From e54399eff7a13e649b6a353486922166b1bf5688 Mon Sep 17 00:00:00 2001
From: tusharjamunkar <tusharjamunkar569@gmail.com>
Date: Sat, 12 Sep 2026 23:07:31 +0530
Subject: [PATCH] test: add direct coverage for content_filter and refusal in
 anthropic and responses adapters

---
 ...al_pass_through_adapters_transformation.py | 40 ++++++++++++
 .../test_litellm_completion_responses.py      | 62 +++++++++++++++++++
 2 files changed, 102 insertions(+)

diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
index 03b9840b1c3..0e09e27f4db 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
@@ -102,6 +102,46 @@ def test_translate_chat_length_takes_precedence_over_refusal():
     assert result.get("stop_details") is None
 
 
+def test_translate_chat_content_filter_to_anthropic_response():
+    response = ModelResponse(
+        id="chatcmpl-content-filter",
+        model="openai-model",
+        choices=[
+            Choices(
+                index=0,
+                finish_reason="content_filter",
+                message=Message(content=None, role="assistant"),
+            )
+        ],
+        usage=Usage(prompt_tokens=1, completion_tokens=0, total_tokens=1),
+    )
+
+    result = LiteLLMAnthropicMessagesAdapter().translate_openai_response_to_anthropic(response)
+
+    assert result["content"] == []
+    assert result["stop_reason"] == "refusal"
+
+
+def test_translate_chat_refusal_finish_reason_to_anthropic_response():
+    response = ModelResponse(
+        id="chatcmpl-refusal-reason",
+        model="openai-model",
+        choices=[
+            Choices(
+                index=0,
+                finish_reason="refusal",
+                message=Message(content=None, role="assistant"),
+            )
+        ],
+        usage=Usage(prompt_tokens=1, completion_tokens=0, total_tokens=1),
+    )
+
+    result = LiteLLMAnthropicMessagesAdapter().translate_openai_response_to_anthropic(response)
+
+    assert result["content"] == []
+    assert result["stop_reason"] == "refusal"
+
+
 def test_translate_streaming_openai_chunk_to_anthropic_content_block():
     choices = [
         StreamingChoices(
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index 46249e50572..f2ebbf316c3 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
@@ -4246,3 +4246,65 @@ class TestStreamingSnapshotItemIds:
         reasoning_items = _bridged_output_items(completed_event.response, "reasoning")
         assert len(reasoning_items) == 1
         assert reasoning_items[0].id == streamed_event.item_id
+
+
+def test_transform_chat_completion_response_incomplete_details():
+    from openai.types.responses.response import IncompleteDetails
+
+    resp_length = ModelResponse(
+        id="resp-length",
+        choices=[Choices(index=0, finish_reason="length", message=Message(content="cutoff", role="assistant"))],
+        model="gpt-4o",
+    )
+    result_length = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+        request_input="test prompt",
+        responses_api_request={},
+        chat_completion_response=resp_length,
+    )
+    assert result_length.status == "incomplete"
+    assert result_length.incomplete_details is not None
+    assert result_length.incomplete_details.reason == "max_output_tokens"
+
+    resp_filter = ModelResponse(
+        id="resp-filter",
+        choices=[Choices(index=0, finish_reason="content_filter", message=Message(content=None, role="assistant"))],
+        model="gpt-4o",
+    )
+    result_filter = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+        request_input="test prompt",
+        responses_api_request={},
+        chat_completion_response=resp_filter,
+    )
+    assert result_filter.status == "incomplete"
+    assert result_filter.incomplete_details is not None
+    assert result_filter.incomplete_details.reason == "content_filter"
+
+    resp_refusal = ModelResponse(
+        id="resp-refusal",
+        choices=[Choices(index=0, finish_reason="refusal", message=Message(content=None, role="assistant"))],
+        model="gpt-4o",
+    )
+    result_refusal = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+        request_input="test prompt",
+        responses_api_request={},
+        chat_completion_response=resp_refusal,
+    )
+    assert result_refusal.status == "incomplete"
+    assert result_refusal.incomplete_details is not None
+    assert result_refusal.incomplete_details.reason == "content_filter"
+
+    existing_details = IncompleteDetails(reason="content_filter")
+    resp_existing = ModelResponse(
+        id="resp-existing",
+        choices=[Choices(index=0, finish_reason="length", message=Message(content="cutoff", role="assistant"))],
+        model="gpt-4o",
+    )
+    resp_existing.incomplete_details = existing_details
+    result_existing = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+        request_input="test prompt",
+        responses_api_request={},
+        chat_completion_response=resp_existing,
+    )
+    assert result_existing.status == "incomplete"
+    assert result_existing.incomplete_details == existing_details
+