smoke-test
Testing & QualityRun and interpret scripts/smoke_test.sh, the on-demand checks for optional dependencies that CI and the default docker compose don't cover: the Postgres and MongoDB checkpointers, the AG-UI endpoint, and LangFuse tracing. Use when you've touched the memory/checkpointer layer, service startup/health, the AG-UI adapter, LangFuse tracing, or bumped one of those dependencies — and want to confirm the real integration still works without waiting for a full CI run. Also use when deciding WHETHER such a check is even warranted for a change.
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Optional-dependency smoke tests
scripts/smoke_test.sh exercises the parts of this project that aren't in the fast
unit suite or the default CI path because they need real infrastructure: the
Postgres and MongoDB checkpointers, the AG-UI endpoint, and LangFuse
tracing. It spins up the real dependency in Docker, runs the service against it, and
verifies the integration end-to-end, then tears everything down.
"Smoke test" here means a quick is-this-obviously-broken confidence check, not exhaustive integration coverage. It's deliberately cheap to run one target and skip the rest.
First: should you run this at all?
Most changes do not need it. It pulls images, starts containers, and takes minutes —
that time and token cost isn't worth it for work that doesn't touch these paths. Skip it
for: adding or editing an agent graph, prompts, or tools; docs; client/Streamlit-only
changes; anything already covered by uv run pytest and normal CI.
Run the relevant target when your change touches its path:
| You changed… | Run |
|---|---|
src/memory/*, initialize_database, a saver/store class, checkpointer wiring | postgres and/or mongo |
langgraph-checkpoint-postgres / -mongodb, pymongo, psycopg versions | postgres / mongo |
src/service/agui.py, the AG-UI adapter, ag-ui-* deps | agui |
LangFuse tracing (the CallbackHandler wiring, /health auth check), langfuse dep | langfuse |
Service startup / lifespan / /health broadly | the most relevant one or two |
| Nothing specific — periodic pre-release confidence pass | all |
Prefer the narrowest target that covers your change. Run all (which includes the
heavy LangFuse stack) only for a deliberate full pass — not as a reflex.
Running it
./scripts/smoke_test.sh # default: postgres, mongo, agui
./scripts/smoke_test.sh mongo # a single target
./scripts/smoke_test.sh postgres agui # a subset
./scripts/smoke_test.sh langfuse # heavy: ~5GB stack, run on its own
./scripts/smoke_test.sh all # everything, incl. langfuse
langfuse is excluded from the default run because it starts LangFuse's full 6-service
self-host stack (~5GB of images). A green run ends with --- All smoke tests passed ---;
exit code is non-zero on any failure or an unknown target.
Interpreting the result — and why a green ≠ "it works" trap is real
The whole design point is that a passing API test does not prove the intended
dependency was used. The persistence test just checks that history survives across two
invokes, which is true for any working checkpointer — including SQLite. So if
DATABASE_TYPE=mongo silently didn't take effect (dropped env, a fallback), the pytest
step would still pass while nothing touched Mongo.
That's why each target does a second, independent check that the specific dependency was really exercised, and that's the line you should actually trust:
✓ verified: N postgres checkpoint rows for this run's thread✓ verified: N mongo checkpoint documents for this run's thread✓ verified: N LangFuse traces recorded for this run✓ verified: AG-UI streamed a complete run with the expected response
Each uses a unique per-run thread id (SMOKE_THREAD_ID), so the count reflects this
run's data even against a non-empty volume. A ✗ FAIL: … was NOT exercised as intended
means the dependency wasn't actually hit — treat that as a real failure, not flakiness.
Other guards worth knowing when you read a failure:
- Port already in use:
start_servicerefuses to run if something is already on:8080, so the health check can't accidentally pass against an unrelated process. - Service died on startup: it fails fast and dumps the service log instead of waiting out the full timeout.
- LangFuse ingestion is async: traces flow through a worker → ClickHouse pipeline, so the script polls the traces API for a bit (usually a few seconds) before deciding.
Cloud-environment quirks (Claude Code on the web / sandboxes)
This script is meant to be runnable by an agent in a sandboxed cloud environment. A few things bite there specifically:
- Docker daemon may not be running (and can stop between steps). If
dockererrors with "Cannot connect to the daemon," start it:(dockerd > /tmp/dockerd.log 2>&1 &)then wait a few seconds. - Don't build the service image in-sandbox. Container builds can't reach package
registries through the egress proxy (TLS/CA), so
docker compose buildfails. This is exactly why the script runs the service on the host viauvand only puts the dependencies in Docker. Don't "fix" it by baking the proxy CA into the committed Dockerfile — that's sandbox-specific. - Registry allowlist for LangFuse. The LangFuse stack's
minioimage comes fromcgr.dev(Chainguard). In a restricted-egress environment addcgr.devto the network allowlist, or the pull 403s. (If a pull still 403s afterward on a different host, add whatever host it names — some registries serve blobs from a separate CDN.) pkill -f run_service.pywill kill your own shell.-fmatches full command lines, and your command text contains that string, so it self-matches. To free port 8080 usefuser -k 8080/tcpinstead.- Long foreground
sleeploops can be killed by the sandbox. When running the script (or waiting on it), launch it in the background (nohup … &) and poll its log file rather than blocking in the foreground. docker compose execneeds.env;docker execdoesn't. The host-based flow deliberately omits.env, anddocker compose execre-parses the full config (which referencesenv_file: .env) and fails without it. The script queries containers viadocker exec <id>(id fromdocker compose ps -q) to sidestep this.
Extending it
The script is built around one principle: every target proves the real dependency was used, not just that the API returned something. Keep that when adding a target.
To add a new optional-dependency target:
- Add a
smoke_<name>()function following the existing shape: start the dependency (Docker),start_serviceon the host with the right env, run an API-level check, then a dependency-identity check (query the dependency directly for this run's data viaassert_positive_count, or assert on captured output like the AG-UI target). - Register it in the
casein the target loop and, if it should be part of a full pass, in theallexpansion. Decide whether it's light enough for the default set (DB-style) or heavy enough to be opt-in (LangFuse-style). - If it needs an add-on compose file, follow the
docker/compose.<dep>.yamlpattern; if it's a large external stack, prefer fetching upstream's compose pinned to a tag (as thelangfusetarget does viaLANGFUSE_REF) rather than vendoring it.
Keep these out of the CI docker job: they live in tests/smoke/ (not tests/integration/,
which CI's test-docker job scopes to) and are marked @pytest.mark.docker so they're
skipped unless --run-docker is passed.