client = OpenAI(api_key=OPEN_AI_KEY)

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import json
 import os
-import openai
+from openai import OpenAI
 import re
 from azure.cognitiveservices.speech import SpeechConfig, SpeechSynthesizer, AudioConfig
 
@@ -14,6 +14,8 @@ AZURE_REGION = os.environ['AZURE_REGION']
 AZURE_API_KEY = os.environ['AZURE_API_KEY']
 
 
+
+
 def validate_and_correct_chat(data, roles=["A", "B"], rounds=2):
     """
     Corrects the chat data to ensure proper roles and number of rounds.
@@ -55,7 +57,7 @@ def extract_json_from_response(response_text):
 
 
 def create_chat_dialogue(rounds, role1, role1_gender, role2, role2_gender, theme, language, cefr_level):
-    openai.api_key = os.environ["OPEN_AI_KEY"]
+    client = OpenAI(api_key=OPEN_AI_KEY)
 
     # 初始化對話
     sentenses_count = int(rounds) * 2
@@ -71,15 +73,16 @@ def create_chat_dialogue(rounds, role1, role1_gender, role2, role2_gender, theme
     print("=====messages=====")
 
 
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=messages,
-        max_tokens=int(500 * int(rounds))  # 設定一個較大的值，可根據需要調整
-    )
+    request_payload = {
+        "model": "gpt-4-1106-preview",
+        "messages": messages,
+        "max_tokens": int(500 * int(rounds))  # 設定一個較大的值，可根據需要調整
+    }
 
+    response = client.chat.completions.create(**request_payload)
     print(response)
     
-    response_text = response.choices[0].message['content'].strip()
+    response_text = response.choices[0].message.content.strip()
     extract_json = extract_json_from_response(response_text)
     dialogue = validate_and_correct_chat(data=extract_json, roles=[role1, role2], rounds=rounds)
 

requirements.txt

@@ -1,4 +1,4 @@
 gradio
 gtts
-openai
+openai >= 1.0.0
 azure-cognitiveservices-speech