初始化提交
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"""音频相关 API 端点 — TTS（文本转语音）、ASR（语音转文本）等。
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音频端点使用神识的模型注册表查找可用的音频模型，并调用对应音频适配器合成 /
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转写。ASR 与 TTS 按 ``tags`` 中的 ``asr`` / ``tts`` 能力区分，ASR 内部再按
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``provider`` 区分协议：``yuanqi`` 走 multipart ``/v1/audio/transcriptions``，
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其他走 MiMo 风格的 ``/chat/completions`` + ``input_audio``。
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"""
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from __future__ import annotations
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from fastapi import APIRouter, File, Form, HTTPException, Response, UploadFile
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from pydantic import BaseModel, Field
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from app.ai_provider.audio import AudioService, AudioServiceError
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from app.ai_provider.manager import ProviderManagerFactory
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from app.core.logging import logger
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router = APIRouter(tags=["audio"])
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_MIME_MAP = {
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"wav": "audio/wav",
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"mp3": "audio/mpeg",
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"opus": "audio/opus",
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"flac": "audio/flac",
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}
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class _AudioModelFactory:
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"""Adapter: wraps ProviderManager to provide ModelFactory interface for AudioService.
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``create_audio(name)`` 按 ``tags`` 判断 ``asr`` / ``tts`` 能力：
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- ``tts`` → ``HunjingTTSOpenAI``（``/chat/completions`` + ``audio``）
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- ``asr`` → 按 ``provider`` 分派：
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- ``yuanqi`` → ``YuanqiASRWhisper``（multipart ``/v1/audio/transcriptions``）
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- 其他 → ``HunjingASROpenAI``（``/chat/completions`` + ``input_audio``）
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"""
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def __init__(self, manager) -> None:
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self._manager = manager
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@property
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def registry(self):
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return self._manager.model_registry
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def create_audio(self, name: str):
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model = self._manager.get_model_config(name)
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is_asr = "asr" in model.tags
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if is_asr:
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return self._create_asr(model)
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return self._create_tts(model)
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def _provider_or_none(self, model):
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"""安全获取 provider 配置（provider 未配置时返回 None，走纯端点解析）。"""
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try:
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return self._manager.get_provider_config(model.provider)
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except Exception:
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return None
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# ── ASR ─────────────────────────────────────────────────────────────
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def _create_asr(self, model):
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"""按 provider 选择 ASR 协议适配器。"""
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# yuanqi 本地引擎走 multipart /v1/audio/transcriptions
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if model.provider == "yuanqi":
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from app.ai_provider.audio.yuanqi_asr import YuanqiASRWhisper
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if model.endpoints:
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return YuanqiASRWhisper.from_model_config(
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model, provider=self._provider_or_none(model)
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)
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provider = self._manager.get_provider_config(model.provider)
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api_key, base_url = self._resolve_credentials(provider)
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if not base_url:
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raise AudioServiceError(
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status_code=500,
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code="audio_asr_no_base_url",
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message=f"Provider '{model.provider}' has no base_url configured.",
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)
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return YuanqiASRWhisper(
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base_url=base_url,
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api_key=api_key or "",
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model=model.model,
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request_timeout_seconds=model.timeout_seconds or 300,
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)
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# MiMo 等走 /chat/completions + input_audio
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from app.ai_provider.audio.asr import HunjingASROpenAI
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if model.endpoints:
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return HunjingASROpenAI.from_model_config(
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model, provider=self._provider_or_none(model)
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)
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provider = self._manager.get_provider_config(model.provider)
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api_key, base_url = self._resolve_credentials(provider)
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if not base_url:
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raise AudioServiceError(
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status_code=500,
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code="audio_asr_no_base_url",
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message=f"Provider '{model.provider}' has no base_url configured.",
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)
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return HunjingASROpenAI(
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base_url=base_url,
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api_key=api_key or "",
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model=model.model,
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request_timeout_seconds=model.timeout_seconds or 300,
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)
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# ── TTS ─────────────────────────────────────────────────────────────
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def _create_tts(self, model):
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from app.ai_provider.audio.tts import HunjingTTSOpenAI
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# 有 endpoints 时交给 from_model_config（按端点的 status/model/超时）
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if model.endpoints:
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return HunjingTTSOpenAI.from_model_config(
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model, provider=self._provider_or_none(model)
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)
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# 无 endpoint 时回退到 provider 级别凭证
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provider = self._manager.get_provider_config(model.provider)
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api_key, base_url = self._resolve_credentials(provider)
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if not base_url:
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raise AudioServiceError(
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status_code=500,
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code="audio_tts_no_base_url",
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message=f"Provider '{model.provider}' has no base_url configured.",
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)
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return HunjingTTSOpenAI(
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base_url=base_url,
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api_key=api_key or "",
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model=model.model,
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request_timeout_seconds=model.timeout_seconds or 120,
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)
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def _resolve_credentials(self, provider):
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"""从 settings 解析 provider 级别的 API key 和 base URL。"""
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from app.core.config import settings
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api_key = (
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settings.__getattribute__(provider.api_key_env.lower())
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if hasattr(settings, provider.api_key_env.lower())
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else ""
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)
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base_url = (
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settings.__getattribute__(provider.base_url_env.lower())
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if hasattr(settings, provider.base_url_env.lower())
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else None
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)
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return api_key, base_url
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class TTSRequest(BaseModel):
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"""TTS 合成请求。"""
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text: str = Field(..., min_length=1, max_length=4096, description="要合成语音的文本。")
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voice: str = Field("default", description="语音角色标识（取决于模型，如 default 或声纹 ID）。")
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format: str = Field("wav", description="音频格式：wav / mp3 / opus / flac。")
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@router.post("/audio/tts")
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async def synthesize_speech(body: TTSRequest) -> Response:
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"""合成文本为语音，返回音频二进制流。
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使用神识注册表中第一个活跃的 TTS 模型（capability: tts）。
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未配置 TTS 模型时返回 503。
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"""
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if not body.text.strip():
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raise HTTPException(status_code=400, detail="text 不能为空。")
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mime = _MIME_MAP.get(body.format, "audio/wav")
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try:
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manager = ProviderManagerFactory.create()
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service = AudioService(_AudioModelFactory(manager))
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async with service:
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result = await service.synthesize(
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text=body.text,
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voice=body.voice,
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response_format=body.format,
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)
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except AudioServiceError as exc:
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logger.error(
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"audio.tts.api_error",
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voice=body.voice,
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format=body.format,
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error_code=exc.code,
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error_message=exc.message,
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)
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raise HTTPException(
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status_code=exc.status_code or 502,
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detail=exc.message,
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) from exc
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logger.info(
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"audio.tts.success",
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voice=body.voice,
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format=body.format,
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audio_bytes=len(result.audio_data),
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)
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return Response(
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content=result.audio_data,
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media_type=mime,
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headers={
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"Content-Disposition": f'inline; filename="speech.{body.format}"',
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"X-Audio-Format": body.format,
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"Cache-Control": "public, max-age=3600",
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},
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)
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# ── ASR（语音转文本）───────────────────────────────────────────────────────
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class TranscriptionResponse(BaseModel):
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"""OpenAI Whisper 兼容的转写响应。"""
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text: str = Field(description="转写后的文本")
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@router.post("/audio/transcriptions", response_model=TranscriptionResponse)
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async def transcribe_audio(
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file: UploadFile = File(..., description="音频文件（wav/mp3/m4a/flac/ogg/opus/webm 等）"),
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language: str | None = Form(default=None, description="语言提示（ISO-639-1：zh/en/ja/ko 等），省略则自动检测"),
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model: str | None = Form(default=None, description="可选，指定使用的 ASR 模型逻辑名（如 funasr-sensevoice / mimo-v2.5-asr），省略则用注册表中第一个"),
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) -> TranscriptionResponse:
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"""转写音频为文本，返回 OpenAI Whisper 兼容的 JSON。
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不指定 ``model`` 时用神识注册表中第一个活跃的 ASR 模型（capability: asr），
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按其 ``provider`` 自动选择协议适配器：``yuanqi`` 走本地 multipart 端点，
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其他走 MiMo 风格的 chat completions。未配置 ASR 模型时返回 503。
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"""
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audio_bytes = await file.read()
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if not audio_bytes:
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raise HTTPException(status_code=400, detail="音频文件为空。")
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fmt = (file.filename or "audio.wav").rsplit(".", 1)[-1].lower() if "." in (file.filename or "") else "wav"
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try:
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manager = ProviderManagerFactory.create()
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service = AudioService(_AudioModelFactory(manager))
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async with service:
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result = await service.transcribe(
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audio_data=audio_bytes,
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format=fmt,
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language=language,
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model_name=model,
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)
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except AudioServiceError as exc:
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logger.error(
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"audio.asr.api_error",
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filename=file.filename,
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format=fmt,
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language=language,
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error_code=exc.code,
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error_message=exc.message,
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)
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raise HTTPException(
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status_code=exc.status_code or 502,
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detail=exc.message,
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) from exc
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logger.info(
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"audio.asr.success",
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filename=file.filename,
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format=fmt,
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language=language,
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text_length=len(result.text),
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text=result.text,
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)
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return TranscriptionResponse(text=result.text)
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