Files
mule-image/mulita.yml
dtoro 574d71371f refactor: strip AI pipeline to binary photo/other classifier
Drops face recognition, OCR, object detection, and semantic embeddings.
The sole remaining vision task is a CLIP-based binary classifier
(photography vs other); photos in "other" get needs_review=true so
screenshots, documents, memes and scans can be triaged from a new
filter pill in the UI.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 22:27:17 +02:00

35 lines
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YAML

# Mulita configuration file
#
# Source roots and discard handling are owned by the database — manage them
# from the UI (left sidebar → "+ Add Source Folder") or via the API. Only
# operational tuning lives here.
thumbnails:
small: 240 # px, longest edge
medium: 640
large: 1280
quality: 85 # JPEG/WebP quality
format: webp # output format for thumbs
scanner:
watch: true # use watchfiles inotify
initial_scan_on_start: true
batch_size: 100
concurrent_workers: 4
performance:
max_concurrent_thumbnails: 10
cache_ttl: 3600
db_pool_size: 20
db_pool_recycle: 3600
# Vision pipeline — single binary classifier (photography vs other).
# Photos landing in 'other' get needs_review=true.
vision:
enabled: true
backend: onnx
models_dir: /data/models
classifier:
min_confidence: 0.3
worker_concurrency: 2