Fix Generate LTX2 Prompt returning an empty string

Non-thinking mode primes a "final" channel, so the Gemma 4 tokenizer decodes
that channel's close marker to a bare </think> with no opening tag. Splitting on
the last </think> then kept everything after it, which is nothing: the node
output an empty string, blanking both Preview Any and the positive conditioning
it feeds in the Text to Video (LTX-2.5) template.

Fall back to the text before the unmatched close, and to the user prompt when
nothing usable is left, which is what both system prompts already ask for.

comfy_extras/nodes_textgen.py

@@ -211,6 +211,24 @@ AESTHETIC QUALITY (in addition to the above, without breaking the objective capt
 """
 
 
+LTX2_MARKERS = re.compile(r"</?think>|<\|channel>\w*\n?|<channel\|>|<\|turn>\w*\n?")
+
+
+def parse_ltx2_prompt(generated_text, prompt):
+    """Strip reasoning blocks and channel markers from the generated LTX2 prompt.
+
+    A close marker with no opening tag leaves nothing after the split, so fall back to the
+    text before it and then to the user prompt. Both system prompts ask for the original
+    prompt back when the model has nothing to give, and an empty string here silently
+    generates the video with no conditioning at all.
+    """
+    text = re.sub(r"<think>.*?</think>", "", generated_text, flags=re.DOTALL)
+    if "</think>" in text:  # unclosed/truncated reasoning: keep what follows the last close
+        head, _, tail = text.rpartition("</think>")
+        text = tail if LTX2_MARKERS.sub("", tail).strip() else head
+    return LTX2_MARKERS.sub("", text).strip() or prompt
+
+
 class TextGenerateLTX2Prompt(TextGenerate):
     @classmethod
     def define_schema(cls):
@@ -256,12 +274,7 @@ class TextGenerateLTX2Prompt(TextGenerate):
 
         out = super().execute(clip, formatted_prompt, max_length, sampling_mode, image=image, thinking=thinking, use_default_template=use_default_template, video=video, audio=audio)
 
-        text = out.args[0]
-        text = re.sub(r"<think>.*?</think>", "", text, flags=re.DOTALL)
-        if "</think>" in text:  # unclosed/truncated reasoning: keep what follows the last close
-            text = text.rsplit("</think>", 1)[-1]
-        text = re.sub(r"</?think>|<\|channel>\w*\n?|<channel\|>|<\|turn>\w*\n?", "", text).strip()
-        return io.NodeOutput(text)
+        return io.NodeOutput(parse_ltx2_prompt(out.args[0], prompt))
 
 
 class TextgenExtension(ComfyExtension):

tests-unit/comfy_extras_test/nodes_textgen_test.py

@@ -0,0 +1,42 @@
+from comfy_extras.nodes_textgen import parse_ltx2_prompt
+
+
+USER_PROMPT = "a fennec girl waving at the camera"
+
+
+class TestParseLTX2Prompt:
+    @staticmethod
+    def _parse(generated_text: str) -> str:
+        return parse_ltx2_prompt(generated_text, USER_PROMPT)
+
+    def test_plain_text(self):
+        assert self._parse("an enhanced prompt") == "an enhanced prompt"
+
+    def test_dangling_close_keeps_text_before_it(self):
+        # Non-thinking mode primes a "final" channel, whose close decodes to a lone </think>.
+        assert self._parse("an enhanced prompt</think>") == "an enhanced prompt"
+
+    def test_text_after_reasoning_block(self):
+        assert self._parse("<think>reasoning</think>an enhanced prompt") == "an enhanced prompt"
+
+    def test_reasoning_only_falls_back_to_prompt(self):
+        assert self._parse("<think>reasoning</think>") == USER_PROMPT
+
+    def test_empty_generation_falls_back_to_prompt(self):
+        assert self._parse("") == USER_PROMPT
+
+    def test_multiline_reasoning_block(self):
+        assert self._parse("<think>\nline one\nline two\n</think>\nan enhanced prompt") == "an enhanced prompt"
+
+    def test_reasoning_block_before_dangling_close(self):
+        assert self._parse("<think>reasoning</think>an enhanced prompt</think>") == "an enhanced prompt"
+
+    def test_channel_markers_are_stripped(self):
+        assert self._parse("<|channel>final\nan enhanced prompt<channel|>") == "an enhanced prompt"
+
+    def test_turn_markers_are_stripped(self):
+        assert self._parse("<|turn>model\nan enhanced prompt") == "an enhanced prompt"
+
+    def test_never_returns_empty(self):
+        for generated_text in ["an enhanced prompt</think>", "<think>x</think>", "<think>x</think>an enhanced prompt", "an enhanced prompt", "</think>", "<channel|>", "   "]:
+            assert self._parse(generated_text) != ""