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Environment:ThreeSR Awesome Inference Time Scaling Semantic Scholar API Environment

From Leeroopedia
Knowledge Sources
Domains Infrastructure, API_Integration, Academic_Search
Last Updated 2026-02-14 00:00 GMT

Overview

Network environment with access to the Semantic Scholar Academic Graph API, required for paper search and detail retrieval operations in the automated workflow.

Description

This environment provides HTTP access to two Semantic Scholar API endpoints used by the fetch_semantic_info.py script:

Both endpoints are public and do not require authentication. However, they are subject to rate limiting by Semantic Scholar.

Usage

Use this environment whenever running the Automated Paper Addition workflow, specifically:

  • Search_Papers_Function -- queries the Graph API for papers matching a keyword
  • Get_Paper_Info_Function -- fetches paper details including arXiv ID and abstract
  • Format_Paper_Info_Function -- internally calls get_paper_info() during formatting

System Requirements

Category Requirement Notes
Network Internet access HTTPS outbound to api.semanticscholar.org
Firewall Port 443 open Standard HTTPS
DNS Able to resolve api.semanticscholar.org Standard DNS resolution

Dependencies

API Endpoints

Rate Limits

Semantic Scholar imposes rate limits on unauthenticated requests. The exact limits are not documented in the script, but the commented-out time.sleep(10) at line 217 suggests the author is aware of this constraint.

Credentials

No API keys or tokens are required. The Semantic Scholar endpoints used by this script are public.

Optional: Semantic Scholar offers an API key program for higher rate limits. If needed, the key would be passed via an x-api-key HTTP header. The current script does not support this.

Quick Install

# No installation needed beyond the Python runtime with requests.
# Verify API access with a simple curl command:
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=test&limit=1" | python3 -m json.tool

Code Evidence

API base URL constant from fetch_semantic_info.py:9:

BASE_URL = "https://api.semanticscholar.org/graph/v1/"

Graph API search call from fetch_semantic_info.py:24-28:

url = f"{BASE_URL}paper/search?query={query}&fields={FIELDS}&limit={limit}&sort=year"
response = requests.get(url)
if response.status_code != 200:
    print("Error fetching data from Semantic Scholar API")
    return []

Legacy v1 paper detail call from fetch_semantic_info.py:44-46:

url = f'https://api.semanticscholar.org/v1/paper/{paper_id}'
response = requests.get(url)
return response.json()

Commented-out rate limiting from fetch_semantic_info.py:217:

# Optionally: pause between queries to avoid too frequent requests
# time.sleep(10)

Common Errors

Error Message Cause Solution
Error fetching data from Semantic Scholar API (printed by script) API returned non-200 status (rate limited, server error, or network issue) Wait and retry; check internet connectivity; consider enabling the commented-out time.sleep(10)
requests.exceptions.ConnectionError No internet access or DNS failure Verify internet connectivity and that api.semanticscholar.org is reachable
json.decoder.JSONDecodeError API returned non-JSON response (e.g., HTML error page) Usually caused by rate limiting; wait before retrying

Compatibility Notes

  • Two API versions: The script uses two different Semantic Scholar API versions. The search function uses Graph API v1 (graph/v1/) while the detail function uses the legacy v1 API (v1/). These have different response schemas.
  • No authentication support: The script does not implement API key headers. For high-volume usage, Semantic Scholar offers an API key program with higher rate limits.
  • No retry logic: The script does not retry failed API calls. A single failure (e.g., rate limiting) will result in an empty result set or incomplete data.

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