boatmanandYueqian Lin
32dddfcef4
Signed-off-by: boatman <109857087+sphinxkkkbc@users.noreply.github.com> Co-authored-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
56 lines
2.4 KiB
Python
56 lines
2.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Fish Speech serving adapter (retires the legacy ``_is_fish_speech`` flag)."""
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from typing import TYPE_CHECKING
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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, conditioning_cache_salt
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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 FishSpeechAdapter(ARTTSAdapter):
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stage_keys = frozenset({"fish_speech_slow_ar"})
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name = "fish_tts"
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def validate(self, request: "OpenAICreateSpeechRequest") -> str | None:
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"""Validate Fish Speech request parameters. Returns error message or None."""
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server = self.ctx.server
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err = server._apply_uploaded_speaker(request)
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if err:
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return err
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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.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 not request.ref_text or not request.ref_text.strip():
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return "Voice cloning requires 'ref_text' (transcript of the reference audio)"
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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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ref_audio_data = None
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if request.ref_audio is not None:
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wav_list, sr = await server._resolve_ref_audio(request.ref_audio)
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ref_audio_data = (wav_list, sr)
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prompt = await server._build_fish_speech_prompt_async(
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request, ref_audio_data=ref_audio_data, has_inline_ref_audio=has_inline_ref_audio
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)
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tts_params = {}
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prompt["cache_salt"] = conditioning_cache_salt(request, tts_params)
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return PreparedRequest(prompt=prompt, tts_params=tts_params, model_type="fish_speech")
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