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75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
"""Voice services — text-to-speech and speech-to-text.
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Public facade used by the API router and the config test runner. Config is
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resolved from the model catalog (``services.tts`` / ``services.stt``) exactly
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like embedding/LLM, so voice providers are configured through the same
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Settings catalog UI.
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"""
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from __future__ import annotations
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from typing import Any
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from deeptutor.services.voice.adapters import get_stt_adapter, get_tts_adapter
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from deeptutor.services.voice.base import VoiceProviderError, strip_markdown_for_speech
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from deeptutor.services.voice.config import STTConfig, TTSConfig
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async def synthesize_speech(
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text: str,
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*,
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catalog: dict[str, Any] | None = None,
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voice: str | None = None,
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response_format: str | None = None,
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strip_markdown: bool = True,
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) -> tuple[bytes, str]:
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"""Synthesize ``text`` using the active TTS catalog selection.
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Returns ``(audio_bytes, content_type)``. ``voice`` / ``response_format``
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override the catalog defaults for this call.
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"""
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from deeptutor.services.config.provider_runtime import resolve_tts_runtime_config
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config = resolve_tts_runtime_config(catalog=catalog)
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if voice:
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config.voice = voice
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if response_format:
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config.response_format = response_format
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prepared = (
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strip_markdown_for_speech(text, max_chars=config.max_input_chars)
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if strip_markdown
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else text.strip()
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)
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if not prepared:
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raise VoiceProviderError("Nothing to speak after cleaning the text.")
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adapter = get_tts_adapter(config.adapter)
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return await adapter.synthesize(prepared, config)
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async def transcribe_audio(
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audio: bytes,
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*,
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catalog: dict[str, Any] | None = None,
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filename: str = "audio.webm",
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content_type: str = "application/octet-stream",
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language: str | None = None,
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) -> str:
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"""Transcribe ``audio`` using the active STT catalog selection."""
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from deeptutor.services.config.provider_runtime import resolve_stt_runtime_config
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config = resolve_stt_runtime_config(catalog=catalog)
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if language:
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config.language = language
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adapter = get_stt_adapter(config.adapter)
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return await adapter.transcribe(audio, config, filename=filename, content_type=content_type)
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__all__ = [
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"VoiceProviderError",
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"TTSConfig",
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"STTConfig",
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"synthesize_speech",
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"transcribe_audio",
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"strip_markdown_for_speech",
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]
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