Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from transformers import WhisperProcessor, WhisperForConditionalGeneration
 from datasets import load_dataset
 import torch
-import librosa
+# import librosa
 
 # 加载 Whisper 模型和 processor
 model_name = "openai/whisper-large-v3-turbo"
@@ -15,8 +15,8 @@ ds = load_dataset("CoIR-Retrieval/CodeSearchNet-php-queries-corpus")
 
 def transcribe(audio_path):
     # 加载音频文件并转换为信号
-    audio, sr = librosa.load(audio_path, sr=16000)
-    input_values = processor(audio, return_tensors="pt", sampling_rate=16000).input_values
+    # audio, sr = librosa.load(audio_path, sr=16000)
+    input_values = processor(audio_path, return_tensors="pt", sampling_rate=16000).input_values
 
     # 模型推理
     with torch.no_grad():
@@ -32,7 +32,7 @@ def transcribe(audio_path):
 # Gradio 界面
 iface = gr.Interface(
     fn=transcribe,
-    inputs=gr.Audio(  type="filepath"),
+    inputs=gr.Audio(sources="microphone",  type="filepath"),
     outputs="text",
     title="Whisper Transcription for Developers",
     description="使用 Whisper 和 bigcode 数据集转录开发者相关术语。"