config.loader.load_config() intentionally returns the raw config with ${VAR}
references intact — env interpolation is a separate, explicit step
(resolve_config_env_vars) so that settings read/edit/save paths never
materialize secrets to disk or to the UI.
The transcription config path does not apply that step: both
channels/base.py (channel voice notes) and webui/transcription_ws.py (WebUI
recording) build their effective config via
resolve_transcription_config(load_config()). As a result a configured
api_key of "${GROQ_API_KEY}" (the documented way to reference secrets) is
passed to the provider verbatim, which fails with 401 Invalid API Key. No
amount of rotating the real key helps, because the literal placeholder
string is what gets sent.
Resolve the reference at the single choke point both callers share —
_resolve_transcription_api_key / _resolve_transcription_api_base — using a
new lenient loader.resolve_env_refs() helper (unset var -> empty string, so
a missing variable degrades to "not configured" rather than raising or
leaking). This fixes both entry points at once and cannot drift the way a
per-call-site fix does. Resolving inside load_config() was rejected: the
~20 settings-UI callers depend on it returning raw ${VAR} placeholders.
Literal keys are unaffected; the settings API only reads the derived
`configured` flag (never the key), which now reflects the resolved value.
Claude-Session: https://claude.ai/code/session_01Q3HuVaJAAQJA3kgVQVJ2Zt
- 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
Add AssemblyAI as a third transcription provider option alongside
OpenAI and Groq. AssemblyAI offers better accuracy for certain
audio types (distant voices, noisy environments) and serves as a
reliable fallback when other providers struggle.
Changes:
- Add AssemblyAITranscriptionProvider class in providers/transcription.py
- Add 'assemblyai' option in base channel's transcribe_audio()
- Per-channel configuration via transcriptionProvider in config
Usage:
Set transcriptionProvider: 'assemblyai' and provide an AssemblyAI
API key via transcriptionApiKey in the channel config.
Add support for Xiaomi MiMo ASR as a third transcription backend alongside
Groq and OpenAI Whisper. Xiaomi ASR uses the /v1/chat/completions endpoint
with base64-encoded audio input, rather than the standard Whisper multipart
upload format.
Co-Authored-By:连 <lian@tangping.homes>
Add a `transcriptionModel` channel setting and an OpenRouter transcription
backend so voice messages can be transcribed through OpenRouter's
speech-to-text endpoint (e.g. nvidia/parakeet-tdt-0.6b-v3, openai/whisper-1),
alongside the existing Groq/OpenAI Whisper providers.
- schema: add channels.transcriptionModel (None = provider default)
- providers/transcription: extract a shared POST/retry skeleton; add a
JSON+base64 OpenRouterTranscriptionProvider; make the STT model a
constructor param on all providers instead of hardcoding it
- channels: route transcriptionProvider="openrouter" and thread the model
through the manager to each channel
- docs + tests
Only dedicated STT models work on OpenRouter's transcription endpoint;
chat LLMs (e.g. google/gemini-3.5-flash) are rejected there.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Correct api_key type hint to str | None in _post_transcription_with_retry
- Remove unreachable final return ""
- Fix test_openai_missing_api_key_short_circuits to actually test
missing-key path (use audio_file fixture so file exists)
- Fix PermissionError patch for Windows (patch class method instead
of instance attribute)
A single transient failure between the agent and an OpenAI/Groq Whisper
endpoint currently vanishes as `return ""` in transcribe(). The voice
message arrives as the empty string and there is no way to tell real
silence apart from a failed upload. A malformed but successful response
body is even worse: the JSON-decode error escapes the helper unhandled.
Add a shared `_post_transcription_with_retry` used by both providers.
Retry behaviour:
- exponential backoff 1s -> 2s -> 4s, up to 3 retries (4 attempts)
- retryable HTTP statuses: 408, 429, 500, 502, 503, 504
- retryable exceptions: TimeoutException, ConnectError, ReadError,
WriteError, RemoteProtocolError
Non-transient failures short-circuit to "" on the first attempt --
retrying a misconfigured key or a broken upload only burns rate-limit
quota. Branches that short-circuit:
- missing API key, missing audio file
- file-read errors (PermissionError, OSError) on the audio path,
preserving the nightly contract for direct provider callers
- HTTP auth/4xx body issues via raise_for_status()
- response.json() parse failures
- non-dict JSON payloads
Sharing one helper means OpenAI and Groq cannot drift apart silently.
Thread `language` through the helper. The multipart files dict is rebuilt
inside the per-attempt loop, so when a caller sets self.language the
`language` field is sent on every attempt -- not just the first.
Tests cover:
- every advertised retryable status and exception, parameterized
- language present on attempts 1 and 2 of a 503->200 sequence
- language absent when unset; present when set (both providers)
- malformed JSON body and non-dict JSON body short-circuit to ""
- PermissionError on file read short-circuits with no HTTP attempt
- max-attempts give-up, exponential-backoff schedule, auth no-retry,
missing-key / missing-file short-circuit
Test stub fix: the _StubResponse in tests/channels/test_channel_plugins.py
declared no status_code, which the new helper reads for retry classification.
Set status_code = 200 so the stub advertises the successful response that
those tests already simulate. Also moved the two transcription-provider
imports to the top of that file (previously placed mid-file) so the file
is ruff-clean (E402).
Xubin Ren
Ben LenartsandXubin Ren
moranandXubin Ren
comadrejaandXubin Ren
04cbandXubin Ren
chengyongru
mohamed-elkholy95andchengyongru