v0.7.3

RealtimeTTS v0.7.3

Features

• PocketTTS GPU
  • Added PocketTTSGpuEngine and PocketTTSGpuVoice for the CUDA-capable pocket-tts-gpu fork.
  • Added built-in voice support, prompt WAV voice cloning, cached prompt state loading/saving, and optional silence trimming for the GPU engine.
  • Added lazy root exports and RealtimeTTS.engines exports for the new GPU engine.

Improvements

• PocketTTS
  • Added explicit device support to PocketTTSEngine so CPU users can stay on CPU while advanced users can move the official PocketTTS model to another Torch device.
  • Kept CPU and GPU PocketTTS paths separate so normal realtimetts[pockettts] installs remain predictable.
• Import Behavior
  • Delayed stream2sentence tokenizer initialization until sentence generation is actually used, keeping import RealtimeTTS quieter and lighter.
• Packaging
  • Bumped the package version to 0.7.3.
  • Added pockettts-gpu and pocket-gpu extras for the shared GPU-engine dependencies.

Fixes

• Avoided import-time tokenizer setup from TextToAudioStream, which could surprise users before they created or played a stream.
• Improved the missing-dependency message for PocketTTSGpuEngine with the pinned GPU fork install command.

Documentation

• Expanded PocketTTS documentation with separate CPU and CUDA fork installation paths.
• Documented CUDA PyTorch installation and the pinned PocketTTS GPU fork revision used for this release.
• Updated installation and engine-selection docs to list PocketTTSGpuEngine and the new GPU extras.
• Updated the README engine matrix to show the optional PocketTTS GPU path.

Tests and Examples

• Added unit coverage for PocketTTSGpuEngine streaming output and PocketTTSGpuVoice representation.
• Expanded PocketTTS tests around device forwarding.
• Verified the PyPI wheel and source distribution with twine check.
• Smoke-tested the built wheel by installing it and importing PocketTTSGpuEngine / PocketTTSGpuVoice.

Notes

• PyPI release: pip install realtimetts==0.7.3
• CPU PocketTTS install: pip install "realtimetts[pockettts]"
• GPU PocketTTS install starts with pip install "realtimetts[pockettts-gpu]", then requires a CUDA-enabled PyTorch build and the pinned pocket-tts-gpu fork documented in docs/engines/pockettts.md.
• No intentional breaking changes.