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v0.5.7 — README trim + .gitattributes + PyPI publish

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@ssmurfgg04-gif ssmurfgg04-gif released this 29 Aug 10:18
· 53 commits to main since this release
v0.5.7
82779dc

What shipped in 0.5.7

Based on a research sweep of the top 1% fastest-growing GitHub AI/infra repos (chroma · mem0 · llama_index · langchain · zep · aider · shadcn/ui · supabase · ollama · vllm · litellm · instructor · smolagents · letta · open-webui · mcp-servers · continuedev) and HN/Reddit launch patterns.

Repo polish

  • .gitattributes — *.html linguist-generated=true removes the trajectory viewer / leaderboard HTML from GitHub's language bar (was inflating "90% HTML" because Linguist counts lines, not files).
  • README.md 742 → 100 lines (85% reduction) — new top fold mirrors Mem0/Aider/Chroma shape: centered title + 6 essential badges + 1-line blockquote hook + 1-paragraph differentiator + 5-line Quick Start + 2-column LongMemEval table + "When to use cortexm vs Mem0/Zep/Chroma" + drop-in plugins list + docs link table.
  • pyproject.toml PEP 639 compliant — SPDX license = "Apache-2.0" (no deprecated {file = "LICENSE"} form), readme.content-type = "text/markdown" (was bare; would have rendered as plain text on PyPI), 11 classifiers, 21 high-search-volume keywords (agent-memory / llm-memory / long-term-memory / mem0 / memgpt / letta / zep / chroma / deterministic-ai / local-first / vector-symbolic-architecture / provenance / bi-temporal / hippocampus / context-engineering / rag / mcp / self-hosted), 5 project URLs (Documentation / Repository / Issues / Changelog).
  • Topics + About + Discussions enabled — 18 GitHub topics for topic-page discovery, description set to the tagline, Discussions on for "how-do-I" questions (mem0/langchain/supabase all do this).

Code-quality state (verified, no changes needed)

  • cortexm/__init__.py exposes Memory, Config, Pipeline, Context, mount_default, LLM_CALLS. Memory class has add, edit, fix, recall_step, preload_context, export_markdown, import_markdown, search, apply_rules, consolidate, close (idempotent).
  • cortexm/config.py defaults: verbatim_ingest_enabled=True, verbatim_search_enabled=True, recall_step_in_search=True — the 0.948 canonical score depends on all three being ON; guarded by tests/test_public_api_smoke.py::test_config_defaults_ensure_verbatim.
  • cortexm/text/embedder.py: HashingEmbedder has PolyglotEncoder fallback for non-English text (CJK/Devanagari/Arabic/Cyrillic/Thai/Hangul/Kana) via the labse_enabled opt-in flag.
  • scripts/longmemeval_canonical_full.py (620 lines) is in the repo — the 500-question canonical run workflow.
  • plugins/dsh-cortexm/package.json version 1.0.0 — independent npm versioning (matches what's published on npm).

Tests + build

  • 517 tests pass, 24 skipped, 0 failures in 21s (regression suite).
  • Wheel cortexm-0.5.7-py3-none-any.whl (438 KB) + sdist (477 KB) build clean.
  • Smoke test on built wheel: import cortexm → __version__ == '0.5.7' → LLM_CALLS == 0 → Memory().add() + Memory().search() roundtrip works.

Live on PyPI

pip install cortexm → https://pypi.org/project/cortexm/0.5.7/

Trusted-publish via .github/workflows/release.yml (OIDC, no API token). Workflow run: https://github.com/ssmurfgg04-gif/context-m/actions/runs/33247162186

Promises intact

✅ Always remembers · ✅ Flat cost μ=0 · ✅ Own your data · ✅ Doesn't lie · ✅ Same every time

No LLM embedder swap (HashingEmbedder stays per user instruction).

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