📄️ Server Overview
The Dokimos server stores your eval run results and gives you a web UI to view, compare, and track quality over time. Run it when you want a shared place for results instead of files on one laptop.
📄️ Getting Started
This page gets the Dokimos server running locally and sends it your first evaluation results, so you can see pass rates in a web UI. No cloning, no building, just Docker.
📄️ Configuration
This page lists every setting that controls the Dokimos server, so you can wire it up to your database, lock down writes, and tune the background workers.
📄️ Deployment
This page shows you how to run the Dokimos server, from your laptop to production. One pre-built Docker image works everywhere. You add configuration as your needs grow.
📄️ Authentication
This page shows you how to protect the Dokimos server with API keys, so only trusted clients can write experiment results. Read access stays open by default, and you can lock down the web UI with a reverse proxy.
📄️ Client
This page shows you how to send experiment results to a Dokimos server from your code, so your evaluation runs land in the web UI instead of staying in the console.
📄️ CI regression gate
Fail a build when an eval run scores worse than a baseline run. You call one endpoint with the run you just ingested, and the server returns a single passed boolean your pipeline can branch on.
📄️ LLM judge
This page shows you how to let the server score your run items and production traces with an LLM, so no API key lives in your test code.
📄️ Production traces
Send traces from your running app to the server, and the server scores them the same way it scores your offline experiments. You get quality monitoring on live traffic without changing how you evaluate.
📄️ Regression alerting
Get a webhook POST the moment a run regresses, so a quality drop reaches your chat or on call tool without anyone watching a dashboard.
📄️ Server datasets
Store your test data on the server once, version it, and point your tests at a specific version by URI. No more copying the same examples into every test.
📄️ Review and curation
Turn a production miss into a regression test. This page shows you how to find run items a human should check, record a verdict on each one, and promote the ones you judged into a new dataset version.
📄️ Comparing runs
The diff view shows you what changed between two runs of the same experiment, item by item, so you can see what a change moved before it ships.