Update app.py

app.py

@@ -1,64 +1,71 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 
-"""
-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")
+# Ibyo dushaka kugenzura: power output (kW) n'ibikoresho bikoresha power
+# Turi gutegura loads 3: amatara, firigo, televiziyo
 
+def energy_management(power_output, light_load, fridge_load, tv_load):
+    total_load = light_load + fridge_load + tv_load
+    messages = []
+    
+    messages.append(f"🔌 Power output available: {power_output} kW")
+    messages.append(f"💡 Total load demand: {total_load} kW")
+    
+    if power_output >= total_load:
+        surplus = power_output - total_load
+        messages.append(f"✅ Power is sufficient. Surplus: {surplus:.2f} kW")
+        messages.append("🔋 Amashanyarazi asigaye ashobora kubikwa cyangwa gukoreshwa mu bindi bikoresho.")
+    else:
+        deficit = total_load - power_output
+        messages.append(f"⚠️ Power deficit! Kurwanya deficit: {deficit:.2f} kW")
+        # Gukata load zidakenewe
+        # Tugena priority: Firigo > TV > Lights
+        load_status = {}
+        remaining_power = power_output
+        
+        # Firigo ifite priority ya mbere
+        if fridge_load <= remaining_power:
+            load_status["Fridge"] = "ON"
+            remaining_power -= fridge_load
+        else:
+            load_status["Fridge"] = "OFF"
+        
+        # TV ifite priority ya kabiri
+        if tv_load <= remaining_power:
+            load_status["TV"] = "ON"
+            remaining_power -= tv_load
+        else:
+            load_status["TV"] = "OFF"
+        
+        # Lights ifite priority ya nyuma
+        if light_load <= remaining_power:
+            load_status["Lights"] = "ON"
+            remaining_power -= light_load
+        else:
+            load_status["Lights"] = "OFF"
+        
+        messages.append("📉 Ibyuma byakozweho:")
+        for device, status in load_status.items():
+            messages.append(f" - {device}: {status}")
+    
+    return "\n".join(messages)
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+with gr.Blocks() as demo:
+    gr.Markdown("## Energy Management System Simulation")
+    
+    power_output = gr.Slider(0, 10, step=0.1, label="Power Output (kW)", value=5)
+    
+    light_load = gr.Slider(0, 5, step=0.1, label="Lights Load (kW)", value=1)
+    fridge_load = gr.Slider(0, 5, step=0.1, label="Fridge Load (kW)", value=2)
+    tv_load = gr.Slider(0, 5, step=0.1, label="TV Load (kW)", value=1)
+    
+    output = gr.Textbox(label="System Report", lines=12)
+    
+    inputs = [power_output, light_load, fridge_load, tv_load]
+    for inp in inputs:
+        inp.change(fn=energy_management, inputs=inputs, outputs=output)
+    
+    # Report ya mbere
+    output.value = energy_management(power_output.value, light_load.value, fridge_load.value, tv_load.value)
+    
+demo.launch()
 
-    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()