Fix mypy type errors for LangChain 1.x compatibility

- Update bind_tools signature to match BaseChatModel (AIMessage return,
  tool_choice parameter)
- Add isinstance checks for content type in integration tests
- Remove unused type: ignore comments
- Add proper type annotations for message lists
- Import AIMessage in oci_data_science.py

Author: fede-kamel

libs/oci/langchain_oci/chat_models/oci_data_science.py

@@ -31,7 +31,12 @@
     agenerate_from_stream,
     generate_from_stream,
 )
-from langchain_core.messages import AIMessageChunk, BaseMessage, BaseMessageChunk
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessage,
+    BaseMessageChunk,
+)
 from langchain_core.output_parsers import (
     JsonOutputParser,
     PydanticOutputParser,
@@ -765,10 +770,14 @@ def _process_response(self, response_json: dict) -> ChatResult:
 
     def bind_tools(
         self,
-        tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
+        tools: Sequence[Union[Dict[str, Any], type, Callable, BaseTool]],
+        *,
+        tool_choice: Optional[str] = None,
         **kwargs: Any,
-    ) -> Runnable[LanguageModelInput, BaseMessage]:
+    ) -> Runnable[LanguageModelInput, AIMessage]:
         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)
 
 

libs/oci/langchain_oci/chat_models/oci_generative_ai.py

@@ -931,8 +931,8 @@ def convert_to_oci_tool(
                     "required": parameters.get("required", []),
                 },
             )
-        elif isinstance(tool, BaseTool):  # type: ignore[unreachable]
-            return self.oci_function_definition(  # type: ignore[unreachable]
+        elif isinstance(tool, BaseTool):
+            return self.oci_function_definition(
                 name=tool.name,
                 description=OCIUtils.remove_signature_from_tool_description(
                     tool.name, tool.description
@@ -1206,13 +1206,13 @@ def _prepare_request(
 
     def bind_tools(
         self,
-        tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
+        tools: Sequence[Union[Dict[str, Any], type, Callable, BaseTool]],
         *,
         tool_choice: Optional[
             Union[dict, str, Literal["auto", "none", "required", "any"], bool]
         ] = None,
         **kwargs: Any,
-    ) -> Runnable[LanguageModelInput, BaseMessage]:
+    ) -> Runnable[LanguageModelInput, AIMessage]:
         """Bind tool-like objects to this chat model.
 
         Assumes model is compatible with Meta's tool-calling API.

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

@@ -308,6 +308,7 @@ def test_max_tokens_limit():
 
     # Response should be truncated due to max_tokens
     # Token count varies, but should be reasonably short
+    assert isinstance(response.content, str)
     assert len(response.content.split()) <= 20  # Rough word count check
 
 
@@ -405,7 +406,7 @@ def test_multi_turn_context_retention(llm):
 def test_long_context_handling(llm):
     """Test handling of longer context windows."""
     # Create a conversation with multiple turns
-    messages = [
+    messages: list[SystemMessage | HumanMessage | AIMessage] = [
         SystemMessage(content="You are a helpful assistant tracking a story."),
     ]
 
@@ -426,4 +427,5 @@ def test_long_context_handling(llm):
     messages.append(HumanMessage(content="What was the knight's horse named?"))
     final_response = llm.invoke(messages)
 
+    assert isinstance(final_response.content, str)
     assert "thunder" in final_response.content.lower()

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

@@ -71,7 +71,7 @@ def test_basic_invoke(chat_model):
     assert isinstance(response, AIMessage)
     assert response.content is not None
     assert len(response.content) > 0
-    assert "hello" in response.content.lower()
+    assert isinstance(response.content, str) and "hello" in response.content.lower()
 
 
 @pytest.mark.requires("oci")
@@ -100,7 +100,7 @@ def test_invoke_multi_turn(chat_model):
     response2 = chat_model.invoke(messages)
 
     assert isinstance(response2, AIMessage)
-    assert "alice" in response2.content.lower()
+    assert isinstance(response2.content, str) and "alice" in response2.content.lower()
 
 
 # =============================================================================
@@ -269,6 +269,7 @@ def test_response_format_json_object(chat_model):
     )
 
     assert isinstance(response, AIMessage)
+    assert isinstance(response.content, str)
     # Response should contain valid JSON (may be wrapped in markdown)
     import json
     import re

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

@@ -427,8 +427,9 @@ def should_continue(state: MessagesState):
     comprehensive analysis."""
 
     # Invoke agent with a diagnostic scenario
+    # Langgraph invoke signature is generic; passing dict is valid at runtime
     result = agent.invoke(
-        {
+        {  # type: ignore[arg-type]
             "messages": [
                 SystemMessage(content=system_prompt),
                 HumanMessage(

libs/oci/tests/unit_tests/chat_models/test_oci_data_science.py

@@ -80,7 +80,7 @@ def __init__(self, json_data: Dict, status_code: int = 200):
     def raise_for_status(self) -> None:
         """Mocked raise for status."""
         if 400 <= self.status_code < 600:
-            raise HTTPError(response=self)  # type: ignore[arg-type]
+            raise HTTPError(response=self)
 
     def json(self) -> Dict:
         """Returns mocked json data."""
@@ -152,7 +152,7 @@ def test_stream_vllm(*args: Any) -> None:
         if output is None:
             output = chunk
         else:
-            output += chunk  # type: ignore[assignment]
+            output += chunk
         count += 1
     # LangChain 1.x adds a final chunk with chunk_position='last', so we get 6 chunks
     assert count >= 5

libs/oci/tests/unit_tests/chat_models/test_oci_generative_ai_responses_api.py

@@ -385,7 +385,7 @@ def call_model(state: AgentState):
     # ---- Act ----
     app = workflow.compile()
     input_message = HumanMessage(content="What is the capital of France?")
-    result = app.invoke({"messages": [input_message]})
+    result = app.invoke({"messages": [input_message]})  # type: ignore[arg-type]
 
     # ---- Assert ----
     content = result["messages"][1].content[0]

libs/oci/tests/unit_tests/llms/test_oci_model_deployment_endpoint.py

@@ -61,7 +61,7 @@ def __init__(self, json_data: Dict, status_code: int = 200) -> None:
     def raise_for_status(self) -> None:
         """Mocked raise for status."""
         if 400 <= self.status_code < 600:
-            raise HTTPError(response=self)  # type: ignore[arg-type]
+            raise HTTPError(response=self)
 
     def json(self) -> Dict:
         """Returns mocked json data."""