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()