Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py - FactoryRAG+: AI Assistant with Real-Time Functional Status by Role
+# app.py - FactoryGPT 5.0: Custom 3D Factory Layout + Real-Time Status and Role Chatbot
 
 import streamlit as st
 import pandas as pd
@@ -6,11 +6,16 @@ import numpy as np
 from sentence_transformers import SentenceTransformer
 from transformers import pipeline
 from sklearn.ensemble import IsolationForest
+import pydeck as pdk
 
-# Page config
-st.set_page_config(page_title="FactoryGPT Humanization for the Factories of the Future in Industry 5.0 – Predict, Perfect, and Connect", page_icon="🧠", layout="wide")
+# Page configuration
+st.set_page_config(
+    page_title="FactoryGPT Humanization for the Factories of the Future in Industry 5.0 – Predict, Perfect, and Connect",
+    page_icon="🧠",
+    layout="wide"
+)
 
-# Custom dark theme styling
+# Dark theme styling
 st.markdown("""
     <style>
     html, body, [class*="css"]  {
@@ -33,7 +38,7 @@ st.markdown("""
 st.markdown("""
     <div style='text-align: center;'>
         <h1 style='color: #58a6ff;'>🏭 FactoryGPT Humanization for the Factories of the Future in Industry 5.0 – Predict, Perfect, and Connect</h1>
-        <p style='color: #bbb;'>AI-Powered Digital Twin- Predict, Perfect, and Connect | Real-Time Sensor Health</p>
+        <p style='color: #bbb;'>AI-Powered Digital Twin | Real-Time Sensor Health with Custom 3D Layout</p>
         <hr style='border-top: 2px solid #888;'>
     </div>
 """, unsafe_allow_html=True)
@@ -53,6 +58,7 @@ if uploaded_file:
     st.markdown("### 🧾 Sensor Log Preview")
     st.dataframe(df.head(), use_container_width=True)
 
+    # Prepare RAG chunks
     def convert_to_chunks(df):
         return [f"[Log {i}] " + ", ".join([f"{col}: {row[col]:.2f}" for col in numeric_cols]) for i, row in df.iterrows()]
 
@@ -62,7 +68,7 @@ if uploaded_file:
         st.session_state.chunks = chunks
         st.session_state.embeddings = embeddings
 
-    # Condition status based on Isolation Forest
+    # Condition Detection
     st.markdown("### ⚙️ Equipment Condition Status")
     iso = IsolationForest(contamination=0.02)
     labels = iso.fit_predict(df[numeric_cols])
@@ -70,8 +76,41 @@ if uploaded_file:
     df['maintenance'] = ['🔧 Needs Maintenance' if x == -1 else '🟢 Stable' for x in labels]
     st.dataframe(df[['status', 'maintenance'] + numeric_cols].head(), use_container_width=True)
 
-    # Role-based chatbot
-    st.markdown("### 💬 Real-Time Role-Based Chat Assistant")
+    # 🧭 Custom 3D Layout Visualization
+    st.markdown("### 🧭 3D Digital Factory Layout (Custom Zones)")
+    zones = ["Assembly", "Packaging", "Inspection", "Robotics", "Warehouse"]
+    df['zone'] = np.random.choice(zones, size=len(df))
+
+    zone_coords = {
+        "Assembly": [0, 0],
+        "Packaging": [10, 5],
+        "Inspection": [5, 15],
+        "Robotics": [15, 10],
+        "Warehouse": [20, 0]
+    }
+
+    df['lat'] = df['zone'].map(lambda z: zone_coords[z][1] + np.random.rand() * 0.5)
+    df['lon'] = df['zone'].map(lambda z: zone_coords[z][0] + np.random.rand() * 0.5)
+    df['value'] = df[numeric_cols[0]] if numeric_cols else 0
+
+    view_state = pdk.ViewState(latitude=10, longitude=10, zoom=2, pitch=45)
+    layer = pdk.Layer(
+        "ScatterplotLayer",
+        data=df.head(500),
+        get_position='[lon, lat]',
+        get_color='[255, 140, 0, 180]',
+        get_radius='value',
+        pickable=True
+    )
+
+    st.pydeck_chart(pdk.Deck(
+        layers=[layer],
+        initial_view_state=view_state,
+        tooltip={"text": "Zone: {zone}\nStatus: {status}\nMaintenance: {maintenance}"}
+    ))
+
+    # 💬 Role-based Chat Assistant
+    st.markdown("### 💬 Role-Based Chat Assistant")
     roles = {
         "Operator": "You are a machine operator. Check if equipment is running properly. If not, flag it immediately.",
         "Maintenance": "You are a maintenance technician. Assess faulty logs and provide service insights.",