import streamlit as st

# ✅ Student Information
My_info = "Student ID: 6319250G, Name: Aung Hlaing Tun"

# ✅ Title and Student Info
st.title("📩 Development of an AI Ticket Classifier Model Using DistilBERT")
st.markdown(f"*{My_info}*")

st.markdown("""
### 🔍 About this App  
- This system predicts the appropriate **team assignment** and **contact email** based on the ticket description.  
- Simply enter up to **6 ticket descriptions**, and the AI will classify them accordingly.
""")

# ✅ Layout for Ticket Inputs and Predictions
col1, col2, col3 = st.columns(3)

# ✅ Dictionary to store ticket descriptions
ticket_inputs = {}

for i in range(6):  # Up to 6 tickets
    with [col1, col2, col3][i % 3]:  # Distribute across 3 columns
        ticket_inputs[f"ticket_{i+1}"] = st.text_area(f"🎟️ Ticket {i+1}", placeholder=f"Enter ticket description {i+1}...")

# ✅ Prediction Button (Without Model Logic)
if st.button("🔮 Predict All Tickets"):
    st.subheader("📌 Prediction Results:")
    for i, (key, text) in enumerate(ticket_inputs.items()):
        if text.strip():
            # 🚀 Placeholder logic since model is removed
            st.success(f"🎟️ **Ticket {i+1}:** Predicted Team → **[Placeholder Team]**, Contact: **placeholder@company.com**")
        else:
            st.warning(f"🚨 Ticket {i+1} is empty. Please enter a description.")

st.write("📌 Enter your ticket descriptions and click **Predict All Tickets** to classify them.")