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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('HF_TOKEN')
os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
os.environ['HF_TOKEN'] = hf
# --- Page Configuration ---
st.set_page_config(page_title="Machine Learning Mentor", layout="wide")
# --- Custom CSS ---
st.markdown("""
<style>
body {
font-family: 'Segoe UI', sans-serif;
background: linear-gradient(135deg, #2c003e, #0f9b8e);
}
.main {
padding: 2rem;
}
.stTextInput>div>div>input {
color: #ffffff !important;
background-color: #00000010;
border: 1px solid #ffffff30;
}
.chat-bubble {
padding: 1rem;
margin: 0.5rem 0;
border-radius: 12px;
max-width: 80%;
}
.user-bubble {
background-color: #4b0082;
color: white;
margin-left: auto;
text-align: right;
}
.mentor-bubble {
background-color: #00bfa6;
color: white;
margin-right: auto;
}
.stButton>button {
background: #ffffff20;
border: 1px solid #ffffff50;
color: white;
font-weight: bold;
border-radius: 10px;
transition: 0.3s ease;
}
.stButton>button:hover {
background: #ffffff40;
}
</style>
""", unsafe_allow_html=True)
# --- Title ---
st.title("🤖 Machine Learning Mentor")
# --- Sidebar Preferences ---
st.sidebar.title("Mentor Preferences")
experience_label = st.sidebar.selectbox("Select your experience level:", ["Beginner", "Intermediate", "Experienced"])
# --- Initialize Model ---
ml_model_skeleton = HuggingFaceEndpoint(
repo_id='Qwen/Qwen3-14B',
provider='nebius',
temperature=0.7,
max_new_tokens=50,
task='conversational'
)
ml_mentor = ChatHuggingFace(
llm=ml_model_skeleton,
repo_id='Qwen/Qwen3-14B',
provider='nebius',
temperature=0.7,
max_new_tokens=50,
task='conversational'
)
PAGE_KEY = "ml_chat_history"
if PAGE_KEY not in st.session_state:
st.session_state[PAGE_KEY] = []
# --- Layout ---
col1, col2 = st.columns([3, 1])
# --- Chat Section ---
with col1:
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"You are a machine learning mentor with {experience_label.lower()} experience. "
f"Answer only machine learning questions in a friendly tone and within 150 words. "
f"Politely inform if the question is out of scope."
)
messages = [SystemMessage(content=system_prompt), HumanMessage(content=user_input)]
result = ml_mentor.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'<div class="chat-bubble user-bubble">{user}</div>', unsafe_allow_html=True)
st.markdown(f'<div class="chat-bubble mentor-bubble">{bot}</div>', unsafe_allow_html=True)
# --- Mentor Tips Sidebar ---
with col2:
st.markdown("### 💡 Tips from Mentor")
st.info("Try asking about:\n- Regression vs Classification\n- Overfitting examples\n- Feature scaling\n- Model evaluation techniques")
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