Fix unit tests

api/src/services/audio.py

@@ -156,7 +156,7 @@ class AudioService:
             speed: The speaking speed of the voice
             chunk_text: The text sent to the model to generate the resulting speech
             is_last_chunk: Whether this is the last chunk
-            is_silent_chunk: Whether this chunk is a silent tag (e.g., [Silent](0.5s))
+            is_silent_chunk: Whether this chunk is a silent tag. e.g. [Silent 0.5s]
             trim_audio: Whether audio should be trimmed
             normalizer: Optional AudioNormalizer instance for consistent normalization
 

api/src/services/text_processing/text_processor.py

@@ -108,10 +108,10 @@ def get_sentence_info(text: str, custom_phenomes_list: Dict[str, str]) -> List[T
                 del custom_phenomes_list[key]
                 
         # Handle silence tags
-        # Eg: "This is a test sentence, [silent](/1s/) with silence for one second."
+        # Eg: "This is a test sentence, [silent 0.5s] with silence for one second."
         while match := SILENCE_TAG.search(sentence):
             match_prefix = sentence[:match.start()] # `This is a test sentence, `
-            match_text = match.group(0)             # `[silent](/1s/)`
+            match_text = match.group(0)             # `[silent 0.5s]`
             match_suffix = sentence[match.end():]   # ` with silence for one second.`
             if match_prefix.strip():
                 tokens = process_text_chunk(match_prefix.strip())

api/src/services/tts_service.py

@@ -62,7 +62,7 @@ class TTSService:
         """Process tokens into audio."""
         async with self._chunk_semaphore:
             try:
-                # Handle silence tags, eg: `[silent](0.5s)`
+                # Handle silence tags, eg: `[silent 0.5s]`
                 if match := SILENCE_TAG.match(chunk_text):
                     silence_duration = float(match.group(1))
                     silence_audio = np.zeros(int(silence_duration * 24000), dtype=np.int16)

api/tests/test_kokoro_v1.py

@@ -19,7 +19,7 @@ def test_initial_state(kokoro_backend):
     assert kokoro_backend._model is None
     assert kokoro_backend._pipelines == {}  # Now using dict of pipelines
     # Device should be set based on settings
-    assert kokoro_backend.device in ["cuda", "cpu"]
+    assert kokoro_backend.device in ["cuda", "cpu", "mps"]
 
 
 @patch("torch.cuda.is_available", return_value=True)

api/tests/test_text_processor.py

@@ -121,7 +121,7 @@ async def test_smart_split_with_punctuation():
 @pytest.mark.asyncio
 async def test_smart_split_with_silence_tags():
     """Test smart splitting handles silence tags correctly."""
-    text = "This is a test sentence, [silent](/1s/) with silence for one second."
+    text = "This is a test sentence, [silent 1s] with silence for one second."
 
     chunks = []
     async for chunk_text, chunk_tokens in smart_split(text):
@@ -129,5 +129,5 @@ async def test_smart_split_with_silence_tags():
     
     assert len(chunks) == 3
     assert chunks[0] == "This is a test sentence, "
-    assert chunks[1] == "[silent](/1s/)"
+    assert chunks[1] == "[silent 1s]"
     assert chunks[2] == " with silence for one second."