Files
Open_Ultra_SAST/plane
Marius CiepluchandClaude Opus 5.5 98fa4ec8cd feat(learn): metered embeddings and the cache (decision-engine 6.2)
plane/models/openrouter-embedding.yaml: openai/text-embedding-3-small via
OpenRouter (embeddings only), input_per_m 0.02, cache/output 0, egress
openrouter.ai; `openrouter` joins the provider extensions.

plane/budget.py MeteredEmbeddingClient: prompt_tokens priced from the
Model manifest, usd/calls ceilings stop the next call, a priced call that
reports no tokens raises UnmeteredUsage (a silent zero is an instrument
failure). OpenRouterEmbeddingClient keeps one usage row per call
(parse_embedding_payload); its api key is out of repr.

learn/embeddings.py + `ousast learn memory embed`: excerpts embedded in
batches into embeddings/<model-slug>/<excerpt_sha>.json (float32 base64),
cached by content hash so a rerun makes no call; the declared dimension is
checked; --dry-run estimates tokens and cost without a call; a paid run
needs --budget-usd and exits 3 (unfinished) at its ceiling. Not run against
the provider: the store embedding waits for its budget go-ahead.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
2026-10-01 09:56:52 +02:00
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