FIX: warn instead of raising on reasoning-model token truncation

pyrit/prompt_target/openai/openai_chat_target.py

@@ -296,11 +296,16 @@ def _validate_response(self, response: Any, request: MessagePiece) -> Message |
             request: The original request MessagePiece.
 
         Returns:
-            None if valid, does not return Message for content filter (handled by _check_content_filter).
+            None when the response is valid and should be constructed normally. Returns an empty
+            response ``Message`` (with ``error="empty"``) when the response was truncated at the
+            token limit (``finish_reason="length"``) before producing any visible output, so the
+            run continues instead of raising. Content filter responses are handled separately by
+            ``_check_content_filter``.
 
         Raises:
             PyritException: For unexpected response structures or finish reasons.
-            EmptyResponseException: When the API returns an empty response.
+            EmptyResponseException: When the API returns an empty response that was not caused by
+                token-limit truncation.
         """
         # Check for missing choices
         if not hasattr(response, "choices") or not response.choices:
@@ -320,6 +325,25 @@ def _validate_response(self, response: Any, request: MessagePiece) -> Message |
         # Check for at least one valid response type
         has_content, has_audio, has_tool_calls = self._detect_response_content(choice.message)
 
+        # A "length" finish_reason means the model hit max_completion_tokens. Reasoning models spend
+        # tokens on hidden reasoning before emitting visible output, so a low limit can truncate the
+        # answer or leave it empty. This may be a deliberate configuration, so warn instead of raising.
+        if finish_reason == "length":
+            logger.warning(
+                "The response was truncated because it reached the token limit (finish_reason='length'). "
+                "Reasoning models consume tokens on hidden reasoning in addition to the visible answer, so a "
+                "low max_completion_tokens can truncate or empty the response. Increase max_completion_tokens "
+                "if you expected complete content."
+            )
+            if not (has_content or has_audio or has_tool_calls):
+                return construct_response_from_request(
+                    request=request,
+                    response_text_pieces=[""],
+                    response_type="text",
+                    error="empty",
+                )
+            return None
+
         if not (has_content or has_audio or has_tool_calls):
             logger.error("The chat returned an empty response (no content, audio, or tool_calls).")
             raise EmptyResponseException(

tests/unit/prompt_target/target/test_openai_chat_target.py

@@ -1039,11 +1039,26 @@ def test_validate_response_success_stop(target: OpenAIChatTarget, dummy_text_mes
     assert result is None
 
 
-def test_validate_response_success_length(target: OpenAIChatTarget, dummy_text_message_piece: MessagePiece):
-    """Test _validate_response passes for valid length response."""
+def test_validate_response_success_length(target: OpenAIChatTarget, dummy_text_message_piece: MessagePiece, caplog):
+    """Test _validate_response passes for a truncated response that still has content, and warns."""
     mock_response = create_mock_completion(content="Hello", finish_reason="length")
-    result = target._validate_response(mock_response, dummy_text_message_piece)
+    with caplog.at_level(logging.WARNING):
+        result = target._validate_response(mock_response, dummy_text_message_piece)
     assert result is None
+    assert "finish_reason='length'" in caplog.text
+
+
+def test_validate_response_length_empty_returns_empty_response(
+    target: OpenAIChatTarget, dummy_text_message_piece: MessagePiece, caplog
+):
+    """Test _validate_response returns a graceful empty response (no raise) when truncated before any output."""
+    mock_response = create_mock_completion(content="", finish_reason="length")
+    with caplog.at_level(logging.WARNING):
+        result = target._validate_response(mock_response, dummy_text_message_piece)
+    assert isinstance(result, Message)
+    assert result.message_pieces[0].original_value == ""
+    assert result.message_pieces[0].response_error == "empty"
+    assert "finish_reason='length'" in caplog.text
 
 
 def test_validate_response_no_choices(target: OpenAIChatTarget, dummy_text_message_piece: MessagePiece):