init

tests/test_speech.py

@@ -0,0 +1,68 @@
+import tempfile
+import unittest
+from pathlib import Path
+
+from assistant_bot.speech import SpeechRecognitionError, SpeechRecognizer
+
+
+class FakeSegment:
+    def __init__(self, text: str) -> None:
+        self.text = text
+
+
+class SpeechRecognizerTests(unittest.TestCase):
+    def test_transcribe_joins_non_empty_segments(self) -> None:
+        factory_calls = []
+        transcribe_calls = []
+
+        class FakeModel:
+            def transcribe(self, audio_path, **kwargs):
+                transcribe_calls.append((audio_path, kwargs))
+                return iter(
+                    [FakeSegment(" Привет "), FakeSegment(""), FakeSegment("мир")]
+                ), None
+
+        def model_factory(*args, **kwargs):
+            factory_calls.append((args, kwargs))
+            return FakeModel()
+
+        recognizer = SpeechRecognizer(
+            model_name="small",
+            device="cpu",
+            compute_type="int8",
+            language="ru",
+            model_factory=model_factory,
+        )
+
+        with tempfile.TemporaryDirectory() as directory:
+            audio_path = Path(directory) / "voice.ogg"
+            result = recognizer.transcribe(audio_path)
+
+        self.assertEqual(result, "Привет мир")
+        self.assertEqual(
+            factory_calls[0],
+            (("small",), {"device": "cpu", "compute_type": "int8"}),
+        )
+        self.assertEqual(
+            transcribe_calls[0][1],
+            {"language": "ru", "beam_size": 5, "vad_filter": True},
+        )
+
+    def test_transcribe_wraps_model_errors(self) -> None:
+        def failing_factory(*_args, **_kwargs):
+            raise RuntimeError("model is unavailable")
+
+        recognizer = SpeechRecognizer(
+            model_name="small",
+            device="cpu",
+            compute_type="int8",
+            language=None,
+            model_factory=failing_factory,
+        )
+
+        with self.assertRaises(SpeechRecognitionError):
+            recognizer.transcribe("voice.ogg")
+
+
+if __name__ == "__main__":
+    unittest.main()