Merge 6d80592607 into 635085ac14

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

@@ -636,6 +636,25 @@ class LiteLLMAnthropicMessagesAdapter:
                     assistant_message["reasoning_content"] = reasoning_content
                 new_messages.append(assistant_message)
 
+        has_conversational_input = any(m.get("role") != "system" for m in replayable_messages)
+        has_translated_conversation = any(m.get("role") != "system" for m in new_messages)
+        if has_conversational_input and not has_translated_conversation:
+            unrecognized_block_types = sorted(
+                {
+                    str(content.get("type"))
+                    for message in replayable_messages
+                    if message.get("role") != "system" and isinstance(message.get("content"), list)
+                    for content in message["content"]
+                    if isinstance(content, dict) and content.get("type") is not None
+                }
+            )
+            type_list = ", ".join(json.dumps(block_type) for block_type in unrecognized_block_types) or "unknown"
+            raise litellm.BadRequestError(
+                message=f"Anthropic pass-through: every message's content blocks were of unrecognized types ({type_list}), so translation produced an empty conversation. Refusing to dispatch a request with no messages.",
+                model=model or "",
+                llm_provider="anthropic",
+            )
+
         return new_messages
 
     @staticmethod

tests/unit/llms/anthropic/pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py

@@ -5167,3 +5167,49 @@ def test_eager_input_streaming_tool_reaches_bedrock_converse_as_beta():
 
     assert data["additionalModelRequestFields"]["anthropic_beta"] == ["fine-grained-tool-streaming-2025-05-14"]
     assert data["toolConfig"]["tools"][0]["toolSpec"]["inputSchema"]["json"] == EAGER_INPUT_SCHEMA
+
+
+def test_translate_anthropic_to_openai_rejects_all_unrecognized_content_blocks():
+    request = {
+        "model": "openai/gpt-4o",
+        "max_tokens": 1024,
+        "messages": [{"role": "user", "content": [{"type": "not_a_real_block", "text": "hello"}]}],
+    }
+
+    with pytest.raises(litellm.BadRequestError, match="not_a_real_block"):
+        LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(request)
+
+    control_chars = {
+        **request,
+        "messages": [{"role": "user", "content": [{"type": "forged\nERROR: injected"}]}],
+    }
+    with pytest.raises(litellm.BadRequestError) as exc_info:
+        LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(control_chars)
+    assert "forged\\nERROR: injected" in str(exc_info.value)
+    assert "forged\nERROR: injected" not in str(exc_info.value)
+
+    with_system = {
+        **request,
+        "messages": [
+            {"role": "system", "content": "keep this"},
+            *request["messages"],
+        ],
+    }
+    with pytest.raises(litellm.BadRequestError):
+        LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(with_system)
+
+    mixed = {
+        "model": "openai/gpt-4o",
+        "max_tokens": 1024,
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "not_a_real_block", "text": "ignored"},
+                    {"type": "text", "text": "hello"},
+                ],
+            }
+        ],
+    }
+    openai_request, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(mixed)
+    assert openai_request["messages"] == [{"role": "user", "content": [{"type": "text", "text": "hello"}]}]