community[patch]: fix structured_output in llamacpp integration

libs/community/langchain_community/chat_models/llamacpp.py

@@ -342,7 +342,7 @@ def bind_tools(
         self,
         tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
         *,
-        tool_choice: Optional[Union[Dict[str, Dict], bool, str]] = None,
+        tool_choice: Optional[Union[dict, bool, str]] = None,
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, BaseMessage]:
         """Bind tool-like objects to this chat model
@@ -538,7 +538,8 @@ class AnswerWithJustification(BaseModel):
                 "Received None."
             )
         tool_name = convert_to_openai_tool(schema)["function"]["name"]
-        llm = self.bind_tools([schema], tool_choice=tool_name)
+        tool_choice = {"type": "function", "function": {"name": tool_name}}
+        llm = self.bind_tools([schema], tool_choice=tool_choice)
         if is_pydantic_schema:
             output_parser: OutputParserLike = PydanticToolsParser(
                 tools=[cast(Type, schema)], first_tool_only=True

libs/community/tests/integration_tests/chat_models/test_llamacpp.py

@@ -0,0 +1,19 @@
+from pydantic import BaseModel, Field
+
+from langchain_community.chat_models import ChatLlamaCpp
+
+
+class Joke(BaseModel):
+    """Joke to tell user."""
+
+    setup: str = Field(description="question to set up a joke")
+    punchline: str = Field(description="answer to resolve the joke")
+
+
+# TODO: replace with standard integration tests
+# See example in tests/integration_tests/chat_models/test_litellm.py
+def test_structured_output() -> None:
+    llm = ChatLlamaCpp(model_path="/path/to/Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf")
+    structured_llm = llm.with_structured_output(Joke)
+    result = structured_llm.invoke("Tell me a short joke about cats.")
+    assert isinstance(result, Joke)