Security audit
Security checks for vulnerabilities and agentic risk
This skill is a literature-review helper that openly retrieves public academic results and writes review files, with privacy and dependency-hygiene notes users should understand before use.
Install only if you are comfortable sending research topics and retrieved paper metadata to public academic services, and do not enable LLM polishing for confidential work unless you trust the configured LLM provider. Prefer a locked or updated dependency set before using it in a sensitive environment.
def search_semantic_scholar(self, keywords: str, years: int, limit: int = 50) -> List[Dict]:
"""从Semantic Scholar检索文献"""
print("\n📚 正在检索 Semantic Scholar...")
url = "https://api.semanticscholar.org/graph/v1/paper/search"
current_year = datetime.now().year
params = {def search_crossref(self, keywords: str, years: int, limit: int = 30) -> List[Dict]:
"""从CrossRef检索文献"""
print("\n📑 正在检索 CrossRef...")
url = "https://api.crossref.org/works"
current_year = datetime.now().year
params = {}
api_base = config.get("llm_api_base")
try:
resp = requests.post(f"{api_base}/chat/completions", headers=headers, json=data, timeout=60)
resp.raise_for_status()
result = resp.json()
content = result["choices"][0]["message"]["content"]- 若用户未提供，使用配置文件中的默认值（默认5年�?0篇） - 自动生成英文同义词和字段变体 ### 2. 文献检�?- 并发调用以下API（优先使用Semantic Scholar，返回结果快且丰富）�? - **Semantic Scholar API**：`https://api.semanticscholar.org/graph/v1/paper/search` - **arXiv API**：`http://export.arxiv.org/api/query` - **CrossRef API**：`https://api.crossref.org/works` - 检索参数：关键词、出版年份范围、按相关性排序、每页最�?00�?- 合并去重（基于DOI或标题相似度�?
### 2. 文献检�?- 并发调用以下API（优先使用Semantic Scholar，返回结果快且丰富）�? - **Semantic Scholar API**：`https://api.semanticscholar.org/graph/v1/paper/search` - **arXiv API**：`http://export.arxiv.org/api/query` - **CrossRef API**：`https://api.crossref.org/works` - 检索参数：关键词、出版年份范围、按相关性排序、每页最�?00�?- 合并去重（基于DOI或标题相似度�? ### 3. 相关性筛选（本地�?- 对摘要和标题进行关键词匹配或TF-IDF向量化，计算与用户关键词的余弦相似度 - 按相似度降序排序，结合引用数加权，保留前 `max_papers` �?- �?`human_review_papers = true`，则生成候选列表并询问用户是否采纳或手动剔�?
|------|------|--------|------| | use_llm_for_writing | bool | false | 是否使用大模型润色综�?| | llm_model | str | deepseek-chat | 大模型名�?| | llm_api_base | str | https://api.deepseek.com/v1 | 大模型API端点 | | llm_api_key | str | - | 大模型API密钥（需配置�?| | output_format | str | markdown | 输出格式（markdown/docx/txt�?| | human_review_papers | bool | false | 是否请求用户确认文献列表 |
# 文献综述生成器依赖 requests>=2.28.0 scikit-learn>=1.0.0 numpy>=1.21.0
# 文献综述生成器依赖 requests>=2.28.0 scikit-learn>=1.0.0 numpy>=1.21.0 # 可选：高级主题聚类
# 文献综述生成器依赖 requests>=2.28.0 scikit-learn>=1.0.0 numpy>=1.21.0 # 可选：高级主题聚类 sentence-transformers>=2.0.0
numpy>=1.21.0 # 可选：高级主题聚类 sentence-transformers>=2.0.0 bertopic>=0.12.0 # 可选：DOCX格式输出
# 可选：高级主题聚类 sentence-transformers>=2.0.0 bertopic>=0.12.0 # 可选：DOCX格式输出 python-docx>=0.8.11
bertopic>=0.12.0 # 可选：DOCX格式输出 python-docx>=0.8.11
No suspicious patterns detected.