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smoke-test

Testing & Quality
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Run 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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Source SKILL.md: https://github.com/JoshuaC215/agent-service-toolkit/blob/HEAD/.claude/skills/smoke-test/SKILL.md

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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 wiringpostgres and/or mongo
langgraph-checkpoint-postgres / -mongodb, pymongo, psycopg versionspostgres / mongo
src/service/agui.py, the AG-UI adapter, ag-ui-* depsagui
LangFuse tracing (the CallbackHandler wiring, /health auth check), langfuse deplangfuse
Service startup / lifespan / /health broadlythe most relevant one or two
Nothing specific — periodic pre-release confidence passall

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_service refuses 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 docker errors 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 build fails. This is exactly why the script runs the service on the host via uv and 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 minio image comes from cgr.dev (Chainguard). In a restricted-egress environment add cgr.dev to 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.py will kill your own shell. -f matches full command lines, and your command text contains that string, so it self-matches. To free port 8080 use fuser -k 8080/tcp instead.
  • Long foreground sleep loops 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 exec needs .env; docker exec doesn't. The host-based flow deliberately omits .env, and docker compose exec re-parses the full config (which references env_file: .env) and fails without it. The script queries containers via docker exec <id> (id from docker 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:

  1. Add a smoke_<name>() function following the existing shape: start the dependency (Docker), start_service on 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 via assert_positive_count, or assert on captured output like the AG-UI target).
  2. Register it in the case in the target loop and, if it should be part of a full pass, in the all expansion. Decide whether it's light enough for the default set (DB-style) or heavy enough to be opt-in (LangFuse-style).
  3. If it needs an add-on compose file, follow the docker/compose.<dep>.yaml pattern; if it's a large external stack, prefer fetching upstream's compose pinned to a tag (as the langfuse target does via LANGFUSE_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.