| 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") |
|
|
|
|
| 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": |
| bard = Bard(token=bardkey) |
| ans = bard.get_answer(query) |
| with st.chat_message("assistant"): |
| st.write(ans['content']) |
|
|
|
|
