Update app.py

app.py

@@ -4,7 +4,7 @@ import os
 import torch
 import numpy as np
 #import ast
-import librosa
+#import librosa
 from transformers import (
     AutomaticSpeechRecognitionPipeline,
     WhisperForConditionalGeneration,
@@ -37,11 +37,11 @@ def transcribe(data):
     output_file_path = "audio.wav"
     with open(output_file_path, "wb") as output_file:
         output_file.write(decode_string)
-        return "Success"
-    #with torch.cuda.amp.autocast():
+        print("Success")
+    with torch.cuda.amp.autocast():
         #data,samplerate = librosa.load(output_file_path)
-        #text = pipe(output_file_path,max_new_tokens=255)["text"]
-        #return text
+        text = pipe(output_file_path,max_new_tokens=255)["text"]
+        return text
     
 #hf_writer = gr.HuggingFaceDatasetSaver(hf_token = api_key,dataset_name="interaction-log2")
 demo = gr.Interface(