From 1a953287ba5ccf5c21be37259a70cb8cb5adc5cd Mon Sep 17 00:00:00 2001 From: Yuren Hao <97327730+YurenHao0426@users.noreply.github.com> Date: Sun, 30 Mar 2025 20:03:57 -0700 Subject: Update fetch_papers.py --- scripts/fetch_papers.py | 155 +++++++++++++++++++++++++++--------------------- 1 file changed, 88 insertions(+), 67 deletions(-) (limited to 'scripts/fetch_papers.py') diff --git a/scripts/fetch_papers.py b/scripts/fetch_papers.py index a847518..1d2417c 100644 --- a/scripts/fetch_papers.py +++ b/scripts/fetch_papers.py @@ -4,32 +4,51 @@ import feedparser import datetime from github import Github -##################### -# 1. 配置/常量 -##################### - +# Step 1: 你的分类限制 ALLOWED_CATEGORIES = [ "cs.AI", "cs.CL", "cs.CV", "cs.LG", "cs.NE", "cs.RO", "cs.IR", "stat.ML" ] +# Step 2: 本地高级匹配 (正负关键词) +def advanced_filter(entry): + """ + 基于标题+摘要，本地进行“正面关键词 + 负面关键词”筛选 + """ + title = getattr(entry, 'title', '').lower() + summary = getattr(entry, 'summary', '').lower() + full_text = title + " " + summary + + # 正面关键词 + general_terms = ["bias", "fairness"] + model_terms = ["llm", "language model", "transformer", "gpt", "nlp", + "pretrained", "embedding", "generation", "alignment", "ai"] + # 负面关键词 + negative_terms = [ + "estimation", "variance", "quantum", "physics", + "sensor", "circuit", "electronics", "hardware" + ] + + # 检查正面关键词 + has_general = any(term in full_text for term in general_terms) + has_model = any(term in full_text for term in model_terms) + # 检查负面关键词 + has_negative = any(term in full_text for term in negative_terms) + + return (has_general and has_model) and (not has_negative) + +# Step 3: 外部API判别 API_URL = "https://uiuc.chat/api/chat-api/chat" -API_KEY = os.getenv("UIUC_API_KEY") # 你自己的密钥 -MODEL_NAME = "qwen2.5:14b-instruct-fp16" # 你的model - +MODEL_NAME = "qwen2.5:14b-instruct-fp16" SYSTEM_PROMPT = ( "Based on the given title and abstract, please determine if the paper " "is relevant to both language models and bias (or fairness). " "If yes, respond 1; otherwise respond 0." ) -##################### -# 2. 函数: 调用外部API 判别 -##################### - -def is_relevant_by_api(title, abstract): +def is_relevant_by_api(title, summary, api_key): """ - 调用外部API, 给一段title+abstract, 返回 True(1) or False(0). + 调用外部API，根据title+summary判别是否相关（返回True/False） """ headers = {"Content-Type": "application/json"} data = { @@ -41,39 +60,32 @@ def is_relevant_by_api(title, abstract): }, { "role": "user", - # 填入我们的标题+摘要, 作为"content" - "content": f"Title: {title}\nAbstract: {abstract}" + "content": SYSTEM_PROMPT + f"Title: {title}\nAbstract: {summary}" } ], - "api_key": API_KEY, + "api_key": api_key, "course_name": "llm-bias-papers", "stream": False, - "temperature": 0.0, - "retrieval_only": False + "temperature": 0.0 } try: resp = requests.post(API_URL, headers=headers, json=data, timeout=30) resp.raise_for_status() - # resp.json() 应该包含 'message' - response_msg = resp.json().get('message','') - # 如果 message="1", 就 True, 否则 False + response_msg = resp.json().get("message", "") return (response_msg.strip() == "1") - except requests.RequestException as e: + except Exception as e: print("[ERROR] calling external API:", e) - # 如果出错, 默认返回 False or do something return False -##################### -# 3. 函数: 抓论文, 调API判别 -##################### - -def fetch_arxiv_papers_with_api(days=1): +# Step 4: 抓arXiv, 先本地筛, 再API筛 +def fetch_papers_combined(days=1): """ - 宽松抓 + 本地分类过滤 + 外部API做判别 + 1) 抓过去days天 arXiv论文(宽松) + 2) 本地先过滤(分类 + advanced_filter) + 3) 对“通过本地筛”的候选，调用API二次判定 """ now_utc = datetime.datetime.now(datetime.timezone.utc) start_utc = now_utc - datetime.timedelta(days=days) - start_str = start_utc.strftime("%Y%m%d%H%M") end_str = now_utc.strftime("%Y%m%d%H%M") @@ -118,40 +130,55 @@ def fetch_arxiv_papers_with_api(days=1): print(f"[DEBUG] total retrieved in date range: {len(all_entries)}") - matched = [] - for entry in all_entries: - title = getattr(entry, 'title', '') - summary = getattr(entry, 'summary', '') - published = getattr(entry, 'published', '') - link = getattr(entry, 'link', '') - # 先检查分类 - if hasattr(entry, 'tags'): - categories = [t.term for t in entry.tags] - else: - categories = [] - - # 是否有至少一个分类在 ALLOWED_CATEGORIES 里 - in_allowed_cat = any(cat in ALLOWED_CATEGORIES for cat in categories) - if not in_allowed_cat: + # --- 本地过滤1: 分类 + advanced_filter --- + local_candidates = [] + for e in all_entries: + title = getattr(e, "title", "") + summary = getattr(e, "summary", "") + published = getattr(e, "published", "") + link = getattr(e, "link", "") + categories = [t.term for t in e.tags] if hasattr(e, 'tags') else [] + + # 分类是否允许 + if not any(cat in ALLOWED_CATEGORIES for cat in categories): + continue + + # 是否通过 advanced_filter + if not advanced_filter(e): continue - # 调用外部 API 判别: relevant or not - relevant = is_relevant_by_api(title, summary) + local_candidates.append({ + "title": title, + "summary": summary, + "published": published, + "link": link, + "categories": categories + }) + + print(f"[DEBUG] local_candidates = {len(local_candidates)} after local filter") + + # --- 2) 调API二次判定 --- + api_key = os.getenv("UIUC_API_KEY") # 你在Secrets中配置 + if not api_key: + print("[WARNING] No UIUC_API_KEY found. Skip second filter.") + # 如果没api key，就直接return本地候选 + return local_candidates + + final_matched = [] + for paper in local_candidates: + relevant = is_relevant_by_api(paper["title"], paper["summary"], api_key) if relevant: - matched.append({ - "title": title, - "published": published, - "link": link, - "categories": categories + final_matched.append({ + "title": paper["title"], + "published": paper["published"], + "link": paper["link"], + "categories": paper["categories"] }) - print(f"[DEBUG] matched {len(matched)} papers after external API check.") - return matched - -##################### -# 4. 函数: update README -##################### + print(f"[DEBUG] final_matched = {len(final_matched)} after API check") + return final_matched +# Step 5: 写README def update_readme_in_repo(papers, token, repo_name): if not papers: print("[INFO] No matched papers, skip README update.") @@ -160,7 +187,6 @@ def update_readme_in_repo(papers, token, repo_name): g = Github(token) repo = g.get_repo(repo_name) - # 获取 README readme_file = repo.get_contents("README.md", ref="main") old_content = readme_file.decoded_content.decode("utf-8") @@ -184,18 +210,13 @@ def update_readme_in_repo(papers, token, repo_name): ) print(f"[INFO] README updated with {len(papers)} papers.") -##################### -# 5. main -##################### - def main(): - days = 7 - papers = fetch_arxiv_papers_with_api(days=days) - print(f"[RESULT] matched {len(papers)} papers. Will update README if not empty.") + days = 1 + papers = fetch_papers_combined(days=days) + print(f"\n[RESULT] matched {len(papers)} papers total after double filter. Now update README if not empty...") github_token = os.getenv("TARGET_REPO_TOKEN") target_repo_name = os.getenv("TARGET_REPO_NAME") - if not github_token or not target_repo_name: print("[ERROR] Missing environment variables: TARGET_REPO_TOKEN / TARGET_REPO_NAME.") return -- cgit v1.2.3