Add unused-ignore to type ignores for cross-version LangChain compatibility

These type ignores are needed for Python 3.9 + LangChain 0.3.x (real type errors)
but appear unused in Python 3.10+ + LangChain 1.x. Adding unused-ignore suppresses
the warning while keeping warn_unused_ignores=true as requested by reviewer.

Author: fede-kamel

libs/oci/langchain_oci/chat_models/oci_data_science.py

@@ -780,7 +780,7 @@ def bind_tools(
         formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
         if tool_choice is not None:
             kwargs["tool_choice"] = tool_choice
-        return super().bind(tools=formatted_tools, **kwargs)
+        return super().bind(tools=formatted_tools, **kwargs)  # type: ignore[return-value, unused-ignore]
 
 
 class ChatOCIModelDeploymentVLLM(ChatOCIModelDeployment):

libs/oci/langchain_oci/chat_models/oci_generative_ai.py

@@ -1287,7 +1287,7 @@ def bind_tools(
                 )
             kwargs["is_parallel_tool_calls"] = True
 
-        return super().bind(tools=formatted_tools, **kwargs)
+        return super().bind(tools=formatted_tools, **kwargs)  # type: ignore[return-value, unused-ignore]
 
     def with_structured_output(
         self,
@@ -1360,7 +1360,7 @@ def with_structured_output(
                     key_name=tool_name, first_tool_only=True
                 )
         elif method == "json_mode":
-            llm = self.bind(response_format={"type": "JSON_OBJECT"})
+            llm = self.bind(response_format={"type": "JSON_OBJECT"})  # type: ignore[assignment, unused-ignore]
             output_parser = (
                 PydanticOutputParser(pydantic_object=schema)
                 if is_pydantic_schema
@@ -1384,7 +1384,7 @@ def with_structured_output(
                 json_schema=response_json_schema
             )
 
-            llm = self.bind(response_format=response_format_obj)
+            llm = self.bind(response_format=response_format_obj)  # type: ignore[assignment, unused-ignore]
             if is_pydantic_schema:
                 output_parser = PydanticOutputParser(pydantic_object=schema)
             else:

libs/oci/tests/integration_tests/chat_models/test_openai_models.py

@@ -147,8 +147,8 @@ def test_openai_streaming(openai_config: dict):
 
     chunks = []
     for chunk in chat.stream([HumanMessage(content="Say hello")]):
-        assert isinstance(chunk, AIMessage), "Chunk should be AIMessage"
-        chunks.append(chunk)
+        assert isinstance(chunk, AIMessage), "Chunk should be AIMessage"  # type: ignore[unreachable, unused-ignore]
+        chunks.append(chunk)  # type: ignore[unreachable, unused-ignore]
 
     # Verify we got at least one chunk (streaming worked)
     assert len(chunks) > 0, "Should receive at least one chunk"