Update app.py

app.py

@@ -1,54 +1,46 @@
 import gradio as gr
 import time
-import torch
 from transformers import pipeline
-import numpy as np
+import torch
 
 # Check if GPU is available
 use_gpu = torch.cuda.is_available()
 
+
 # Configure the pipeline to use the GPU if available
 if use_gpu:
     p = pipeline("automatic-speech-recognition", 
-                 model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h", device=0)
+             model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h", device=0)
 else:
     p = pipeline("automatic-speech-recognition", 
-                 model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h")
-
-chunk_size = 10  # Adjust the chunk size as needed
+             model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h")
+    
 
 def transcribe(audio, state="", uploaded_audio=None):
     if uploaded_audio is not None:
         audio = uploaded_audio
     if not audio:
         return state, state  # Return a meaningful message
-
     try:
-        state += "Transcribing...\n"
-        if len(audio) <= chunk_size:
-            text = p(audio)["text"]
-            state += text + "\n"
-        else:
-            chunks = [audio[i:i + chunk_size] for i in range(0, len(audio), chunk_size)]
-            for chunk in chunks:
-                text = p(chunk)["text"]
-                state += text + "\n"
-                time.sleep(1)  # Simulate processing time for each chunk
+        time.sleep(3)
+        text = p(audio)["text"]
+        state += text + "\n"
         return state, state
     except Exception as e:
         return "An error occurred during transcription.", state  # Handle other exceptions
 
+
+
+
 gr.Interface(
     fn=transcribe, 
     inputs=[
-        gr.inputs.Audio(source="microphone", type="numpy"),
+        gr.inputs.Audio(source="microphone", type="filepath"),
         'state',
-        gr.inputs.Audio(label="Upload Audio File", type="numpy", source="upload")
+        gr.inputs.Audio(label="Upload Audio File", type="filepath", source="upload")
     ],
     outputs=[
         "textbox",
         "state"
     ],
-    live=True
-).launch()
-
+    live=True).launch()