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")

# Improved custom CSS
st.markdown("""
    <style>
    .main {
        background: linear-gradient(to right, #1f4037, #99f2c8);
        padding: 2rem;
        font-family: 'Segoe UI', sans-serif;
    }
    .stButton>button {
        background-color: #ffffff10;
        color: white;
        font-weight: 600;
        border-radius: 10px;
        padding: 0.6rem 1rem;
        transition: all 0.3s ease;
        border: 1px solid white;
    }
    .stButton>button:hover {
        background-color: #ffffff30;
        color: white;
        border-color: #fff;
    }
    h1, h3, p, label {
        color: white;
        text-align: center;
    }
    .chat-bubble-user {
        background-color: #ffffff25;
        padding: 0.75rem 1rem;
        border-radius: 1rem;
        margin-bottom: 0.5rem;
        color: #fff;
        font-weight: 500;
        text-align: left;
        width: fit-content;
        max-width: 90%;
        align-self: flex-end;
    }
    .chat-bubble-bot {
        background-color: #ffffff15;
        padding: 0.75rem 1rem;
        border-radius: 1rem;
        margin-bottom: 0.5rem;
        color: #fff;
        text-align: left;
        width: fit-content;
        max-width: 90%;
        align-self: flex-start;
    }
    .chat-container {
        display: flex;
        flex-direction: column;
        gap: 0.5rem;
        margin-top: 2rem;
    }
    </style>
""", unsafe_allow_html=True)
# Title
st.title("📊 Statistics Mentor Chat")

# Sidebar
st.sidebar.title("Mentor Preferences")
exp = st.sidebar.selectbox("Select your experience level:", ["Beginner", "Intermediate", "Expert"])

# Model setup
stats_model_skeleton = HuggingFaceEndpoint(
    repo_id='THUDM/GLM-4-32B-0414',
    provider='novita',
    temperature=0.7,
    max_new_tokens=110,
    task='conversational'
)

stats_mentor = ChatHuggingFace(
    llm=stats_model_skeleton,
    repo_id='THUDM/GLM-4-32B-0414',
    provider='novita',
    temperature=0.7,
    max_new_tokens=110,
    task='conversational'
)

# Session key
PAGE_KEY = "chat_history_stats"
if PAGE_KEY not in st.session_state:
    st.session_state[PAGE_KEY] = []

# Chat form
with st.form(key="chat_form"):
    user_input = st.text_input("Ask your question:")
    submit = st.form_submit_button("Send")

# Chat logic
if submit and user_input:
    system_prompt = ( f"""Act as a statistics mentor with {exp} years of experience. Teach in a friendly, approachable manner while following these strict rules:
        1. Only answer questions related to statistics
        2. For any non-statistics query, respond with exactly: "I specialize only in statistics programming. This appears to be a non-statistics topic."
        3. Never suggest you can help with non-statistics topics
        4. Keep explanations clear, practical, and beginner-friendly when appropriate
        5. Include practical examples when explaining concepts
        6. For advanced topics, assume the student has basic statistics knowledge"""    
    )
    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
st.subheader("🗨️ Chat History")
for user, bot in st.session_state[PAGE_KEY]:
    st.markdown(f"**You:** {user}")
    st.markdown(f"**Mentor:** {bot}")
    st.markdown("---")