v0.1.9

v0.1.9 — 2026-10-05

Whistle is now the default engine. This release ships the Whistle integration
prepared on the feat/whistle-primary branch.

Changed

• Whistle is the default engine; openai-whisper becomes an explicit opt-in.
  Whistle is a CPU-only native CLI that needs no PyTorch, so a fresh
  pip install textflowkit no longer pulls the torch stack. openai-whisper
  moves to a new optional whisper extra and is selected with --engine whisper
  (or engine="whisper" on the Python/MCP/HTTP surfaces); the all extra still
  includes it. A saved request or checkpoint from before this change keeps running
  on the engine it names, so legacy Whisper work is never silently migrated, and
  legacy engine aliases are preserved so older decoders keep working.
• Engine selection is never silent. An unknown engine name, an unsupported
  language, or a non-CPU device for Whistle is refused at request construction —
  before any media is fetched — and the message names --engine whisper as the
  GPU alternative. The engine is not switched to satisfy a request.

Added

• Whistle engine. Seven advertised languages (en, de, fr, es, it,
  nl, pl); native Windows x86-64/arm64, Linux x86-64/arm64, and Apple Silicon
  (an Intel Mac is refused and pointed at the explicit Whisper engine); no WSL.
  One pinned native binary and one pinned model are downloaded and hash-verified
  on first use, outside the package. Long audio is split into 26-second cores with
  up to 2 seconds of context (each clip ≤ 30 s); a word is owned by the clip whose
  core contains its midpoint, so repeated phrases are preserved. Native
  --audio-stream is never used.
• Durable per-block resume for Whistle. A long run persists a partial
  checkpoint after each core; a resume validates the source and decoded-WAV
  hashes and the configuration, then re-runs only the unfinished blocks and adopts
  the rest. A partial body is Whistle-only. Reuses the existing single SQLite
  store and its one-owning-process model.
• Prompt, bounded cancellation. A running Whistle run polls for cancellation
  between clips and terminates its exact owned child process, bounded by a
  per-clip timeout and a bounded stdout cap. A single long openai-whisper model
  call is still cancellable only at its next stage boundary.
• Telemetry off, unconditionally. Every Whistle child process forces
  NEEDLE_TELEMETRY=0, DO_NOT_TRACK=1, and CI=1, overriding a parent that
  opted in, and there is no opt-in setting. The product adds no analytics, usage
  SDK, anonymous ids, or events. TEXTFLOWKIT_OFFLINE refuses downloads and
  TEXTFLOWKIT_MODELS_DIR chooses the asset directory; the pinned first-use
  asset/model download is not telemetry.

Documentation

• README, user manual, install/adapter/architecture/roadmap/release docs and the
  website source now describe Whistle as the shipped default. ROCm (and the
  torch-pinning caveat) is scoped to the explicit whisper engine and
  diarization, never to Whistle.
• Self-contained checked-in SVG architecture drawings were added under
  docs/assets and embedded in the README, both manuals (user-manual.md and the
  renamed Developer and integration manual, adapters.md), the architecture
  guide, and the landing page.
• The live YouTube release smoke pins --engine whisper --model tiny so its
  measured default-clip word stays reproducible across the default-engine change.

Verification boundary

Local evidence only: a 4-hour (14,407-second) CPU run produced 555
clips / 34,596 words / 2,875 segments in 731 seconds, offline with telemetry
forced off, and a separate two-process run proved durable block resume. These are
first local test numbers on one machine — not a universal performance claim, and
not a claim that Whistle's accuracy equals Whisper's. No human-scored
word-error rate is claimed.

Release verification

• PR #25 merged at 3ae03dd336f87615d2f9e87c976b46b13f1c7a1c.
• Exact-commit main CI succeeded: Windows/macOS/Linux Python matrix, installed-wheel entry points and lint. Cloudflare deployment also succeeded.
• Trusted Publishing workflow succeeded. Optional fonts0.1.6 were reused, not rebuilt or republished.
• Fresh native Windows install from PyPI (textflowkit[export,mcp,http]==0.1.9) has no torch or openai-whisper. CLI/MCP/HTTP report0.1.9; Whistle speech selftest and real JSON/SRT/TXT/PDF/DOCX export passed using the verified local model/runtime cache.
• Downloaded GitHub assets match PyPI SHA256 and sizes for all four distributions; see SHA256SUMS.
• Live local YouTube release smoke passed on the exact merged commit with explicitly selected Whisper tiny and expected speech. This is not default-Whistle YouTube or other-platform certification.

Documentation

• Landing page and architecture drawings
• User manual
• Developer and integration manual
• Architecture guide