PG requires a partitioned table's unique constraints to include the
partition key, so issue #12's RANGE partitioning on created_at forces
the primary key to (call_id, created_at). The old
`ON CONFLICT (call_id) DO NOTHING` then matches no constraint and PG
rejects every row with
there is no unique or exclusion constraint matching the
ON CONFLICT specification
which the recorder swallows as a per-row warning: telemetry would go
silently dark under a partitioned deployment. The target-free form is
valid on both table shapes and is literally equivalent on a plain table
(the primary key is its only unique constraint). SQLite's
`INSERT OR IGNORE` already carries no target and is untouched.
Integration coverage on the real PG instance, both inside self-created
temp schemas: a plain table still keeps one row per call_id, and a
table partitioned by created_at now accepts writes and reads them back.
The second case was red before this change with the error above.
DDL, column order and backfill statements lived twice, once in each
recorder. A public telemetry_schema_sql() would have made three copies,
and the drift shows up downstream as "I ran the printed SQL and the
library still reports a missing column".
Move both DDLs, both backfill lists and the 24 INSERT fields into
telemetry/schema.py verbatim; the recorders now import them and build
_INSERT through insert_sql(backend, COLUMNS) at import time. The
generated statements are byte-identical to the previous constants, so
runtime behaviour is unchanged (the postgres conflict target stays
bound to call_id for now).
insert_sql() validates its columns against COLUMNS: from the next task
on those names come from database probing, not from a constant, so the
subset check is the gate on the only injection surface. The new
telemetry_schema_sql() prints a paste-ready migration script; its
postgres backfill deliberately uses ADD COLUMN IF NOT EXISTS while the
library's own statements do not, because that form takes an ACCESS
EXCLUSIVE lock even when the column exists. Both variants are derived
from one declaration list so their column sets cannot drift.
The cache-key test only asserted a hit, so a key degraded to a constant
would still pass it. Adding a namespace control group that must miss
proves the key still distinguishes inputs; verified by degrading
build_cache_key to a constant and watching the case go red.
The allow_nan=False branch had no test at all. A ChatRequest built with
a nan meta value (bypassing the entry validation, i.e. a future entry
point that forgets to validate) must drop the row and not raise;
verified red by removing allow_nan=False.
Also restore the read-only file permissions in a finally block, so a
failing assertion does not get masked by a PermissionError from tmp_path
cleanup; rename the warnings fixture to captured_warnings so it stops
shadowing the stdlib module; and drop a downstream business term from a
fixture value (zero-business-assumption rule).
Both telemetry backends gain tenant_id and meta at the end of the
column list, and TelemetryEmitter fills them from the request. The two
halves ship together because the emitter is the only caller of
record_llm_call: adding the columns without filling them leaves every
row short of two keys, and the backends read those keys outside their
try block, so the KeyError degrades to a warning and the whole table
stops filling.
The columns are appended, never inserted. An old table can only gain
columns through ALTER, which puts them last; a new table built from the
DDL would put them wherever the DDL says. Anywhere but the end and the
two paths produce different physical column orders, while the INSERT
uses positional placeholders.
The two backends spell the default differently for different reasons.
SQLite refuses a NOT NULL column without a non-NULL constant default
outright, so the default is what makes the backfill legal at all. On
Postgres a non-volatile constant default is what keeps the ALTER from
rewriting the table, and NOT NULL DEFAULT '' is what keeps old rows out
of the black hole a NULL tenant_id falls into under an RLS policy.
Normalisation happens in the emitter, not the recorder, matching how
canonical_sampling_json already settles the sampling column: None
becomes the empty string, an empty mapping becomes the literal '{}'.
Keys are sorted so one set of dimensions serialises identically on
every row, and allow_nan=False is a second gate behind the entry
validation -- json.dumps would otherwise write a bare NaN, which JSONB
rejects, and the failed insert would be swallowed as a warning.
All three emit entry points read the request. Cache hits read it too,
rather than the replayed response: the dimensions answer who made this
call, not who made the one whose result is being replayed.
PostgreSQL checks the schema CREATE privilege before the IF NOT EXISTS
existence test, so an account with only table-level INSERT was denied on
CREATE TABLE IF NOT EXISTS even though the table was right there and
writable. The denial set _failed and the whole recorder went no-op for
the process lifetime, silently: 150+ calls downstream lost their latency,
token and cost rows with nothing but one warning to show for it.
The probe is the direct fix. The larger fix is the criterion: structural
degradation now means "provably cannot write" (pool creation failed, or
the table is absent and cannot be created), not "something threw during
init" -- a probe or acquire failure just skips the row and retries on the
next call.
SQLite stays as it is on purpose. Measured: it short-circuits the
statement at parse time, so it passes even under another connection's
EXCLUSIVE lock or on a read-only file. A probe there would buy nothing;
the docstring now says so to keep symmetry-minded future edits away.
Reasoning tokens are already counted inside completion_tokens, so the
cost total was never wrong -- what was missing is the attribution: how
much of a call was spent thinking rather than answering.
LLMResponse and TransportResult each gain a trailing reasoning_tokens
field, and the telemetry port grows from 21 to 22 columns with the new
column appended in both backends so fresh and migrated schemas keep the
same physical order.
None means this particular call did not report the field, not that the
source never reports it: a relay that falls back to a local tokenizer
replaces the whole usage object and drops completion_tokens_details.
Downstream checks must therefore read "in (None, 0)"; no provider was
observed reporting a literal zero.
The test passed overlay and sampling as separate objects while production
aliases them, so an in-place mutation slipped through it. Also syncs the
telemetry schema page and adds the missing postgres round-trip assertion.
The fixture used to DROP the shared llm_calls table on every run, wiping
concurrent migration-batch telemetry (and its own count assertion was
polluted in return). Assertions now filter by a per-run call_id prefix
and teardown deletes only its own rows.
iomgaa