# -*- coding: utf-8 -*- """ Created on Thu Sep 21 22:17:43 2023 @author: Loges """ import streamlit as st import sentencepiece from gtts import gTTS import base64 from transformers import pipeline, T5Tokenizer, T5ForConditionalGeneration model=T5ForConditionalGeneration.from_pretrained("Logeswaransr/T5_MineAI_Prototype").to("cpu") tokenizer=T5Tokenizer.from_pretrained("Logeswaransr/T5_MineAI_Prototype") pipe=pipeline('text2text-generation', model=model, tokenizer=tokenizer) sound_file = BytesIO() greetings=["Hello! My name is MineAI, A specially trained LLM here to assist you on your Mining Related Queries.","How may I help you?"] st.set_page_config(page_title='Sample Chatbot', layout='wide') if 'messages' not in st.session_state: st.session_state.messages=[] st.subheader("Mine AI") audio_stream=r"sample_audio.mp3" for message in st.session_state.messages: with st.chat_message(message['role']): st.markdown(message['content']) ## messages element format: {'role':'user', 'content':''} if st.session_state.messages==[]: for gr in greetings: with st.chat_message("assistant"): st.markdown(gr) tts=gTTS(prompt) tts.save(audio_stream) with open(audio_stream, 'rb') as file: audio_data=file.read() audio_base64 = base64.b64encode(audio_data).decode('utf-8') audio_tag = f'