Create app.py

This is early version of Dost.ai application. It helps you practice your language skills. Currently only supports, whatever language you speak. Just kidding.

app.py

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+import os
+import gradio as gr
+import whisper
+import openai
+import tempfile
+from neon_tts_plugin_coqui import CoquiTTS
+
+model = whisper.load_model("small")
+
+class Dost:
+  LANGUAGES = list(CoquiTTS.langs.keys())
+  coquiTTS = CoquiTTS()
+  openai.api_key = "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"
+  def __init__(self):
+    self.convHistory = []
+    self.voice = None
+    self.result = []
+
+  def recognize(self, audio):
+    audio = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audio)
+
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+    
+    _, probs = model.detect_language(mel)
+    lang = max(probs, key=probs.get)
+
+    options = whisper.DecodingOptions(fp16 = False)
+    result = whisper.decode(model, mel, options)
+
+    print("-------------------RECOGNIZE---------------------")
+    print(self.result)
+    self.response(result.text, lang)
+  
+  def response(self, prompt, lang):
+    response = openai.Completion.create(
+      model="text-davinci-002",
+      prompt=f"You: {prompt}Friend: ",
+      temperature=0.5,
+      max_tokens=60,
+      top_p=1.0,
+      frequency_penalty=0.5,
+      presence_penalty=0.0,
+      stop=["You:"]
+    )
+    choice = response['choices'][0]['text']
+    print("-------------------RESPONSE---------------------")
+    print(self.result)
+    self.convHistory.append((prompt, choice))
+    self.result.append(self.convHistory)
+    print(self.convHistory[0])
+    print(type(self.convHistory[0]))
+    self.say(choice, lang)
+
+  def say(self, text, language):
+    coqui_langs = ['en' ,'es' ,'fr' ,'de' ,'pl' ,'uk' ,'ro' ,'hu' ,'bg' ,'nl' ,'fi' ,'sl' ,'lv' ,'ga']
+    if language not in coqui_langs:
+      language = 'en'
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
+        self.coquiTTS.get_tts(text, fp, speaker = {"language" : language})
+        print("-------------------AUDIOOUTPUT---------------------")
+        print(self.result)
+        self.result.append(fp.name)
+
+  def start(self, audio):
+    self.result = []
+    self.recognize(audio)
+    print(self.result)
+    return tuple(self.result)
+    
+dost = Dost()
+with gr.Blocks() as demo:
+  with gr.Row():
+    with gr.Column():
+      input_audio = gr.Audio(source="microphone", type="filepath")
+      btn = gr.Button("Submit")
+      conversation = gr.Chatbot(value=dost.convHistory)
+      output_audio = gr.Audio(label="AI voice response")
+    btn.click(dost.start, inputs=[input_audio], outputs=[conversation, output_audio])
+
+demo.launch(debug=True)