60 lines
2.5 KiB
Python
60 lines
2.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Voxtral TTS serving adapter."""
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from typing import TYPE_CHECKING, Any
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from vllm_omni.entrypoints.openai.tts_adapters import register_tts_adapter
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from vllm_omni.entrypoints.openai.tts_adapters.base import ARTTSAdapter, PreparedRequest, apply_max_new_tokens
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if TYPE_CHECKING:
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from vllm_omni.entrypoints.openai.protocol.audio import OpenAICreateSpeechRequest
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@register_tts_adapter
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class VoxtralTTSAdapter(ARTTSAdapter):
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stage_keys = frozenset({"audio_generation"})
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name = "voxtral_tts"
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def validate(self, request: "OpenAICreateSpeechRequest") -> str | None:
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"""Validate Voxtral TTS request parameters. Returns error message or None."""
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server = self.ctx.server
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if not request.input or not request.input.strip():
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return "Input text cannot be empty"
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# Voxtral TTS requires either a preset voice or ref_audio for voice cloning.
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if request.voice is None and request.ref_audio is None:
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return "Either 'voice' (preset speaker) or 'ref_audio' (voice cloning) must be provided"
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if request.ref_audio is not None:
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fmt_err = server._validate_ref_audio_format(request.ref_audio)
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if fmt_err:
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return fmt_err
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if request.voice is not None:
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request.voice = request.voice.lower()
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if server.supported_speakers and request.voice not in server.supported_speakers:
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return f"Invalid speaker '{request.voice}'. Supported: {', '.join(sorted(server.supported_speakers))}"
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if request.max_new_tokens is not None:
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if request.max_new_tokens < self.max_new_tokens_min:
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return f"max_new_tokens must be at least {self.max_new_tokens_min}"
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if request.max_new_tokens > self.max_new_tokens_max:
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return f"max_new_tokens cannot exceed {self.max_new_tokens_max}"
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return None
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async def build(
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self, request: "OpenAICreateSpeechRequest", sampling_params_list: list, has_inline_ref_audio: bool
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) -> PreparedRequest:
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prompt = await self.ctx.server._build_voxtral_prompt_async(request)
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return PreparedRequest(prompt=prompt, tts_params={}, model_type="voxtral_tts")
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def apply_sampling_overrides(
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self,
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sampling_params_list: list,
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request: "OpenAICreateSpeechRequest",
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prompt: dict[str, Any] | None = None,
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request_id: str | None = None,
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) -> list:
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return apply_max_new_tokens(sampling_params_list, request)
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