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# kasl-server
Team server for [kasl](https://github.com/lacodda/kasl). Employees run kasl on their machines; the agents send work-time data to the server. Managers get dashboards, charts, and reports across the whole team; every employee gets a personal page.
> **Status: pre-alpha.** The door for kasl agents is open and survives a bad connection: a day at a time on `POST /api/v1/days`, a backlog on `/days/batch`, and a task the employee deleted can be deleted here too. History from before the server arrived can be imported from an agent's own database, and people can now sign in. The tables are filled; almost nothing reads them back yet — dashboards and the personal page are the next milestones, and there is still nothing to deploy for real use.
## Try it
Requires Rust and Docker.
```console
$ git clone https://github.com/lacodda/kasl-server && cd kasl-server
$ docker compose up -d db
$ export DATABASE_URL=postgres://kasl:kasl@localhost:5433/kasl
$ export KASL_AGENTS=employee@example.com:agent-token
$ cargo run
2026-08-19T00:00:50.330100Z INFO kasl_server: database schema is up to date version=20260818000001
2026-08-19T00:00:50.460212Z INFO kasl_server::provision: provisioned agents from KASL_AGENTS agents=1
2026-08-19T00:00:50.466427Z INFO kasl_server: kasl-server listening version="0.6.0" addr=0.0.0.0:8080 max_batch_days=31 max_body_bytes=4194304
$ curl http://127.0.0.1:8080/health
{"database":"ok","status":"ok","version":"0.6.0"}
# An agent back from three days offline. The middle day is impossible - it ends
# before it starts - and the others land anyway.
$ curl -X POST http://127.0.0.1:8080/api/v1/days/batch \
-H "Authorization: Bearer agent-token" -H "Content-Type: application/json" \
-d '{"days":[
{"date":"2026-08-15","started_at":"2026-08-15T09:04:00-03:00","ended_at":"2026-08-15T18:12:00-03:00",
"tasks":[{"agent_task_id":7,"recorded_at":"2026-08-15T18:10:00-03:00","name":"Reliable ingest","completeness":60}]},
{"date":"2026-08-16","started_at":"2026-08-16T19:00:00-03:00","ended_at":"2026-08-16T09:00:00-03:00"},
{"date":"2026-08-17","started_at":"2026-08-17T09:11:00-03:00","ended_at":"2026-08-17T17:40:00-03:00",
"tasks":[{"agent_task_id":7,"recorded_at":"2026-08-17T17:38:00-03:00","name":"Reliable ingest","completeness":100}],
"tasks_are_complete":true}]}'
{"accepted":2,"rejected":1,"results":[
{"status":"accepted","workday_id":"82ca500d-feeb-4d1f-8fb7-0b376339be02","date":"2026-08-15","pauses":0,"tasks":1,"deleted_tasks":0},
{"status":"rejected","date":"2026-08-16","error":"ended_at is before started_at"},
{"status":"accepted","workday_id":"2ea46d40-3aa0-48d3-8d8d-e1bb152a36bc","date":"2026-08-17","pauses":0,"tasks":1,"deleted_tasks":0}]}
# The employee deletes the task in kasl; the agent re-sends the day and says so.
$ curl -X POST http://127.0.0.1:8080/api/v1/days \
-H "Authorization: Bearer agent-token" -H "Content-Type: application/json" \
-d '{"date":"2026-08-17","started_at":"2026-08-17T09:11:00-03:00","ended_at":"2026-08-17T17:40:00-03:00",
"tasks":[],"tasks_are_complete":true}'
{"workday_id":"2ea46d40-3aa0-48d3-8d8d-e1bb152a36bc","date":"2026-08-17","pauses":0,"tasks":0,"deleted_tasks":1}
```
The task is gone from the 17th - and still there on the 15th, where the employee
did not delete it.
The dev database listens on 5433, leaving a PostgreSQL you may already run on
5432 alone; override with `KASL_DB_PORT`.
## The API
`/api/v1` from the first endpoint: agents update on their own schedule, so a
path keeps meaning what it meant when the agent calling it shipped.
**`POST /api/v1/days`** — upload one day. Requires `Authorization: Bearer
<token>`. The body is the workday with its pauses and tasks; `ended_at` is
absent while the day is still running, and so is a pause's, and `tasks` may be
empty.
Two properties are worth knowing before writing a client:
- **Every instant needs a UTC offset**, and the day carries its own `date`.
`2026-08-14T09:12:00` without an offset is refused (422): one team's hours
have to stay comparable across time zones, and which calendar day work
belongs to is the agent's call, not a value derived on the server.
- **The last upload wins.** Re-sending a day replaces what is stored, so a
correction made in kasl lands and a retry after a lost connection is safe -
the same payload twice leaves the same rows. Pauses are replaced as a set;
tasks are matched on `agent_task_id`, so a task carried into the next day
moves rather than multiplying.
- **Deleting a task takes one word.** Send `"tasks_are_complete": true` and the
date's tasks the payload omits are deleted, which is how a task the employee
removed in kasl disappears here too. Other dates are untouched. Leave the flag
out - as agents written before it did - and nothing is ever deleted.
**`POST /api/v1/days/batch`** — upload a backlog. The body is `{"days": [...]}`
with the same day objects, and the answer reports each one:
```json
{"accepted": 2, "rejected": 1, "results": [
{"status": "accepted", "date": "2026-08-10", "workday_id": "...", "pauses": 1, "tasks": 3, "deleted_tasks": 0},
{"status": "rejected", "date": "2026-08-11", "error": "ended_at is before started_at"},
{"status": "accepted", "date": "2026-08-12", "workday_id": "...", "pauses": 0, "tasks": 1, "deleted_tasks": 0}
]}
```
Each day is written on its own, so one the server will never accept does not
block the rest - an agent that could not deliver *any* of its backlog because of
a single bad row would retry the same request forever. The batch carries at most
`KASL_MAX_BATCH_DAYS` days (31) and the body at most `KASL_MAX_BODY_BYTES`
(4 MiB); past either, `413`.
**Which failures are worth retrying.** `4xx` means the payload will not be
accepted as sent, however many times it is tried - fix it or drop it. `5xx`
means the fault is on this side; send it again later. A batch that answers `5xx`
stopped partway: the days already accepted are stored, and re-sending them is
safe because the last upload wins.
A malformed day is refused with `400` and a reason naming the field
(`{"error":"tasks[0]: completeness must be between 0 and 100"}`); an
unrecognized, revoked or deactivated token gets `401`. The reasoning behind all
of this is in [ADR 0004](https://github.com/lacodda/kasl-server/blob/main/docs/adr/0004-the-ingest-contract.md)
and [ADR 0005](https://github.com/lacodda/kasl-server/blob/main/docs/adr/0005-deletions-and-backfill.md).
## Signing in
People sign in with an email and a password; kasl agents keep using their bearer
token and are unaffected by any of this.
```console
$ kasl-server admin --email boss@example.com --password '...'
admin boss@example.com is ready
$ curl -i -X POST http://127.0.0.1:8080/api/v1/auth/login -H "Content-Type: application/json" -d '{"email":"boss@example.com","password":"..."}'
HTTP/1.1 200 OK
set-cookie: kasl_session=b7857303342e1a4b...; Path=/; HttpOnly; SameSite=Strict; Max-Age=1209600
{"status":"ok"}
$ curl -H "Cookie: kasl_session=b7857303342e1a4b..." http://127.0.0.1:8080/api/v1/auth/me
{"id":"de836432-5dce-4705-9344-a65b356fc662","email":"boss@example.com","display_name":"boss@example.com","role":"admin"}
```
`POST /auth/logout` ends this session, `POST /auth/logout-everywhere` ends all of
them, and `GET /auth/me` says who the caller is.
Sessions are rows in the database, not signed tokens. The query per request buys
the thing a self-contained token cannot give: access ends when it is ended — the
afternoon someone leaves, not whenever their token happens to expire. A session
lasts a fortnight and each use pushes that out again.
An unknown email, a deactivated account and a wrong password all answer
`{"error":"wrong email or password"}`, so the login form cannot be used to find
out who works somewhere.
**The first administrator** comes from `kasl-server admin` or
`KASL_ADMIN=email:password` in the environment. Running it again resets the
password and promotes the account, which is both the way back in after a
forgotten password and the way to make an admin of someone whose account already
exists because their agent has been reporting. Accounts created by `KASL_AGENTS`
have no password and cannot be signed into — they exist to own an agent's data.
Set `KASL_SECURE_COOKIES=false` when serving over plain `http://`. A `Secure`
cookie is silently dropped by the browser there, which looks exactly like login
doing nothing. The reasoning is in
[ADR 0007](https://github.com/lacodda/kasl-server/blob/main/docs/adr/0007-sessions-and-the-first-admin.md).
## Importing history from before the server
Someone can track their time with kasl for a year before their team runs a
server. That history is an ordinary SQLite file on their machine, and it does
not have to be lost because the server arrived second:
```console
$ kasl-server import --db kasl.db --user employee@example.com --timezone -03:00
read 240 workdays, 312 pauses, 460 tasks from kasl.db
skipped 17 tasks the employee had deleted
imported 240 days as employee@example.com at -03:00
```
`--timezone` is required and has no default. kasl stores bare wall-clock text,
so nothing in the file says which offset it was recorded in - and a wrong guess
produces a perfectly plausible-looking year of work at the wrong hour. The
answer comes from whoever knows, and is echoed back so it is on the record.
- `--dry-run` reads and reports without writing anything.
- `--since` / `--until` bound the import by date, both ends inclusive. This is
how someone who moved between time zones is imported correctly: one run per
stretch, each with the offset that stretch was recorded in.
- The account must already exist - an import will not create it, so a typo in
the email address cannot quietly file a year of history under a stranger.
- Re-importing replaces rather than duplicates, so a run that failed partway can
simply be repeated, and a wrong offset is fixed by importing again with the
right one.
The agent's file is opened read-only and never written to. Details and the
trade-offs behind the fixed offset are in
[ADR 0006](https://github.com/lacodda/kasl-server/blob/main/docs/adr/0006-importing-local-history.md).
## The data model
Migrations live in `migrations/` and are applied on startup. The shape follows
kasl's own model, so a reader who knows the agent recognizes it:
| `users` | People and their role: admin, manager, employee |
| `sessions` | Browser sign-ins; a token hash each, never the token |
| `agents` | Installed kasl instances; a token hash each, never the token |
| `workdays` | One row per person per date: when the day started and ended |
| `pauses` | Idle stretches and manual breaks inside a day |
| `tasks`, `tags`, `task_tags` | What was worked on, and how it is labelled |
| `reports` | That a report was submitted, when, and with which figures |
Two differences from the agent's database are deliberate: instants are stored
with a time zone (the agent stores bare wall-clock text, which does not survive
a team spread across zones), and rows are tied together by foreign keys rather
than by comparing dates. Both are recorded in [ADR 0003](https://github.com/lacodda/kasl-server/blob/main/docs/adr/0003-time-and-identity-in-the-schema.md).
## Running it somewhere real
`docker-compose.prod.yml` builds the server and starts it next to PostgreSQL.
The image is built on the machine that will run it, so a stand on a Raspberry
Pi gets an aarch64 binary without cross-compiling anything:
```console
$ cat > .env <<'ENV'
POSTGRES_PASSWORD=<a long random string>
KASL_AGENTS=employee@example.com:<the agent's token>
ENV
$ chmod 600 .env
$ docker compose -f docker-compose.prod.yml up -d --build
```
The database publishes no port — only the server reaches it, over the compose
network — and the server runs as an unprivileged user. The first build takes a
while on a small machine (about fifteen minutes on a Pi 4); later ones reuse
the cached layers.
This is a stand, not a supported deployment: backups, restore and an install
guide come with the deployment milestone.
## Configuration
Everything comes from the environment:
| `DATABASE_URL` | PostgreSQL connection string | required |
| `KASL_SERVER_ADDR` | Address the HTTP server binds to | `0.0.0.0:8080` |
| `KASL_AGENTS` | Agents to provision on startup, as `email:token` pairs separated by commas | none |
| `RUST_LOG` | Log filter (tracing syntax) | `kasl_server=info,tower_http=info` |
Database migrations are embedded in the binary and applied on startup.
`KASL_AGENTS` is how the first agents get in while the admin UI does not exist
yet: each entry becomes an employee and an agent holding that token's hash.
Re-running with a changed token rotates it and revokes the old one. Tokens are
secrets — pass them through your deployment's secret store, not a committed
file — and the variable stops being the way in once tokens are issued from the
UI.
## What it will do
- Ingest work-time data from kasl agents: workdays, pauses, tasks, reports *(days, backfill and history import: done)*
- Manager dashboards: who is working right now, hours per person, trends over time
- Personal pages: every employee sees their own history
- Roles: admin, manager, employee
- Self-hosted: a single binary (Docker image planned) plus PostgreSQL — your data stays on your infrastructure
## Stack
Rust REST API (axum) + PostgreSQL (sqlx), React single-page app for the web UI. Architectural decisions are recorded in [docs/adr/](https://github.com/lacodda/kasl-server/tree/main/docs/adr).
## License
[MIT](https://github.com/lacodda/kasl-server/blob/main/LICENSE)