Everything this stack adds now carries issue in its file name, workflow name
and job id, so one search finds all of it:
ls .github/workflows/issue_*
grep -ril issue scripts .github/prompts .github/*.json
Renames: label_sync.yml -> issue_label_sync.yml, label_claude_code.yml ->
issue_label_claude_code.yml, .github/labels.json -> .github/issue-labels.json,
scripts/sync-labels(.test).ts -> scripts/sync-issue-labels(.test).ts. Job ids
now match the script they run: classify-issue-tests, classify-issue,
label-issue, sync-issue-labels-tests, sync-issue-labels, label-claude-code
An edit during the first run used to cancel it, and the edited run then
skipped because the webhook payload had no needs:template yet, so a
well-formed issue edited within the first minute was never labelled.
Runs for one issue now queue, and the script decides an edited event
against the live labels: a domain label means leave it alone, a gated
issue is re-run, and an unlabelled issue is re-run for its first hour
Split the issue body only on headings the two forms actually emit, keep the
first value when a heading repeats, cap each field on its own so a long config
cannot push the repro out of the model's view, and only treat comments from
github-actions[bot] as the template notice. The claude code keyword label the
deleted component labeler used to add gets its own small workflow.
Every issue opened from now on is gated on the template headings, sent once
through the LiteLLM proxy with a strict JSON schema, and labelled from the
manifest in .github/labels.json. Old-template issues are not touched. The bug
template shrinks to Description, Config, LiteLLM Version and Steps to Repro,
both templates gain a domain dropdown, and the labelers that keyed off the old
component dropdown go away.
Regenerated every touched file from origin/main applying only the B1 test deletions and the unused import and helper cleanup they leave behind, without running the formatter across untouched code. CI only checks ruff format under litellm/, so the earlier reflows of test files were pure diff noise for reviewers
Also drops the tests/local_testing/test_prompt_caching.py entry from the caching-local shard in test-unit.yml since that file is deleted
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Split the Rust workflow into fmt, clippy, nextest and wheel jobs so they run in parallel, replace manual actions/cache with Swatinem/rust-cache, and install a pinned checksum-verified cargo-nextest. Make two python-bridge tests self-contained so they pass when nextest runs each test in its own process.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Wolfi's security database names zlib 1.3.3-r0 as the fix for CVE-2026-85091,
but the newest zlib published to the Wolfi apk repo is 1.3.2-r7. Every
wolfi-base digest, including the current latest, still reports the CVE, so no
base image bump or apk upgrade can clear it and image-scan fails on every PR
touching a Dockerfile or the lockfile, and on the nightly schedule.
Ignore that CVE and its GHSA alias for the zlib apk package only, so a fixable
High in anything else still fails the job.
The baked-in default meant a repo that never set the variable silently
got the most expensive candidate. Cost per issue spans roughly 20x
across the models this can run on, so the workflow now fails with a
clear message rather than picking one.
A verdict is now dropped when it names a pull request, the issue itself,
or a newer issue, and the label goes on before the comment so a failed
comment leaves no marker and the rerun finishes the job. The flag logic
lives in scripts/flag-duplicate-issue.ts next to the sweep it feeds,
sharing normalizeTitle and the marker format, with bun tests that run on
pull requests touching it
The old check_duplicate_issues.yml matched on title wording, so it missed the
same bug reported in different words. Over one full week of new issues (167,
5 to 12 Sep) it flagged 2, both wrong, while hand review found 11 real
duplicates that nothing caught.
The new workflow fetches the issue through the API into a file, runs
openai/codex-action with a fixed prompt and an output schema, and lets Codex
search the tracker with gh. At a 0.95 confidence gate it would have posted 12
comments that week, 9 naming a real duplicate. It reuses the same marker
comment and potential-duplicate label as before so auto-close-duplicates.yml
keeps working unchanged, and warns about the auto-close only when the titles
actually match.
Traffic goes through LiteLLM: the key is a virtual key and the endpoint is
the proxy's /v1/responses. Comments and labels stay off until the
DUPLICATE_CHECK_ENABLED repo variable is set.
create-release.yml is back to calling the chaos test through no mechanism at
all; it never called it. Also drops the E2E_REDIS_CHAOS opt-in gate itself:
the redis_chaos marker still exists for -m selection and is still excluded
from the per-PR selector by path (tests/e2e/(ui|claude_code|load)/), but the
test no longer needs an env var to run once its file is targeted.
Co-Authored-By: Claude Code <noreply@anthropic.com>
Now that create-release.yml gates stable and RC releases on this test directly,
the weekly schedule is redundant: every release gets a run against its own
commit instead of whatever happened to be on the default branch that Saturday.
workflow_dispatch stays for manual runs.
Co-Authored-By: Claude Code <noreply@anthropic.com>
The chaos test only ran on a weekly cron, so a release could be cut from a
commit it had never covered. Making it callable lets create-release.yml run it
against the exact commit being tagged and refuse to tag if it fails.
Dev, nightly, alpha and beta tags skip the gate: they are cut far more often
than stable and RC tags, and the weekly schedule already covers the default
branch. Input validation moves into the gate job so a malformed tag or SHA
fails before spending a multi-minute chaos run.
Co-Authored-By: Claude Code <noreply@anthropic.com>
Pad the locust payload to tens of KB so per-request bookkeeping cost scales with
body size instead of hiding behind a 40-byte prompt. Turn on
use_redis_transaction_buffer in the chaos config and JSON_LOGS in the workflow so
the spend buffer, pod lock, and JSON-encoded breaker tracebacks are all part of
the measured chaos cost. Add a log-bytes-per-request budget alongside latency,
RSS, and CPU, reading the proxy's log file size at each phase split; its ceiling
is uncalibrated since no chaos run has measured it yet.
Co-Authored-By: Claude Code <noreply@anthropic.com>
The sequential version sent one request at a time, so a Redis outage never
reached the concurrency where the failed-tracking alert body actually grows.
This drives the proxy with locust against one model group of three mock
deployments, two failing at order 1 and one serving at order 2, so every
request spends its retries on the failing pair and lands on the serving
deployment through the order-based fallback. Two phases, a healthy baseline
and a CLIENT PAUSE WRITE window, and every request must succeed in both.
Latency, RSS and CPU are reported as p50/p90/p99 per phase rather than
asserted on: RSS and CPU come from psutil on the proxy's process tree, since
a multi-worker proxy serves /metrics from the prometheus multiprocess
collector and that drops the process collector's series. Thresholds stay open
until weekly runs give real baselines.
Co-Authored-By: Claude Code <noreply@anthropic.com>
* feat(proxy): offload spend tracking to a pod-local spend worker sidecar
py-spy on the gateway showed the post-response _PROXY_track_cost_callback,
spend-log and DBSpendUpdateWriter work running on the inference workers'
event loop, so a DB or Redis stall backed up the request path.
When LITELLM_SPEND_WORKER_ENABLED=true, _ProxyDBLogger serializes one compact
typed SpendEvent per success and hands it to a SpendEventProducer that ships
it over a unix socket (default) or loopback-only TCP to a sidecar started as
`python -m gateway.spend_worker`. The sidecar runs the unchanged
_ProxyDBLogger pipeline against the pod's PgBouncer (pooled_database_url).
When the sidecar is unreachable, the buffer is full, or the gateway shuts
down with events still queued or in flight, the producer applies
LITELLM_SPEND_WORKER_ON_UNAVAILABLE (fallback in-process, or drop). The
sidecar half-closes producers on SIGTERM and drains, the producer treats
EOF as unavailable, and the gateway flushes buffered spend counters on
shutdown. The sidecar honors LITELLM_LOG so its writes are visible in its
own process log.
Helm: both charts gain an opt-in spend-worker sidecar container sharing an
emptyDir socket dir, and the componentized chart's HPA uses a
ContainerResource CPU metric scoped to the gateway container so sidecar
CPU does not drive inference scaling.
* feat(terraform): opt-in spend-worker sidecar for the AWS and GCP gateway stacks
Adds spend_worker_* inputs to both modules. On ECS Fargate the sidecar is a second, non-essential container in the gateway task; on Cloud Run it is a second container in the gateway service. Both listen on loopback TCP, share the gateway's DB/Redis/secret env, and set LITELLM_JOB_ROLE=spend_worker. Disabled by default. Plan-only tests cover both, and the terraform CI workflow now runs the gcp module too
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* test(proxy): retrieve a completed batch in the in-process spend path test
The base now defers cost tracking for batches that are still in flight, so an in_progress batch never reaches update_database
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* refactor(proxy): rename the spend worker sidecar to collector
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): run the collector from the installed litellm package and finish in-flight fallbacks on shutdown
The sidecar command becomes python -m litellm.proxy.collector so the classic image, whose runtime
stage copies only the installed package, can run it. The module now assembles DATABASE_URL and the
pod-local pgbouncer URL itself, replacing gateway/collector.py
The componentized collector sidecar inherits gateway.volumeMounts so custom CA mounts reach it.
SpendEventProducer shields an in-progress fallback from the writer task cancellation so close()
no longer loses an event already handed to the in-process pipeline
Helpers used across modules (address_argument, should_store_prompts_and_responses_in_spend_logs,
flush_spend_counters_on_shutdown) become public so the change adds no reportPrivateUsage errors
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci(terraform): drop the gcp job duplicated by the aws/gcp matrix
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(collector): keep metrics env off the classic sidecar and reject shared loopback ports
The classic chart no longer hands PROMETHEUS_METRICS_PORT and the billing metrics env to the collector container, and gives it the same /.npm scratch mount as the proxy on a read-only root. AWS and GCP now refuse a plan where the spend collector and the metrics sidecar bind the same loopback port. A regression test drives a sidecar crash mid-stream on asyncio and uvloop and checks no event is billed by both the sidecar and the in-process fallback; the producer docstring spells out why a failed drain() cannot double count
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* style(proxy): format pooled_database_url after the pgbouncer rebase
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): keep the cache-hit preset key and survive dead producers on collector drain
Cache hits updated the logging object after the early return, so the offloaded spend event carried
preset_cache_key=None and the collector re-hashed reconstructed kwargs. Also guard write_eof() against
producer transports uvloop already closed so one dead connection cannot abort the drain
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(terraform): keep the gcp collector port off the metrics sidecar health port
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): collector connects to Postgres directly under IAM or Entra token auth
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(proxy): mark the collector's DATABASE_URL as pooled when it uses the pod's pgbouncer
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
