75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
from typing import Literal
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import numpy as np
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from pydantic import BaseModel, Field, field_validator
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class OpenAICreateSpeechRequest(BaseModel):
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input: str
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model: str | None = None
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voice: str | None = Field(
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default=None,
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description="Voice to use. For OpenAI: alloy, echo, etc. For Qwen3-TTS: Vivian, Ryan, etc.",
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)
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instructions: str | None = Field(
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default=None,
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description="Instructions for voice style/emotion (maps to 'instruct' for Qwen3-TTS)",
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)
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response_format: Literal["wav", "pcm", "flac", "mp3", "aac", "opus"] = "wav"
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speed: float | None = Field(
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default=1.0,
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ge=0.25,
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le=4.0,
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)
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stream_format: Literal["sse", "audio"] | None = "audio"
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# Qwen3-TTS specific parameters
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task_type: Literal["CustomVoice", "VoiceDesign", "Base"] | None = Field(
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default=None,
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description="TTS task type: CustomVoice, VoiceDesign, or Base (voice clone)",
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)
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language: str | None = Field(
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default=None,
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description="Language code (e.g., 'Chinese', 'English', 'Auto')",
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)
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ref_audio: str | None = Field(
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default=None,
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description="Reference audio for voice cloning (Base task). URL, base64, or file path.",
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)
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ref_text: str | None = Field(
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default=None,
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description="Transcript of reference audio for voice cloning (Base task)",
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)
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x_vector_only_mode: bool | None = Field(
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default=None,
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description="Use speaker embedding only without in-context learning (Base task)",
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)
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max_new_tokens: int | None = Field(
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default=None,
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description="Maximum tokens to generate",
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)
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@field_validator("stream_format")
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@classmethod
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def validate_stream_format(cls, v: str) -> str:
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if v == "sse":
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raise ValueError("'sse' is not a supported stream_format yet. Please use 'audio'.")
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return v
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class CreateAudio(BaseModel):
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audio_tensor: np.ndarray
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sample_rate: int = 24000
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response_format: str = "wav"
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speed: float = 1.0
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stream_format: Literal["sse", "audio"] | None = "audio"
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base64_encode: bool = True
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class Config:
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arbitrary_types_allowed = True
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class AudioResponse(BaseModel):
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audio_data: bytes | str
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media_type: str
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