* test(integration): give chaos and timing tests a harness API and gate raw signals
Chaos tests killed and suspended proxy workers with raw os.kill and psutil
calls and bounded elapsed time with fixed literals, so they raced the uvicorn
worker healthcheck and failed on slow CI boxes
OwnedProxy now offers kill_worker and replacing_worker, which return only once
a replacement answers readiness with its own pid, and suspended, which is
refused unless the proxy was launched with a lenient worker healthcheck.
timing.py bounds durations against a measured control or the injected delay.
run.py measures the proxy import time once and derives readiness deadlines and
the per-test timeout from it, writing boot-calibration.json
check_test_quality.py adds TQ010 (raw process signals) and TQ011 (elapsed time
asserted under a numeric literal) for tests/integration outside _support, and
every call site is migrated so both report zero with no suppressions
* test(integration): steer the assistants wire burst onto both workers
The mixed-status burst assumed the OS would spread 48 connections across both workers and failed when one worker took them all. Each half is now sent while the other worker is suspended, and the test asserts an exact 24 and 24 split
* test(integration): restore product-enforced timing bounds lost in the migration
Some TQ011 migrations dropped or loosened a bound whose time is the behaviour
under test. The websocket session cap only kept its floor, so a cap closing at
300 s would have passed, and several timeouts were bounded by the injected stall
instead of the configured product value
assert_enforced_within bounds an elapsed time by the configured value plus
explicit slack, with an optional floor. The websocket cap, the MCP validation
timeout, the guardrail litellm_params timeout, the prisma command timeouts, the
baseline projection lock timeout and the key metadata statement timeout use it.
The device code refusal keeps its 15 s margin, and the langfuse retried prompt
fetch is now bounded by a cold fetch of a steady prompt as well as by the
ignored retry-after
* fix(tests): wait for the supervisor to reap killed workers and fix real-kill migrations
The lenient worker healthcheck was the whole case budget, so uvicorn's supervisor sat
in a ping on the killed worker for up to that long before respawning it. It now uses
the graceful stop budget, and a worker kill returns only after the victim is reaped,
so pooled connections no longer race the dead worker's socket.
Several tests on main picked the multiprocessing resource tracker as their victim and
never killed a worker. Now that they kill a real one, presidio counts streams cut by
the death, delete_model waits for the config reload that removes a deleted model from
a replacement worker, and the wedged coordination Redis test kills before the wedge
and waits for every parked publish to fail before resuming Redis.
The redis cluster test imports the harness through the tests package so it collects
in the unit job, and the per-model fallback rig exposes the owned proxy it now needs.
* test(observability): only require S3 deliveries the killed worker could not have buffered
A real SIGKILL drops the victim's unflushed batch, so requests it already answered can't be expected to land. The test now requires every request served after the replacement to land, some of the surviving worker's burst share to land, and nothing unsent to land
---------
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
* fix(databricks): call the ai_decide AI Function route for decisions and the auto-router
Databricks serves ai_decide at POST <host>/api/2.0/ai-functions/ai-decide, not
on a serving endpoint's /invocations route. The decisions provider and the
auto-router classifier now accept only the ai_decide model, post to that route
without a model field, unwrap the response envelope, and map a noul answer's
probability to the System One noul field.
* test(databricks): bound the megabyte model name test by scaling, not wall time
* test(databricks): assert the whole OpenAI-format decision and floor the liveliness bound
* test(decisions): move the Databricks OpenAI-format wire row to the ai_decide route
* fix(databricks): keep serving endpoint decisions beside the ai_decide route
* test(databricks): assert the whole classifier request body in the test routing case
* test(databricks): correct System One spend call type
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: mateo <mateo@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(decisions): add Databricks ai_decide as a /v1/decisions provider and auto-router decider
* fix(decisions): reject Databricks endpoint names carrying URL separators and keep the provider wiring under llms/
* fix(decisions): reject dot-segment Databricks endpoint names and add Databricks to the dashboard's OSS classifier editor
* fix(ui): name every OSS classifier provider in the classifier radio copy
* feat(decisions): register the Databricks OpenJev decider as an evaluation-mode cost-map entry
* fix(cost-map): declare zero cache rates on the databricks-openjev-qwen35-4b entry
* fix(proxy): reconcile every DB deployment when a registry miss lands on an auto router
A /model/new for an auto router lands on one replica. A request routed to
that auto router on a sibling replica missed it, the model read-through
loaded only the auto router's own row, and the pre-routing hook then picked
a tier the sibling had not loaded, so the caller got a 400 "no healthy
deployments for <tier>" until the next periodic reload. An auto router miss
now runs the full add_deployment reconcile, tiers included. Found by the
audit's two-worker rig on this PR's routing cells; CircleCI's one-worker
proxy never opens the window.
* test(integration): audit cells for Databricks decisions and the Databricks auto-router classifier
Wire cells for /v1/decisions with databricks/<endpoint> deployments, routing
cells for the complexity router's databricks classifier on all three
endpoints with the Postgres rows read back, management cells for the
classifier's spend writes and for the evaluation-mode health check of a
Databricks serving endpoint.