app.py

import gradio as gr
from gtts import gTTS
import json
import os
import openai
import re


PASSWORD = os.environ['PASSWORD']
OPEN_AI_KEY = os.environ['OPEN_AI_KEY']


def validate_and_correct_chat(data, roles=["A", "B"], rounds=2):
    """
    Corrects the chat data to ensure proper roles and number of rounds.

    Parameters:
    - data (list): The chat data list of dicts, e.g. [{"role": "A", "content": "Hi"}, ...]
    - roles (list): The expected roles, default is ["A", "B"]
    - rounds (int): The number of rounds expected

    Returns:
    - list: Corrected chat data
    """
    
    # Validate role names
    for item in data:
        if item['role'] not in roles:
            print(f"Invalid role '{item['role']}' detected. Correcting it.")
            # We will change the role to the next expected role in the sequence.
            prev_index = roles.index(data[data.index(item) - 1]['role'])
            next_index = (prev_index + 1) % len(roles)
            item['role'] = roles[next_index]

    # Validate number of rounds
    expected_entries = rounds * len(roles)
    if len(data) > expected_entries:
        print(f"Too many rounds detected. Trimming the chat to {rounds} rounds.")
        data = data[:expected_entries]

    return data

def extract_json_from_response(response_text):
    # 使用正則表達式匹配 JSON 格式的對話
    match = re.search(r'\[\s*\{.*?\}\s*\]', response_text, re.DOTALL)
    if match:
        json_str = match.group(0)
        return json.loads(json_str)
    else:
        raise ValueError("JSON dialogue not found in the response.")


def create_chat_dialogue(rounds, role1, role2, theme, language):
    openai.api_key = os.environ["OPEN_AI_KEY"]

    # 初始化對話
    sentenses_count = int(rounds) * 2
    sys_content = f"你是一個{language}家教，請用{language}生成對話"
    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，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}\", content: \".....\"}}, {{role:\"{role2}\", content: \".....\"}}]"
    messages = [
        {"role": "system", "content": sys_content},
        {"role": "user", "content": prompt}
    ]

    print("=====messages=====")
    print(messages)
    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
    )

    print(response)
    
    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)

    print(dialogue)
    # 這裡直接返回JSON格式的對話，但考慮到這可能只是一個字符串，您可能還需要將它解析為一個Python對象
    return dialogue


def generate_dialogue(rounds, method, role1, role2, theme, language):
    if method == "auto":
        dialogue = create_chat_dialogue(rounds, role1, role2, theme, language)
    else:
        dialogue = [{"role": role1, "content": "手動輸入文本 1"}, {"role": role2, "content": "手動輸入文本 2"}]
    return dialogue

def main_function(password: str, theme: str, language: str, method: str, rounds: int, role1: str, role1_gender: str, role2: str, role2_gender: str):
    if password != os.environ.get("PASSWORD", ""):
        return "错误的密码，请重新输入。", "", ""

    structured_dialogue = generate_dialogue(rounds, method, role1, role2, theme, language)

    # Convert structured dialogue for Chatbot component to show "role1: content1" and "role2: content2" side by side
    chatbot_dialogue = []
    for i in range(0, len(structured_dialogue), 2):  # We iterate with a step of 2 to take pairs
        # Get the content for the two roles in the pair
        role1_content = f"{structured_dialogue[i]['content']}"
        role2_content = f"{structured_dialogue[i+1]['content']}" if i+1 < len(structured_dialogue) else ""
        
        chatbot_dialogue.append((role1_content, role2_content))

    audio_path = dialogue_to_audio(structured_dialogue, role1_gender, role2_gender)
    json_output = json.dumps({"dialogue": structured_dialogue}, ensure_ascii=False, indent=4)

    # 儲存對話為 JSON 文件
    file_name = "dialogue_output.txt"
    with open(file_name, "w", encoding="utf-8") as f:
        f.write(json_output)

    return chatbot_dialogue, audio_path, file_name

def dialogue_to_audio(dialogue, role1_gender, role2_gender):
    engine = pyttsx3.init()

    # Fetch the list of available voices
    voices = engine.getProperty('voices')

    # Get voice IDs for male and female voices (you might need to adjust these based on available voices on your system)
    male_voice_id = "com.apple.speech.synthesis.voice.alex"  # Example ID for a male voice
    female_voice_id = "com.apple.speech.synthesis.voice.victoria"  # Example ID for a female voice
    
    file_path = "temp_audio.mp3"
    
    for i, item in enumerate(dialogue):
        gender = role1_gender if i % 2 == 0 else role2_gender
        voice_id = male_voice_id if gender == "male" else female_voice_id
        
        # Set the voice
        engine.setProperty('voice', voice_id)

        # Now, synthesize the speech
        engine.save_to_file(item['content'], file_path)
        engine.runAndWait()

    return file_path



if __name__ == "__main__":
    gr.Interface(
        main_function, 
        [
            gr.components.Textbox(label="输入密码", type="password"),
            gr.components.Textbox(label="對話主題"),  # 加入 theme 的輸入框，設定預設值為 '購物'
            gr.components.Dropdown(choices=["中文", "英文"], label="語言"),
            gr.components.Dropdown(choices=["auto", "manual"], label="生成方式"),
            gr.components.Slider(minimum=2, maximum=6, step=2, label="對話輪數"),
            gr.components.Textbox(label="角色 1 名稱"),
            gr.components.Dropdown(choices=["male", "female"], label="角色 1 性別"),
            gr.components.Textbox(label="角色 2 名稱"),
            gr.components.Dropdown(choices=["male", "female"], label="角色 2 性別")
        ], 
        [
            gr.components.Chatbot(label="生成的對話"),
            gr.components.Audio(type="filepath", label="對話朗讀"),
            gr.components.File(label="下載對話 JSON 文件")
        ]
    ).launch()