Third approved port change: TelemetryRecorder.record_llm_call gains
stall_ms/stall_count (assembly gate derives from this signature).
Schema five edit points (both DDLs, both backfill decls, COLUMNS)
with INTEGER nullable columns appended last; telemetry_schema_sql
regenerates from the same constants untouched. Emitter forwards the
pair from retry._emit on the success branch only (cancelled hedge
loser rows stay NULL by construction); cache-hit and terminal rows
pass explicit None. Both **fields recorders pick the columns up with
zero signature change.
Twenty-five columns and not one of them answered "which tier was this?",
so the question the whole issue exists to settle - does a higher tier buy
anything - had no way to group its data.
The three emit entry points deliberately disagree, the way sampling
already does. A successful attempt records what the transport actually
sent: with EFFORT_FALLBACK=nearest a request for medium goes out as low,
and recomputing here would file the row under a tier that never left the
process. A failed attempt has no response to read, so it falls back to
the requested tier - which is exactly right for the tier errors that are
rejected before any HTTP happens, because the rejected tier is the
signal. Cache hits and terminal failures have no chosen source at all,
so a source-level tier is not a thing they could report.
emit_attempt now demands to be told whether the path reasons at all.
Embedding and OCR share the emitter but never send reasoning parameters;
without the flag a source that mistakenly carries ENABLE_THINKING would
hang a tier on a call that could not possibly have run at one.
The value lands as a plain str. StrEnum is a str subclass and asyncpg
promises nothing about encoding subclasses, and a telemetry write that
fails is only a warning - Postgres would just quietly lose the column.
NULL means nobody declared a tier, which is not the same statement as
'none', and the two must never be folded together.
This issue surfaced only because someone ran a slow suite that is
excluded by default and had not been run for eighteen days. As a column
it becomes a query: which model stopped being observable, and when.
The emitter unwraps the enum to a plain str at the single _record exit.
asyncpg makes no promise about encoding a str subclass, and a telemetry
write that fails is downgraded to one warning — it would not crash, it
would just quietly cost the Postgres path a column. Normalising at the
emitter follows what tenant_id, meta and sampling already do.
The column is appended last in COLUMNS and in both DDLs. An existing
table can only take ALTER at the end, so putting it anywhere else
forks the physical column order between a freshly built database and a
backfilled one.
Telemetry degradation used to be a single warning and a private boolean.
In a long-running process that is indistinguishable from telemetry working:
issue #15 was only found by hand-reconciling milestone log lines against
llm_calls rows, after 19 calls had silently gone unrecorded. The SQLite
side was worse — once init failed, every write returned without even a
log line.
Degradation now has one shared owner. TelemetryStatusTracker holds the
state machine (enter/recover/drop/should-retry), announces entry and
recovery once each, and repeats the drop count under a row-and-time
double threshold so a degraded backend neither floods the log nor goes
quiet. Both recorders hold one; both count the rows they drop.
For programmatic consumers, TelemetryStatus is a frozen snapshot exposed
as telemetry_status on all three clients, resolved through a single
isinstance check. It is a separate optional port rather than a member of
TelemetryRecorder: that protocol is @runtime_checkable, so adding an
attribute would make every implementation that only defines
record_llm_call stop satisfying it — downstream isinstance assertions
would break on upgrade. The existing assertion in test_ports.py is what
keeps that decision honest.
Failure criteria are deliberately untouched here: Postgres still treats a
pool failure as permanent, only now visibly. `_failed` and the tracker
therefore both carry the verdict for the span of this one change; the
cooldown rework collapses them into the tracker alone.
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.
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.
Includes config aggregation for multi-source env keys, from_env and
from_settings factories with explicit shared-backend injection,
gather_bounded, top-level exports, tightened import-linter layers with
the gate removed from the Makefile, and the finalized .env.example.
iomgaa