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import streamlit as st
import os
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_core.messages import HumanMessage, SystemMessage
# Set environment variables for Hugging Face token
hf = os.getenv('HF_TOKEN')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf
# Page config
st.set_page_config(page_title="Deep Learning Mentor Chat", layout="centered")
# Custom CSS for modern chat UI
st.markdown("""
<style>
.main {
background: linear-gradient(135deg, #430089 0%, #82ffa1 100%);
padding: 2rem;
font-family: 'Segoe UI', sans-serif;
}
.stButton>button {
background: #ffffff10;
border: 2px solid #ffffff50;
color: white;
font-size: 18px;
font-weight: 600;
padding: 0.8em 1.2em;
border-radius: 12px;
width: 100%;
transition: 0.3s ease;
box-shadow: 0 4px 10px rgba(0, 0, 0, 0.15);
}
.stButton>button:hover {
background: #ffffff30;
border-color: #fff;
color: #ffffff;
}
h1, h3, p, label {
color: #ffffff;
text-align: center;
}
hr {
border: 1px solid #ffffff50;
margin: 2em 0;
}
.css-1aumxhk {
color: white;
}
</style>
""", unsafe_allow_html=True)
# App title
st.markdown("<h1>🤖 Deep Learning Mentor Chat</h1>", unsafe_allow_html=True)
st.markdown("<p>Learn Deep Learning with personalized AI mentorship</p>", unsafe_allow_html=True)
# Sidebar for experience level
st.sidebar.title("🎓 Select Your Level")
exp = st.sidebar.selectbox("Experience Level", ["Beginner", "Intermediate", "Expert"])
# Load Deep Learning model
mentor_llm = HuggingFaceEndpoint(
repo_id='Qwen/Qwen3-32B',
provider='sambanova',
temperature=0.7,
max_new_tokens=150,
task='conversational'
)
deep_mentor = ChatHuggingFace(llm=mentor_llm)
# Session key for conversation
PAGE_KEY = "deep_learning_chat_history"
if PAGE_KEY not in st.session_state:
st.session_state[PAGE_KEY] = []
# Chat input form
st.markdown("<hr>", unsafe_allow_html=True)
with st.form(key="chat_form"):
user_input = st.text_input("💬 Ask your deep learning question:")
submit = st.form_submit_button("Send")
# Handle chat submission
if submit and user_input:
system_prompt = f"""You are a knowledgeable Deep Learning mentor with {exp} years of practical experience. Your communication style is friendly, supportive, and focused. Please adhere to the following strict instructions:
1. Only respond to queries that are specifically about deep learning programming — this includes related libraries, tools, and frameworks.
2. If a question is outside the scope of deep learning, respond exactly with: "I specialize only in deep learning programming. This appears to be a non-deep learning topic."
3. Do not offer help or advice on non-deep learning subjects.
4. Aim for clarity and practical relevance in your explanations, keeping them beginner-friendly when needed.
5. Reinforce learning through relevant code snippets and applied examples.
6. For more advanced discussions, assume the learner has a working knowledge of deep learning fundamentals."""
messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
result = deep_mentor.invoke(messages)
st.session_state[PAGE_KEY].append((user_input, result.content))
# Chat history display with bubble styling
if st.session_state[PAGE_KEY]:
st.markdown('<div class="chat-container">', unsafe_allow_html=True)
for user, bot in st.session_state[PAGE_KEY]:
st.markdown(f'<div class="chat-user">👤 <strong>You:</strong> {user}</div>', unsafe_allow_html=True)
st.markdown(f'<div class="chat-bot">🧑🏫 <strong>Mentor:</strong> {bot}</div>', unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
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