nvidia-cudnn-cu12/cublas-cu12 are namespace packages with no
__file__, so os.path.dirname() raised TypeError and the install cell
aborted. Locate libcublas.so/libcudnn.so under site-packages with
find and build LD_LIBRARY_PATH from those. Also add a CTranslate2
GPU check cell (ctranslate2.get_cuda_device_count) right after
install so GPU usability is confirmed before transcription.
Colab now ships CUDA 13.0 (driver 580); CTranslate2 wheels are CUDA 12
so GPU init fails with 'unsupported device cuda:0'. Install
nvidia-cublas-cu12/nvidia-cudnn-cu12 and set LD_LIBRARY_PATH in the
install cell; transcription cell reports failures cleanly.
API smoke: api_keys.json stores only digests (raw key shown once), so
the notebook now captures RAW_KEY at creation and uses it for upload
instead of reading the digest file (fixes 401).
Cell 1 now detects an existing /content/luke_scribe/.git and runs
git fetch + checkout feat/full-platform + pull --ff-only instead of
rm -rf + clone, so re-running the notebook updates instead of wiping
local changes.
Colab 'python3 -m venv' fails with ensurepip error (no .venv created,
so every subsequent cell hit 'command not found'). Switch to system pip
(Colab standard) and run the API server via nohup background with log
fallback diagnostics.
CPU-only dev env verified via mocks; the notebook runs the full real
pipeline on Colab Pro T4: clone → ffmpeg/venv install → detect (GPU
capability tier) → 127 unit/integration tests → sample TTS (KO+EN
tech terms) → real faster-whisper transcription → hotword/postprocess
→ API smoke → benchmark.
lukehemmin