pages/deep_learning.py

import streamlit as st
import os
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_core.messages import HumanMessage, AIMessage, SystemMessage



hf = os.getenv('Data_science')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf
# --- Config ---
st.set_page_config(page_title="AI Mentor Chat", layout="centered")
st.title("🤖 AI Mentor Chat")

# --- Sidebar for selections ---
st.sidebar.title("Mentor Preferences")
exp1 = ['<1', '1', '2', '3', '4', '5', '5+']
exp = st.sidebar.selectbox("Select experience:", exp1)

# Map experience to label
experience_map = {
    '<1': 'New bie mentor',
    '1': '1', '2': '2', '3': '3', '4': '4', '5': '5',
    '5+': 'Professional'
}
experience_label = experience_map[exp]

# --- Initialize Chat Model ---
deep_seek_skeleton = HuggingFaceEndpoint(
    repo_id='Qwen/Qwen3-32B',
    provider='sambanova',
    temperature=0.7,
    max_new_tokens=150,
    task='conversational'
)

deep_seek = ChatHuggingFace(
    llm=deep_seek_skeleton,
    repo_id='Qwen/Qwen3-32B',
    provider='sambanova',
    temperature=0.7,
    max_new_tokens=150,
    task='conversational'
)
PAGE_KEY = "deep_learning_chat_history" 
# --- Session State ---
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:
    # Add system context
    system_prompt = f"Act as a deep learning mentor who has {experience_label} years of experience who teaches in a very friendly manner and also tells everything in within 150 words. If any question is asked other than deep learning then you must not answer and tell that it is out of topic query."

    # Create message list
    messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]

    # Get model response
    result = deep_seek.invoke(messages)

    # Append to history
    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("---")