Surface gen_ai.* model + token attributes onto the active span so Langfuse
can compute cost — without touching everalgo:
- UsageRecordingClient wraps the LLM client and records response.usage after
each chat(); get_llm_client composes it over the existing _LoggingLLMClient
only when observability is enabled (disabled default stays overhead-free).
- OpenAIEmbeddingProvider records its response.usage (input tokens) onto the
active span too.
Tokens land on the everos.extract / everos.reflect.consolidate generation
spans and the search embedding recall; no-op when tracing is off.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
md-first memory extraction framework for AI agents.
Markdown is the single source of truth; SQLite holds state and LanceDB
provides the rebuildable vector + BM25 + scalar index. The codebase follows
a single-direction DDD layering (entrypoints -> service -> memory -> infra,
with component / core / config cross-cutting) enforced by import-linter.
Engineering surface:
- Coding conventions in .claude/rules/ (path-scoped) and workflows in
.claude/skills/ (/commit, /new-branch, /pr).
- GitHub Actions CI runs make lint + test + integration; pre-commit mirrors
the gates locally (ruff, hygiene hooks, gitlint commit-msg).
- Commit messages follow Conventional Commits, enforced by gitlint.
- make lint also enforces datetime two-zone discipline and OpenAPI drift.