Local usage trial — FluxMeter（中文）

Engine/API 4.8.4. No model-provider key is needed. Use a local development machine with Git, Java 17, Docker + Docker Compose, and Python 3.10+ (python3). The demo runs Kafka, Flink, Redis, API, Gateway, and Grafana; allow memory for the full stack.

code

git clone https://github.com/10kshuaizhang/fluxmeter.git
cd fluxmeter
make demo

make demo builds the engine, starts Compose, then runs demos/quickstart.py:

Wait for GET /ready to confirm Redis, Kafka, and Flink probe consumption.
Generate a unique customer and event ID. Send /ingest 1,200 input and 400 output tokens for gpt-4o-mini; omit timestamp so the server assigns current time.
Require an accepted receipt. A 202 receipt is custody, not settlement.
Poll /usage/customer/{id} until it reports exactly one event, 1,600 total tokens, and numeric cost_usd: 0.00042, using default catalog input/output prices of $0.15/$0.60 per million tokens.
Print the response and PASS. Any timeout, quarantine, or mismatch exits nonzero.

The script makes no LLM call and creates synthetic test usage only. Every run uses new IDs, so it does not depend on clearing Redis or disabling deduplication. The normal projection delay is roughly 10–15 seconds; startup and lag can take longer. Readiness, custody, and projection each have a default 180-second bound.

code

# Repeat against the running stack without rebuilding:
make demo-verify

# Optional authenticated endpoint (use an ingest/read key that can access the
# generated customers; an existing customer-scoped key will not match):
export FLUXMETER_API_KEY='your-ingest-read-key'
python3 demos/quickstart.py --url http://localhost:8000 --timeout 300

# Only when intentionally using a different catalog, supply its fixture cost:
python3 demos/quickstart.py --expected-cost 0.00042

Do not paste this example API key literally. Demo Compose allows unauthenticated access when keys are unset; use production deployment configuration before sharing an endpoint. Stop local services with make stop.

Troubleshooting#

Swipe horizontally to view all columns左右滑动查看全部列

Failure	Check
`/ready` times out	`docker compose ps`; inspect `docker compose logs job-submitter jobmanager taskmanager api` and Flink UI `http://localhost:8081`
Custody retries `429`/`503`	Check API capacity, Redis identity storage, Kafka ACKs. The script reuses the same event ID/payload for retries
`401`/`403`	Match the API key and customer scope to the endpoint
Accepted but no projection	Check Flink job, consumer lag, and `WATERMARK_HEARTBEAT_ENABLED=true` on API for idle windows
Token/cost mismatch	Inspect printed last response, API/Flink catalog consistency, and custom pricing; `202` alone is not success
Quarantine receipt	Investigate timestamp skew; quarantined events are not normally billed

For optional reserve → stream kill → settlement → ClickHouse audit assertions, use a Python 3 environment with httpx:

code

python3 -m venv .venv-proof
.venv-proof/bin/python -m pip install httpx
make demo-proof PYTHON=.venv-proof/bin/python

It starts the audit overlay at local proof sizing (one API worker and two Flink slots) and a local mock provider. It is a deeper control test, not a throughput benchmark. The main terminal recording (make demo-record) uses the simple trial and has no manually seeded Intelligence data. Intelligence examples elsewhere are synthetic analytics fixtures and are not evidence of this metering path.