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64bfa5725f |
feat(telemetry): a read surface over retrieval_logs — the tuning loop had no read half (#2975)
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`retrieval_logs` was write-only. `record_retrieval` inserted rows and nothing in the tree ever selected from them: the only `select()` over RetrievalLog lived in a test. So #1038's gate — "build the reranker once telemetry shows precision is the bottleneck" — was unsatisfiable by construction, and the one real tuning decision on record (the 0.68 write-path threshold, #2223) had to be reached by hand-probing the live instance with eight payloads. This adds the half that was missing. `retrieval_summary(user_id, days=30)` returns two aggregates side by side, each read from the table built for it — NOT a join. NoteUsageEvent's docstring is explicit that the two are complements ("RetrievalLog tunes the threshold, this tunes the corpus") and that RetrievalLog's JSONB `result_ids` cannot be indexed at the per-note grain, so correlating through it would be both slower and less honest than reading each source directly. That corrects the approach sketched on the task. - `sources`, per surface: calls, zero_result_calls, cleared_threshold (how often the best hit beat the threshold in force for THAT call), the top_score spread as p10/p50/p90/min/max, avg_result_count, p90 duration. Zero-result calls are counted apart from low-scoring ones — they are a different failure and averaging them together would hide both. - `usage`, from note_usage_events: ranked surfacings, ambient surfacings, and pulls split into `pulled_by_agent` / `pulled_by_human`. That split is not decoration. NoteUsageEvent's own comment says the mcp_/rest_ prefix is load-bearing and names #1038 while saying so: "is this dead weight?" is answered by any pull, "was that injected line useful?" only by an agent pull. `pull_through` exists to answer the second, so it counts agent pulls over ranked surfacings; both halves ship so the first stays answerable. Two things the code made me get right rather than guess: - Distinct-note counts get their own queries. `count(distinct note_id)` per (event, source) group cannot be summed across groups — a note surfaced by two sources is one distinct note and would be counted twice. A wrong number labelled "distinct" is worse than no number. - No CASE in the GROUP BY. #2663 is the bug where a second case() rendered its own expanding bind names, Postgres rejected the query, a broad except swallowed it, and every counter read zero in production while mocked tests passed. Grouping on raw `source` and classifying in Python cannot fail that way. For the same reason the readout distinguishes `read_failed` from an empty window, and its tests are integration against real Postgres — percentile_cont ... WITHIN GROUP only proves it parses against a database. Exposed as the `retrieval_telemetry` MCP tool, added to `_READ_ONLY_TOOLS`: it mutates nothing, but its name carries no read prefix, so the completeness test cannot derive it and it would otherwise have failed closed for read-only keys in silence — the same reason `enter_project` is spelled out there. Docs updated to name both exceptions rather than leave the rule looking derivable. Scoped to the caller's own telemetry: a retrieval log records what one user's agent asked for, query text included, and is not a shared record kind — the owner filter is the whole access rule, not a shortcut past access.py. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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bbee0d0db1 |
refactor(tests): one definition each for the copied fixtures and fakes (#2825, milestone 296 area 1)
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The shape ledger showed the same test scaffolding defined over and over: _bind_user x12 (byte-identical), _dispose_engine x10 in three wordings, _no_supersession x3, _make_mock_session x7 in three subsets, a get-or-create User helper x2 (+3 inlined), and fifteen hand-rolled MagicMock note factories each re-explaining the same "an auto-MagicMock attribute is truthy" hazard (note 2109). Now: conftest.py carries _bind_user / _dispose_engine / _no_supersession as opt-in fixtures (pytestmark = usefixtures(...) per module, so unit tests pay nothing), and tests/helpers.py carries make_mock_session(), ensure_user() and fake_note(**attrs) — the hazard documented once, real values on every attribute the product reads. Call sites were rewritten by AST so titles with dashes and commas survived; the three SimpleNamespace _note stand-ins that only feed a single function stay local. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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807f478cac |
feat(search): retrieval telemetry — log every semantic retrieval
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Add retrieval_logs (migration 0068) + services/retrieval_telemetry with a fire-and-forget record_retrieval(), wired into the MCP search tool (source=mcp_search) and the REST search route (source=rest_search). Captures query, effective params, and the per-result score distribution so KB-injection thresholds can be tuned from data rather than guessed. Scribe: project 2, milestone 93, task 1032. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E |