pages/gen_ai.py

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

# Set Hugging Face tokens
hf = os.getenv('Data_science')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf

# --- Page Configuration ---
st.set_page_config(page_title="GenAI Mentor Chat", layout="centered")
st.title("🤖 GenAI Mentor Chat")

# --- Sidebar: Experience Level ---
st.sidebar.title("Mentor Preferences")
experience_label = st.sidebar.selectbox(
    "Select your experience level:", ["Beginner", "Intermediate", "Experienced"]
)

# --- Initialize Chat Model ---
genai_skeleton = HuggingFaceEndpoint(
    repo_id='google/gemma-2-9b-it',
    provider='nebius',
    temperature=0.7,
    max_new_tokens=50,
    task='conversational'
)

genai_chat = ChatHuggingFace(
    llm=genai_skeleton,
    repo_id='google/gemma-2-9b-it',
    provider='nebius',
    temperature=0.7,
    max_new_tokens=50,
    task='conversational'
)

PAGE_KEY = "genai_chat_history"

# --- Session State Initialization ---
if PAGE_KEY not in st.session_state:
    st.session_state[PAGE_KEY] = []

# --- Chat Input 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"You are a Generative AI mentor with {experience_label.lower()} experience. "
        f"Answer only Generative AI questions in a friendly tone, within 150 words. "
        f"Politely inform if the question is out of scope."
    )
    messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
    result = genai_chat.invoke(messages)
    st.session_state[PAGE_KEY].append((user_input, result.content))

# --- Chat History Display ---
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("---")