fix(audio): improve compatibility with third-party extensions (LazyAudioMap support)

aiia_e2e_diarizer.py

@@ -181,11 +181,36 @@ class AIIA_E2E_Speaker_Diarization:
         if not model_path:
             return (self._assign_speakers_to_chunks(whisper_chunks, [{"start":0, "end":0, "speaker":f"error_model_not_found_{backend_model}"}]),)
         
-        if audio is None or not isinstance(audio, dict) or \
-           "waveform" not in audio or not isinstance(audio["waveform"], torch.Tensor) or \
-           "sample_rate" not in audio or not isinstance(audio["sample_rate"], int) or \
-           audio["waveform"].ndim < 1:
-            print("错误: [AIIA E2E Diarization] 音频数据缺失、格式不正确或无效。")
+        if audio is None:
+             print("错误: [AIIA E2E Diarization] 音频数据为 None")
+             return (self._assign_speakers_to_chunks(whisper_chunks, [{"start":0, "end":0, "speaker":"error_no_audio"}]),)
+             
+        # Handle cases where audio might be passed as a single-item list
+        if isinstance(audio, list) and len(audio) > 0:
+            audio = audio[0]
+
+        # Try to treat as a dictionary or object with waveform/sample_rate
+        try:
+            waveform = audio["waveform"]
+            sample_rate = audio["sample_rate"]
+        except (KeyError, TypeError):
+             try:
+                 waveform = getattr(audio, "waveform", None)
+                 sample_rate = getattr(audio, "sample_rate", None)
+             except:
+                 waveform, sample_rate = None, None
+
+        if waveform is None or sample_rate is None:
+            print(f"错误: [AIIA E2E Diarization] 音频数据格式错误: 无法获取 waveform 或 sample_rate (输入类型: {type(audio)})")
+            return (self._assign_speakers_to_chunks(whisper_chunks, [{"start":0, "end":0, "speaker":"error_no_audio"}]),)
+
+        # Ensure waveform is a tensor and sample_rate is a number
+        if not isinstance(waveform, torch.Tensor) or not isinstance(sample_rate, (int, float)):
+             print(f"错误: [AIIA E2E Diarization] 音频数据类型错误: waveform={type(waveform)}, sample_rate={type(sample_rate)}")
+             return (self._assign_speakers_to_chunks(whisper_chunks, [{"start":0, "end":0, "speaker":"error_no_audio"}]),)
+
+        if waveform.ndim < 1:
+            print("错误: [AIIA E2E Diarization] 音频波形维度不足")
             return (self._assign_speakers_to_chunks(whisper_chunks, [{"start":0, "end":0, "speaker":"error_no_audio"}]),)
         
         if not isinstance(whisper_chunks, dict) or not isinstance(whisper_chunks.get("chunks"), list) :

aiia_generate_segments.py

@@ -172,11 +172,19 @@ class AIIA_GenerateSpeakerSegments:
         if isinstance(audio, list) and len(audio) > 0:
             audio = audio[0]
 
-        if not isinstance(audio, dict) or "waveform" not in audio or "sample_rate" not in audio:
-            return self._create_error_output(f"音频格式不匹配 (预期为 dict, 实际为 {type(audio)})")
+        # Try to treat as a dictionary or object with waveform/sample_rate
+        try:
+            waveform = audio["waveform"]
+            sample_rate = audio["sample_rate"]
+        except (KeyError, TypeError):
+             try:
+                 waveform = getattr(audio, "waveform", None)
+                 sample_rate = getattr(audio, "sample_rate", None)
+             except:
+                 waveform, sample_rate = None, None
 
-        waveform = audio["waveform"]
-        sample_rate = audio["sample_rate"]
+        if waveform is None or sample_rate is None:
+            return self._create_error_output(f"音频数据格式错误: 无法获取 waveform 或 sample_rate (输入类型: {type(audio)})")
 
         # Ensure waveform is a tensor and sample_rate is a number
         if not isinstance(waveform, torch.Tensor) or not isinstance(sample_rate, (int, float)):