str.strip

# 提取子主题
            sub_topics = []
            sub_topics_text = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "sub_topics")
            if sub_topics_text:
                sub_topics = [topic.strip() for topic in sub_topics_text.split(",")]

            # 提取语言
            language = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "language")

            # 提取最低星标数
            min_stars = 0
            min_stars_text = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "min_stars")
            if min_stars_text and min_stars_text.isdigit():
                min_stars = int(min_stars_text)

            # 解析GitHub搜索参数 - 英文
            english_github_query = self._extract_tag(extracted_responses[self.GITHUB_QUERY_INDEX], "query")

            # 解析GitHub搜索参数 - 中文
            chinese_github_query = self._extract_tag(extracted_responses[2], "query")

            # 构建GitHub参数
            github_params = {
                "query": english_github_query,

try:
            response = self.llm.invoke(prompt)

            # Handle different response formats (string or object with content attribute)
            if hasattr(response, "content"):
                optimized_query = response.content.strip()
            else:
                # Handle string responses
                optimized_query = str(response).strip()

            # Validate the optimized query
            if optimized_query and len(optimized_query) > 0:
                logger.info(
                    f"LLM optimized query from '{query}' to '{optimized_query}'"
                )
                return optimized_query
            else:
                logger.warning("LLM returned empty query, using original")
                return query

        except Exception:
            logger.exception("Error optimizing query with LLM")
            return query

    def _search_github(self, query: str) -> List[Dict[str, Any]]: