Files
codex-py/codex/sources/semanticscholar.py
Tarik Moussa c7fae5c877 fix(sources): drop no-op try/except + url-encode S2 ids (audit R-4, R-5)
- R-4: arxiv.fetch_source had a try/except httpx.RequestError that only re-raised
  — removed (no behaviour change, less noise).
- R-5: semanticscholar URLs now quote(paper_id, safe=':') so a legacy-arXiv '/'
  (arXiv:math/0603097) doesn't corrupt the path and silently return no references.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-06-15 21:39:48 +02:00

136 lines
4.1 KiB
Python

"""Semantic Scholar API client.
Provides:
- fetch_references: retrieve references for a paper as Citation dataclasses.
- fetch_recommendations: retrieve recommended paper IDs.
Rate-limited to ≤1 req/s (per-request floor via monotonic clock).
Retried on 429/5xx with exponential back-off via tenacity.
"""
from __future__ import annotations
import logging
import threading
import time
from typing import Any
from urllib.parse import quote
import httpx
from tenacity import retry, retry_if_exception, stop_after_attempt, wait_exponential
from codex.models import Citation
logger = logging.getLogger(__name__)
_BASE_GRAPH = "https://api.semanticscholar.org/graph/v1"
_BASE_RECS = "https://api.semanticscholar.org/recommendations/v1"
# Per-request rate limit: ≤1 req/s without an API key.
_rate_lock = threading.Lock()
_last_request_time: float = 0.0
_MIN_INTERVAL = 1.0
def _rate_limit() -> None:
global _last_request_time
with _rate_lock:
now = time.monotonic()
wait = _MIN_INTERVAL - (now - _last_request_time)
if wait > 0:
time.sleep(wait)
_last_request_time = time.monotonic()
def _is_retryable(exc: BaseException) -> bool:
if isinstance(exc, httpx.HTTPStatusError):
return exc.response.status_code == 429 or exc.response.status_code >= 500
return False
@retry(
retry=retry_if_exception(_is_retryable),
stop=stop_after_attempt(5),
wait=wait_exponential(min=1, max=30),
before_sleep=lambda rs: logger.warning(
"SemanticScholar retry %d after %s",
rs.attempt_number,
rs.outcome.exception(), # type: ignore[union-attr]
),
)
def _get(url: str, params: dict[str, Any] | None = None) -> httpx.Response:
_rate_limit()
response = httpx.get(url, params=params, timeout=30)
response.raise_for_status()
return response
def fetch_references(paper_id: str) -> list[Citation]:
"""Fetch references for a paper from Semantic Scholar.
Parameters
----------
paper_id:
Semantic Scholar paper ID (or ``arXiv:…`` / ``DOI:…`` prefixed ID).
Returns
-------
list[Citation]
One Citation per reference, with optional context snippet.
"""
# quote the id so a legacy-arXiv "/" (e.g. arXiv:math/0603097) doesn't break
# the URL path; keep ":" for the arXiv:/DOI: scheme prefix (audit R-5).
url = f"{_BASE_GRAPH}/paper/{quote(paper_id, safe=':')}/references"
params: dict[str, Any] = {"fields": "externalIds,contexts"}
try:
response = _get(url, params=params)
except httpx.HTTPStatusError as exc:
if exc.response.status_code == 404:
return []
raise
data = response.json()
raw_refs: list[dict[str, Any]] = data.get("data", [])
citations: list[Citation] = []
for entry in raw_refs:
cited_paper: dict[str, Any] = entry.get("citedPaper", {})
external_ids: dict[str, str] = cited_paper.get("externalIds") or {}
contexts: list[str] = entry.get("contexts", [])
context: str | None = contexts[0] if contexts else None
cited_id: str = (
external_ids.get("DOI") or external_ids.get("ArXiv") or cited_paper.get("paperId") or ""
)
if cited_id:
citations.append(Citation(citing_id=paper_id, cited_id=cited_id, context=context))
return citations
def fetch_recommendations(paper_id: str, limit: int = 20) -> list[str]:
"""Fetch recommended paper IDs from Semantic Scholar.
Parameters
----------
paper_id:
Semantic Scholar paper ID.
limit:
Maximum number of recommendations to return.
Returns
-------
list[str]
List of recommended paper IDs.
"""
url = f"{_BASE_RECS}/papers/forpaper/{quote(paper_id, safe=':')}"
params: dict[str, Any] = {"limit": limit}
try:
response = _get(url, params=params)
except httpx.HTTPStatusError as exc:
if exc.response.status_code == 404:
return []
raise
data = response.json()
recommended: list[dict[str, Any]] = data.get("recommendedPapers", [])
return [p["paperId"] for p in recommended if p.get("paperId")]