Merge branch 'main' of https://huggingface.co/spaces/ChanMeng666/interactive-story-generator

app.py

@@ -1,3 +1,205 @@
+# 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
@@ -466,3 +668,4 @@ if __name__ == "__main__":
         server_port=7860,
         share=False
     )
+