sjcode

ein terminal coding agent, der die ollama API nutzt

Setup

cp config.toml.example config.toml   # then edit port / model / limits
python3 server/server.py             # starts the daemon + admin CLI

config.toml is machine-local and git-ignored; config.toml.example is the template. On first start the daemon creates the SQLite database (sjcode.db).

Daemon (server.py)

On startup it prints its settings and drops into a minimal admin CLI (accounts are stored in SQLite):

command	effect
`create <name> [role]`	create account (asks for password, default role `user`)
`list`	show all accounts
`delete <name>`	remove account
`role <name> <role>`	change role
`passwd <name>`	set a new password
`usage [name]`	used minutes today vs. limit
`reset [name]`	reset the daily usage counter
`status`	show daemon settings
`quit`	stop the daemon

While the CLI runs, an HTTP API is served in the background:

POST /login — {"username", "password"} → {"token", ...}
POST /chat — {"token", "message", "model"?} → {"response", ...}
GET /models?token=... — list ollama models

Every user row stores: username, password_hash, last_logged_in, role, used_today (minutes of AI usage; resets on a new day).

Roles and limits

In config.toml each role gets a daily limit in minutes:

[limits]
user  = 120   # default role for new accounts
admin = -1    # negative = unlimited

Client (client.py)

./coder                               # or: python3 client.py
python3 client.py 10.0.0.5:8420       # explicit daemon address
python3 client.py --model qwen3-coder # skip the model picker
python3 client.py --no-probe          # skip the reachability check (use behind
                                      # HTTP proxies that answer on every port)

On start the client asks which server to connect to: pick one of the saved ones, or add a new one (n). Every server you use is saved in ~/.config/sjcode/client.json together with the username and the last model, so the next start is just Enter-Enter. Addresses without a port use 8420; host:port, http(s)://... URLs and IPv6 literals are accepted.

After login and model choice you get the agent banner and a chat REPL. Commands:

command	effect
`/help`	list commands
`/server`	show the connected server
`/models`	list models on the server
`/model <n>`	switch model (saved for this server)
`/limit`	remaining minutes today (last known)
`/clear`	forget the conversation history
`/quit`	exit

Anything else is sent to the model. The client keeps the last few turns as context (the daemon API itself is stateless) and renders the reply in the agent style (✓ lines for actions the model reports).

Requirements

Python 3.11+ (stdlib only; tomllib is included)
ollama listening on the address from config.toml