Track bundled vendor runtime sources

vendor/funclip/tests/test_recognition_result_compat.py

@@ -0,0 +1,103 @@
+import sys
+import unittest
+from pathlib import Path
+
+import numpy as np
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT / "funclip"))
+
+from videoclipper import VideoClipper
+
+
+class DummyASRModel:
+    def __init__(self, result):
+        self.result = result
+
+    def generate(self, *args, **kwargs):
+        return [self.result]
+
+
+class TestRecognitionResultCompat(unittest.TestCase):
+    def _recognize(self, result):
+        clipper = VideoClipper(DummyASRModel(result))
+        clipper.lang = "zh"
+        audio = (16000, np.zeros(16000, dtype=np.float32))
+        return clipper.recog(audio)
+
+    def test_fun_asr_nano_result_without_sentence_info_or_raw_text_still_builds_state(self):
+        text, srt, state = self._recognize(
+            {
+                "key": "utt",
+                "text": "你好世界。",
+                "text_tn": "你好世界",
+                "timestamp": [[0, 500], [500, 1000]],
+                "sentence_info": [],
+            }
+        )
+
+        self.assertEqual(text, "你好世界。")
+        self.assertEqual(state["recog_res_raw"], "你好世界")
+        self.assertEqual(
+            state["sentences"],
+            [{"text": "你好世界。", "timestamp": [[0, 500], [500, 1000]]}],
+        )
+        self.assertIn("00:00:00,000 --> 00:00:01,000", srt)
+
+    def test_none_sentence_timestamp_falls_back_to_top_level_timestamp(self):
+        text, srt, state = self._recognize(
+            {
+                "key": "utt",
+                "text": "测试文本",
+                "raw_text": "测试文本",
+                "timestamp": [[0, 1000]],
+                "sentence_info": [{"text": "测试文本", "timestamp": None}],
+            }
+        )
+
+        self.assertEqual(text, "测试文本")
+        self.assertEqual(
+            state["sentences"], [{"text": "测试文本", "timestamp": [[0, 1000]]}]
+        )
+        self.assertIn("测试文本", srt)
+
+    def test_sensevoice_rich_tags_are_removed_from_text_and_srt(self):
+        text, srt, state = self._recognize(
+            {
+                "key": "utt",
+                "text": "<|zh|><|NEUTRAL|><|Speech|><|woitn|>你好世界",
+                "timestamp": [[0, 300], [300, 600], [600, 900], [900, 1200]],
+                "sentence_info": [
+                    {
+                        "text": "<|zh|><|NEUTRAL|><|Speech|><|woitn|>你好世界",
+                        "timestamp": [[0, 300], [300, 600], [600, 900], [900, 1200]],
+                    }
+                ],
+            }
+        )
+
+        self.assertEqual(text, "你好世界")
+        self.assertEqual(state["sentences"][0]["text"], "你好世界")
+        self.assertNotIn("<|zh|>", state["recog_res_raw"])
+        self.assertNotIn("<|zh|>", srt)
+
+    def test_long_token_level_sentence_is_split_into_subtitle_chunks(self):
+        long_text = "一二三四五六七八九十甲乙"
+        timestamps = [[i * 1000, (i + 1) * 1000] for i in range(len(long_text))]
+
+        _, srt, state = self._recognize(
+            {
+                "key": "utt",
+                "text": long_text,
+                "timestamp": timestamps,
+                "sentence_info": [{"text": long_text, "timestamp": timestamps}],
+            }
+        )
+
+        self.assertGreater(len(state["sentences"]), 1)
+        self.assertIn("00:00:00,000 --> 00:00:08,000", srt)
+        self.assertIn("00:00:08,000 --> 00:00:12,000", srt)
+
+
+if __name__ == "__main__":
+    unittest.main()