Remove redundant code that has been commented out

app.py

@@ -1,205 +1,3 @@
-# import gradio as gr
-# from huggingface_hub import InferenceClient
-# import time
-# from typing import Optional, Generator
-# import logging
-# import os
-# from dotenv import load_dotenv
-
-# # 加载环境变量
-# load_dotenv()
-
-# # 设置日志
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # 初始化故事生成器的系统提示
-# STORY_SYSTEM_PROMPT = """你是一个专业的故事生成器。你需要根据用户提供的场景或角色描述，生成引人入胜的故事情节。
-# 请确保故事具有连贯性和创意性。每次回应都应该是故事情节的自然延续。"""
-
-# STORY_STYLES = [
-#     "奇幻",
-#     "科幻",
-#     "悬疑",
-#     "冒险",
-#     "爱情",
-#     "恐怖"
-# ]
-
-# MAX_RETRIES = 3
-# RETRY_DELAY = 2
-
-# def create_client() -> InferenceClient:
-#     hf_token = os.getenv('HF_TOKEN')
-#     if not hf_token:
-#         raise ValueError("HF_TOKEN 环境变量未设置")
-#     return InferenceClient(
-#         "HuggingFaceH4/zephyr-7b-beta",
-#         token=hf_token
-#     )
-
-# def generate_story(
-#     scene: str,
-#     style: str,
-#     history: Optional[list[dict]] = None,
-#     temperature: float = 0.7,
-#     max_tokens: int = 512,
-#     top_p: float = 0.95,
-# ) -> Generator[str, None, None]:
-#     if history is None:
-#         history = []
-        
-#     style_prompt = f"请以{style}风格续写以下故事："
-    
-#     messages = [
-#         {"role": "system", "content": STORY_SYSTEM_PROMPT},
-#         {"role": "user", "content": f"{style_prompt}\n{scene}"}
-#     ]
-    
-#     for msg in history:
-#         messages.append(msg)
-    
-#     response = ""
-#     retries = 0
-    
-#     while retries < MAX_RETRIES:
-#         try:
-#             client = create_client()
-#             for message in client.chat_completion(
-#                 messages,
-#                 max_tokens=max_tokens,
-#                 stream=True,
-#                 temperature=temperature,
-#                 top_p=top_p,
-#             ):
-#                 if hasattr(message.choices[0].delta, 'content'):
-#                     token = message.choices[0].delta.content
-#                     if token is not None:
-#                         response += token
-#                         yield response
-#             break
-#         except Exception as e:
-#             retries += 1
-#             logger.error(f"生成故事时发生错误 (尝试 {retries}/{MAX_RETRIES}): {str(e)}")
-#             if retries < MAX_RETRIES:
-#                 time.sleep(RETRY_DELAY)
-#             else:
-#                 yield f"抱歉，生成故事时遇到了问题：{str(e)}\n请稍后重试。"
-
-# def create_demo():
-#     with gr.Blocks() as demo:
-#         gr.Markdown("# 互动式故事生成器")
-#         gr.Markdown("请输入一个场景或角色描述，AI将为您生成一个有趣的故事。您可以继续输入来推进故事情节的发展。")
-        
-#         style_select = gr.Dropdown(
-#             choices=STORY_STYLES,
-#             value="奇幻",
-#             label="选择故事风格"
-#         )
-#         scene_input = gr.Textbox(
-#             lines=3,
-#             placeholder="请输入一个场景或角色描述...",
-#             label="场景描述"
-#         )
-        
-#         temperature = gr.Slider(
-#             minimum=0.1,
-#             maximum=2.0,
-#             value=0.7,
-#             step=0.1,
-#             label="创意度(Temperature)"
-#         )
-#         max_tokens = gr.Slider(
-#             minimum=64,
-#             maximum=1024,
-#             value=512,
-#             step=64,
-#             label="最大生成长度"
-#         )
-#         top_p = gr.Slider(
-#             minimum=0.1,
-#             maximum=1.0,
-#             value=0.95,
-#             step=0.05,
-#             label="采样范围(Top-p)"
-#         )
-        
-#         chatbot = gr.Chatbot(
-#             label="故事对话",
-#             type="messages"
-#         )
-#         status_msg = gr.Markdown("")
-        
-#         submit_btn = gr.Button("生成故事")
-#         clear_btn = gr.Button("清除对话")
-        
-#         def user_input(user_message, history):
-#             if history is None:
-#                 history = []
-#             history.append({"role": "user", "content": user_message})
-#             return "", history
-        
-#         def bot_response(history, style, temperature, max_tokens, top_p):
-#             try:
-#                 current_message = {"role": "assistant", "content": ""}
-#                 history.append(current_message)
-                
-#                 for text in generate_story(
-#                     history[-2]["content"],
-#                     style,
-#                     history[:-2],
-#                     temperature,
-#                     max_tokens,
-#                     top_p
-#                 ):
-#                     current_message["content"] = text
-#                     yield history
-#             except Exception as e:
-#                 logger.error(f"处理响应时发生错误: {str(e)}")
-#                 current_message["content"] = f"抱歉，生成故事时遇到了问题。请稍后重试。"
-#                 yield history
-        
-#         scene_input.submit(
-#             user_input,
-#             [scene_input, chatbot],
-#             [scene_input, chatbot]
-#         ).then(
-#             bot_response,
-#             [chatbot, style_select, temperature, max_tokens, top_p],
-#             chatbot
-#         )
-        
-#         submit_btn.click(
-#             user_input,
-#             [scene_input, chatbot],
-#             [scene_input, chatbot]
-#         ).then(
-#             bot_response,
-#             [chatbot, style_select, temperature, max_tokens, top_p],
-#             chatbot
-#         )
-        
-#         def clear_chat():
-#             return [], ""
-        
-#         clear_btn.click(
-#             clear_chat,
-#             None,
-#             [chatbot, status_msg],
-#         )
-        
-#         return demo
-
-# if __name__ == "__main__":
-#     demo = create_demo()
-#     demo.queue().launch(
-#         server_name="0.0.0.0",
-#         server_port=7860,
-#         share=False
-#     )
-
-
-
 import gradio as gr
 from huggingface_hub import InferenceClient
 import time