app.py

import os
#import numpy as np
import gradio as gr
import whisper
import requests 
import tempfile
from neon_tts_plugin_coqui import CoquiTTS

# Whisper: Speech-to-text
model = whisper.load_model("base")

# The LLM : Bloom
API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
HF_TOKEN = os.environ["HF_TOKEN"]
headers = {"Authorization": f"Bearer {HF_TOKEN}"}

# Text-to-Speech
LANGUAGES = list(CoquiTTS.langs.keys())
coquiTTS = CoquiTTS()


# Processing input Audio
def fun(audio) : 
  text1 = model.transcribe(audio)["text"]
  text2 = lang_model_response(text1)
  speech = tts(text, language)
  return text1, text2, speech
  
def lang_model_response(prompt): 
  print(f"*****Inside meme_generate - Prompt is :{prompt}")
  if len(prompt) == 0:
    prompt = """Can you help me please?"""
  
  json_ = {"inputs": prompt,
            "parameters":
            {
          "top_p": 0.90, #0.90 default
          "max_new_tokens": 64,
          "temperature": 1.1, #1.1 default
          "return_full_text": True,
          "do_sample": True,
          }, 
          "options": 
          {"use_cache": True,
          "wait_for_model": True, 
          },}
  response = requests.post(API_URL, headers=headers, json=json_)
  print(f"Response  is : {response}")
  output = response.json()
  print(f"output is : {output}") 
  output_tmp = output[0]['generated_text']
  print(f"output_tmp is: {output_tmp}")
  solution = output_tmp.split(".")[1]   
  print(f"Final response after splits is: {solution}")
  return solution

#Text-to-Speech
def tts(text, language):
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
        coquiTTS.get_tts(text, fp, speaker = {"language" : language})
        return fp.name

#inputs = [gr.Textbox(label="Input", value=CoquiTTS.langs["en"]["sentence"], max_lines=3), 
#            gr.Radio(label="Language", choices=LANGUAGES, value="en")]
#outputs = gr.Audio(label="Output")

demo = gr.Interface(fn=tts, inputs=inputs, outputs=outputs)

demo.launch()  
gr.Interface(
    title = 'Testing Whisper', 
    fn=fun, 
    inputs=[
        gr.Audio(source="microphone",  type="filepath"), #streaming = True,
       # "state"
    ],
    outputs=[
        "textbox",  "textbox", "audio",
    ],
    live=True).launch()