diff --git a/SupportPC.py b/SupportPC.py
index fa8e06e..25fd7bf 100644
--- a/SupportPC.py
+++ b/SupportPC.py
@@ -1,10 +1,6 @@
 import sys
-import requests
-import json
-import os
 import openai
-from PyQt5.QtWidgets import QApplication, QMainWindow, QGridLayout, QTextEdit, QPushButton, QLineEdit, QWidget
-
+from PyQt5.QtWidgets import QApplication, QMainWindow, QTextEdit, QPushButton, QLineEdit, QWidget
 
 class MainWindow(QMainWindow):
     def __init__(self):
@@ -23,98 +19,38 @@ class MainWindow(QMainWindow):
         self.text_input = QLineEdit(self)
         self.text_input.setGeometry(20, 540, 550, 40)
 
-        # Create send button to send user's messages
-        self.send_button = QPushButton("Send", self)
-        self.send_button.setGeometry(580, 540, 200, 40)
-        self.send_button.clicked.connect(self.send_message)
+        # Initialize API needs
+        openai.api_key = "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"
+        self.chat_log = [{"role": "system", "content": "Tu es un prof de Python"}]
 
         # Create chat window to display conversation
         self.chat_window = QTextEdit(self)
         self.chat_window.setGeometry(20, 20, 760, 500)
         self.chat_window.setReadOnly(True)
 
-        # Initialize message counter
-        self.num_messages = 0
+        # Create send button to send user's messages
+        self.send_button = QPushButton("Send", self)
+        self.send_button.setGeometry(580, 540, 200, 40)
+        self.send_button.clicked.connect(self.send_message)
 
     def send_message(self):
         # Get user's message from text input field
         user_message = self.text_input.text()
 
-        # TEMPORAIRE
-        tokens = 100
-        temperature = 0.1
-
-        # Increment message counter
-        self.num_messages += 1
-
-        # Define the API endpoint URL
-        endpoint = 'https://api.openai.com/v1/completions'
-        apiKey = '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'
-
-        # Load your API key from an environment variable or secret management service
-        openai.api_key = os.getenv("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")
-
-        response = openai.Completion.create(model="gpt-3.5-turbo", prompt="Say this is a test", temperature=0, max_tokens=7)
-
-        openai.ChatCompletion.create(
+        self.chat_log.append({"role": "user", "content": user_message})
+        reply = openai.ChatCompletion.create(
             model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": "Who won the world series in 2020?"},
-                {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
-                {"role": "user", "content": "Where was it played?"}
-            ]
-        )
-
-        """
-        {
-        'id': 'chatcmpl-6p9XYPYSTTRi0xEviKjjilqrWU2Ve',
-        'object': 'chat.completion',
-        'created': 1677649420,
-        'model': 'gpt-3.5-turbo',
-        'usage': {'prompt_tokens': 56, 'completion_tokens': 31, 'total_tokens': 87},
-        'choices': [
-        {
-            'message': {
-              'role': 'assistant',
-              'content': 'The 2020 World Series was played in Arlington, Texas at the Globe Life Field, which was the new home stadium for the Texas Rangers.'},
-            'finish_reason': 'stop',
-            'index': 0
-        }
-        ]
-        }
-        """
-
-        # Define the request headers (if needed)
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {apiKey}"
-        }
-
-        json_data = {
-            "model": "gpt-3.5-turbo",
-            "prompt": user_message,
-            "max_tokens": tokens,
-            "temperature": temperature
-        }
-
-        # Send the POST request and capture the response
-        response = requests.post(endpoint, headers=headers, data=json.dumps(json_data))
-
-        # Retrieve the response from the API
-        response_dict = response.json()
-        ext = response_dict["choices"][0]["text"]
-        bot_response = f"{ext}"
+            messages=self.chat_log)
+        response=reply['choices'][0]['message']['content']
+        self.chat_log.append({"role": "assistant", "content":response})
 
         # Add user's message and bot's response to chat window
         self.chat_window.append(f"<p style='color: #0084ff;'><strong>You:</strong> {user_message}</p>")
-        self.chat_window.append(f"<p style='color: #008000;'><strong>Bot:</strong> {bot_response}</p>")
+        self.chat_window.append(f"<p style='color: #008000;'><strong>Bot:</strong> {response}</p>")
 
         # Clear text input field
         self.text_input.clear()
 
-
-
 if __name__ == "__main__":
     # Create QApplication instance
     app = QApplication(sys.argv)