fix(openai): add type: message to Responses API input items (#35693)

libs/langchain_v1/tests/unit_tests/conftest.py

@@ -1,5 +1,6 @@
 """Configuration for unit tests."""
 
+import json
 from collections.abc import Iterator, Sequence
 from importlib import util
 from typing import Any
@@ -41,6 +42,7 @@ def remove_response_headers(response: dict[str, Any]) -> dict[str, Any]:
 def vcr_config() -> dict[str, Any]:
     """Extend the default configuration coming from langchain_tests."""
     config = base_vcr_config()
+    config["match_on"] = [m if m != "body" else "json_body" for m in config.get("match_on", [])]
     config.setdefault("filter_headers", []).extend(_EXTRA_HEADERS)
     config["before_record_request"] = remove_request_headers
     config["before_record_response"] = remove_response_headers
@@ -49,9 +51,27 @@ def vcr_config() -> dict[str, Any]:
     return config
 
 
+def _json_body_matcher(r1: Any, r2: Any) -> None:
+    """Match request bodies as parsed JSON, ignoring key order."""
+    b1 = r1.body or b""
+    b2 = r2.body or b""
+    if isinstance(b1, bytes):
+        b1 = b1.decode("utf-8")
+    if isinstance(b2, bytes):
+        b2 = b2.decode("utf-8")
+    try:
+        j1 = json.loads(b1)
+        j2 = json.loads(b2)
+    except (json.JSONDecodeError, ValueError):
+        assert b1 == b2, f"body mismatch (non-JSON):\n{b1}\n!=\n{b2}"
+        return
+    assert j1 == j2, f"body mismatch:\n{j1}\n!=\n{j2}"
+
+
 def pytest_recording_configure(config: dict[str, Any], vcr: VCR) -> None:  # noqa: ARG001
     vcr.register_persister(CustomPersister())
     vcr.register_serializer("yaml.gz", CustomSerializer())
+    vcr.register_matcher("json_body", _json_body_matcher)
 
 
 def pytest_addoption(parser: pytest.Parser) -> None:

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -4387,8 +4387,10 @@ def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
                         pass
                 msg["content"] = new_blocks
                 if msg["content"]:
+                    msg["type"] = "message"
                     input_.append(msg)
             else:
+                msg["type"] = "message"
                 input_.append(msg)
         else:
             input_.append(msg)

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -718,7 +718,9 @@ def test_image_token_counting_jpeg() -> None:
     actual = model.get_num_tokens_from_messages([message])
     assert expected == actual
 
-    image_data = base64.b64encode(httpx.get(image_url, timeout=10.0).content).decode("utf-8")
+    image_data = base64.b64encode(httpx.get(image_url, timeout=10.0).content).decode(
+        "utf-8"
+    )
     message = HumanMessage(
         content=[
             {"type": "text", "text": "describe the weather in this image"},
@@ -750,7 +752,9 @@ def test_image_token_counting_png() -> None:
     actual = model.get_num_tokens_from_messages([message])
     assert expected == actual
 
-    image_data = base64.b64encode(httpx.get(image_url, timeout=10.0).content).decode("utf-8")
+    image_data = base64.b64encode(httpx.get(image_url, timeout=10.0).content).decode(
+        "utf-8"
+    )
     message = HumanMessage(
         content=[
             {"type": "text", "text": "how many dice are in this image"},

libs/partners/openai/tests/integration_tests/chat_models/test_base_standard.py

@@ -92,7 +92,9 @@ class TestOpenAIStandard(ChatModelIntegrationTests):
     def test_openai_pdf_inputs(self, model: BaseChatModel) -> None:
         """Test that the model can process PDF inputs."""
         url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
-        pdf_data = base64.b64encode(httpx.get(url, timeout=10.0).content).decode("utf-8")
+        pdf_data = base64.b64encode(httpx.get(url, timeout=10.0).content).decode(
+            "utf-8"
+        )
 
         message = HumanMessage(
             [

libs/partners/openai/tests/integration_tests/chat_models/test_responses_standard.py

@@ -87,7 +87,9 @@ class TestOpenAIResponses(TestOpenAIStandard):
     def test_openai_pdf_tool_messages(self, model: BaseChatModel) -> None:
         """Test that the model can process PDF inputs in `ToolMessage` objects."""
         url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
-        pdf_data = base64.b64encode(httpx.get(url, timeout=10.0).content).decode("utf-8")
+        pdf_data = base64.b64encode(httpx.get(url, timeout=10.0).content).decode(
+            "utf-8"
+        )
 
         tool_message = ToolMessage(
             content_blocks=[

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -2151,6 +2151,7 @@ def test__construct_responses_api_input_human_message_with_text_blocks_conversio
     result = _construct_responses_api_input(messages)
 
     assert len(result) == 1
+    assert result[0]["type"] == "message"
     assert result[0]["role"] == "user"
     assert isinstance(result[0]["content"], list)
     assert len(result[0]["content"]) == 1
@@ -2267,6 +2268,7 @@ def test__construct_responses_api_input_human_message_with_image_url_conversion(
     result = _construct_responses_api_input(messages)
 
     assert len(result) == 1
+    assert result[0]["type"] == "message"
     assert result[0]["role"] == "user"
     assert isinstance(result[0]["content"], list)
     assert len(result[0]["content"]) == 2
@@ -2459,17 +2461,21 @@ def test__construct_responses_api_input_multiple_message_types() -> None:
     assert len(result) == len(messages)
 
     # Check system message
+    assert result[0]["type"] == "message"
     assert result[0]["role"] == "system"
     assert result[0]["content"] == "You are a helpful assistant."
 
+    assert result[1]["type"] == "message"
     assert result[1]["role"] == "system"
     assert result[1]["content"] == [
         {"type": "input_text", "text": "You are a very helpful assistant!"}
     ]
 
     # Check human message
+    assert result[2]["type"] == "message"
     assert result[2]["role"] == "user"
     assert result[2]["content"] == "What's the weather in San Francisco?"
+    assert result[3]["type"] == "message"
     assert result[3]["role"] == "user"
     assert result[3]["content"] == [
         {"type": "input_text", "text": "What's the weather in San Francisco?"}
@@ -2519,14 +2525,47 @@ def test__construct_responses_api_input_multiple_message_types() -> None:
     payload = llm._get_request_payload(message_dicts)
     result = payload["input"]
     assert len(result) == 2
+    assert result[0]["type"] == "message"
     assert result[0]["role"] == "developer"
     assert result[0]["content"] == "This is a developer message."
+    assert result[1]["type"] == "message"
     assert result[1]["role"] == "developer"
     assert result[1]["content"] == [
         {"type": "input_text", "text": "This is a developer message!"}
     ]
 
 
+def test__construct_responses_api_input_message_type_on_all_roles() -> None:
+    """Test that user/system/developer messages include type: 'message'.
+
+    Regression test for https://github.com/langchain-ai/langchain/issues/35688.
+    Strict OpenAI-compatible endpoints (e.g. Azure AI Foundry) require the
+    'type' field on every input item; omitting it causes HTTP 400.
+    """
+    messages: list = [
+        SystemMessage(content="You are helpful."),
+        HumanMessage(content="Hello"),
+        HumanMessage(content=[{"type": "text", "text": "Hello again"}]),
+    ]
+    result = _construct_responses_api_input(messages)
+
+    assert len(result) == 3
+    for item in result:
+        assert item["type"] == "message", (
+            f"Expected type='message' for role={item['role']}, got {item.get('type')!r}"
+        )
+
+    # Also test developer messages via dict input
+    llm = ChatOpenAI(model="o4-mini", use_responses_api=True)
+    payload = llm._get_request_payload(
+        [{"role": "developer", "content": "Translate English to Italian"}]
+    )
+    result = payload["input"]
+    assert len(result) == 1
+    assert result[0]["type"] == "message"
+    assert result[0]["role"] == "developer"
+
+
 def test_service_tier() -> None:
     llm = ChatOpenAI(model="o4-mini", service_tier="flex")
     payload = llm._get_request_payload([HumanMessage("Hello")])

libs/partners/openai/tests/unit_tests/test_tools.py

@@ -83,7 +83,7 @@ def test_custom_tool() -> None:
     ]
     payload = llm._get_request_payload(message_history)  # type: ignore[attr-defined]
     expected_input = [
-        {"content": "Use the tool", "role": "user"},
+        {"content": "Use the tool", "role": "user", "type": "message"},
         {
             "type": "custom_tool_call",
             "id": "ctc_abc123",