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Name the voice files after the voices
voices/libri_male_6209.json is now voices/daniel.json. The model repo keeps the LibriTTS-R reader ids — renaming there would break every client pinned to the published bundle — so the catalog carries both: `remote` is what is fetched, `file` is what it is called on disk. The old stems are retired so they are deleted rather than discovered a second time as "Libri Male 6209", and aliased so a caller that pinned one still resolves to the voice it named. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0138DB6F6YxWtYWy7WNaLAsUd0a3534 -
Bump serverless image tag to v7
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0138DB6F6YxWtYWy7WNaLAsU0a3acd3 -
Ignore sparse nikud, and split partial nikud between front ends
Phonikud spells a Hebrew word out of its points, so a word handed to it without them comes back as consonant soup: שלוש -> ʃˈlʃ. The Hebrew branch routed the whole segment through it whenever *any* mark was present, so one shuruk dot in השלמוּת was enough to mangle a paragraph that Renikud would have read correctly. A word now counts as vocalized only if it carries a vowel point and more than one mark overall — short words excepted, since לֹא is fully specified by its one vowel. Everything else is stripped and goes to Renikud. When both kinds are present the text is split into runs so a properly pointed word keeps its reading while its neighbours keep Renikud. Also ship Russian in the serverless image. RUAccent/RUPhon go in before the serverless set so onnxruntime-gpu still wins the wheel collision, torch comes from the CPU index (the front end runs on CPU anyway), and the ~1 GB of weights is warmed at build time rather than on a cold worker's first job. Co-Authored-By: Claude Opus …7daf341
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Install onnxruntime last so the GPU wheel is not clobbered
The Space logs said "onnxruntime has no CUDA provider", which is why the probe kept reporting cpu on ZeroGPU hardware. renikud-plus depends on `onnxruntime` (the CPU build) and we ask for `onnxruntime-gpu`; both wheels install into the same onnxruntime/ directory, so whichever pip writes last wins. With the GPU wheel first in the file, renikud-plus's CPU wheel overwrote it and CUDAExecutionProvider disappeared. Confirmed in a clean linux/amd64 container: gpu installed last -> [Tensorrt, CUDA, CPU] cpu installed last -> [Azure, CPU] Move onnxruntime to the end of every requirements file. The Docker image happened to land the right way round already, so this is a no-op there — which is exactly the problem, so the build now asserts the provider survived rather than printing it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0138DB6F6YxWtYWy7WNaLAsU9f6a881