fix(responses): read prompt_cache_breakpoint without validating content blocks

The marker read ran every chat content block through
TypeAdapter(dict[str, object]).validate_python, which rejects dict blocks
with non-string keys that chat completion callers passing Python dicts
could previously send; the request then failed with a pydantic
ValidationError on the bridge keep path, the strip path, and the
image/file conversions alike. item is already isinstance-narrowed to a
dict at every read site, so read the marker with dict.get directly and
drop the adapter.

Adds a regression test covering text/image_url/file blocks carrying
non-string keys on both the keep (gpt-5.6) and strip (gpt-4o) paths.

litellm/completion_extras/litellm_responses_transformation/transformation.py

@@ -19,7 +19,7 @@ from openai.types.responses.response_input_param import (
 from openai.types.responses.tool_choice_custom_param import ToolChoiceCustomParam
 from openai.types.responses.tool_choice_function_param import ToolChoiceFunctionParam
 from openai.types.responses.tool_param import FunctionToolParam
-from pydantic import BaseModel, TypeAdapter
+from pydantic import BaseModel
 
 import litellm
 from litellm import ModelResponse
@@ -78,7 +78,6 @@ _CHAT_COMPLETION_FIELDS: Final = frozenset((*ModelResponse.model_fields, "usage"
 _RESPONSES_API_ONLY_FIELDS: Final = frozenset((*Response.model_fields, *ResponsesAPIResponse.model_fields)) - frozenset(
     ChatCompletion.model_fields
 )
-_CHAT_CONTENT_ITEM: Final = TypeAdapter(dict[str, object])
 
 
 def _strip_prompt_cache_breakpoint_from_content_block(value: object) -> object:
@@ -1118,7 +1117,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                     if original_type == "text":
                         converted = with_prompt_cache_breakpoint(
                             self._convert_content_str_to_input_text(item.get("text", ""), role),
-                            _CHAT_CONTENT_ITEM.validate_python(item).get("prompt_cache_breakpoint"),
+                            item.get("prompt_cache_breakpoint"),
                         )
                         result.append(converted)
                         verbose_logger.debug("Chat provider:   text -> %s", converted)
@@ -1131,7 +1130,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                                     role,
                                 )
                             ),
-                            _CHAT_CONTENT_ITEM.validate_python(item).get("prompt_cache_breakpoint"),
+                            item.get("prompt_cache_breakpoint"),
                         )
                         result.append(converted)
                         verbose_logger.debug("Chat provider:   image_url -> %s", converted)
@@ -1147,7 +1146,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                                 _input_file_from_file_value(
                                     cast("ChatCompletionFileObject", item).get("file"),  # cast-ok: type tag checked
                                 ),
-                                _CHAT_CONTENT_ITEM.validate_python(item).get("prompt_cache_breakpoint"),
+                                item.get("prompt_cache_breakpoint"),
                             )
                             result.append(converted)
                             verbose_logger.debug("Chat provider:   file -> %s", converted)

tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py

@@ -4233,6 +4233,44 @@ def test_prompt_cache_breakpoint_survives_chat_to_responses_conversion(
     assert request["prompt_cache_options"] == cache_breakpoint
 
 
+def test_prompt_cache_breakpoint_read_tolerates_non_string_content_block_keys() -> None:
+    handler: Final = LiteLLMResponsesTransformationHandler()
+    # Non-string keys are not JSON-representable but are accepted by chat completion
+    # callers passing Python dicts; reading the marker must not validate or reject them.
+    content: Final = [
+        {"type": "text", "text": "Stable prefix", 1: "ignored"},
+        {"type": "image_url", "image_url": "https://example.com/image.png", 2: "ignored"},
+        {"type": "file", "file": {"file_id": "file-123"}, 3: "ignored"},
+    ]
+    messages: Final = [{"role": "user", "content": content}]
+
+    for model in ("gpt-5.6", "gpt-4o"):  # marker keep path and strip path both read the block
+        request: dict[str, object] = handler.transform_request(
+            model=model,
+            messages=messages,
+            optional_params={},
+            litellm_params={},
+            headers={},
+            litellm_logging_obj=Mock(),
+        )
+
+        assert request["input"] == [
+            {
+                "type": "message",
+                "role": "user",
+                "content": [
+                    {"type": "input_text", "text": "Stable prefix"},
+                    {
+                        "type": "input_image",
+                        "image_url": "https://example.com/image.png",
+                        "detail": "auto",
+                    },
+                    {"type": "input_file", "file_id": "file-123"},
+                ],
+            }
+        ]
+
+
 def test_prompt_cache_breakpoints_are_dropped_for_unsupported_models() -> None:
     handler: Final = LiteLLMResponsesTransformationHandler()
     cache_breakpoint: Final = {"mode": "explicit"}