Update: Refactored app.py with improved UI and error handling

app.py

@@ -16,11 +16,7 @@ from database import (
     get_vehicles_by_state,
     get_hourly_traffic,
     get_top_plates,
-    get_suspicious_vehicles,
-    HF_TOKEN,
-    DATABASE_URL,
-    client,
-    engine
+    get_suspicious_vehicles
 )
 
 # =========================================================
@@ -40,18 +36,16 @@ def detect_and_save(image):
     if image is None:
 
         return (
-            "❌ No image uploaded",
-            {
-                "error": "No image uploaded"
-            }
+            "No image uploaded",
+            {"error": "No image uploaded"}
         )
 
-    now = datetime.now()
+    try:
 
-    date = now.strftime("%Y-%m-%d")
-    time = now.strftime("%H:%M:%S")
+        now = datetime.now()
 
-    try:
+        date = now.strftime("%Y-%m-%d")
+        time = now.strftime("%H:%M:%S")
 
         plate, state, vehicle_type, vehicle_conf, success = detect_plate(image)
 
@@ -67,18 +61,17 @@ def detect_and_save(image):
             )
 
         result_text = f"""
-✅ Detection Success
+Detection Success
 
-📅 Date: {date}
-⏰ Time: {time}
+Date: {date}
+Time: {time}
 
-🚗 Vehicle Type: {vehicle_type}
-🔢 Plate Number: {plate}
-🌍 State: {state}
+Vehicle Type: {vehicle_type}
+Plate: {plate}
+State: {state}
 
-🎯 Confidence: {round(vehicle_conf, 3)}
-
-💾 Saved to Database: {success}
+Confidence: {round(vehicle_conf, 3)}
+Saved: {success}
 """
 
         result_json = {
@@ -87,8 +80,8 @@ def detect_and_save(image):
             "plate": plate,
             "state": state,
             "vehicle_type": vehicle_type,
-            "vehicle_confidence": round(vehicle_conf, 3),
-            "saved": bool(success and plate)
+            "confidence": round(vehicle_conf, 3),
+            "saved": success
         }
 
         return result_text, result_json
@@ -96,30 +89,25 @@ def detect_and_save(image):
     except Exception as e:
 
         return (
-            f"❌ Error: {str(e)}",
-            {
-                "error": str(e)
-            }
+            f"Error: {str(e)}",
+            {"error": str(e)}
         )
 
-
 # =========================================================
-# QUERY DATABASE
+# NLP QUERY
 # =========================================================
 
 def query_database(user_query):
 
-    if not user_query.strip():
+    try:
 
-        return (
-            "",
-            pd.DataFrame(),
-            {
-                "error": "Please enter a query"
-            }
-        )
+        if not user_query.strip():
 
-    try:
+            return (
+                "",
+                pd.DataFrame(),
+                {"error": "Empty query"}
+            )
 
         response = run_query(user_query)
 
@@ -127,16 +115,11 @@ def query_database(user_query):
 
         results = response.get("result", [])
 
-        if results and len(results) > 0:
-
+        if len(results) > 0:
             df = pd.DataFrame(results)
-
         else:
-
             df = pd.DataFrame({
-                "message": [
-                    "No matching records found"
-                ]
+                "message": ["No results found"]
             })
 
         return (
@@ -149,13 +132,12 @@ def query_database(user_query):
 
         return (
             "",
-            pd.DataFrame(),
-            {
-                "error": str(e)
-            }
+            pd.DataFrame({
+                "error": [str(e)]
+            }),
+            {"error": str(e)}
         )
 
-
 # =========================================================
 # CHATBOT
 # =========================================================
@@ -172,41 +154,35 @@ def chatbot_query(message, history):
 
         count = response.get("count", 0)
 
-        if len(results) > 5:
-            preview = results[:5]
-        else:
-            preview = results
+        preview = results[:5]
 
         bot_reply = f"""
-🔍 SQL Generated:
-
+SQL:
 {sql}
 
-📊 Results Found: {count}
-
-📁 Preview:
+Rows Found: {count}
 
+Preview:
 {preview}
 """
 
-        history.append(
-            (message, bot_reply)
-        )
+        # IMPORTANT FIX
+        history = history + [
+            {"role": "user", "content": message},
+            {"role": "assistant", "content": bot_reply}
+        ]
 
         return history, ""
 
     except Exception as e:
 
-        history.append(
-            (
-                message,
-                f"❌ Error: {str(e)}"
-            )
-        )
+        history = history + [
+            {"role": "user", "content": message},
+            {"role": "assistant", "content": f"Error: {str(e)}"}
+        ]
 
         return history, ""
 
-
 # =========================================================
 # ANALYTICS
 # =========================================================
@@ -215,50 +191,43 @@ def refresh_analytics():
 
     try:
 
-        state_data = pd.DataFrame(
+        state_df = pd.DataFrame(
             get_vehicles_by_state()
         )
 
-        hourly_data = pd.DataFrame(
+        hourly_df = pd.DataFrame(
             get_hourly_traffic()
         )
 
-        top_data = pd.DataFrame(
+        top_df = pd.DataFrame(
             get_top_plates()
         )
 
-        suspicious_data = pd.DataFrame(
+        suspicious_df = pd.DataFrame(
             get_suspicious_vehicles()
         )
 
         return (
-            state_data,
-            hourly_data,
-            top_data,
-            suspicious_data
+            state_df,
+            hourly_df,
+            top_df,
+            suspicious_df
         )
 
     except Exception as e:
 
-        err_df = pd.DataFrame({
+        err = pd.DataFrame({
             "error": [str(e)]
         })
 
-        return (
-            err_df,
-            err_df,
-            err_df,
-            err_df
-        )
-
+        return err, err, err, err
 
 # =========================================================
-# HEALTH CHECK
+# HEALTH
 # =========================================================
 
 status, msg = health_check()
 
-
 # =========================================================
 # UI
 # =========================================================
@@ -268,73 +237,19 @@ with gr.Blocks(
     theme=gr.themes.Soft()
 ) as demo:
 
-    # =====================================================
-    # HEADER
-    # =====================================================
-
     gr.Markdown("""
-# 🚗 Vehicle Intelligence System
-
-AI-powered Vehicle Detection + NLP-to-SQL Intelligence Platform
-""")
-
-    if status:
-        gr.Success(msg)
-    else:
-        gr.Warning(msg)
-
-    # =====================================================
-    # CONFIGURATION STATUS
-    # =====================================================
-
-    gr.Markdown("### 🔧 Configuration Status")
-
-    config_status = []
-
-    if HF_TOKEN:
-        gr.Success("✅ Mistral LLM Configured - NLP features enabled")
-    else:
-        gr.Warning("❌ HF_TOKEN missing - NLP/AI features disabled. Add HF_TOKEN to Space Secrets")
-        config_status.append("HF_TOKEN")
-
-    if DATABASE_URL:
-        gr.Success("✅ Database Configured - Query features enabled")
-    else:
-        gr.Warning("❌ DATABASE_URL missing - Database features disabled. Add DATABASE_URL to Space Secrets")
-        config_status.append("DATABASE_URL")
-
-    if config_status:
-        with gr.Group():
-            gr.Markdown(f"""
-### ⚙️ Setup Instructions
-
-Your Space is **missing these environment variables**:
-- **{', '.join(config_status)}**
+# Vehicle Intelligence System
 
-**To fix this:**
-1. Go to Space Settings → Repository secrets
-2. Add the following variables:
-   - `HF_TOKEN`: Get from https://huggingface.co/settings/tokens
-   - `DATABASE_URL`: Your PostgreSQL connection string
-3. Restart the Space
-
-Without these, NLP queries and database operations won't work.
+AI Powered Vehicle Detection + NLP SQL Engine
 """)
 
+    gr.Markdown(f"### {msg}")
 
     # =====================================================
-    # TAB 1 - DETECTION
+    # TAB 1
     # =====================================================
 
-    with gr.Tab("🎥 Detection"):
-
-        gr.Markdown("""
-Upload a vehicle image for:
-
-- License Plate Detection
-- Vehicle Type Classification
-- Database Logging
-""")
+    with gr.Tab("Detection"):
 
         with gr.Row():
 
@@ -342,12 +257,11 @@ Upload a vehicle image for:
 
                 input_img = gr.Image(
                     type="numpy",
-                    label="Upload Vehicle Image",
-                    sources=["upload", "webcam"]
+                    label="Upload Image"
                 )
 
                 detect_btn = gr.Button(
-                    "🔍 Detect Vehicle",
+                    "Detect Vehicle",
                     variant="primary"
                 )
 
@@ -355,11 +269,11 @@ Upload a vehicle image for:
 
                 output_text = gr.Textbox(
                     label="Detection Result",
-                    lines=12
+                    lines=10
                 )
 
                 output_json = gr.JSON(
-                    label="Structured Output"
+                    label="JSON Output"
                 )
 
         detect_btn.click(
@@ -368,68 +282,35 @@ Upload a vehicle image for:
             outputs=[
                 output_text,
                 output_json
-            ],
-            show_progress=True
+            ]
         )
 
     # =====================================================
-    # TAB 2 - NLP QUERY
+    # TAB 2
     # =====================================================
 
-    with gr.Tab("🔍 NLP Database Query"):
+    with gr.Tab("NLP Database Query"):
 
         gr.Markdown("""
-Ask questions using natural language.
-
-Examples:
-- Show TN vehicles
-- Track TN63MB3157
-- Show traffic in Adyar
-- Top repeated plates
-- Hourly traffic
+Ask natural language questions
 """)
 
         query_input = gr.Textbox(
-            label="Ask a Question",
-            placeholder="Example: Show all TN vehicles",
-            lines=2
+            label="Query",
+            placeholder="Show TN vehicles"
         )
 
         search_btn = gr.Button(
-            "🔍 Search Database",
+            "Search",
             variant="primary"
         )
 
-        gr.Examples(
-            examples=[
-                ["Show TN vehicles"],
-                ["Track TN63MB3157"],
-                ["Show all vehicles from Adyar"],
-                ["Top repeated plates"],
-                ["Hourly traffic"],
-                ["Show suspicious vehicles"],
-                ["Show vehicle type distribution"],
-                ["Show latest detections"],
-                ["Count vehicles in Guindy"],
-                ["Show KA state vehicles"],
-                ["Show buses"],
-                ["Show traffic on 2026-05-01"]
-            ],
-            inputs=query_input
+        sql_output = gr.Code(
+            language="sql",
+            label="Generated SQL"
         )
 
-        with gr.Row():
-
-            sql_output = gr.Code(
-                label="Generated SQL",
-                language="sql"
-            )
-
         results_output = gr.Dataframe(
-            headers=None,
-            datatype="str",
-            interactive=False,
-            wrap=True,
             label="Results"
         )
 
@@ -444,80 +325,67 @@ Examples:
                 sql_output,
                 results_output,
                 json_output
-            ],
-            show_progress=True
+            ]
         )
 
     # =====================================================
-    # TAB 3 - CHATBOT
+    # TAB 3
     # =====================================================
 
-    with gr.Tab("🤖 AI Assistant"):
-
-        gr.Markdown("""
-Chat with the Vehicle Intelligence Database
-""")
+    with gr.Tab("AI Assistant"):
 
         chatbot = gr.Chatbot(
+            type="messages",
             height=500
         )
 
-        msg_box = gr.Textbox(
+        msg = gr.Textbox(
             placeholder="Ask something..."
         )
 
-        clear_btn = gr.Button("🗑 Clear Chat")
+        clear = gr.Button("Clear")
 
-        msg_box.submit(
+        msg.submit(
             chatbot_query,
-            [msg_box, chatbot],
-            [chatbot, msg_box]
+            [msg, chatbot],
+            [chatbot, msg]
         )
 
-        clear_btn.click(
-            lambda: None,
-            None,
-            chatbot,
+        clear.click(
+            lambda: [],
+            outputs=chatbot,
             queue=False
         )
 
     # =====================================================
-    # TAB 4 - ANALYTICS
+    # TAB 4
     # =====================================================
 
-    with gr.Tab("📊 Analytics Dashboard"):
-
-        gr.Markdown("""
-Real-time traffic analytics from vehicle intelligence database
-""")
+    with gr.Tab("Analytics"):
 
         refresh_btn = gr.Button(
-            "🔄 Refresh Analytics",
+            "Refresh Analytics",
             variant="primary"
         )
 
         with gr.Row():
 
             state_table = gr.Dataframe(
-                label="🚘 Vehicles By State",
-                interactive=False
+                label="Vehicles By State"
             )
 
             hourly_table = gr.Dataframe(
-                label="🕒 Traffic By Hour",
-                interactive=False
+                label="Traffic By Hour"
             )
 
         with gr.Row():
 
             top_table = gr.Dataframe(
-                label="🏆 Top Repeated Plates",
-                interactive=False
+                label="Top Plates"
             )
 
             suspicious_table = gr.Dataframe(
-                label="⚠ Suspicious Vehicles",
-                interactive=False
+                label="Suspicious Vehicles"
             )
 
         refresh_btn.click(
@@ -540,28 +408,13 @@ Real-time traffic analytics from vehicle intelligence database
             ]
         )
 
-    # =====================================================
-    # FOOTER
-    # =====================================================
-
-    gr.Markdown("""
----
-### 🚀 Features
-
-✅ AI Vehicle Detection  
-✅ License Plate Recognition  
-✅ NLP-to-SQL Query Engine  
-✅ Supabase PostgreSQL Integration  
-✅ Analytics Dashboard  
-✅ Real-time Vehicle Tracking  
-✅ Hugging Face AI Integration  
-""")
-
 # =========================================================
-# ENABLE QUEUE
+# QUEUE
 # =========================================================
 
-demo.queue()
+demo.queue(
+    max_size=20
+)
 
 # =========================================================
 # LAUNCH
@@ -571,6 +424,5 @@ if __name__ == "__main__":
 
     demo.launch(
         server_name="0.0.0.0",
-        server_port=7860,
-        share=False
+        server_port=7860
     )