fix(anthropic): don't mutate read-only requests and tighten system list typing

- copy the request before stripping the Claude Code identity so a read-only
  wire-body mapping (shadow evaluation) no longer raises TypeError on pop/assign
- annotate the system-list helper as list[object] instead of bare list
- drop a comment that restated the equality check it precedes
- add a regression test for the read-only request path

litellm/llms/anthropic/common_utils.py

@@ -143,7 +143,9 @@ def strip_claude_code_identity(text: str) -> str | None:
     return text
 
 
-def strip_claude_code_identity_from_system(system_param: str | list | None) -> str | list | None:
+def strip_claude_code_identity_from_system(
+    system_param: str | list[object] | None,
+) -> str | list[object] | None:
     """Strip Claude Code's self-identification sentence from a full system parameter.
 
     Unlike :func:`strip_claude_code_identity`, which operates on a single text
@@ -169,7 +171,6 @@ def strip_claude_code_identity_from_system(system_param: str | list | None) -> s
                 stripped_text = strip_claude_code_identity(text)
                 if stripped_text is None:
                     continue
-                # Only copy the block when the text changed.
                 if stripped_text == text:
                     filtered_list.append(content_block)
                 else:

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

@@ -1239,10 +1239,14 @@ class LiteLLMAnthropicMessagesAdapter:
         system_param: Final = anthropic_message_request.get("system")
         if system_param is not None:
             stripped_system = strip_claude_code_identity_from_system(system_param)
-            if stripped_system is None:
-                anthropic_message_request.pop("system", None)
-            elif stripped_system != system_param:
-                anthropic_message_request["system"] = stripped_system
+            if stripped_system is None or stripped_system != system_param:
+                # This adapter is also invoked with a read-only wire-body mapping
+                # (shadow evaluation); mutate a copy, never the caller's request.
+                anthropic_message_request = cast(AnthropicMessagesRequest, dict(anthropic_message_request))
+                if stripped_system is None:
+                    anthropic_message_request.pop("system", None)
+                else:
+                    anthropic_message_request["system"] = stripped_system
 
         ## CONVERT ANTHROPIC MESSAGES TO OPENAI
         messages_list: Final[list[AllAnthropicPassThroughMessageValues]] = cast(

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

@@ -143,7 +143,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
         return False
 
     @staticmethod
-    def _strip_claude_code_identity_from_system(system_param) -> str | list | None:
+    def _strip_claude_code_identity_from_system(system_param: str | list[object] | None) -> str | list[object] | None:
         """
         Strip Claude Code's self-identification sentence from system parameter.
 

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

@@ -2900,6 +2900,30 @@ def test_translate_anthropic_to_openai_strips_claude_code_identity(system, expec
         assert system_messages[0]["content"] == expected_system_content
 
 
+def test_translate_anthropic_to_openai_strips_claude_code_identity_read_only_request():
+    """Identity stripping must not mutate a read-only request (shadow evaluation passes a
+    MappingProxyType, so the adapter must copy before rewriting ``system``)."""
+    from types import MappingProxyType
+
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    request = MappingProxyType(
+        {
+            "model": "hosted_vllm/kimi-k3",
+            "max_tokens": 1024,
+            "messages": [{"role": "user", "content": "hi"}],
+            "system": f"{CLAUDE_CODE_IDENTITY}\nYou are an interactive agent.",
+        }
+    )
+
+    openai_request, _ = adapter.translate_anthropic_to_openai(
+        anthropic_message_request=request,
+        custom_llm_provider="hosted_vllm",
+    )
+
+    system_messages = [m for m in openai_request["messages"] if m["role"] == "system"]
+    assert [m["content"] for m in system_messages] == ["You are an interactive agent."]
+
+
 def test_translate_openai_content_to_anthropic_reasoning_content_without_thinking_blocks():
     """
     Test that reasoning_content is converted to thinking block when thinking_blocks is not present.