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"""
Daily refresh: yesterday's arXiv papers and recent citation counts, into the
live stores. Small by design: a few hundred to ~1,500 papers a day.
What it updates, and what that makes current on the site without a deploy
--------------------------------------------------------------------------
* Qdrant `arxiv_recent` (vectors) and Turso `papers` (metadata): new papers
reach personalised feeds, paper pages, similarity/neighbours and the map's
on-demand placement the moment they are written.
* Turso citation counts for the last three months of papers.
The metadata sidecar is NOT touched: it ships inside the Docker image, so the
starter feed and the keyword half of search only see new papers after the next
sidecar publish and deploy (docs/phases/PHASE7 Β§8).
Stages, each with a check that fails the run
--------------------------------------------
1. preflight credentials, both stores reachable, recent-shard size under
--max-recent-points, baseline counts
2. ingest scripts/ingest_arxiv.py over [today - lookback, today + 1);
re-run once if its coverage check reports a gap (exit 3)
3. citations Semantic Scholar counts for papers from the last 3 months;
only changed rows are written
4. verify new Qdrant points == new Turso rows == papers the ingest
reported; sampled new vectors are 1024-dim unit vectors and
their Turso rows are complete
5. licences how many new papers have a `paper_licences` row, and how many
of those may show figures (reported, never fails the run)
6. summary printed as JSON, and to $GITHUB_STEP_SUMMARY when set
Re-running is always safe: the ingest skips papers already stored and point
ids are derived from the arXiv id, so overlapping runs cannot collide.
Usage
-----
python scripts/daily_refresh.py # the daily run
python scripts/daily_refresh.py --dry-run # stages 1 and 5 only
"""
from __future__ import annotations
import argparse
import datetime as dt
import importlib.util
import json
import os
import re
import subprocess
import sys
import tempfile
import time
from collections import deque
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
import httpx
HERE = Path(__file__).resolve().parent
sys.path.insert(0, str(HERE.parent))
from app import licences # noqa: E402 (standard library only)
REQUIRED_ENV = ("QDRANT_RECENT_URL", "QDRANT_RECENT_API_KEY", "TURSO_URL", "TURSO_DB_TOKEN")
COLLECTION = os.getenv("QDRANT_RECENT_COLLECTION", "arxiv_recent")
# ββ small clients ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class Stores:
def __init__(self):
self.qurl = os.environ["QDRANT_RECENT_URL"].rstrip("/")
self.qkey = os.environ["QDRANT_RECENT_API_KEY"]
self.turl = os.environ["TURSO_URL"].replace("libsql://", "https://").rstrip("/")
self.ttok = os.environ["TURSO_DB_TOKEN"]
self.http = httpx.Client(timeout=180)
def q(self, path: str, body: dict | None = None, method: str = "POST"):
r = self.http.request(method, f"{self.qurl}{path}", json=body,
headers={"api-key": self.qkey})
r.raise_for_status()
return r.json()["result"]
def t(self, sql: str, args: tuple = ()) -> list[list]:
stmt = {"sql": sql, "args": [{"type": "integer" if isinstance(a, int) else "text",
"value": str(a)} for a in args]}
r = self.http.post(f"{self.turl}/v2/pipeline", headers={"Authorization": f"Bearer {self.ttok}"},
json={"requests": [{"type": "execute", "stmt": stmt}, {"type": "close"}]})
r.raise_for_status()
res = r.json()["results"][0]
if res.get("type") != "ok":
raise RuntimeError(str(res)[:300])
return [[c.get("value") for c in row] for row in res["response"]["result"]["rows"]]
def t_many(self, stmts: list[dict]) -> None:
r = self.http.post(f"{self.turl}/v2/pipeline", headers={"Authorization": f"Bearer {self.ttok}"},
json={"requests": [{"type": "execute", "stmt": s} for s in stmts] + [{"type": "close"}]})
r.raise_for_status()
errs = [x for x in r.json().get("results", []) if x.get("type") == "error"]
if errs:
raise RuntimeError(str(errs[0])[:300])
def counts(self) -> dict:
tmax, tcnt = self.t("SELECT MAX(rowid), COUNT(*) FROM papers")[0]
return {"recent_points": self.q(f"/collections/{COLLECTION}/points/count", {"exact": True})["count"],
"turso_rows": int(tcnt), "turso_max_rowid": int(tmax)}
# ββ pure helpers (unit-tested) βββββββββββββββββββββββββββββββββββββββββββββββ
def window(today: dt.date, lookback_days: int) -> tuple[str, str]:
"""[today - lookback, today + 1): arXiv's submittedDate upper bound is
midnight, so +1 day includes today. Overlap is free, since re-runs skip
stored papers, and it absorbs weekend and announcement delays."""
return ((today - dt.timedelta(days=lookback_days)).isoformat(),
(today + dt.timedelta(days=1)).isoformat())
def recent_prefix(today: dt.date, months: int = 3) -> str:
"""YYMM id prefix of the first month in the citation window."""
total = today.year * 12 + (today.month - 1) - (months - 1)
return f"{(total // 12) % 100:02d}{total % 12 + 1:02d}"
def parse_ingest_new(output: str) -> int | None:
m = re.findall(r"done: examined [\d,]+, new ([\d,]+)", output)
return int(m[-1].replace(",", "")) if m else None
def changed_counts(current: dict[str, tuple[int, int]], fetched: dict[str, dict | None]) -> list[tuple[str, int, int]]:
"""Rows whose (citations, influential) differ. Papers Semantic Scholar
does not know keep their stored counts: absent is not zero."""
out = []
for aid, paper in fetched.items():
if not paper or paper.get("citationCount") is None:
continue
new = (int(paper["citationCount"]), int(paper.get("influentialCitationCount") or 0))
if current.get(aid) != new:
out.append((aid, *new))
return out
def verify_counts(before: dict, after: dict, ingest_new: int | None) -> list[str]:
problems = []
dq = after["recent_points"] - before["recent_points"]
dt_rows = after["turso_rows"] - before["turso_rows"]
if dq != dt_rows:
problems.append(f"new Qdrant points ({dq}) != new Turso rows ({dt_rows})")
if ingest_new is not None and dt_rows != ingest_new:
problems.append(f"new Turso rows ({dt_rows}) != papers the ingest reported ({ingest_new})")
if after["turso_max_rowid"] != after["turso_rows"]:
problems.append("Turso rowids are no longer contiguous (a row was deleted or replaced)")
return problems
# ββ stages βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def stage_ingest(since: str, until: str, timeout_s: int = 3600) -> tuple[int | None, str]:
state = Path(tempfile.mkdtemp()) / "state.json"
cmd = [sys.executable, str(HERE / "ingest_arxiv.py"), "--source", "oai",
"--since", since, "--until", until, "--state", str(state)]
log = ""
for attempt in (1, 2):
try:
p = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout_s)
except subprocess.TimeoutExpired as e:
out = (e.stdout or b"").decode(errors="replace") if isinstance(e.stdout, bytes) else (e.stdout or "")
err = (e.stderr or b"").decode(errors="replace") if isinstance(e.stderr, bytes) else (e.stderr or "")
print(out[-4000:], err[-6000:], sep="\n", flush=True) # includes faulthandler stacks
raise SystemExit(f"ingest exceeded {timeout_s // 60} min; stacks above") from None
log += p.stdout + p.stderr
print(p.stdout[-4000:], p.stderr[-2000:], sep="\n", flush=True)
if p.returncode == 0:
break
if p.returncode != 3 or attempt == 2:
raise SystemExit(f"ingest failed with exit {p.returncode}")
print("[daily] coverage gap; resuming once", flush=True)
# The resumed run only reports what IT added, so sum both.
news = [int(n.replace(",", "")) for n in re.findall(r"done: examined [\d,]+, new ([\d,]+)", log)]
return (sum(news) if news else None), log
def stage_citations(st: Stores, prefix: str) -> dict:
spec = importlib.util.spec_from_file_location("refresh_citations", HERE / "refresh_citations.py")
rc = importlib.util.module_from_spec(spec)
spec.loader.exec_module(rc)
rows = st.t("SELECT arxiv_id, citation_count, influential_citations FROM papers "
"WHERE arxiv_id >= ? AND arxiv_id < ?", (prefix, "9999"))
current = {r[0]: (int(r[1] or 0), int(r[2] or 0)) for r in rows}
ids = sorted(current)
fetched: dict[str, dict | None] = {}
chunks = [ids[i:i + rc.BATCH] for i in range(0, len(ids), rc.BATCH)]
workers = 4 if rc._KEY["value"] else 1 # _post keeps keyed starts 1.1 s apart
with httpx.Client(timeout=120) as client, ThreadPoolExecutor(workers) as pool:
pending: deque = deque()
nxt = 0
for chunk in chunks: # bounded window, consumed in order
while nxt < len(chunks) and len(pending) < workers:
pending.append(pool.submit(rc._post, client, chunks[nxt]))
nxt += 1
res = pending.popleft().result()
if res is None:
for f in pending:
f.cancel()
raise SystemExit(f"Semantic Scholar batch failed at {chunk[0]}")
fetched.update(zip(chunk, res))
changes = changed_counts(current, fetched)
sql = "UPDATE papers SET citation_count = ?, influential_citations = ? WHERE arxiv_id = ?"
for i in range(0, len(changes), 500):
st.t_many([{"sql": sql, "args": [{"type": "integer", "value": str(c)},
{"type": "integer", "value": str(f)},
{"type": "text", "value": a}]} for a, c, f in changes[i:i + 500]])
found = sum(1 for v in fetched.values() if v)
return {"papers": len(ids), "found": found, "changed": len(changes)}
def licence_coverage(codes: list[str | None]) -> dict:
"""One code per new paper; None or "" when it has no licence row."""
known = [c for c in codes if c]
figures = sum(1 for c in known if licences.allows_figures(c))
n = len(codes)
return {"new_papers": n, "with_licence": len(known),
"with_licence_share": round(len(known) / n, 3) if n else None,
"open": sum(1 for c in known if licences.is_open(c)),
"allow_figures": figures, "allow_figures_share": round(figures / n, 3) if n else None,
"figure_policy": licences.figure_policy()}
def stage_licences(st: Stores, after_rowid: int) -> dict:
try:
rows = st.t("SELECT l.licence FROM papers p LEFT JOIN paper_licences l ON l.arxiv_id = p.arxiv_id "
"WHERE p.rowid > ?", (after_rowid,))
except RuntimeError as e: # no table yet: no licence has been written
return {"error": str(e)[:160]}
return licence_coverage([r[0] for r in rows])
def stage_sample_new(st: Stores, after_rowid: int, n: int = 5) -> list[str]:
"""Spot-check up to n papers this run added."""
rows = st.t("SELECT arxiv_id, title, authors, abstract_preview, categories, primary_topic "
"FROM papers WHERE rowid > ? ORDER BY rowid DESC LIMIT ?", (after_rowid, n))
problems = []
if not rows:
return problems
got = st.q(f"/collections/{COLLECTION}/points/scroll", {
"filter": {"must": [{"key": "arxiv_id", "match": {"any": [r[0] for r in rows]}}]},
"limit": 3 * len(rows), "with_payload": True, "with_vector": True})["points"]
by_id: dict[str, list] = {}
for p in got:
by_id.setdefault(p["payload"]["arxiv_id"], []).append(p["vector"])
for aid, title, authors, abstract, cats, label in rows:
vecs = by_id.get(aid, [])
if len(vecs) != 1:
problems.append(f"{aid}: {len(vecs)} vectors in {COLLECTION} (expected 1)")
continue
v = vecs[0]
norm = sum(x * x for x in v) ** 0.5
if len(v) != 1024 or not 0.99 < norm < 1.01:
problems.append(f"{aid}: vector dim {len(v)} norm {norm:.3f}")
if not (title and authors and len(abstract or "") >= 20 and cats and label):
problems.append(f"{aid}: incomplete Turso row")
return problems
def main() -> int:
ap = argparse.ArgumentParser()
ap.add_argument("--lookback-days", type=int, default=3)
ap.add_argument("--citation-months", type=int, default=3)
ap.add_argument("--max-recent-points", type=int, default=600_000,
help="refuse to write past this many points (free-tier headroom)")
ap.add_argument("--today", default="", help="YYYY-MM-DD, for re-running a past day")
ap.add_argument("--ingest-timeout-min", type=int, default=60,
help="fail the run if one ingest attempt takes longer")
ap.add_argument("--dry-run", action="store_true")
ap.add_argument("--skip-citations", action="store_true")
args = ap.parse_args()
summary: dict = {"started": dt.datetime.now(dt.timezone.utc).isoformat(timespec="seconds")}
missing = [k for k in REQUIRED_ENV if not os.getenv(k)]
if missing:
print(f"[daily] missing env: {', '.join(missing)}", file=sys.stderr)
return 2
today = dt.date.fromisoformat(args.today) if args.today else dt.datetime.now(dt.timezone.utc).date()
since, until = window(today, args.lookback_days)
st = Stores()
before = st.counts()
summary.update({"window": [since, until], "before": before})
if before["recent_points"] >= args.max_recent_points:
summary["error"] = f"recent shard at {before['recent_points']:,} points, limit {args.max_recent_points:,}"
return _finish(summary, 4)
if args.dry_run:
summary["dry_run"] = True
return _finish(summary, 0)
t0 = time.time()
ingest_new, _log = stage_ingest(since, until, args.ingest_timeout_min * 60)
summary["ingest"] = {"new_papers": ingest_new, "minutes": round((time.time() - t0) / 60, 1)}
if not args.skip_citations:
t0 = time.time()
summary["citations"] = stage_citations(st, recent_prefix(today, args.citation_months))
summary["citations"]["minutes"] = round((time.time() - t0) / 60, 1)
after = st.counts()
summary["after"] = after
summary["licences"] = stage_licences(st, before["turso_max_rowid"])
problems = verify_counts(before, after, ingest_new) + stage_sample_new(st, before["turso_max_rowid"])
summary["problems"] = problems
return _finish(summary, 1 if problems else 0)
def _finish(summary: dict, code: int) -> int:
summary["exit"] = code
text = json.dumps(summary, indent=1)
print(text)
path = os.getenv("GITHUB_STEP_SUMMARY")
if path:
with open(path, "a") as fh:
fh.write(f"### Daily refresh {'OK' if code == 0 else 'FAILED'}\n\n```json\n{text}\n```\n")
return code
if __name__ == "__main__":
sys.exit(main())
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