进行文件的逻辑拆分

初步对ui.py以及novel_generator.py进行了拆分

novel_generator/common.py

@@ -0,0 +1,59 @@
+#novel_generator/common.py
+# -*- coding: utf-8 -*-
+"""
+通用重试、清洗、日志工具
+"""
+import logging
+import re
+import time
+import traceback
+
+def call_with_retry(func, max_retries=3, sleep_time=2, fallback_return=None, **kwargs):
+    """
+    通用的重试机制封装。
+    :param func: 要执行的函数
+    :param max_retries: 最大重试次数
+    :param sleep_time: 重试前的等待秒数
+    :param fallback_return: 如果多次重试仍失败时的返回值
+    :param kwargs: 传给func的命名参数
+    :return: func的结果，若失败则返回 fallback_return
+    """
+    for attempt in range(1, max_retries + 1):
+        try:
+            return func(**kwargs)
+        except Exception as e:
+            logging.warning(f"[call_with_retry] Attempt {attempt} failed with error: {e}")
+            traceback.print_exc()
+            if attempt < max_retries:
+                time.sleep(sleep_time)
+            else:
+                logging.error("Max retries reached, returning fallback_return.")
+                return fallback_return
+
+def remove_think_tags(text: str) -> str:
+    """移除 <think>...</think> 包裹的内容"""
+    return re.sub(r'<think>.*?</think>', '', text, flags=re.DOTALL)
+
+def debug_log(prompt: str, response_content: str):
+    logging.info(
+        f"\n[#########################################  Prompt  #########################################]\n{prompt}\n"
+    )
+    logging.info(
+        f"\n[######################################### Response #########################################]\n{response_content}\n"
+    )
+
+def invoke_with_cleaning(llm_adapter, prompt: str) -> str:
+    """
+    调用 LLM，增加重试和清洗逻辑
+    如果多次失败，则返回空字符串以继续流程，而不是中断。
+    """
+    def _invoke(prompt):
+        return llm_adapter.invoke(prompt)
+
+    response = call_with_retry(func=_invoke, max_retries=3, fallback_return="", prompt=prompt)
+    if not response:
+        logging.warning("No response from model after retry. Return empty.")
+        return ""
+    cleaned_text = remove_think_tags(response)
+    debug_log(prompt, cleaned_text)
+    return cleaned_text.strip()