#!/usr/bin/env python3 """Paper research helper for ML Intern Codex. Emulates the useful parts of upstream ml-intern's hf_papers tool with public HTTP APIs: Hugging Face Papers, arXiv/ar5iv HTML, and Semantic Scholar. """ from __future__ import annotations import argparse import html.parser import json import os import re import sys import urllib.error import urllib.parse import urllib.request from concurrent.futures import ThreadPoolExecutor, as_completed from typing import Any HF_API = "https://huggingface.co/api" ARXIV_HTML = "https://arxiv.org/html" AR5IV_HTML = "https://ar5iv.labs.arxiv.org/html" S2_API = "https://api.semanticscholar.org" MAX_SECTION_TEXT_LEN = 8000 def request_json(url: str, params: dict[str, Any] | None = None, method: str = "GET", body: dict[str, Any] | None = None) -> Any: if params: url = f"{url}?{urllib.parse.urlencode({k: v for k, v in params.items() if v is not None})}" data = None headers = {"User-Agent": "ml-intern-codex/0.1"} if body is not None: data = json.dumps(body).encode("utf-8") headers["Content-Type"] = "application/json" s2_key = os.environ.get("S2_API_KEY") if s2_key and url.startswith(S2_API): headers["x-api-key"] = s2_key request = urllib.request.Request(url, data=data, headers=headers, method=method) try: with urllib.request.urlopen(request, timeout=30) as response: return json.loads(response.read().decode("utf-8")) except urllib.error.HTTPError as exc: text = exc.read().decode("utf-8", errors="replace") raise RuntimeError(f"{url} returned HTTP {exc.code}: {text[:500]}") from exc def request_text(url: str) -> str: request = urllib.request.Request(url, headers={"User-Agent": "ml-intern-codex/0.1"}) with urllib.request.urlopen(request, timeout=30) as response: return response.read().decode("utf-8", errors="replace") def arxiv_s2_id(arxiv_id: str) -> str: return f"ARXIV:{arxiv_id}" def truncate(text: str, limit: int) -> str: text = re.sub(r"\s+", " ", text).strip() return text if len(text) <= limit else text[:limit].rstrip() + "..." def paper_arxiv_id(paper: dict[str, Any]) -> str: external = paper.get("externalIds") or paper.get("external_ids") or {} return external.get("ArXiv") or paper.get("arxiv_id") or paper.get("id", "") def format_hf_paper(paper: dict[str, Any], idx: int) -> str: nested = paper.get("paper") if isinstance(paper.get("paper"), dict) else paper title = nested.get("title") or paper.get("title") or "(untitled)" arxiv_id = nested.get("id") or nested.get("arxivId") or paper.get("id") or "" summary = nested.get("summary") or nested.get("abstract") or "" lines = [f"### {idx}. {title}"] if arxiv_id: lines.append(f"arxiv_id: {arxiv_id}") lines.append(f"https://arxiv.org/abs/{arxiv_id}") if nested.get("publishedAt"): lines.append(f"Published: {nested['publishedAt']}") if nested.get("githubUrl"): lines.append(f"GitHub: {nested['githubUrl']}") if summary: lines.append(truncate(summary, 500)) return "\n".join(lines) def format_s2_paper(paper: dict[str, Any], idx: int) -> str: title = paper.get("title") or "(untitled)" year = paper.get("year") or "?" cites = paper.get("citationCount", 0) venue = paper.get("venue") or "" arxiv_id = paper_arxiv_id(paper) tldr = (paper.get("tldr") or {}).get("text", "") parts = [f"Year: {year}", f"Citations: {cites}"] if venue: parts.append(f"Venue: {venue}") if arxiv_id: parts.append(f"arxiv_id: {arxiv_id}") lines = [f"### {idx}. {title}", " | ".join(parts)] if arxiv_id: lines.append(f"https://arxiv.org/abs/{arxiv_id}") if tldr: lines.append(f"TL;DR: {tldr}") return "\n".join(lines) class ArxivHTMLParser(html.parser.HTMLParser): def __init__(self) -> None: super().__init__() self.capture_title = False self.capture_abstract = False self.capture_heading = False self.capture_paragraph = False self.title_parts: list[str] = [] self.abstract_parts: list[str] = [] self.sections: list[dict[str, Any]] = [] self.current_heading: list[str] = [] self.current_paragraph: list[str] = [] self.current_section: dict[str, Any] | None = None def handle_starttag(self, tag: str, attrs: list[tuple[str, str | None]]) -> None: classes = dict(attrs).get("class", "") or "" if tag == "h1" and "ltx_title" in classes: self.capture_title = True elif tag == "div" and "ltx_abstract" in classes: self.capture_abstract = True elif tag in {"h2", "h3"} and "ltx_title" in classes: self.capture_heading = True self.current_heading = [] elif tag == "p": self.capture_paragraph = True self.current_paragraph = [] def handle_endtag(self, tag: str) -> None: if tag == "h1" and self.capture_title: self.capture_title = False elif tag == "div" and self.capture_abstract: self.capture_abstract = False elif tag in {"h2", "h3"} and self.capture_heading: heading = truncate(" ".join(self.current_heading), 500) section_id = "" match = re.match(r"^([A-Z]?\d+(?:\.\d+)*)\s", heading) if match: section_id = match.group(1) self.current_section = {"id": section_id, "title": heading, "text": ""} self.sections.append(self.current_section) self.capture_heading = False elif tag == "p" and self.capture_paragraph: paragraph = truncate(" ".join(self.current_paragraph), 4000) if paragraph: if self.capture_abstract: self.abstract_parts.append(paragraph) elif self.current_section is not None: existing = self.current_section["text"] self.current_section["text"] = (existing + "\n\n" + paragraph).strip() self.capture_paragraph = False def handle_data(self, data: str) -> None: text = data.strip() if not text: return if self.capture_title: self.title_parts.append(text.removeprefix("Title:")) if self.capture_heading: self.current_heading.append(text) if self.capture_paragraph: self.current_paragraph.append(text) def parse_arxiv_html(html_text: str) -> dict[str, Any]: parser = ArxivHTMLParser() parser.feed(html_text) return { "title": truncate(" ".join(parser.title_parts), 500), "abstract": truncate(" ".join(parser.abstract_parts), 2000), "sections": parser.sections, } def op_trending(args: argparse.Namespace) -> str: params: dict[str, Any] = {"limit": args.limit * 3 if args.query else args.limit} if args.date: params["date"] = args.date papers = request_json(f"{HF_API}/daily_papers", params) if args.query: needle = args.query.lower() papers = [ paper for paper in papers if needle in json.dumps(paper, ensure_ascii=False).lower() ] lines = ["# Trending Papers"] for idx, paper in enumerate(papers[: args.limit], 1): lines.append(format_hf_paper(paper, idx)) lines.append("") return "\n".join(lines) def op_search(args: argparse.Namespace) -> str: if not args.query: raise SystemExit("search requires --query") use_s2 = any([args.date_from, args.date_to, args.categories, args.min_citations, args.sort_by != "relevance"]) if use_s2: params: dict[str, Any] = { "query": args.query, "limit": args.limit, "fields": "title,externalIds,year,citationCount,tldr,venue,publicationDate", } if args.date_from or args.date_to: params["publicationDateOrYear"] = f"{args.date_from or ''}:{args.date_to or ''}" if args.categories: params["fieldsOfStudy"] = args.categories if args.min_citations: params["minCitationCount"] = str(args.min_citations) if args.sort_by != "relevance": params["sort"] = f"{args.sort_by}:desc" data = request_json(f"{S2_API}/graph/v1/paper/search/bulk", params) papers = data.get("data", []) lines = [f"# Papers matching '{args.query}' (Semantic Scholar)"] for idx, paper in enumerate(papers[: args.limit], 1): lines.append(format_s2_paper(paper, idx)) lines.append("") return "\n".join(lines) papers = request_json(f"{HF_API}/papers/search", {"q": args.query, "limit": args.limit}) lines = [f"# Papers matching '{args.query}' (Hugging Face Papers)"] for idx, paper in enumerate(papers[: args.limit], 1): lines.append(format_hf_paper(paper, idx)) lines.append("") return "\n".join(lines) def op_paper_details(args: argparse.Namespace) -> str: if not args.arxiv_id: raise SystemExit("paper_details requires --arxiv-id") paper = request_json(f"{HF_API}/papers/{args.arxiv_id}") lines = [f"# {paper.get('title', args.arxiv_id)}", f"https://huggingface.co/papers/{args.arxiv_id}", f"https://arxiv.org/abs/{args.arxiv_id}"] for key in ("publishedAt", "submittedOnDailyAt", "githubUrl"): if paper.get(key): lines.append(f"{key}: {paper[key]}") if paper.get("summary"): lines.append("") lines.append("## Abstract") lines.append(paper["summary"]) if paper.get("ai_summary"): lines.append("") lines.append("## AI Summary") lines.append(str(paper["ai_summary"])) return "\n".join(lines) def op_read_paper(args: argparse.Namespace) -> str: if not args.arxiv_id: raise SystemExit("read_paper requires --arxiv-id") parsed = None for base in (ARXIV_HTML, AR5IV_HTML): try: parsed = parse_arxiv_html(request_text(f"{base}/{args.arxiv_id}")) if parsed["sections"]: break except Exception: parsed = None if not parsed or not parsed["sections"]: return op_paper_details(args) + f"\n\nHTML sections unavailable. PDF: https://arxiv.org/pdf/{args.arxiv_id}" if not args.section: lines = [f"# {parsed['title'] or args.arxiv_id}", f"https://arxiv.org/abs/{args.arxiv_id}", "", "## Abstract", parsed["abstract"], "", "## Sections"] for section in parsed["sections"]: preview = truncate(section.get("text", ""), 280) lines.append(f"- {section['title']}: {preview}") return "\n".join(lines) wanted = args.section.lower() selected = None for section in parsed["sections"]: if section["id"].lower() == wanted or wanted in section["title"].lower(): selected = section break if not selected: available = "\n".join(f"- {section['title']}" for section in parsed["sections"]) raise SystemExit(f"section not found. Available sections:\n{available}") return "\n".join([ f"# {selected['title']}", f"https://arxiv.org/abs/{args.arxiv_id}", "", truncate(selected.get("text", ""), MAX_SECTION_TEXT_LEN), ]) def format_citation(entry: dict[str, Any]) -> str: paper = entry.get("citingPaper") or entry.get("citedPaper") or {} title = paper.get("title") or "(untitled)" year = paper.get("year") or "?" cites = paper.get("citationCount", 0) arxiv_id = paper_arxiv_id(paper) line = f"- {title} ({year}, {cites} cites)" if arxiv_id: line += f" arxiv:{arxiv_id}" if entry.get("isInfluential"): line += " [influential]" contexts = entry.get("contexts") or [] if contexts: line += f"\n > {truncate(contexts[0], 220)}" return line def op_citation_graph(args: argparse.Namespace) -> str: if not args.arxiv_id: raise SystemExit("citation_graph requires --arxiv-id") fields = "title,externalIds,year,citationCount,influentialCitationCount,contexts,intents,isInfluential" params = {"fields": fields, "limit": args.limit} paths: dict[str, str] = {} if args.direction in {"references", "both"}: paths["References"] = f"/graph/v1/paper/{arxiv_s2_id(args.arxiv_id)}/references" if args.direction in {"citations", "both"}: paths["Citations"] = f"/graph/v1/paper/{arxiv_s2_id(args.arxiv_id)}/citations" lines = [f"# Citation Graph for {args.arxiv_id}", f"https://arxiv.org/abs/{args.arxiv_id}"] with ThreadPoolExecutor(max_workers=2) as pool: futures = {pool.submit(request_json, f"{S2_API}{path}", params): name for name, path in paths.items()} for future in as_completed(futures): name = futures[future] lines.append("") lines.append(f"## {name}") try: data = future.result() for entry in data.get("data", []): lines.append(format_citation(entry)) except Exception as exc: lines.append(f"Error: {exc}") return "\n".join(lines) def op_resources(args: argparse.Namespace) -> str: if not args.arxiv_id: raise SystemExit(f"{args.operation} requires --arxiv-id") sort = {"downloads": "downloads", "likes": "likes", "trending": "trendingScore"}[args.sort] calls: dict[str, tuple[str, dict[str, Any]]] = {} if args.operation in {"find_datasets", "find_all_resources"}: calls["Datasets"] = (f"{HF_API}/datasets", {"filter": f"arxiv:{args.arxiv_id}", "limit": args.limit, "sort": sort, "direction": -1}) if args.operation in {"find_models", "find_all_resources"}: calls["Models"] = (f"{HF_API}/models", {"filter": f"arxiv:{args.arxiv_id}", "limit": args.limit, "sort": sort, "direction": -1}) if args.operation in {"find_collections", "find_all_resources"}: calls["Collections"] = (f"{HF_API}/collections", {"paper": args.arxiv_id}) lines = [f"# Resources linked to paper {args.arxiv_id}", f"https://huggingface.co/papers/{args.arxiv_id}"] with ThreadPoolExecutor(max_workers=3) as pool: futures = {pool.submit(request_json, url, params): name for name, (url, params) in calls.items()} for future in as_completed(futures): name = futures[future] lines.append("") lines.append(f"## {name}") try: items = future.result() for item in items[: args.limit]: repo_id = item.get("id") or item.get("modelId") or item.get("slug") or item.get("title") likes = item.get("likes") downloads = item.get("downloads") meta = [] if downloads is not None: meta.append(f"downloads={downloads}") if likes is not None: meta.append(f"likes={likes}") lines.append(f"- {repo_id}" + (f" ({', '.join(meta)})" if meta else "")) except Exception as exc: lines.append(f"Error: {exc}") return "\n".join(lines) def op_snippet_search(args: argparse.Namespace) -> str: if not args.query: raise SystemExit("snippet_search requires --query") params: dict[str, Any] = {"query": args.query, "limit": args.limit, "fields": "title,externalIds,year,citationCount"} if args.date_from or args.date_to: params["publicationDateOrYear"] = f"{args.date_from or ''}:{args.date_to or ''}" if args.categories: params["fieldsOfStudy"] = args.categories if args.min_citations: params["minCitationCount"] = str(args.min_citations) data = request_json(f"{S2_API}/graph/v1/snippet/search", params) lines = [f"# Snippet Search: {args.query}"] for idx, item in enumerate(data.get("data", [])[: args.limit], 1): paper = item.get("paper") or {} snippet = item.get("snippet") or {} lines.append(f"### {idx}. {paper.get('title', '(untitled)')}") arxiv_id = paper_arxiv_id(paper) if arxiv_id: lines.append(f"arxiv:{arxiv_id}") if snippet.get("section"): lines.append(f"Section: {snippet['section']}") if snippet.get("text"): lines.append(f"> {truncate(snippet['text'], 400)}") lines.append("") return "\n".join(lines) def op_recommend(args: argparse.Namespace) -> str: if not args.arxiv_id and not args.positive_ids: raise SystemExit("recommend requires --arxiv-id or --positive-ids") fields = "title,externalIds,year,citationCount,tldr,venue" if args.positive_ids and not args.arxiv_id: positive = [arxiv_s2_id(item.strip()) for item in args.positive_ids.split(",") if item.strip()] negative = [arxiv_s2_id(item.strip()) for item in args.negative_ids.split(",") if item.strip()] data = request_json( f"{S2_API}/recommendations/v1/papers/", {"fields": fields, "limit": args.limit}, method="POST", body={"positivePaperIds": positive, "negativePaperIds": negative}, ) else: data = request_json( f"{S2_API}/recommendations/v1/papers/forpaper/{arxiv_s2_id(args.arxiv_id)}", {"fields": fields, "limit": args.limit, "from": "recent"}, ) papers = data.get("recommendedPapers", []) lines = ["# Recommended Papers"] for idx, paper in enumerate(papers[: args.limit], 1): lines.append(format_s2_paper(paper, idx)) lines.append("") return "\n".join(lines) def build_parser() -> argparse.ArgumentParser: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("operation", choices=[ "trending", "search", "paper_details", "read_paper", "citation_graph", "snippet_search", "recommend", "find_datasets", "find_models", "find_collections", "find_all_resources", ]) parser.add_argument("--query") parser.add_argument("--arxiv-id") parser.add_argument("--section") parser.add_argument("--direction", choices=["citations", "references", "both"], default="both") parser.add_argument("--date") parser.add_argument("--date-from", default="") parser.add_argument("--date-to", default="") parser.add_argument("--categories") parser.add_argument("--min-citations", type=int) parser.add_argument("--sort-by", choices=["relevance", "citationCount", "publicationDate"], default="relevance") parser.add_argument("--positive-ids", default="") parser.add_argument("--negative-ids", default="") parser.add_argument("--sort", choices=["downloads", "likes", "trending"], default="downloads") parser.add_argument("--limit", type=int, default=10) return parser def main() -> int: args = build_parser().parse_args() args.limit = min(max(args.limit, 1), 50) handlers = { "trending": op_trending, "search": op_search, "paper_details": op_paper_details, "read_paper": op_read_paper, "citation_graph": op_citation_graph, "snippet_search": op_snippet_search, "recommend": op_recommend, "find_datasets": op_resources, "find_models": op_resources, "find_collections": op_resources, "find_all_resources": op_resources, } try: print(handlers[args.operation](args)) except Exception as exc: print(f"Error running papers {args.operation}: {exc}", file=sys.stderr) return 1 return 0 if __name__ == "__main__": sys.exit(main())