Add tests for cache_control preservation in Responses API content transformation

tests/test_litellm/responses/litellm_completion_transformation/test_cache_control_preservation.py

@@ -0,0 +1,106 @@
+"""
+Tests for preserving cache_control in Responses API content transformation.
+
+Anthropic prompt caching requires a cache_control directive on content blocks.
+When transforming Responses API input items to Chat Completion messages, the
+cache_control field must be preserved on text content items.
+"""
+
+from litellm.responses.litellm_completion_transformation.transformation import (
+    LiteLLMCompletionResponsesConfig,
+)
+
+
+def test_cache_control_preserved_on_text_content():
+    """cache_control on a text content item should be preserved in the
+    transformed Chat Completion content block."""
+    content = [
+        {
+            "type": "input_text",
+            "text": "You are a helpful assistant.",
+            "cache_control": {"type": "ephemeral"},
+        }
+    ]
+
+    result = LiteLLMCompletionResponsesConfig._transform_responses_api_content_to_chat_completion_content(
+        content=content
+    )
+
+    assert len(result) == 1
+    assert result[0]["text"] == "You are a helpful assistant."
+    assert result[0]["cache_control"] == {"type": "ephemeral"}
+
+
+def test_cache_control_absent_when_not_provided():
+    """When cache_control is not on the input item, it should not appear
+    in the output."""
+    content = [
+        {
+            "type": "input_text",
+            "text": "Hello",
+        }
+    ]
+
+    result = LiteLLMCompletionResponsesConfig._transform_responses_api_content_to_chat_completion_content(
+        content=content
+    )
+
+    assert len(result) == 1
+    assert result[0]["text"] == "Hello"
+    assert "cache_control" not in result[0]
+
+
+def test_cache_control_only_on_tagged_items():
+    """In a mixed list, only the item with cache_control should have it."""
+    content = [
+        {"type": "input_text", "text": "first"},
+        {
+            "type": "input_text",
+            "text": "second",
+            "cache_control": {"type": "ephemeral"},
+        },
+        {"type": "input_text", "text": "third"},
+    ]
+
+    result = LiteLLMCompletionResponsesConfig._transform_responses_api_content_to_chat_completion_content(
+        content=content
+    )
+
+    assert len(result) == 3
+    assert "cache_control" not in result[0]
+    assert result[1]["cache_control"] == {"type": "ephemeral"}
+    assert "cache_control" not in result[2]
+
+
+def test_cache_control_end_to_end_via_input_items():
+    """cache_control should survive the full input-to-messages transformation."""
+    input_items = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "input_text",
+                    "text": "Cached system context",
+                    "cache_control": {"type": "ephemeral"},
+                },
+            ],
+        },
+    ]
+
+    messages = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+        input=input_items,
+        responses_api_request={},
+    )
+
+    # Find the user message
+    user_msgs = [
+        m for m in messages
+        if (m.get("role") if isinstance(m, dict) else getattr(m, "role", "")) == "user"
+    ]
+    assert len(user_msgs) == 1
+
+    content = user_msgs[0].get("content") if isinstance(user_msgs[0], dict) else getattr(user_msgs[0], "content", None)
+    assert isinstance(content, list)
+    text_blocks = [b for b in content if (b.get("type") if isinstance(b, dict) else getattr(b, "type", "")) == "text"]
+    assert len(text_blocks) == 1
+    assert text_blocks[0]["cache_control"] == {"type": "ephemeral"}