c_2

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import os
 import time
+import sys
+import io
 import tempfile
 import subprocess
 import requests
@@ -11,9 +13,31 @@ import torch
 from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
 import yt_dlp
 
+class LogCapture(io.StringIO):
+    def __init__(self, callback):
+        super().__init__()
+        self.callback = callback
+
+    def write(self, s):
+        super().write(s)
+        self.callback(s)
+
 # Set up logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
+# Clone and install faster-whisper from GitHub
+try:
+    subprocess.run(["git", "clone", "https://github.com/SYSTRAN/faster-whisper.git"], check=True)
+    subprocess.run(["pip", "install", "-e", "./faster-whisper"], check=True)
+except subprocess.CalledProcessError as e:
+    logging.error(f"Error during faster-whisper installation: {e}")
+    sys.exit(1)
+
+sys.path.append("./faster-whisper")
+
+from faster_whisper import WhisperModel
+from faster_whisper.transcribe import BatchedInferencePipeline
+
 # Check for CUDA availability
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 logging.info(f"Using device: {device}")