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130 lines
4.1 KiB
130 lines
4.1 KiB
import sys
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import requests
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import json
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import os
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import openai
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from PyQt5.QtWidgets import QApplication, QMainWindow, QGridLayout, QTextEdit, QPushButton, QLineEdit, QWidget
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class MainWindow(QMainWindow):
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def __init__(self):
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super().__init__()
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# Set window title
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self.setWindowTitle("Chatbot")
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# Set window size
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self.setGeometry(100, 100, 800, 600)
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# Create central widget
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central_widget = QWidget()
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# Create text input field for user's messages
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self.text_input = QLineEdit(self)
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self.text_input.setGeometry(20, 540, 550, 40)
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# Create send button to send user's messages
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self.send_button = QPushButton("Send", self)
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self.send_button.setGeometry(580, 540, 200, 40)
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self.send_button.clicked.connect(self.send_message)
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# Create chat window to display conversation
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self.chat_window = QTextEdit(self)
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self.chat_window.setGeometry(20, 20, 760, 500)
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self.chat_window.setReadOnly(True)
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# Initialize message counter
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self.num_messages = 0
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def send_message(self):
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# Get user's message from text input field
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user_message = self.text_input.text()
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# TEMPORAIRE
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tokens = 100
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temperature = 0.1
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# Increment message counter
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self.num_messages += 1
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# Define the API endpoint URL
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endpoint = 'https://api.openai.com/v1/completions'
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apiKey = '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'
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# Load your API key from an environment variable or secret management service
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openai.api_key = os.getenv("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")
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response = openai.Completion.create(model="gpt-3.5-turbo", prompt="Say this is a test", temperature=0, max_tokens=7)
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openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Who won the world series in 2020?"},
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{"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
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{"role": "user", "content": "Where was it played?"}
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]
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)
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"""
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{
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'id': 'chatcmpl-6p9XYPYSTTRi0xEviKjjilqrWU2Ve',
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'object': 'chat.completion',
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'created': 1677649420,
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'model': 'gpt-3.5-turbo',
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'usage': {'prompt_tokens': 56, 'completion_tokens': 31, 'total_tokens': 87},
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'choices': [
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{
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'message': {
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'role': 'assistant',
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'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.'},
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'finish_reason': 'stop',
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'index': 0
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}
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]
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}
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"""
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# Define the request headers (if needed)
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {apiKey}"
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}
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json_data = {
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"model": "gpt-3.5-turbo",
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"prompt": user_message,
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"max_tokens": tokens,
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"temperature": temperature
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}
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# Send the POST request and capture the response
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response = requests.post(endpoint, headers=headers, data=json.dumps(json_data))
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# Retrieve the response from the API
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response_dict = response.json()
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ext = response_dict["choices"][0]["text"]
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bot_response = f"{ext}"
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# Add user's message and bot's response to chat window
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self.chat_window.append(f"<p style='color: #0084ff;'><strong>You:</strong> {user_message}</p>")
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self.chat_window.append(f"<p style='color: #008000;'><strong>Bot:</strong> {bot_response}</p>")
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# Clear text input field
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self.text_input.clear()
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if __name__ == "__main__":
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# Create QApplication instance
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app = QApplication(sys.argv)
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# Create MainWindow instance
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main_window = MainWindow()
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# Show MainWindow
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main_window.show()
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# Execute QApplication event loop
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sys.exit(app.exec_())
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