- New whisper_live/diarization.py: SpeakerDiarizer with online clustering
- Uses pyannote.audio speaker embeddings (optional dependency)
- Cosine similarity threshold for speaker matching (default 0.55)
- Running average embedding update for speaker stability
- Configurable max_speakers limit (default 10)
- Client options: enable_diarization, max_speakers
- Segments include 'speaker' field when diarization is active
- Graceful fallback: logs warning if pyannote not installed
- Added 12 unit tests (mock-based, no GPU required)
- New whisper_live/metrics.py with Counter, Gauge, Histogram metrics
- Track connections (opened/closed/rejected), transcription latency,
audio processed, segments emitted, REST requests, and errors
- All metric helpers are no-ops when prometheus_client not installed
- --metrics_port CLI flag to expose /metrics endpoint (0 = disabled)
- Metrics integrated into server.py, base.py at key instrumentation points
- 17 new tests in tests/test_metrics.py (178 total passing)
- max_clients must be >= 1
- max_connection_time must be > 0
- batch_max_size must be >= 1 (when batch enabled)
- batch_window_ms must be >= 0 (when batch enabled)
- Added 5 new tests for parameter validation
- Add MAX_TRANSCRIPT_LENGTH (500) and MAX_TRANSLATION_QUEUE_SIZE (100)
class constants to ServeClientBase
- Trim transcript and text lists after each update_segments() call
- Create translation queue with maxsize to prevent unbounded growth
- Added tests for _trim_transcript()
- All ClientManager methods (add_client, get_client, remove_client,
get_wait_time, is_server_full, is_client_timeout) now protected by
a threading.Lock
- cleanup() called outside the lock to avoid holding it during I/O
- is_server_full() computes wait time inline under lock instead of
calling get_wait_time() to avoid nested lock acquisition
- Added concurrent thread safety tests for add/remove and get operations
Previously, the server only accepted local file paths for custom Faster Whisper
models. This change allows passing HuggingFace repo IDs which are automatically
downloaded and converted to CTranslate2 format by the backend if not already in
CTranslate2 format.
Signed-off-by: makaveli10 <vineet.suryan@collabora.com>
Translate from any language to any language with alirezamsh/small100
running in a thread and reading from a queue shared with transcription thread.
Signed-off-by: makaveli10 <vineet.suryan@collabora.com>