Changelog

1.0.1 — metadata and documentation update

Refreshes the immutable PyPI project description from the cleaned public README. Runtime behavior is unchanged from 1.0.0; only package version metadata changes in runtime source. Detailed benchmark methodology and measured latency tradeoffs remain in BENCHMARKS.md and historical records. No faster execution or absence of latency impact is claimed.

Adds the owner-issued Google Search Console verification file and updates current installation/release/citation metadata. Canonical installation remains pip install implicit-ai. The 1.0.0 tag and artifacts remain unchanged.

1.0.0 — stable release

Promotes the validated 1.0.0rc2 public source to stable 1.0.0 with version metadata, release documentation and Trusted Publishing workflow updates. Canonical installation: pip install implicit-ai. Adds the required package implicit.__version__ metadata; execution, storage and materialization behavior are unchanged. Stable artifacts differ from RC2 and have their own checksums. The v1.0.0rc2 tag and assets remain historical evidence.

The preserved rc1 benchmark remains 155/155 equivalent cases, 93.88% aggregate, 94.40% mean and 99.55% median retained serialized/materialized-state reduction, with approximately +0.554 seconds/case mean full-pipeline latency overhead. Bytes are not RAM; this promotion does not create a new native benchmark result.

1.0.0rc2 — initial public preview

Adds bounded local stdio MCP, client/schema tests, deterministic public extraction, agent/plugin assets, crawlable documentation and launch rehearsals. Public metadata excludes research dependencies; CLI doctor reports Core rather than private adapter availability. Core execution/storage/materialization remain inherited from rc1; no new native 155-case result is claimed.

1.0.0rc1 — internal

Preserved systems equivalence in the 155-case population, durable recovery/migration, bounded residency and external adapter integration. Retained serialized/materialized bytes fell 93.88% overall and 99.55% median with approximately +0.554 seconds/case mean pipeline overhead. Not RAM or learning claims.