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#!/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())