SOTA AI Model Tracker

What to consider before installing/running: - If you only need up-to-date SOTA data, prefer downloading the published data/sota_export.json or CSV (SKILL.md Option 1) instead of running scrapers or enabling servers. - Running scrapers requires pip install -r requirements.txt and playwright install chromium (downloads a browser binary). Scrapers will make network requests to LMArena, ArtificialAnalysis, HuggingFace, Civitai, etc.; review scraper code if you have policy concerns about any source. - The project will modify user config if you follow the embedding instructions (writes ~/.claude/CLAUDE.md) and may add a user-level systemd timer; these are normal but persistent changes — back up the file first. - If you run the REST API or MCP server locally, consider firewalling or adding authentication (SKILL.md and SECURITY.md show how) so the service isn't exposed publicly by accident. - The repo includes GitHub Actions automation in its workflow docs; if you fork and enable Actions, the workflow will auto-commit updated data to your fork. Be mindful of what you allow a workflow to push from your account. - To reduce risk: run inside a dedicated virtualenv, inspect init_db.py and scrapers for unexpected behavior, use the static JSON export where possible, and avoid enabling MCP or systemd timers until you’re comfortable with the code. Overall this appears coherent and consistent with its stated purpose; the main risks are operational (network access, local file writes, running a local server) rather than deceptive behavior.