| 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 = os.environ["OPENAI_API_KEY"] | |
| 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(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(choice) | |
| 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("DONE", fp.name) | |
| self.result.append(fp.name) | |
| def start(self, audio, state): | |
| self.convHistory = state | |
| self.result = [] | |
| self.recognize(audio) | |
| print(self.result) | |
| return tuple(self.result) | |
| dost = Dost() | |
| with gr.Blocks() as demo: | |
| state = gr.State([]) | |
| 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, state], outputs=[conversation, output_audio]) | |
| demo.launch(debug=True) |