import streamlit as st
import os
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_core.messages import HumanMessage, SystemMessage
# Set environment variables
hf = os.getenv('HF_TOKEN')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf
# Page setup
st.set_page_config(page_title="Statistics Mentor Chat", layout="centered")
# Modern CSS
st.markdown("""
""", unsafe_allow_html=True)
# Title
st.markdown("
📊 Statistics Mentor Chat
", unsafe_allow_html=True)
st.markdown("Ask anything about statistics!
", unsafe_allow_html=True)
# Sidebar
st.sidebar.title("Mentor Preferences")
exp = st.sidebar.selectbox("Select your experience level:", ["Beginner", "Intermediate", "Expert"])
# Chat form
st.markdown("
", unsafe_allow_html=True)
with st.form(key="chat_form"):
user_input = st.text_input("💬 Ask a statistics question:")
submit = st.form_submit_button("Send")
# Chat logic
if submit and user_input:
system_prompt = (
f"Act as a statistics mentor with {exp.lower()} expertise. "
f"Answer in a friendly tone and within 150 words. "
f"If the question is not statistics-related, politely say it's out of scope."
)
messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
result = stats_mentor.invoke(messages)
st.session_state[PAGE_KEY].append((user_input, result.content))
# Display chat history
if st.session_state[PAGE_KEY]:
st.markdown('', unsafe_allow_html=True)
for user, bot in st.session_state[PAGE_KEY]:
st.markdown(f'
👤 You: {user}
', unsafe_allow_html=True)
st.markdown(f'
📘 Mentor: {bot}
', unsafe_allow_html=True)
st.markdown('
', unsafe_allow_html=True)