Handle None content in OpenAI representation (#2353)

bertopic/representation/_openai.py

@@ -229,9 +229,12 @@ def extract_topics(
 
             # Check whether content was actually generated
             # Addresses #1570 for potential issues with OpenAI's content filter
-            # Addresses #2176 for potential issues when openAI returns a None type object
-            if response and hasattr(response.choices[0].message, "content"):
-                label = response.choices[0].message.content.strip().replace("topic: ", "")
+            # Addresses #2176 and #2353 for potential issues when OpenAI returns a None
+            # type object. The ``content`` field is always present but can be ``None``
+            # (e.g. when ``finish_reason='content_filter'``), so ``hasattr`` is not enough.
+            content = response.choices[0].message.content if response else None
+            if content is not None:
+                label = content.strip().replace("topic: ", "")
             else:
                 label = "No label returned"
 

pyproject.toml

@@ -76,6 +76,7 @@ spacy = [
     "spacy>=3.0.1",
 ]
 test = [
+    "openai>=1.0.0",
     "pytest>=5.4.3",
     "pytest-cov>=2.6.1",
     "ruff~=0.14.0",

tests/test_representation/test_openai.py

@@ -0,0 +1,67 @@
+"""Unit tests for the OpenAI representation model."""
+
+from unittest.mock import MagicMock
+
+import pytest
+
+# The OpenAI representation imports the ``openai`` package at module load time,
+# so skip these tests entirely when it is not installed.
+pytest.importorskip("openai")
+
+from bertopic.representation._openai import OpenAI
+
+
+def _make_client(content):
+    """Build a mock OpenAI client whose chat completion returns ``content``."""
+    message = MagicMock()
+    message.content = content
+    choice = MagicMock()
+    choice.message = message
+    response = MagicMock()
+    response.choices = [choice]
+
+    client = MagicMock()
+    client.chat.completions.create.return_value = response
+    return client
+
+
+def _make_topic_model():
+    """Build a mock topic model returning a single topic with representative docs."""
+    topic_model = MagicMock()
+    topic_model.verbose = False
+    topic_model._extract_representative_docs.return_value = (
+        {0: ["A document about pets.", "Another document about pets."]},
+        None,
+        None,
+        None,
+    )
+    return topic_model
+
+
+def test_openai_extract_topics_handles_none_content():
+    """Regression test for #2353.
+
+    When OpenAI returns a message whose ``content`` is ``None`` (for example when the
+    response is blocked by the content filter and ``finish_reason='content_filter'``),
+    the ``content`` field is still present, so the previous ``hasattr`` guard passed
+    and ``None.strip()`` raised ``AttributeError``. The representation must instead
+    fall back to a placeholder label.
+    """
+    representation = OpenAI(_make_client(content=None))
+
+    updated_topics = representation.extract_topics(
+        _make_topic_model(), documents=None, c_tf_idf=None, topics={0: [("pets", 0.9)]}
+    )
+
+    assert updated_topics == {0: [("No label returned", 1)]}
+
+
+def test_openai_extract_topics_strips_normal_content():
+    """A normal (non-None) response is stripped and the ``topic: `` prefix removed."""
+    representation = OpenAI(_make_client(content="topic: Pets\n"))
+
+    updated_topics = representation.extract_topics(
+        _make_topic_model(), documents=None, c_tf_idf=None, topics={0: [("pets", 0.9)]}
+    )
+
+    assert updated_topics == {0: [("Pets", 1)]}