Update app.py

app.py

@@ -1,95 +1,64 @@
 import streamlit as st
-import os
-from langchain_community.chat_models import ChatHuggingFace
-from langchain_community.llms import HuggingFaceEndpoint
-from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
 
-# --- Load API Token ---
-hf_token = os.getenv("Data_science")
-if not hf_token:
-    st.error("❌ Hugging Face token not found. Please set the 'Data_science' environment variable.")
-    st.stop()
+# Set page config
+st.set_page_config(page_title="Innomatics Online Trainer Bot", layout="centered")
 
-os.environ["HUGGINGFACEHUB_API_KEY"] = hf_token
-os.environ["HF_TOKEN"] = hf_token
-
-# --- Load Hugging Face model (Qwen) ---
-model = HuggingFaceEndpoint(
-    repo_id="Qwen/Qwen3-32B",
-    provider="nebius",
-    temperature=0.6,
-    max_new_tokens=500,
-    task="text-generation"
-)
-
-chat_model = ChatHuggingFace(llm=model)
-
-# --- Streamlit styles ---
+# Inject custom CSS for background and buttons
 st.markdown("""
-<style>
-    .subject-btn {
-        display: inline-block;
-        margin: 0.3em;
+    <style>
+    .main {
+        background-color: #8B0000;
+        padding: 20px;
     }
-    .output-box {
-        background-color: #f9f9f9;
+    .stButton>button {
+        background-color: #B76F27;
+        color: #8B0000;
+        border: 2px solid #8B0000;
         border-radius: 10px;
-        padding: 20px;
-        margin-top: 20px;
-        box-shadow: 0 2px 6px rgba(0, 0, 0, 0.05);
+        padding: 10px 20px;
+        font-size: 18px;
+        font-weight: bold;
+        width: 100%;
+        transition: 0.3s ease-in-out;
+    }
+    .stButton>button:hover {
+        background-color: #8B0000;
+        color: #ffffff;
+        border: 2px solid white;
     }
-</style>
+    h1, h3, p {
+        color: white;
+    }
+    </style>
 """, unsafe_allow_html=True)
 
-# --- Session state ---
-if "message_history" not in st.session_state:
-    st.session_state.message_history = []
-
-if "selected_subject" not in st.session_state:
-    st.session_state.selected_subject = "Python"
-
-# --- UI Header ---
-st.title("🎓 Data Science Mentor")
-st.markdown("Ask subject-specific questions and get guidance based on your experience level.")
-
-# --- Experience level ---
-experience = st.selectbox("👤 Select your experience level:", ["Beginner", "Intermediate", "Expert"])
-
-# --- Subject buttons ---
-st.markdown("### 📚 Choose a Subject:")
-cols = st.columns(4)
-subjects = ["Python", "SQL", "Power BI", "Statistics", "Machine Learning", "Deep Learning", "Generative AI"]
-for i, subject in enumerate(subjects):
-    if cols[i % 4].button(subject):
-        st.session_state.selected_subject = subject
-        st.session_state.message_history = []  # Reset chat on subject change
-
-# --- Set system message based on subject & experience ---
-if not st.session_state.message_history:
-    system_prompt = f"""
-You are a highly knowledgeable data science mentor specialized in {st.session_state.selected_subject}.
-Your job is to guide a {experience.lower()} learner with clear, concise, and actionable advice.
-Explain concepts, best practices, and answer questions with patience and professionalism.
-If relevant, include example code, use-cases, or tips.
-"""
-    st.session_state.message_history.append(SystemMessage(content=system_prompt.strip()))
+# Title and intro
+st.title("Innomatics Online Trainer Bot")
+st.markdown("### 👋 Welcome to the Innomatics Online Trainer Bot!")
+st.markdown("This dashboard will guide you through your doubts in various modules.")
+st.markdown("## In which module do you have doubt?")
 
-# --- Chat Input ---
-user_question = st.text_input(f"💬 Ask your {st.session_state.selected_subject} question:")
+# Button layout - 2 per row
+col1, col2 = st.columns(2)
+with col1:
+    if st.button("Python"):
+        st.switch_page("pages/python.py")
+with col2:
+    if st.button("Machine Learning"):
+        st.switch_page("pages/machine_learning.py")
 
-if st.button("Ask Mentor"):
-    if user_question.strip():
-        with st.spinner("Thinking..."):
-            st.session_state.message_history.append(HumanMessage(content=user_question))
-            try:
-                response = chat_model.invoke(st.session_state.message_history)
-                st.session_state.message_history.append(AIMessage(content=response.content))
+col3, col4 = st.columns(2)
+with col3:
+    if st.button("Deep Learning"):
+        st.switch_page("pages/deep_learning.py")
+with col4:
+    if st.button("Statistics"):
+        st.switch_page("pages/statistics.py")
 
-                st.markdown('<div class="output-box">', unsafe_allow_html=True)
-                st.markdown("### 🧠 Mentor's Response:")
-                st.markdown(response.content)
-                st.markdown("</div>", unsafe_allow_html=True)
-            except Exception as e:
-                st.error(f"❌ Error: {e}")
-    else:
-        st.warning("⚠️ Please enter a question before submitting.")
+col5, col6 = st.columns(2)
+with col5:
+    if st.button("Excel"):
+        st.switch_page("pages/excel.py")
+with col6:
+    if st.button("SQL"):
+        st.switch_page("pages/sql.py")