moran
9ed638ad70
- Register SiliconFlow in transcription registry with default model FunAudioLLM/SenseVoiceSmall and alias 'silicon' - Reuse existing OpenAITranscriptionProvider adapter (Whisper-compatible) - Add generic key/base resolution: fallback to registry env_key and default_api_base when provider config is absent - Add tests for registry entry, alias, adapter, default model, and config resolution with env var fallback
102 lines
3.3 KiB
Python
102 lines
3.3 KiB
Python
"""Registry for speech-to-text providers.
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Provider-specific HTTP adapters live in ``nanobot.providers.transcription``.
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This module is the app-level source of truth for provider names, aliases,
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default models, and adapter class paths.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from importlib import import_module
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from pathlib import Path
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from typing import Any, Protocol
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class TranscriptionProviderAdapter(Protocol):
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"""Runtime protocol implemented by provider-specific transcription adapters."""
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def __init__(
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self,
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api_key: str | None = None,
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api_base: str | None = None,
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language: str | None = None,
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model: str | None = None,
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) -> None: ...
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async def transcribe(self, file_path: str | Path) -> str: ...
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@dataclass(frozen=True)
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class TranscriptionProviderSpec:
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name: str
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default_model: str
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adapter: str
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aliases: tuple[str, ...] = ()
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def load_adapter(self) -> type[TranscriptionProviderAdapter]:
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module_name, _, class_name = self.adapter.partition(":")
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if not module_name or not class_name:
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raise RuntimeError(f"Invalid transcription adapter path: {self.adapter}")
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adapter = getattr(import_module(module_name), class_name)
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return adapter
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TRANSCRIPTION_PROVIDERS: tuple[TranscriptionProviderSpec, ...] = (
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TranscriptionProviderSpec(
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name="groq",
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default_model="whisper-large-v3",
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adapter="nanobot.providers.transcription:GroqTranscriptionProvider",
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),
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TranscriptionProviderSpec(
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name="openai",
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default_model="whisper-1",
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adapter="nanobot.providers.transcription:OpenAITranscriptionProvider",
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),
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TranscriptionProviderSpec(
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name="openrouter",
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default_model="openai/whisper-1",
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adapter="nanobot.providers.transcription:OpenRouterTranscriptionProvider",
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),
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TranscriptionProviderSpec(
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name="xiaomi_mimo",
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default_model="mimo-v2.5-asr",
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adapter="nanobot.providers.transcription:XiaomiMiMoTranscriptionProvider",
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aliases=("mimo", "xiaomi"),
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),
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TranscriptionProviderSpec(
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name="stepfun",
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default_model="stepaudio-2.5-asr",
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adapter="nanobot.providers.transcription:StepFunTranscriptionProvider",
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),
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TranscriptionProviderSpec(
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name="assemblyai",
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default_model="universal-3-pro,universal-2",
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adapter="nanobot.providers.transcription:AssemblyAITranscriptionProvider",
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),
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TranscriptionProviderSpec(
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name="siliconflow",
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default_model="FunAudioLLM/SenseVoiceSmall",
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adapter="nanobot.providers.transcription:OpenAITranscriptionProvider",
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aliases=("silicon",),
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),
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)
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_BY_NAME = {spec.name: spec for spec in TRANSCRIPTION_PROVIDERS}
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_BY_ALIAS = {alias: spec for spec in TRANSCRIPTION_PROVIDERS for alias in spec.aliases}
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def transcription_provider_names() -> tuple[str, ...]:
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return tuple(spec.name for spec in TRANSCRIPTION_PROVIDERS)
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def get_transcription_provider(name: str) -> TranscriptionProviderSpec | None:
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return _BY_NAME.get(name)
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def resolve_transcription_provider(value: Any) -> TranscriptionProviderSpec | None:
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if not isinstance(value, str):
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return None
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name = value.strip().lower()
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return _BY_NAME.get(name) or _BY_ALIAS.get(name)
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