Update app.py

app.py

@@ -1,50 +1,50 @@
-import gradio as gr
-from funasr import AutoModel
-import torch
-
-model_name = "iic/SenseVoice"
-
-device = "cuda:0" if torch.cuda.is_available() else "cpu"
-
-try:
-    model = AutoModel(
-        model=model_name,
-        vad_model="fsmn-vad",
-        vad_kwargs={"max_single_segment_time": 30000},
-        device=device,
-    )
-    model_loaded_successfully = True
-except Exception:
-    model = None
-    model_loaded_successfully = False
-
-
-def transcribe_audio(audio_file_path):
-    if not model_loaded_successfully:
-        return "模型加载失败。很可能是免费硬件的内存不足，请按教程切换到 'iic/SenseVoiceSmall' 模型。"
-
-    if audio_file_path is None:
-        return "错误：请上传或录制音频。"
-
-    res = model.generate(
-        input=audio_file_path,
-        batch_size_s=60,
-        language="auto",
-        use_itn=True,
-    )
-
-    return res[0]["text"]
-
-
-iface = gr.Interface(
-    fn=transcribe_audio,
-    inputs=gr.Audio(
-        sources=["upload", "microphone"], type="filepath", label="上传音频或录音"
-    ),
-    outputs=gr.Textbox(label="识别结果"),
-    title="SenseVoice 在线体验版",
-    description="应用启动时需要下载和加载模型，请耐心等待。",
-    allow_flagging="never",
-)
-
-iface.launch()
+import gradio as gr
+from funasr import AutoModel
+import torch
+
+model_name = "iic/SenseVoiceSmall"
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+try:
+    model = AutoModel(
+        model=model_name,
+        vad_model="fsmn-vad",
+        vad_kwargs={"max_single_segment_time": 30000},
+        device=device,
+    )
+    model_loaded_successfully = True
+except Exception:
+    model = None
+    model_loaded_successfully = False
+
+
+def transcribe_audio(audio_file_path):
+    if not model_loaded_successfully:
+        return "模型加载失败。很可能是免费硬件的内存不足，请按教程切换到 'iic/SenseVoiceSmall' 模型。"
+
+    if audio_file_path is None:
+        return "错误：请上传或录制音频。"
+
+    res = model.generate(
+        input=audio_file_path,
+        batch_size_s=60,
+        language="auto",
+        use_itn=True,
+    )
+
+    return res[0]["text"]
+
+
+iface = gr.Interface(
+    fn=transcribe_audio,
+    inputs=gr.Audio(
+        sources=["upload", "microphone"], type="filepath", label="上传音频或录音"
+    ),
+    outputs=gr.Textbox(label="识别结果"),
+    title="SenseVoice 在线体验版",
+    description="应用启动时需要下载和加载模型，请耐心等待。",
+    allow_flagging="never",
+)
+
+iface.launch()