Update app.py

app.py

@@ -1,64 +1,61 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import random
+
+# Ahantu na coordinates
+locations = {
+    "Downtown": {"lat": -1.95, "lon": 30.05, "avg_speed": 30, "avg_vehicles": 60},
+    "Highway": {"lat": -1.92, "lon": 30.06, "avg_speed": 100, "avg_vehicles": 40},
+    "Industrial Area": {"lat": -1.94, "lon": 30.07, "avg_speed": 50, "avg_vehicles": 30},
+    "School Zone": {"lat": -1.93, "lon": 30.03, "avg_speed": 20, "avg_vehicles": 20}
+}
+
+def simulate_traffic_map(area):
+    info = locations[area]
+    speed = round(random.gauss(info["avg_speed"], 10), 1)
+    vehicle_count = int(random.gauss(info["avg_vehicles"], 10))
+    if speed < 20 and vehicle_count > 50:
+        traffic_level = "🚦 High Traffic Jam"
+        status = "Blocked"
+    elif speed < 40 or vehicle_count > 40:
+        traffic_level = "⚠️ Moderate Traffic"
+        status = "Restricted"
+    else:
+        traffic_level = "✅ Light Traffic"
+        status = "Clear"
+    
+    report = (f"📍 **{area}**\n"
+              f"🚗 Speed: {speed} km/h\n"
+              f"🚙 Vehicles: {vehicle_count}\n"
+              f"📊 Status: {status}\n"
+              f"📣 Traffic: {traffic_level}")
+    
+    lat, lon = info["lat"], info["lon"]
+    html = f"""
+    <div id="map" style="width:100%;height:400px;"></div>
+    <link rel="stylesheet" href="https://unpkg.com/leaflet/dist/leaflet.css"/>
+    <script src="https://unpkg.com/leaflet/dist/leaflet.js"></script>
+    <script>
+      var map = L.map('map').setView([{lat}, {lon}], 14);
+      L.tileLayer('https://{{s}}.tile.openstreetmap.org/{{z}}/{{x}}/{{y}}.png', {{
+        maxZoom: 19
+      }}).addTo(map);
+      L.marker([{lat}, {lon}])
+        .addTo(map)
+        .bindPopup("{area}: {traffic_level}")
+        .openPopup();
+    </script>
+    """
+    return report, html
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🗺️ Traffic Monitoring with Real Map View")
+    
+    location = gr.Dropdown(list(locations.keys()), label="Choose Location", value="Downtown")
+    simulate_btn = gr.Button("Simulate Traffic")
+    output = gr.Markdown()
+    map_view = gr.HTML()
+    
+    simulate_btn.click(fn=simulate_traffic_map, inputs=location, outputs=[output, map_view])
+
+demo.launch()
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()