fix(llm): prevent IndexError when reasoning items are absent in responses API

src/memos/llms/openai_new.py

@@ -50,7 +50,7 @@ def generate(self, messages: MessageList, **kwargs) -> str:
         output_reasoning = [
             item for item in response.output if isinstance(item, ResponseReasoningItem)
         ]
-        summary = output_reasoning[0].summary
+        summary = output_reasoning[0].summary if output_reasoning else None
 
         if self.config.remove_think_prefix:
             return remove_thinking_tags(output_text)
@@ -138,7 +138,7 @@ def generate(self, messages: MessageList, **kwargs) -> str:
         output_reasoning = [
             item for item in response.output if isinstance(item, ResponseReasoningItem)
         ]
-        summary = output_reasoning[0].summary
+        summary = output_reasoning[0].summary if output_reasoning else None
 
         if self.config.remove_think_prefix:
             return remove_thinking_tags(output_text)

tests/llms/test_openai_responses_llm.py

@@ -0,0 +1,104 @@
+"""Tests for OpenAIResponsesLLM and AzureResponsesLLM generate reasoning handling."""
+
+from types import SimpleNamespace
+from unittest.mock import MagicMock
+
+import pytest
+
+from openai.types.responses.response_reasoning_item import ResponseReasoningItem, Summary
+
+from memos.configs.llm import AzureLLMConfig, OpenAIResponsesLLMConfig
+from memos.llms.openai_new import AzureResponsesLLM, OpenAIResponsesLLM
+
+
+MESSAGES = [{"role": "user", "content": "Hello"}]
+
+
+def _make_openai_llm(
+    *, enable_thinking: bool = False, remove_think_prefix: bool = False
+) -> OpenAIResponsesLLM:
+    llm = OpenAIResponsesLLM.__new__(OpenAIResponsesLLM)
+    llm.config = OpenAIResponsesLLMConfig(
+        api_key="test-key",
+        model_name_or_path="gpt-4o",
+        enable_thinking=enable_thinking,
+        remove_think_prefix=remove_think_prefix,
+    )
+    llm.client = MagicMock()
+    return llm
+
+
+def _make_azure_llm(
+    *, enable_thinking: bool = False, remove_think_prefix: bool = False
+) -> AzureResponsesLLM:
+    llm = AzureResponsesLLM.__new__(AzureResponsesLLM)
+    llm.config = AzureLLMConfig(
+        api_key="test-key",
+        model_name_or_path="gpt-4o",
+        enable_thinking=enable_thinking,
+        remove_think_prefix=remove_think_prefix,
+    )
+    llm.client = MagicMock()
+    return llm
+
+
+@pytest.mark.parametrize(
+    "make_llm",
+    [_make_openai_llm, _make_azure_llm],
+    ids=["openai", "azure"],
+)
+class TestResponsesLLMGenerate:
+    def test_generate_without_reasoning_item_returns_output_text(self, make_llm):
+        llm = make_llm(enable_thinking=False)
+        llm.client.responses.create.return_value = SimpleNamespace(
+            output=[SimpleNamespace(type="message")],
+            output_text="plain answer",
+        )
+
+        result = llm.generate(MESSAGES)
+
+        assert result == "plain answer"
+
+    def test_generate_with_empty_reasoning_summary_returns_output_text(self, make_llm):
+        llm = make_llm(enable_thinking=True)
+        reasoning_item = ResponseReasoningItem(id="rs_1", summary=[], type="reasoning")
+        llm.client.responses.create.return_value = SimpleNamespace(
+            output=[reasoning_item],
+            output_text="plain answer",
+        )
+
+        result = llm.generate(MESSAGES)
+
+        assert result == "plain answer"
+
+    def test_generate_with_reasoning_summary_prepends_think_tag(self, make_llm):
+        llm = make_llm(enable_thinking=True, remove_think_prefix=False)
+        reasoning_item = ResponseReasoningItem(
+            id="rs_1",
+            summary=[Summary(text="step by step", type="summary_text")],
+            type="reasoning",
+        )
+        llm.client.responses.create.return_value = SimpleNamespace(
+            output=[reasoning_item],
+            output_text="final answer",
+        )
+
+        result = llm.generate(MESSAGES)
+
+        assert result == "<think>step by step</think>final answer"
+
+    def test_generate_with_remove_think_prefix_strips_thinking(self, make_llm):
+        llm = make_llm(enable_thinking=True, remove_think_prefix=True)
+        reasoning_item = ResponseReasoningItem(
+            id="rs_1",
+            summary=[Summary(text="step by step", type="summary_text")],
+            type="reasoning",
+        )
+        llm.client.responses.create.return_value = SimpleNamespace(
+            output=[reasoning_item],
+            output_text="<think>inline thought</think>final answer",
+        )
+
+        result = llm.generate(MESSAGES)
+
+        assert result == "final answer"