Update pages/deep_learning.py

pages/deep_learning.py

@@ -3,62 +3,6 @@ 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
-
-# Page config
-st.set_page_config(page_title="Python Mentor Chat", layout="centered")
-
-# Inject home page CSS style
-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)
-
-# Title
-st.title("🐍 Python Mentor Chat")
-
-# Sidebar
-st.sidebar.title("Mentor Preferences")
-experience_label = st.sidebar.selectbox(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')
 os.environ['HUGGINGFACEHUB_API_TOKEN'] = hf
@@ -154,53 +98,6 @@ if submit and user_input:
 
 # 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("---")
-
-    "Select your experience level:", ["Beginner", "Intermediate", "Experienced"]
-)
-
-# Initialize model
-deep_seek_skeleton = HuggingFaceEndpoint(
-    repo_id='meta-llama/Llama-3.2-3B-Instruct',
-    provider='sambanova',
-    temperature=0.7,
-    max_new_tokens=50,
-    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=50,
-    task='conversational'
-)
-
-PAGE_KEY = "python_chat_history"
-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"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))
-
-# 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}")