import gradio as gr import logging import json import numpy as np from scipy.io import wavfile from utils.chatgpt import Chatgpt from utils.my_tts import MY_TTS from utils.config import Config from utils.common import Common from utils.logger import Configure_logger common = Common() # 日志文件路径 log_path = "./log/log-" + common.get_bj_time(1) + ".txt" Configure_logger(log_path) # 获取 httpx 库的日志记录器 httpx_logger = logging.getLogger("httpx") # 设置 httpx 日志记录器的级别为 WARNING httpx_logger.setLevel(logging.WARNING) config_path = "config.json" config = Config(config_path) # Chatgpt chatgpt = Chatgpt(config.get("openai"), config.get("chatgpt")) my_tts = MY_TTS(config_path) config_data = None try: with open(config_path, 'r', encoding="utf-8") as config_file: config_data = json.load(config_file) except Exception as e: logging.error(f"无法读取配置文件！\n{e}") """ 通用函数 """ def textarea_data_change(data): """ 字符串数组数据格式转换 """ tmp_str = "" for tmp in data: tmp_str = tmp_str + tmp + "\n" return tmp_str def reset_record(): # 这里的代码将在客户端执行，以重置录音组件 return """ document.getElementById("component-2").getElementsByTagName("button")[0].click(); """ def send_msg(audio, text): try: if text: stt_ret = text if audio: # 创建一个示例的 int16 音频数据 int16_audio_data = np.array(audio[1], dtype=np.int16) # 创建一个临时文件来存储录制的音频数据 output_file = "out/" + common.get_bj_time(4) + ".wav" # 使用 scipy.io.wavfile 将数据保存为 WAV 文件 wavfile.write(output_file, audio[0], int16_audio_data) audio_file= open(output_file, "rb") # 调用 openai 接口，并传递音频文件路径 stt_ret = chatgpt.STT(audio_file) logging.info(f"语音识别内容：{stt_ret}") # 数据回显 text_input.value = stt_ret chat_ret = chatgpt.get_gpt_resp("主人", stt_ret) logging.info(f"对话返回：{chat_ret}") data = { "type": config_data["openai_tts"]["type"], "api_ip_port": config_data["openai_tts"]["api_ip_port"], "model": config_data["openai_tts"]["model"], "voice": config_data["openai_tts"]["voice"], "api_key": config_data["openai_tts"]["api_key"], "content": chat_ret } audio_path = my_tts.openai_tts_api(data) logging.info(f"合成音频输出在：{audio_path}") return audio_path, chat_ret except Exception as e: logging.error(f"Error processing audio: {str(e)}") return None # 保存配置 def save_config(api, api_key, model, temperature, max_tokens, top_p, presence_penalty, frequency_penalty, preset, openai_tts_api_ip_port, openai_tts_api_key, openai_tts_model, openai_tts_voice, gradio_share, gradio_save_local): global config_data, chatgpt try: with open(config_path, 'r', encoding="utf-8") as config_file: config_data = json.load(config_file) except Exception as e: logging.error(f"无法读取配置文件！\n{e}") gr.Error(f"无法读取配置文件！\n{e}") return f"无法读取配置文件！{e}" def common_textarea_handle(content): """通用的textEdit 多行文本内容处理 Args: content (str): 原始多行文本内容 Returns: _type_: 处理好的多行文本内容 """ # 通用多行分隔符 separators = [" ", "\n"] ret = [token.strip() for separator in separators for part in content.split(separator) if (token := part.strip())] if 0 != len(ret): ret = ret[1:] return ret config_data["openai"]["api"] = api config_data["openai"]["api_key"] = common_textarea_handle(api_key) config_data["chatgpt"]["model"] = model config_data["chatgpt"]["temperature"] = float(temperature) config_data["chatgpt"]["max_tokens"] = int(max_tokens) config_data["chatgpt"]["top_p"] = float(top_p) config_data["chatgpt"]["presence_penalty"] = float(presence_penalty) config_data["chatgpt"]["frequency_penalty"] = float(frequency_penalty) config_data["chatgpt"]["preset"] = preset config_data["openai_tts"]["api_ip_port"] = openai_tts_api_ip_port config_data["openai_tts"]["api_key"] = openai_tts_api_key.strip() config_data["openai_tts"]["model"] = openai_tts_model config_data["openai_tts"]["voice"] = openai_tts_voice config_data["gradio"]["share"] = gradio_share config_data["gradio"]["save_local"] = gradio_save_local # 重载chatgpt chatgpt = Chatgpt(config_data["openai"], config_data["chatgpt"]) if False == gradio_save_local: logging.info("配置已加载") return "配置已加载" # 写入配置到配置文件 try: with open(config_path, 'w', encoding="utf-8") as config_file: json.dump(config_data, config_file, indent=2, ensure_ascii=False) config_file.flush() # 刷新缓冲区，确保写入立即生效 logging.info("配置数据已成功写入文件！") gr.Info("配置数据已成功写入文件！") return "配置数据已成功写入文件！" except Exception as e: logging.error(f"无法读取配置文件！\n{e}") gr.Error(f"无法读取配置文件！\n{e}") return f"无法读取配置文件！{e}" with gr.Blocks() as demo: # 创建 Tab 组件，用于容纳不同的页面 with gr.Tab("对话页") as tab1: with gr.Row(): record = gr.Audio(interactive=True) text_input = gr.Textbox(label="输入文本", lines=10) submit_button = gr.Button("发送") # 添加一个空的Textbox来增加间距 with gr.Row(): gr.Textbox(value="", visible=False, interactive=False, label="") with gr.Row(): resp_display = gr.Textbox(label="Bot回复") with gr.Row(): # 创建一个音频播放器组件，它将使用音频路径来加载音频 audio_player = gr.Audio(interactive=False, label="合成的音频", autoplay=True) submit_button.click( send_msg, inputs=[record, text_input], outputs=[audio_player, resp_display], js=reset_record ) with gr.Tab("配置页") as tab2: with gr.Group(): with gr.Row(): openai_api_input = gr.Textbox(label="OpenAI API地址", value=config.get("openai", "api")) openai_api_key_input = gr.Textbox( label="OpenAI API密钥", value=textarea_data_change(config.get("openai", "api_key")), lines=3 ) with gr.Row(): chatgpt_model_dropdown = gr.Dropdown( choices=[ "gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-instruct", "gpt-3.5-turbo-instruct-0914", "gpt-4", "gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613", "gpt-4-1106-preview", "text-embedding-ada-002", "text-davinci-003", "text-davinci-002", "text-curie-001", "text-babbage-001", "text-ada-001", "text-moderation-latest", "text-moderation-stable", ], label="模型", value=config.get("chatgpt", "model"), ) with gr.Row(): chatgpt_temperature_input = gr.Textbox(value=config.get("chatgpt", "temperature"), label="temperature") chatgpt_max_tokens_input = gr.Textbox(value=config.get("chatgpt", "max_tokens"), label="max_tokens") chatgpt_top_p_input = gr.Textbox(value=config.get("chatgpt", "top_p"), label="top_p") with gr.Row(): chatgpt_presence_penalty_input = gr.Textbox(value=config.get("chatgpt", "presence_penalty"), label="presence_penalty") chatgpt_frequency_penalty_input = gr.Textbox(value=config.get("chatgpt", "frequency_penalty"), label="frequency_penalty") chatgpt_preset_input = gr.Textbox(value=config.get("chatgpt", "preset"), label="预设", lines=5) with gr.Group(): with gr.Row(): openai_tts_api_ip_port_input = gr.Textbox( label="OpenAI TTS API地址", value=config.get("openai_tts", "api_ip_port"), lines=1 ) openai_tts_api_key_input = gr.Textbox( label="OpenAI API密钥", value=config.get("openai_tts", "api_key"), lines=1 ) with gr.Row(): openai_tts_model_dropdown = gr.Dropdown( choices=[ "tts-1", "tts-1-hd", ], label="模型", value=config.get("openai_tts", "model"), ) openai_tts_voice_dropdown = gr.Dropdown( choices=[ "alloy", "echo", "fable", "onyx", "nova", "shimmer", ], label="说话人", value=config.get("openai_tts", "voice"), ) with gr.Group(): with gr.Row(): gradio_share_checkbox = gr.Checkbox(value=config.get("gradio", "share"), label="生成公网链接") gradio_save_local_checkbox = gr.Checkbox(value=config.get("gradio", "save_local"), label="保存配置到本地文件") with gr.Group(): with gr.Row(): save_btn = gr.Button("保存") output_label = gr.Label(label="结果") save_btn.click( save_config, inputs=[openai_api_input, openai_api_key_input, chatgpt_model_dropdown, chatgpt_temperature_input, chatgpt_max_tokens_input, chatgpt_top_p_input, chatgpt_presence_penalty_input, chatgpt_frequency_penalty_input, chatgpt_preset_input, openai_tts_api_ip_port_input, openai_tts_api_key_input, openai_tts_model_dropdown, openai_tts_voice_dropdown, gradio_share_checkbox, gradio_save_local_checkbox], outputs=output_label, js=None ) demo.launch(share=config.get("gradio", "share"))