* feat(vertex-ai): support gemini 3.1 flash tts
* fix(vertex-ai): keep TTS metadata compatible with the cost map guard
* fix(vertex-ai): preserve existing Gemini TTS models and voice mappings
* fix(vertex-ai): recognize provider-stripped TTS model names
* test(vertex-ai): match current speech HTTP error response
* fix(vertex-ai): preserve nested speech locale and voice
* fix(vertex-ai): use provider speech media type in proxy
* fix(gemini): preserve TTS dispatch and nested speech settings
* test(gemini): run TTS regressions in CI shards
* fix(vertex-ai): account for Gemini Cloud TTS audio cost
* fix(vertex-ai): bill Gemini TTS without optional audio decoder
* test(gemini): cover TTS mapping and billing edge cases
* test(vertex-ai): cover Gemini voice normalization in provider shard
* fix(vertex-ai): keep Gemini TTS routing with generic provider metadata
* chore(vertex-ai): remove obsolete lint suppressions
* fix(gemini): strip audio format from speech configuration
* chore(vertex-ai): remove obsolete mutation suppressions
* fix(vertex-ai): preserve FLAC billing and wrapped audio headers
* fix(vertex-ai): reject unmeasurable FLAC before billing
* fix(vertex-ai): reconcile speech support with current provider mappings
* fix(vertex-ai): validate speech mappings and usage types
* fix(vertex-ai): preserve speech mapper override forwarding
* fix(gemini): map voice aliases across speech request forms
* fix(vertex-ai): send only formats the speech bridge cannot serve to Cloud TTS
Gemini TTS detection now goes by model name, so newer Vertex Gemini TTS
models keep working, and only mp3, opus, alaw, mulaw and other container
formats move to Cloud Text-to-Speech. wav and pcm requests stay on
generateContent as on main.
A Cloud TTS response whose duration cannot be measured now returns the
audio unbilled with a warning instead of raising after a paid call. FLAC
handling is removed because Cloud TTS has no FLAC encoding.
The cost map, the google_genai mappers and the proxy error path go back
to main, since those changes were outside this feature.
* fix(vertex_ai): keep Gemini TTS formats, region and instructions on routes that serve them
Only mp3, opus, alaw and mulaw go to Cloud Text-to-Speech. Every other
format gets a local 400 that lists the supported ones, before Google is
called.
Cloud TTS uses the deployment's us or eu regional host. Other regions
and a custom api_base get a 400 that says to request wav or pcm.
instructions is sent as the Cloud TTS style prompt, and a request with
no voice keeps the Gemini model.
get_usage_object is back to main's code, so dict usages still go
through Usage.__init__, and the proxy no longer labels pcm16 or
linear16 output as WAV.
* fix(vertex_ai): send Gemini TTS to every regional Cloud TTS host and keep speak tags as text
Cloud Text-to-Speech serves Gemini TTS on a host named after each Vertex
location, so a non-global vertex_location now uses
{location}-texttospeech.googleapis.com instead of only the us and eu hosts.
Google answers for regions it does not serve.
Gemini TTS voices reject SSML, so input that contains <speak> is sent as
text for Gemini TTS models. Chirp keeps the SSML auto-detect.
Removes the proxy alaw and mulaw media-type entries. Cloud TTS returns
those encodings with a WAV header, so the response is labeled audio/wav
and the entries never applied.
Adds a regression test that custom per-token pricing bills the usage a
speech response reports.
* fix(vertex_ai): map Gemini TTS regions to Google's Cloud TTS locations and keep a bad voice from cooling down the deployment
US and EU Vertex regions go to the us and eu Cloud TTS hosts, northamerica-northeast1 to its own, global or unset to global, and any other region gets a local 400. A Cloud TTS 404 on the Gemini path, such as a misspelled voice, comes back as a 400 so the router keeps the deployment serving wav. Usage reads the sent request from the response instead of the logging object.
* fix(vertex_ai): default Gemini TTS Cloud formats to a Gemini voice and validate speakers
Parse only usage fields from the sent Cloud TTS request, so a numeric speakingRate no longer fails after Google bills it.
Send the Gemini voice Kore when no voice is named, and reject Cloud TTS voice names unless drop_params is set.
Reject malformed speaker entries unless drop_params is set, and translate Cloud TTS speaker fields on wav and chat audio.
Use the Vertex default region when no location is set, so mp3 and wav share a region.
* test(vertex_ai): cover two-speaker Gemini TTS mp3 through aspeech with fake credentials
Replaces two tests that patched the Vertex TTS config's own token and URL methods.
* fix(vertex_ai): reject malformed Gemini TTS voices and keep beta Chirp and Lyria params unmapped
* fix(vertex_ai): drop unknown Gemini TTS voice keys on wav and pcm instead of rejecting them
* fix(vertex_ai): reject unknown Gemini TTS voice keys on wav, pcm, and chat audio unless drop_params is set
* fix(vertex_ai): honor every drop_params setting in the Gemini TTS voice key check
Global drop_params, batch row and deployment drop_params on Vertex batch
file uploads now drop unknown voice keys. A voice object with both
speechConfig and speech_config gets a 400 for the ignored speech_config.
* fix(gemini): drop unknown nested voice fields under drop_params and detect TTS by served model
* fix(gemini): filter unknown speech config fields with fixed-depth helpers and pass audio params through unchanged
* fix(gemini): camel-case snake replicated voice keys so drop_params keeps them
* fix(vertex-ai): reject voice fields Cloud TTS cannot send unless drop_params is set
* fix(vertex-ai): reject wrong-typed Cloud TTS voice values and check speakers as sent
Gemini TTS on mp3, opus, alaw, or mulaw now answers 400 for a voice field whose value Cloud TTS cannot send, such as a list languageCode or a string voiceConfig, and for nested voice fields under a speaker that also names speakerId. drop_params still drops them.
* fix(vertex-ai): reject wrong-typed speech config wrappers and speakerId overriding a prebuilt voice on Cloud TTS
* fix(vertex-ai): keep speakers and voice_config beside a speech_config wrapper on Cloud TTS
* fix(vertex-ai): pick Cloud TTS voices from the same speech config the WAV path sends to Gemini
* fix(files): carry the deployment's drop_params on model= file uploads so Vertex batch rows drop unknown voice keys
* fix(gemini): keep a structured speech voice when the model is a model_alias_map alias for a Gemini TTS model
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Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
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