mcp server

app.py

@@ -1,11 +1,77 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import cv2
+import numpy as np
+from mcp import MCP
+import time
+import os
+from datetime import datetime
 
 """
 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")
+mcp = MCP()
 
+def detect_fire(frame):
+    # Convert frame to HSV color space
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    
+    # Define range for fire colors (red and orange)
+    lower_fire = np.array([0, 50, 50])
+    upper_fire = np.array([30, 255, 255])
+    
+    # Create mask for fire colors
+    mask = cv2.inRange(hsv, lower_fire, upper_fire)
+    
+    # Calculate percentage of fire-colored pixels
+    fire_percentage = (np.sum(mask > 0) / (frame.shape[0] * frame.shape[1])) * 100
+    
+    return fire_percentage > 5  # Return True if more than 5% of pixels are fire-colored
+
+def send_alert(detection_type, location):
+    # Get current timestamp
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    message = f"{detection_type} detected at {location} on {timestamp}"
+    
+    # Send SMS using MCP
+    mcp.sms.send(
+        to="YOUR_PHONE_NUMBER",  # Replace with actual phone number
+        message=message
+    )
+    
+    # Send email using MCP
+    mcp.email.send(
+        to="YOUR_EMAIL",  # Replace with actual email
+        subject=f"{detection_type} Alert",
+        body=message
+    )
+
+def check_for_fire():
+    # Request webcam access
+    cap = cv2.VideoCapture(0)
+    if not cap.isOpened():
+        return "Error: Could not access webcam"
+    
+    # Read a frame
+    ret, frame = cap.read()
+    if not ret:
+        cap.release()
+        return "Error: Could not read from webcam"
+    
+    # Detect fire
+    fire_detected = detect_fire(frame)
+    
+    # Release webcam
+    cap.release()
+    
+    if fire_detected:
+        # Get location (you might want to implement a more sophisticated location detection)
+        location = "Webcam Location"  # Replace with actual location detection
+        send_alert("Fire", location)
+        return f"Fire detected at {location}! Alerts have been sent."
+    else:
+        return "No fire detected"
 
 def respond(
     message,
@@ -15,6 +81,10 @@ def respond(
     temperature,
     top_p,
 ):
+    # Check if user wants to detect fire
+    if "detect fire" in message.lower():
+        return check_for_fire()
+    
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
@@ -35,7 +105,6 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
@@ -61,4 +130,4 @@ demo = gr.ChatInterface(
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(mcp_server=True)