Update app.py

app.py

@@ -1,28 +1,25 @@
 import gradio as gr
 from transformers import pipeline
 import numpy as np
-#from google.cloud import speech_v1
-#from google.protobuf import timestamp_pb2
+from google.cloud import speech_v1
+from google.protobuf import timestamp_pb2
 
 transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
 
-def transcribe(stream, audio_bytes):
+def transcribe(audio_bytes):
     """Transcribe audio bytes to text using Google Cloud Speech to Text."""
 
     sr, y = audio_bytes
     y = y.astype(np.float32)
     y /= np.max(np.abs(y))
-    if stream is not None:
-        stream = np.concatenate([stream, y])
-    else:
-        stream = y
-    return stream, transcriber({"sampling_rate": sr, "raw": stream})["text"]
+    
+    return transcriber({"sampling_rate": sr, "raw": y})["text"]
 
 
 demo = gr.Interface(
     transcribe,
-    ["state", gr.Audio(sources=["microphone"], streaming=False)],
-    ["state", "text"],
+    gr.Audio(sources=["microphone"], streaming=False),
+    "text",
     live=True,
 )