| from bardapi import Bard | |
| import os | |
| import streamlit as st | |
| from transformers import pipeline | |
| intent = pipeline(model="facebook/bart-large-mnli") | |
| fetchvalue = pipeline(model="Jean-Baptiste/camembert-ner", aggregation_strategy="simple") | |
| bardkey = os.environ.get("BARD_API_KEY") | |
| bard = Bard(token=bardkey) | |
| if query := st.chat_input("Hi, how can I help you"): | |
| usrintent = intent(query, candidate_labels=["Reminder", "General Conversation"]) | |
| if usrintent["labels"][0] == "Reminder": | |
| values = fetchvalue(query) | |
| with st.chat_message("assistant"): | |
| st.write(values) | |
| elif usrintent["labels"][0] == "General Conversation": | |
| ans = bard.get_answer(query) | |
| with st.chat_message("assistant"): | |
| st.write(ans['content']) | |