Update app.py

app.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from pyannote.audio import Pipeline
-from openai import whisper  # Changed import
+import whisper  # Changed import
 import tempfile
 import os
 import torch
@@ -14,7 +14,7 @@ def load_models():
             use_auth_token=st.secrets["hf_token"]
         )
         
-        transcriber = whisper.load_model("base")  # This should work now
+        transcriber = whisper.load_model("turbo")  
         
         summarizer = tf_pipeline(
             "summarization", 
@@ -27,7 +27,7 @@ def load_models():
         st.error(f"Error loading models: {str(e)}")
         return None, None, None
 
-def process_audio(audio_file, max_duration=300):  # limit to 5 minutes initially
+def process_audio(audio_file, max_duration=600):  # limit to 5 minutes initially
     try:
         with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
             tmp.write(audio_file.getvalue())