agent-zero/plugins/_whisper_stt/api/status.py
Alessandro 675afa8dee
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Refactor speech stack into built-in Kokoro TTS and Whisper STT plugins
Split the legacy core speech stack into two built-in, independently toggleable plugins: `_kokoro_tts` for TTS and `_whisper_stt` for STT.

This refactor keeps dependency installation and bootstrap concerns in Docker/bootstrap/preload, while moving speech-specific tooling, APIs, prompts, UI, and runtime behavior into the plugins. Core now exposes engine-agnostic `tts-service` and `stt-service` brokers, with browser-native TTS preserved as the fallback when Kokoro is disabled.

Included in this change:
- add built-in `_kokoro_tts` plugin with plugin-owned synth API, config, status UI, and provider registration
- add built-in `_whisper_stt` plugin with plugin-owned transcribe API, mic runtime, device UI, prompt injection, and provider registration
- remove legacy core speech APIs/helpers/settings/UI and delete unused `webui/js/speech_browser.js`
- replace the old hardcoded speech settings section with a generic voice surface backed by plugin extensions
- update preload/docs/tests to match the new plugin-owned speech architecture

Behavioral intent:
- both plugins are built-in but not `always_enabled`
- users can now hot-switch TTS and STT independently
- browser TTS remains available when `_kokoro_tts` is off
- Whisper mic UI only appears when `_whisper_stt` is enabled
2026-05-21 05:41:59 +02:00

31 lines
1,006 B
Python

import importlib.metadata
from helpers.api import ApiHandler, Request, Response
from plugins._whisper_stt.helpers import migration, runtime
class Status(ApiHandler):
async def process(self, input: dict, request: Request) -> dict | Response:
migration.ensure_config_seeded()
package_version = ""
package_error = ""
try:
package_version = importlib.metadata.version("openai-whisper")
except Exception as e:
package_error = str(e)
return {
"plugin": "_whisper_stt",
"enabled": runtime.is_globally_enabled(),
"config": runtime.get_config(),
"model": {
"ready": await runtime.is_downloaded(),
"loading": await runtime.is_downloading(),
"loaded_model": runtime.get_loaded_model_name(),
},
"package": {
"version": package_version,
"error": package_error,
},
}