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import gradio as gr |
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import time |
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from transformers import pipeline |
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from gtts import gTTS |
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pipe = pipeline("text-generation", model="sriramgs/RPL_gpt2_new") |
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asr = pipeline("automatic-speech-recognition", model="openai/whisper-small") |
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global bot_message |
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with gr.Blocks() as demo: |
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chatbot = gr.Chatbot(avatar_images=("human.png", "bot.png"), value=[[None, "Welcome to the Indore-Ekk Number Superstore family! We're thrilled to have you on board. \n How can I assist you today?"]]) |
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with gr.Row(label="Voice Input and Output"): |
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with gr.Column(variant="panel"): |
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audio_file = gr.Audio(label='Voice based Input',source="microphone",type="filepath",optional=True) |
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with gr.Column(variant="panel"): |
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play_audio = gr.Audio(label='Output Audio', autoplay=True) |
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audio_out = gr.Textbox(visible=False) |
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with gr.Row(label="Voice Input and Output"): |
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with gr.Column(label='Text Based Input', variant="panel"): |
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msg = gr.Textbox(placeholder="Ask me your doubts") |
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with gr.Column(variant="panel"): |
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with gr.Row(): |
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clear = gr.Button("Clear the Chatbot Conversation") |
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def text_to_speech(text): |
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var = gTTS(text = text,lang = 'en') |
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var.save('eng.mp3') |
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return gr.Audio.update(value='eng.mp3') |
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def user(user_message, history): |
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global query |
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global fck |
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query = user_message |
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fck = model_response(query) |
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print(user_message,fck) |
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return '', history + [[user_message, None]],gr.Textbox.update(value=fck) |
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def model_response(query): |
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global a |
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a = pipe("Q: " + str(query)) |
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a = a[0]['generated_text'].split('\n')[1][3:] |
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return a |
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def bot(history): |
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global bot_message |
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bot_message = model_response(query) |
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history[-1][1] = "" |
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for character in fck: |
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history[-1][1] += character |
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time.sleep(0.05) |
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yield history |
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def speech_to_text(audio_file,history): |
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if audio_file == None: |
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return "", history + [[None, None]] |
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else: |
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global query |
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global fck |
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text = asr(audio_file)["text"] |
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query = text |
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fck = model_response(query) |
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print(text) |
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return None, history + [[text, None]],gr.Textbox.update(value=fck) |
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audio_file.stop_recording(speech_to_text, [audio_file,chatbot], [audio_file,chatbot,audio_out], queue=False, show_progress=False).then(bot, chatbot, chatbot) |
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msg.submit(user, [msg, chatbot], [msg, chatbot,audio_out], queue=False).then( |
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bot, chatbot, chatbot |
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) |
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clear.click(lambda: None, None, chatbot, queue=False) |
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audio_out.change(text_to_speech,inputs=[audio_out], outputs=play_audio) |
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demo.queue() |
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demo.launch(debug=True) |
