Commit Graph

3 Commits

Author SHA1 Message Date
Safi 5164d972ed ci: add v2 branch to CI triggers 2026-04-06 01:29:28 +01:00
Safi cf7f42d3e7 docs: lead with Karpathy problem → graphify answer framing
fix: add pytest to CI install step

docs: reframe README as Claude Code skill, fix worked/ description

fix: use graphifyy on PyPI until graphify name is reclaimed

fix: pyproject.toml structure, URLs, description; README clarifications

feat: keywords, CHANGELOG, requires note, CI end-to-end install check
2026-04-05 00:20:56 +01:00
Safi 24bcd6d448 docs: CI, architecture guide, worked examples, README fixes
- Add GitHub Actions CI workflow (Python 3.10 and 3.12)
- Add CI badge to README
- Add ARCHITECTURE.md: pipeline overview, module table, schema, how to
  add a language extractor, security summary
- Move eval reports from tests/ to worked/httpx/ and worked/mixed-corpus/
- Fix README: test count 163→212, language table (13 languages via
  tree-sitter), extract.py description, worked examples links

benchmark: 8.8x token reduction on nanoGPT + minGPT + micrograd

- Run AST extraction on 29 Python files across 3 Karpathy repos
- 177 nodes, 246 edges, 17 communities (Leiden)
- 8.8x avg token reduction vs naive full-corpus context stuffing
- Notable: micrograd cleanly splits into engine/nn communities;
  nanoGPT model vs training loop correctly separated
- Honest: stdlib import noise flagged, config isolates documented

benchmark: 71.5x token reduction on mixed corpus (code+papers+images)

Full run: nanoGPT+minGPT+micrograd + 5 research papers + 4 images
285 nodes, 340 edges, 53 communities
Average BFS query: 1,726 tokens vs 123,488 naive (71.5x)
Code-only (AST) sub-benchmark: 8.8x on 13k-word corpus
2026-04-05 00:20:56 +01:00