a32b0acb09
qwen3 backend: model list pointed at nonexistent HF repos (Qwen3-ASR-2B/8B don't exist), and inference went through the generic HF ASR pipeline with Whisper-only options (return_timestamps, task/language generate_kwargs) that Qwen3-ASR's chat-style architecture doesn't support. Switched to the real 0.6B/1.7B-hf checkpoints and drive them via processor.apply_transcription_request() + model.generate(). Also added an ffmpeg pre-conversion step since the model's feature extractor can't decode m4a via librosa. faster-whisper backend: speaker diarization was broken by two pyannote.audio API changes it hadn't caught up with (use_auth_token= renamed to token=, and pipeline() now returns a DiarizeOutput wrapper instead of an Annotation directly). Also pinned LD_LIBRARY_PATH for that worker so it picks up its own venv's cuDNN instead of the older one shadowing it via the container's global LD_LIBRARY_PATH, which crashed pyannote's GPU init. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>