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from transformers import pipeline | |
import pandas as pd | |
qa_pipeline = pipeline("question-answering", model='deepset/roberta-base-squad2') | |
def chatbot(question): | |
with open(r"ayurdata.txt", "r", encoding="utf-8") as file: | |
context = file.read() | |
answer = qa_pipeline(question=question, context=context) | |
return answer | |
def prints(questions): | |
response = chatbot(questions) | |
return response['answer'] | |
import streamlit as st | |
st.title("AyurEasy AI Bot") | |
if "messages" not in st.session_state: | |
st.session_state.messages = [] | |
st.session_state.messages.append({ | |
'role':'assistant', | |
'content':"Hi! I'm your AI Bot" | |
}) | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.markdown(message["content"]) | |
prompt = st.chat_input("What is up?") | |
if prompt: | |
with st.chat_message("user"): | |
st.markdown(prompt) | |
st.session_state.messages.append({"role":"user","content":prompt}) | |
response = f"ChatBot: {prints(prompt)}" | |
with st.chat_message("assistant"): | |
st.markdown(response) | |
st.session_state.messages.append({"role":"assistant","content":response}) |