app.py

# >>>>>>   Adapted/frankensteined from these scripts:   <<<<<<<
#                 for Summary Interface:
# >>>>https://huggingface.co/spaces/khxu/pegasus-text-summarizers/blob/main/app.py
# 

import gradio as gr
from transformers import pipeline
from gradio.mix import Parallel, Series

# >>>>>>>>>>>>>>>>>>>> Danger Below <<<<<<<<<<<<<<<<<<<<<<
# Load Interfaces:
s2t = gr.Interface.load('huggingface/facebook/s2t-medium-librispeech-asr')
grammar = gr.Interface.load('huggingface/prithivida/grammar_error_correcter_v1')
lss = gr.Interface.load('huggingface/SamuelMiller/lil_sum_sum') 

# Audio Functions:
def out(audio):
  if audio1==None:
    return "no audio"
    
  else:               
    x = s2t(audio)
    s = lss(x)                              # Summarize Audio with Lil_sumsum
    return grammar(s)                       # Grammar Filter 


# Construct Interfaces:
iface = gr.Interface(
  fn=out, 
  title="Speech Audio to text (with corrected grammar)",
  description="Let's Hear It!! This app transforms your speech (input) to text with corrected grammar after (output)!",
  inputs=[gr.inputs.Audio(source="microphone", type="filepath", label=None, optional=True)],
  outputs=['text']
)
  # From Original Code:
# gr.inputs.Audio(source="upload", type="filepath", label=None, optional=True),  
  # examples=[["Grammar-Correct-Sample.mp3"], ["Grammar-Wrong-Sample.mp3"],],

# Launch Interface
iface.launch(enable_queue=True,show_error=True)