[Bugfix] Fix KeyError in parse_response_input for reasoning items with optional content

tests/entrypoints/openai/parser/test_harmony_utils.py

@@ -14,6 +14,7 @@
     parse_chat_output,
 )
 from vllm.entrypoints.openai.responses.harmony import (
+    response_input_to_harmony,
     response_previous_input_to_harmony,
 )
 
@@ -841,3 +842,89 @@ def test_all_standard_channels_present(self) -> None:
                 assert channel in valid_channels, (
                     f"{channel} missing when with_custom_tools={with_tools}"
                 )
+
+
+class TestResponseInputToHarmonyReasoningItem:
+    """Tests for response_input_to_harmony handling of reasoning input items.
+
+    Per the OpenAI spec, ResponseReasoningItem.content is
+    Optional[List[Content]] = None. Clients like langchain-openai may omit
+    this field when constructing multi-turn input from previous responses.
+
+    Reasoning items with content are converted to Harmony messages on the
+    'analysis' channel. All content items are concatenated. Items without
+    content return None (skipped by the caller).
+    """
+
+    def test_reasoning_with_single_content(self):
+        """Test reasoning item with a single content entry."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_123",
+            "content": [{"type": "reasoning_text", "text": "Thinking step by step"}],
+        }
+
+        msg = response_input_to_harmony(item, prev_responses=[])
+
+        assert msg is not None
+        assert msg.author.role == Role.ASSISTANT
+        assert msg.content[0].text == "Thinking step by step"
+        assert msg.channel == "analysis"
+
+    def test_reasoning_with_multiple_content_items(self):
+        """Test reasoning item with multiple content entries concatenated."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_123",
+            "content": [
+                {"type": "reasoning_text", "text": "First, let me analyze"},
+                {"type": "reasoning_text", "text": "Second, I should consider"},
+                {"type": "reasoning_text", "text": "Finally, the answer is"},
+            ],
+        }
+
+        msg = response_input_to_harmony(item, prev_responses=[])
+
+        assert msg is not None
+        assert msg.author.role == Role.ASSISTANT
+        assert msg.content[0].text == (
+            "First, let me analyze\nSecond, I should consider\nFinally, the answer is"
+        )
+        assert msg.channel == "analysis"
+
+    def test_reasoning_without_content_returns_none(self):
+        """Test reasoning item without content field returns None."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_123",
+            "summary": [{"type": "summary_text", "text": "Thinking about math"}],
+        }
+
+        msg = response_input_to_harmony(item, prev_responses=[])
+
+        assert msg is None
+
+    def test_reasoning_with_none_content_returns_none(self):
+        """Test reasoning item with content=None returns None."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_123",
+            "content": None,
+            "summary": [{"type": "summary_text", "text": "Thinking about math"}],
+        }
+
+        msg = response_input_to_harmony(item, prev_responses=[])
+
+        assert msg is None
+
+    def test_reasoning_with_empty_content_returns_none(self):
+        """Test reasoning item with empty content list returns None."""
+        item = {
+            "type": "reasoning",
+            "id": "rs_123",
+            "content": [],
+        }
+
+        msg = response_input_to_harmony(item, prev_responses=[])
+
+        assert msg is None

vllm/entrypoints/openai/responses/harmony.py

@@ -138,8 +138,12 @@ def _parse_chat_format_message(chat_msg: dict) -> list[Message]:
 def response_input_to_harmony(
     response_msg: ResponseInputOutputItem,
     prev_responses: list[ResponseOutputItem | ResponseReasoningItem],
-) -> Message:
-    """Convert a single ResponseInputOutputItem into a Harmony Message."""
+) -> Message | None:
+    """Convert a single ResponseInputOutputItem into a Harmony Message.
+
+    Returns None for reasoning items with empty or absent content so
+    the caller can skip them.
+    """
     if not isinstance(response_msg, dict):
         response_msg = response_msg.model_dump()
     if "type" not in response_msg or response_msg["type"] == "message":
@@ -172,9 +176,13 @@ def response_input_to_harmony(
             response_msg["output"],
         )
     elif response_msg["type"] == "reasoning":
-        content = response_msg["content"]
-        assert len(content) == 1
-        msg = Message.from_role_and_content(Role.ASSISTANT, content[0]["text"])
+        content = response_msg.get("content")
+        if content and len(content) >= 1:
+            reasoning_text = "\n".join(item["text"] for item in content)
+            msg = Message.from_role_and_content(Role.ASSISTANT, reasoning_text)
+            msg = msg.with_channel("analysis")
+        else:
+            return None
     elif response_msg["type"] == "function_call":
         msg = Message.from_role_and_content(Role.ASSISTANT, response_msg["arguments"])
         msg = msg.with_channel("commentary")

vllm/entrypoints/openai/responses/serving.py

@@ -1108,7 +1108,7 @@ def _construct_input_messages_with_harmony(
                 prev_outputs = []
             for response_msg in request.input:
                 new_msg = response_input_to_harmony(response_msg, prev_outputs)
-                if new_msg.author.role != "system":
+                if new_msg is not None and new_msg.author.role != "system":
                     messages.append(new_msg)
 
                 # User passes in a tool call request and its output. We need