calculation for free tier size adjusted

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 from stable_whisper import load_model
 from stable_whisper import load_hf_whisper
-import ffmpeg
 import requests
 import os
 
@@ -19,14 +18,14 @@ api_token = st.text_input("API Token (Unlimited)")
 model_size = st.selectbox("Model Size", ("tiny", "base", "small", "medium"))
 
 def transcribe_to_subtitle(audio_bytes, model_name):
-  st.error(ffmpeg.probe('audio_bytes')['format']['duration'])
   """Transcribe audio to subtitle using OpenAI Whisper"""
   # Load model based on selection
   model = load_model(model_name)
   #speedmodel = load_hf_whisper(model_name)
   
   # Check file size for free tier
-  if use_free_tier and len(audio_bytes) > 2 * 60 * 1024:
+  if use_free_tier and len(audio_bytes) > 0.048 * 2 * 60 * 1024:
+      st.error(audio_bytes)
       st.error("Free tier only supports audio files under 2 minutes")
       return
   

requirements.txt

@@ -1,3 +1,2 @@
 openai-whisper
-stable-ts
-ffmpeg-python
+stable-ts