tool-like objects to this chat model.
@@ -705,6 +706,22 @@ class ChatMistralAI(BaseChatModel):
         """
 
         formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
+        if tool_choice:
+            tool_names = []
+            for tool in formatted_tools:
+                if "function" in tool and (name := tool["function"].get("name")):
+                    tool_names.append(name)
+                elif name := tool.get("name"):
+                    tool_names.append(name)
+                else:
+                    pass
+            if tool_choice in tool_names:
+                kwargs["tool_choice"] = {
+                    "type": "function",
+                    "function": {"name": tool_choice},
+                }
+            else:
+                kwargs["tool_choice"] = tool_choice
         return super().bind(tools=formatted_tools, **kwargs)
 
     def with_structured_output(

libs/partners/mistralai/tests/integration_tests/test_standard.py

@@ -1,6 +1,6 @@
 """Standard LangChain interface tests"""
 
-from typing import Optional, Type
+from typing import Type
 
 from langchain_core.language_models import BaseChatModel
 from langchain_tests.integration_tests import (  # type: ignore[import-not-found]
@@ -22,8 +22,3 @@ class TestMistralStandard(ChatModelIntegrationTests):
     @property
     def supports_json_mode(self) -> bool:
         return True
-
-    @property
-    def tool_choice_value(self) -> Optional[str]:
-        """Value to use for tool choice when used in tests."""
-        return "any"

libs/partners/xai/tests/integration_tests/test_chat_models_standard.py

@@ -1,6 +1,6 @@
 """Standard LangChain interface tests"""
 
-from typing import Optional, Type
+from typing import Type
 
 import pytest  # type: ignore[import-not-found]
 from langchain_core.language_models import BaseChatModel
@@ -30,11 +30,6 @@ class TestXAIStandard(ChatModelIntegrationTests):
             "rate_limiter": rate_limiter,
         }
 
-    @property
-    def tool_choice_value(self) -> Optional[str]:
-        """Value to use for tool choice when used in tests."""
-        return "tool_name"
-
     @pytest.mark.xfail(reason="Not yet supported.")
     def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
         super().test_usage_metadata_streaming(model)