fix(anthropic): map stop_sequences to stop in /v1/messages adapter

litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py

@@ -324,6 +324,7 @@ class LiteLLMAnthropicMessagesAdapter:
         return [
             "messages",
             "metadata",
+            "stop_sequences",
             "system",
             "tool_choice",
             "tools",
@@ -903,6 +904,21 @@ class LiteLLMAnthropicMessagesAdapter:
             # metadata will be passed to litellm.acompletion(), it's a litellm_param
             new_kwargs["metadata"] = anthropic_message_request.pop("litellm_metadata")
 
+    def _translate_stop_sequences_to_openai(
+        self,
+        anthropic_message_request: AnthropicMessagesRequest,
+        new_kwargs: ChatCompletionRequest,
+    ) -> None:
+        """Translate Anthropic ``stop_sequences`` to OpenAI ``stop``.
+
+        Anthropic-native backends map OpenAI ``stop`` back to ``stop_sequences``,
+        while OpenAI-format providers reject the ``stop_sequences`` field, so the
+        adapter must normalize to ``stop`` rather than passing it through verbatim.
+        """
+        stop_sequences = anthropic_message_request.get("stop_sequences")
+        if stop_sequences:
+            new_kwargs["stop"] = stop_sequences
+
     def _translate_tool_choice_to_openai(
         self,
         anthropic_message_request: AnthropicMessagesRequest,
@@ -1082,6 +1098,11 @@ class LiteLLMAnthropicMessagesAdapter:
             anthropic_message_request=anthropic_message_request,
             new_kwargs=new_kwargs,
         )
+        ## CONVERT STOP SEQUENCES
+        self._translate_stop_sequences_to_openai(
+            anthropic_message_request=anthropic_message_request,
+            new_kwargs=new_kwargs,
+        )
         ## CONVERT TOOL CHOICE
         self._translate_tool_choice_to_openai(
             anthropic_message_request=anthropic_message_request,

tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py

@@ -3111,3 +3111,37 @@ def test_translate_anthropic_tools_to_openai_preserves_parameters_type():
     params = new_tools[0]["function"]["parameters"]
     assert params["type"] == "object"
     assert new_tools[0]["type"] == "function"
+
+
+def test_translate_anthropic_to_openai_maps_stop_sequences_to_stop():
+    """Regression for #33075: Anthropic `stop_sequences` must be translated to
+    the OpenAI `stop` param, otherwise OpenAI-format providers 400 on the
+    unknown `stop_sequences` field."""
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    request = {
+        "model": "azure_ai/gpt-4o",
+        "max_tokens": 100,
+        "messages": [{"role": "user", "content": "hi"}],
+        "stop_sequences": ["\n\nHuman:", "END"],
+    }
+
+    result, _ = adapter.translate_anthropic_to_openai(anthropic_message_request=cast(Any, request))
+
+    assert result["stop"] == ["\n\nHuman:", "END"]
+    assert "stop_sequences" not in result
+
+
+def test_translate_anthropic_to_openai_omits_stop_when_no_stop_sequences():
+    """No `stop` key should be added when the Anthropic request has no
+    `stop_sequences`."""
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    request = {
+        "model": "azure_ai/gpt-4o",
+        "max_tokens": 100,
+        "messages": [{"role": "user", "content": "hi"}],
+    }
+
+    result, _ = adapter.translate_anthropic_to_openai(anthropic_message_request=cast(Any, request))
+
+    assert "stop" not in result
+    assert "stop_sequences" not in result