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)