82 lines
3.9 KiB
Python
82 lines
3.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""VoxCPM2 serving adapter (AR base-LM + diffusion side-computation)."""
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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 VoxCPM2Adapter(ARTTSAdapter):
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"""VoxCPM2 shares ``latent_generator`` with VoxCPM; selected when no ``vae``
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stage is present (and/or via ``model_arch``)."""
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stage_keys = frozenset({"latent_generator"})
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model_archs = frozenset({"VoxCPM2TalkerForConditionalGeneration"})
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name = "voxcpm2"
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# The talker architecture is authoritative and is tested ahead of every
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# stage key, so a VoxCPM2 talker deployed under a stage key another model
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# claims still resolves to VoxCPM2.
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detect_priority = 10
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def validate(self, request: "OpenAICreateSpeechRequest") -> str | None:
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"""Validate VoxCPM2 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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if request.voice is not None:
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request.voice = request.voice.lower()
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available_voices = set(server.uploaded_speakers) | set(server.precomputed_speakers) | {"default"}
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if request.voice not in available_voices:
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supported = ", ".join(sorted(available_voices)) or "none"
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return f"Invalid voice '{request.voice}'. Supported: {supported}"
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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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server = self.ctx.server
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# VoxCPM2 needs the raw waveform tuple for prefill-length accounting, so
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# it loads uploaded audio directly rather than via _apply_uploaded_speaker.
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uploaded_ref = None
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if request.voice:
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voice_lower = request.voice.lower()
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if voice_lower in server.uploaded_speakers and not has_inline_ref_audio:
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if server.uploaded_speakers[voice_lower].get("embedding_source") == "direct":
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raise ValueError(
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f"Uploaded voice '{request.voice}' uses a speaker embedding (Qwen3-only). "
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f"Re-upload with an audio file for VoxCPM2."
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)
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if request.ref_audio is None:
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uploaded_ref = server._load_uploaded_audio(voice_lower)
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prompt = await server._build_voxcpm2_prompt(request, uploaded_ref=uploaded_ref)
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tts_params = {}
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if request.voice:
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voice_lower = request.voice.lower()
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if voice_lower in server.uploaded_speakers or voice_lower in server.precomputed_speakers:
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additional = prompt.setdefault("additional_information", {})
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additional["voice_name"] = voice_lower
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additional["voice_created_at"] = server._voice_created_at(voice_lower)
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return PreparedRequest(prompt=prompt, tts_params=tts_params, model_type="voxcpm2")
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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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