Merge 9a74100727 into 982d3a5476

litellm/llms/deepseek/chat/transformation.py

@@ -73,7 +73,8 @@ class DeepSeekChatConfig(OpenAIGPTConfig):
              (LiteLLM stores provider-specific response fields there).
           2. Otherwise inject a single space — the minimum value the API accepts.
         """
-        result: Final[list[AllMessageValues]] = []
+        result: list[AllMessageValues] = []
+        placeholder_injections = 0
         for msg in messages:
             if msg.get("role") == "assistant" and not msg.get("reasoning_content"):
                 patched = dict(cast(dict, msg))
@@ -85,20 +86,29 @@ class DeepSeekChatConfig(OpenAIGPTConfig):
                     cleaned.pop("reasoning_content", None)
                     patched["provider_specific_fields"] = cleaned
                 else:
-                    litellm.verbose_logger.warning(
-                        "DeepSeek thinking mode: assistant message is missing "
-                        "`reasoning_content` and none was saved in "
-                        "`provider_specific_fields`. A single-space placeholder "
-                        "is being injected to satisfy API validation, but the "
-                        "model will receive a blank reasoning chain for this turn, "
-                        "which may silently degrade multi-turn response quality. "
-                        "Preserve `reasoning_content` from the original assistant "
-                        "response when building multi-turn conversation history."
-                    )
+                    placeholder_injections += 1
                     patched["reasoning_content"] = " "
                 result.append(cast(AllMessageValues, patched))
             else:
                 result.append(msg)
+
+        # Emit a single aggregated warning per request instead of one per
+        # affected message. The old per-message warning produced an identical
+        # line for every historical assistant turn (issue #37629): a 6-message
+        # conversation logged 6 copies on every request, drowning out real
+        # errors. Aggregating keeps the diagnostic while reporting the count.
+        if placeholder_injections:
+            litellm.verbose_logger.warning(
+                "DeepSeek thinking mode: %d assistant message(s) were missing "
+                "`reasoning_content` and none was saved in "
+                "`provider_specific_fields`. A single-space placeholder was "
+                "injected for each to satisfy API validation, but the model "
+                "will receive a blank reasoning chain for those turns, which "
+                "may silently degrade multi-turn response quality. Preserve "
+                "`reasoning_content` from the original assistant response when "
+                "building multi-turn conversation history.",
+                placeholder_injections,
+            )
         return result
 
     @overload

tests/test_litellm/llms/deepseek/chat/test_deepseek_chat_transformation.py

@@ -1,7 +1,113 @@
+import logging
+from copy import deepcopy
+
 import litellm
 from litellm.llms.deepseek.chat.transformation import DeepSeekChatConfig
 
 
+class _ListHandler(logging.Handler):
+    def __init__(self) -> None:
+        super().__init__(level=logging.WARNING)
+        self.records: list[logging.LogRecord] = []
+
+    def emit(self, record: logging.LogRecord) -> None:
+        self.records.append(record)
+
+
+def _capture_reasoning_warnings(messages):
+    handler = _ListHandler()
+    logger = litellm.verbose_logger
+    previous_level = logger.level
+    logger.addHandler(handler)
+    logger.setLevel(logging.WARNING)
+    try:
+        result = DeepSeekChatConfig()._fill_reasoning_content(messages)
+    finally:
+        logger.removeHandler(handler)
+        logger.setLevel(previous_level)
+    records = [record for record in handler.records if "reasoning_content" in record.getMessage()]
+    return result, records
+
+
+def test_fill_reasoning_content_warns_once_per_request_with_count():
+    messages = [{"role": "system", "content": "You are helpful."}]
+    for index in range(6):
+        messages.append({"role": "user", "content": f"q{index}"})
+        messages.append({"role": "assistant", "content": f"a{index}"})
+
+    result, warning_records = _capture_reasoning_warnings(messages)
+
+    placeholders = [
+        message for message in result if message.get("role") == "assistant" and message.get("reasoning_content") == " "
+    ]
+    assert len(placeholders) == 6
+    assert len(warning_records) == 1
+    assert "6 assistant message(s)" in warning_records[0].getMessage()
+
+
+def test_fill_reasoning_content_does_not_warn_when_nothing_is_missing():
+    messages = [
+        {"role": "user", "content": "hi"},
+        {"role": "assistant", "content": "hello", "reasoning_content": "thinking"},
+        {
+            "role": "assistant",
+            "content": "sure",
+            "provider_specific_fields": {"reasoning_content": "stored"},
+        },
+    ]
+
+    _result, warning_records = _capture_reasoning_warnings(messages)
+
+    assert warning_records == []
+
+
+def test_transform_request_replays_warn_once_and_preserve_history():
+    messages = [
+        {"role": "user", "content": "Use both tools."},
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "first"}],
+            "reasoning_content": "",
+        },
+        {"role": "tool", "tool_call_id": "first", "content": "first result"},
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "second"}],
+            "reasoning_content": "",
+        },
+        {"role": "tool", "tool_call_id": "second", "content": "second result"},
+        {"role": "user", "content": "Continue."},
+    ]
+    original_messages = deepcopy(messages)
+    handler = _ListHandler()
+    logger = litellm.verbose_logger
+    previous_level = logger.level
+    logger.addHandler(handler)
+    logger.setLevel(logging.WARNING)
+    try:
+        results = [
+            DeepSeekChatConfig().transform_request(
+                model="deepseek-reasoner",
+                messages=messages,
+                optional_params={"thinking": {"type": "enabled"}},
+                litellm_params={},
+                headers={},
+            )
+            for _ in range(2)
+        ]
+    finally:
+        logger.removeHandler(handler)
+        logger.setLevel(previous_level)
+
+    warnings = [record for record in handler.records if "reasoning_content" in record.getMessage()]
+    assert len(warnings) == 2
+    assert all("2 assistant message(s)" in record.getMessage() for record in warnings)
+    assert all([result["messages"][index]["reasoning_content"] for index in (1, 3)] == [" ", " "] for result in results)
+    assert messages == original_messages
+
+
 def _function_tool(name: str) -> dict:
     return {
         "type": "function",