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| # Based on: https://github.com/allenai/s2-folks/tree/main/examples/python | |
| # | |
| # | |
| import os | |
| import traceback | |
| import requests | |
| S2_API_KEY = os.getenv("S2_API_KEY") | |
| result_limit = 10 | |
| def find_basis_paper(query, result_limit=10): | |
| papers = None | |
| info = """Search results: | |
| """ | |
| while not papers: | |
| if not query: | |
| continue | |
| try: | |
| if len(S2_API_KEY): | |
| print("Using S2_API_KEY...") | |
| rsp = requests.get( | |
| "https://api.semanticscholar.org/graph/v1/paper/search", | |
| headers={"X-API-KEY": S2_API_KEY}, | |
| params={ | |
| "query": query, | |
| "limit": 100, | |
| "fields": "title,url,authors,year,tldr,journal,citationCount", | |
| "sort": "citationCount:desc", | |
| }, | |
| ) | |
| rsp.raise_for_status() | |
| results = rsp.json() | |
| total = results["total"] | |
| if not total: | |
| return "No matches found. Please try another query." | |
| print(f"Found {total} results. Showing up to {result_limit}.") | |
| papers = results["data"] | |
| info += format_paper_list(papers, int(result_limit)) | |
| except Exception as e: | |
| print(traceback.format_exc()) | |
| info += "There was a problem...\n\n%s" % e | |
| print(info) | |
| return info | |
| def get_element(paper, part): | |
| simple_parts = ["year", "url", "title", "citationCount"] | |
| if part in simple_parts: | |
| if part in paper and paper[part] is not None: | |
| v = paper[part] | |
| return v.strip() if isinstance(v, str) else v | |
| else: | |
| return "???" | |
| elif part == "journal": | |
| if part in paper and paper[part] is not None: | |
| return paper[part]["name"].strip() | |
| else: | |
| return "???" | |
| elif part == "authors": | |
| if part in paper and paper[part] is not None: | |
| return paper[part][0]["name"].strip() | |
| else: | |
| return "???" | |
| elif part == "tldr": | |
| if part in paper and paper[part] is not None: | |
| return paper[part]["text"].strip() | |
| else: | |
| return "???" | |
| else: | |
| return "<unknown field %s>" % part | |
| def format_paper_list(all_papers, result_limit): | |
| list = "" | |
| sorted_papers = sorted(all_papers, key=lambda d: d["citationCount"], reverse=True)[ | |
| :result_limit | |
| ] | |
| print(sorted_papers) | |
| for idx, paper in enumerate(sorted_papers): | |
| list += f"{idx}: **{get_element(paper, 'authors')} et al. {get_element(paper, 'year')}**, [{get_element(paper, 'journal')}]({get_element(paper, 'url')}) {get_element(paper, 'title')}. Cited by {get_element(paper, 'citationCount')}\n\n" | |
| if paper["tldr"] and paper["tldr"]["text"]: | |
| list += f"> _{paper['tldr']['text'].strip()}_ \n\n" | |
| return list | |
| if __name__ == "__main__": | |
| find_basis_paper("NeuroML") | |