Update app.py

app.py

@@ -1,9 +1,28 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
+import requests
 from huggingface_hub import hf_hub_download
 
-# 1. Download and Load Model
+# --- 1. Fetch Route Options for Dropdown ---
+print("Fetching route list for dropdown...")
+try:
+    resp = requests.get("https://hkbus.github.io/hk-bus-crawling/routeFareList.min.json")
+    if resp.status_code == 200:
+        data = resp.json()
+        # Get all keys (e.g. "968+1+Yuen Long+Tin Hau")
+        # We sort them so they are easy to find
+        all_routes = sorted(list(data['routeList'].keys()))
+    else:
+        all_routes = []
+except Exception as e:
+    print(f"Error fetching routes: {e}")
+    all_routes = []
+
+# Add "UNKNOWN" as the first/default option
+route_choices = ["UNKNOWN"] + all_routes
+
+# --- 2. Download and Load Model ---
 print("Downloading model...")
 model_path = hf_hub_download(repo_id="WheelsTransit/HK-TransitFlow-Net", filename="hk_transit_flow_net.keras")
 
@@ -43,7 +62,7 @@ def predict_eta(distance_meters, num_stops, hour, day_name, route_id):
     except Exception as e:
         return f"Error: {str(e)}"
 
-# 2. Build the UI using Blocks (Standard Theme)
+# --- 3. Build the UI ---
 with gr.Blocks() as demo:
     gr.Markdown("# HK-TransitFlow-Net Demo 🚌")
     gr.Markdown("Live inference for HK Bus ETA prediction.")
@@ -55,7 +74,15 @@ with gr.Blocks() as demo:
             stops_input = gr.Number(label="Number of Stops", value=10)
             hour_input = gr.Slider(minimum=0, maximum=23, step=1, label="Hour of Day (0-23)", value=9)
             day_input = gr.Dropdown(choices=list(DAY_MAP.keys()), label="Day of Week", value="Monday")
-            route_input = gr.Textbox(label="Route ID (Optional)", placeholder="968+1+...", value="UNKNOWN")
+            
+            # UPDATED: Dropdown with search capabilities
+            route_input = gr.Dropdown(
+                choices=route_choices, 
+                label="Route ID", 
+                value="UNKNOWN",
+                filterable=True, # Allows typing to search
+                interactive=True
+            )
             
             predict_btn = gr.Button("Predict ETA", variant="primary")