- Runs can now do any mix of: tags & descriptions, clearer names, and
collection suggestions. A run without tags doesn't mark models as tagged.
- Collection ideas reuse your collections and earlier ideas where they fit and
wait on the AI page, grouped by name, until you create/add or dismiss them.
Dismissed ideas aren't suggested for that model again; spelling variants
group together under the capitalised spelling.
- A reply that isn't the JSON asked for is asked again once; both requests
count towards the run's tokens and cost.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
A run option asks the AI for a clearer name only when the current one is messy
(file-name leftovers, typos, site boilerplate). The previous name is kept, the
run feed shows what was renamed, and the model page offers Undo. Giving a model
a name yourself clears the undo.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- 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>
