Create app.py

app.py

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+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(server_port=6006)