Update app.py

app.py

@@ -1,11 +1,31 @@
 import os
+import json
 import gradio as gr
-from ultralytics import YOLO  # Menggunakan YOLOv8 untuk deteksi objek
+from ultralytics import YOLO  
 from PIL import Image, ImageDraw
 import torch
+from langchain.chat_models import ChatGoogleGenerativeAI
 
-# Load model YOLOv8 (pastikan model ini telah di-download)
-model = YOLO("yolov8n.pt")  # Bisa diganti dengan model yang lebih besar jika diperlukan
+# Load model YOLOv8 
+model = YOLO("yolov8n.pt") 
+
+# Load credentials (stringified JSON) from environment variable for Gemini
+credentials_string = os.environ.get("GOOGLE_APPLICATION_CREDENTIALS")
+if not credentials_string:
+    raise ValueError("GOOGLE_APPLICATION_CREDENTIALS is not set in the environment!")
+
+# Parse the stringified JSON back to a Python dictionary
+credentials = json.loads(credentials_string)
+
+# Save the credentials to a temporary JSON file (required by Google SDKs)
+with open("service_account.json", "w") as f:
+    json.dump(credentials, f)
+
+# Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the temporary file
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "service_account.json"
+
+# Initialize Gemini model (chatbot)
+llm = ChatGoogleGenerativeAI(model='gemini-1.5-pro')
 
 # Global chat history
 chat_history = []
@@ -13,7 +33,8 @@ chat_history = []
 # Fungsi untuk chatting dengan chatbot
 def chat_with_bot(message):
     global chat_history
-    bot_response = f"Bot: Saya menerima pesan Anda: '{message}'"  # Placeholder response
+    response = llm.predict(message)  # Menggunakan Gemini untuk menghasilkan respon
+    bot_response = f"Bot: {response}"
     chat_history.append((message, bot_response))
     return chat_history