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feat(learn): metered embeddings and the cache (decision-engine 6.2)

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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
This commit is contained in:
Marius Ciepluch
2026-10-01 09:56:52 +02:00
co-authored by Claude Opus 5.5
parent 7b81c9ac4e
commit 98fa4ec8cd
11 changed files with 498 additions and 11 deletions
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.kiro/specs/learned-decision-engine/tasks.md
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@@ -46,7 +46,7 @@ a model or embedding call.
10% of a source has no excerpt); `example` added to `KINDS`; `put_blob`/`get_blob` on both backends.
- Tests: `test_learn_excerpt.py`, example-builder refusals, blob round trip on FileStore (MinIO gated).
- _Requirements: 3.2, 3.6, 7.2_
- [ ] 6.2 Metered embeddings and the cache
- [x] 6.2 Metered embeddings and the cache
- `plane/models/openrouter-embedding.yaml` (`input_per_m: 0.02`), `MeteredEmbeddingClient` in
`plane/budget.py`, usage kept by `parse_embedding_response`; cache `embeddings/<model>/<excerpt_sha>.json`;
`ousast learn memory embed`; scripted-client tests.