0f49fe8c1a
- AI tagging through any OpenAI-compatible API: DeepSeek by default, or OpenRouter, OpenAI, or a local server (Ollama, LM Studio). Settings → AI with presets, prices and "Save & test connection"; the key never leaves the server except to the provider. - Runs over untagged models, all models, or one model from its page: live progress, tokens and cost, stop/resume (retrying failures), an optional spending limit, and paused rather than resumed after a restart. Adapts to models without JSON mode or image input; stops on a rejected key or no credit. Tags are only added; descriptions filled only where empty unless asked. - Search by meaning: local bge-small-en-v1.5 embeddings (transformers.js), indexed in the background whenever a model's text changes; Words/Meaning switch on the search box. Stored as REAL[] in Postgres, no pgvector needed. - Automatic tags: strict whole-word rules (part types, mechanisms, materials, techniques) over names, file names and archive contents, plus your own word -> tag rules; on/off (optionally removing its tags) and re-apply. - Tags remember where they came from (user / rule / ai); edits keep that, rule and AI passes never touch your own tags, and the model page marks them. - Docker: ships the embedding model and only Linux onnxruntime binaries. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
13 lines
112 B
Text
13 lines
112 B
Text
node_modules/
|
|
data/
|
|
uploads/
|
|
thumbnails/
|
|
*.log
|
|
.DS_Store
|
|
|
|
.env
|
|
glb/
|
|
tools/venv/
|
|
__pycache__/
|
|
extracted/
|
|
models/
|