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import streamlit as st | |
from src.models.predict_model import * | |
with st.sidebar: | |
st.write("# 🤖 Language Models") | |
"[![GitHub Repo](https://github.com/codespaces/badge.svg)](https://github.com/Foxxy-HCMUS/e2eqa)" | |
st.title("💬 Question-Answering System") | |
if "messages" not in st.session_state: | |
st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}] | |
for msg in st.session_state.messages: | |
st.chat_message(msg["role"]).write(msg["content"]) | |
if prompt := st.chat_input(): | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
st.chat_message("user").write(prompt) | |
msg = { | |
"role": "assistant", | |
"content": get_answer_e2e(prompt) | |
} | |
st.session_state.messages.append(msg) | |
st.chat_message("assistant").write(msg["content"]) | |