Mistral models reject chat_template_kwargs, causing 400 errors. Make
thinking params (chat_template_kwargs, reasoning_budget) opt-in via
NIM_ENABLE_THINKING env var (default false) so only models that need it
(kimi, nemotron) receive them.
## Summary
Added NVIDIA NIM as a second transcription option ( alongside local
Whisper). This lets you transcribe voice notes using NVIDIA's cloud API
instead of running Whisper locally.
## What changed
- **Transcription**: Now supports the two backends
- Local Whisper: Free, runs on your GPU/CPU (existing)
- NVIDIA NIM: Cloud API via Riva gRPC (new)
- **Supported models**: 8 NVIDIA NIM models added (Parakeet variants for
different languages, Whisper Large V3)
---------
Co-authored-by: Alishahryar1 <alishahryar2@gmail.com>
- `max_concurrency` is now always an `int` (default 5) — `None`/unlimited
is no longer a valid state; omitting the env var uses the default
- `GlobalRateLimiter`: semaphore is always created; `concurrency_slot()`
no longer has None guards; log message always includes concurrency
- `ProviderConfig.max_concurrency`: `int = 5` (was `int | None = None`)
- `Settings.provider_max_concurrency`: `int = Field(default=5, ...)` —
setting env var to an invalid value (e.g. empty string) raises
- `.env.example`: uncommented `PROVIDER_MAX_CONCURRENCY=5`
- README: updated config table default from `—` to `5`
- Tests: removed `test_concurrency_slot_noop_when_not_configured`;
updated mock settings to use `5` instead of `None`
https://claude.ai/code/session_014mrF1WMNgmNjtPBuoQHsbg
The flag was unnecessary: running claude-pick implies wanting the picker.
Remove MODEL_PICKER from claude-pick and README, restore .env.example
to upstream.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add `claude-pick` bash script: reads PROVIDER_TYPE from .env, fetches
available models (NVIDIA NIM, OpenRouter, LM Studio), and launches Claude
with the selected model via fzf. Falls back to direct launch when
MODEL_PICKER=false.
- Add MODEL_PICKER=false flag to .env.example.
- Document setup in README (fzf install, alias, fixed-model alias pattern).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated transcription logic to utilize Hugging Face's Whisper models instead of faster-whisper.
- Introduced new model mapping and pipeline loading functions.
- Adjusted tests to reflect changes in the transcription process.
- Updated documentation in README, .env.example, and settings to align with the new implementation.
- Ensured compatibility with CUDA 13 and removed unnecessary dependencies.
- Validate whisper_device in Settings and _get_local_model
- Reject 'auto' with clear ValueError/ValidationError
- Update docs in config, .env.example, README
- Add tests for invalid device and valid cpu/cuda
Co-authored-by: Ali Khokhar <alishahryar2@gmail.com>
- Remove _cuda_failed_models and inference-time CPU fallback
- auto: try CUDA only, fail fast on RuntimeError (no CPU fallback)
- cpu/cuda: use device directly, fail fast on errors
- Update docs in config, .env.example, README
Co-authored-by: Ali Khokhar <alishahryar2@gmail.com>
- Introduced voice note handling for Discord and Telegram platforms.
- Added configuration options for voice note functionality in settings.py and .env.example.
- Updated README to include voice note instructions and configuration details.
- Implemented audio attachment processing and transcription using faster-whisper.
- Enabled voice note support through message handlers in both platforms.
