import gradio as gr import random import time # 假设这是队标的URL或本地路径 team_logo_url = './team-logo.jpg' # 替换为你的队标图片路径 speakers = ["subway"] project_intro = """ ## Automatic learning DEMO **atomatic learning是一个训练方式的探索** **通过采样视频素材来微调LLM和音色模型** 尽可能模仿出训练对象的说话语气和音色 _训练结果来自嘉然4个视频,时长6小时_ 项目使用方案 - **语音**:bert-vits2 - **LLM**:Chat GLM-2 特别感谢:trochkera开源训练库 **注意** - 所有文本数据来自视频ASR提取,价值观与基本信息未经人工对齐。所以我们不能对输出结果进行保证 _(例如她不知道自己是女生还是男生,因为视频未提及。也可能出现LLM的“幻觉”现象)_ - 所用的BERT-VITS2版本缘故,项目暂时只支持中文 项目即将开源,测试完成后率先打包至autodl社区-Code with GPU _我们诚挚地感谢您的支持与反馈。_ _feedback email:hhyxnh@gmail_ """ with gr.Blocks() as demo: with gr.Row(): with gr.Column(scale=4): gr.Image(value=team_logo_url, width=400) gr.Markdown(project_intro) with gr.Column(scale=8): chatbot = gr.Chatbot() msg = gr.Textbox(placeholder="Type your message here...") # people_speak = gr.Textbox(value="Human", label="Your name") bot_speak = gr.Dropdown( choices=speakers, value=speakers[0], label="Speaker" ) with gr.Row(): submit = gr.Button("Chat!", variant="primary") clear = gr.ClearButton([msg, chatbot]) def respond(people_speak, bot_speak, message, chat_history): bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"]) chat_history.append(( message, bot_speak + ": " + bot_message)) time.sleep(1) return "", chat_history submit.click(respond, inputs=[bot_speak, msg, chatbot], outputs=[msg, chatbot]) if __name__ == "__main__": demo.launch(share=True)