refactor

json_textbox = gr.Textbox(readonly=True, label="對話 JSON 內容", lines=10)

demo.launch(inline=False, share=True)

with gr.Blocks(theme="light") as demo: # 使用 'light' 主题作为默认值

layout = gr.Row(

layout="1:3" # 新增這一行

readonly=True, label="對話 JSON 內容", lines=10

prompt = f"您將進行一場以{theme}為主題的對話。{role1} (gender: {role1_gender}) 和{role2} (gender: {role2_gender})將是參與者。請依次交談{rounds}輪。(1輪對話的定義是 {role1} 和 {role2} 各說一句話，總共 {sentenses_count} 句話。)以json格式儲存對話。並回傳對話JSON文件。格式為：[{{role:\"{role1}\", \"gender\": {role1_gender} , content: \".....\"}}, {{role:\"{role2}\", \"gender\": {role2_gender}, content: \".....\"}}]"

delete audio

def detect_language(text):

azure-cognitiveservices-speech

speech_config = speechsdk.SpeechConfig(subscription=AZURE_API_KEY, region=AZURE_REGION)

import pyttsx3

engine = pyttsx3.init()

audio_path = dialogue_to_audio(structured_dialogue, role1_gender, role2_gender)

def dialogue_to_audio(dialogue, role1_gender, role2_gender):

def main_function(password: str, theme: str, language: str, method: str, rounds: int, role1: str, role1_gender: str, role2: str, role2_gender: str):

def main_function(password: str, theme: str, language: str, method: str, rounds: int, role1_data: tuple, role2_data: tuple):

text = " ".join([f"{item['content']}" for item in dialogue])

role1_content = f"{structured_dialogue[i]['content']}"

dialogue = create_chat_dialogue(rounds, role1, role2, theme, language)

def create_chat_dialogue(rounds, role1, role2, theme, language):

gr.components.Dropdown(choices=["中文", "英文"], label="語言"),

import gradio as gr

prompt = f"您將進行一場以{theme}為主題的對話。{role1}和{role2}將是參與者。請依次交談{rounds}輪。(1輪對話的定義是 {role1} 和 {role2} 各說一句話。)以json格式儲存對話。並回傳對話JSON文件。格式為：[{{role:\"{role1}\", content: \".....\"}}, {{role:\"{role2}\", content: \".....\"}}]"

sys_content = f"你是一個英文家教，請用英文生成對話，請嚴格控制 {rounds} 輪對話的長度。 1輪對話的定義是 {role1} 和 {role2} 各說一句話。"

sys_content = f"你是一個英文家教，請用英文生成對話，請嚴格控制 {rounds} 輪對話的長度。"

prompt = f"您將進行一場以{theme}為主題的對話。{role1}和{role2}將是參與者。請依次交談{rounds}輪。以json格式儲存對話。並回傳對話JSON文件。格式為：[{{role:\"{role1}\", content: \".....\"}}, {{role:\"{role2}\", content: \".....\"}}]"

dialogue = validate_and_correct_chat(data=extract_json, roles=[role1, role2], rounds=rounds)

roles = [role1, role2]

dialogue = validate_and_correct_chat(extract_json, roles=[role1, role2], rounds)

prompt = f"您將進行一場以{theme}為主題的對話。{role1}和{role2}將是參與者。請依次交談{rounds}輪。以json格式儲存對話。並回傳對話JSON文件。格式為：[{{role1:\"{role1}\", content: \".....\"}}, {{role2:\"{role2}\", content: \".....\"}}]"

print(messages)

def generate_dialogue(rounds, method, role1, role2, theme):

def generate_dialogue(rounds=2, method="auto", role1="Mary", role2="Ken", theme="購物"):

def main_function(password: str, theme: str, method: str, rounds: int, role1: str, role2: str):

max_tokens=int(500 * int(rounds)) # 設定一個較大的值，可根據需要調整

max_tokens=500 * rounds # 設定一個較大的值，可根據需要調整

ne desult

gr.components.Textbox(label="角色 2 名稱", default="Alex"),

main_function,

sys_content = f"你是一個英文家教，請用英文生成對話"

gr.components.Textbox(label="對話主題", default="購物"), # 加入 theme 的輸入框，設定預設值為 '購物'

response = openai.ChatCompletion.create(

def extract_json_from_response(response_text):

create_chat_dialogue

def generate_dialogue_with_openai(rounds, role1, role2):

response = openai.Completion.create(

def main_function(password: str, rounds: int, method: str, role1: str, role2: str):

2