pages/deep_learning.py

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

hf = os.getenv('Data_science')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf

st.set_page_config(page_title="Python Mentor Chat", layout="centered")
st.title("🐍 Python Mentor Chat")

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

deep_seek_skeleton = HuggingFaceEndpoint(
    repo_id='meta-llama/Llama-3.2-3B-Instruct',
    provider='sambanova',
    temperature=0.7,
    max_new_tokens=150,
    task='conversational'
)

deep_seek = ChatHuggingFace(
    llm=deep_seek_skeleton,
    repo_id='meta-llama/Llama-3.2-3B-Instruct',
    provider='sambanova',
    temperature=0.7,
    max_new_tokens=150,
    task='conversational'
)

PAGE_KEY = "python_chat_history"

if PAGE_KEY not in st.session_state:
    st.session_state[PAGE_KEY] = []

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

if submit and user_input:
    system_prompt = (
        f"Act as a python mentor with {experience_label.lower()} experience. "
        f"Teach in a friendly manner and keep answers within 150 words. "
        f"If a question is not about python, politely mention it's out of scope."
    )
    messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
    result = deep_seek.invoke(messages)
    st.session_state[PAGE_KEY].append((user_input, result.content))

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("---")