minion

A single-file, single-dependency terminal coding agent. One Python file, one pip install openai, no framework, no bloat. Point it at any OpenAI-compatible endpoint — a local llama.cpp / vLLM / SGLang server, or a remote API like Z.ai or OpenAI itself — and start chatting with an agent that can read, write, edit, and run shell commands in your project.

The whole thing is one file (minion.py, ~2200 lines). No TUI framework, no plugin system, no config file format. It reads from environment variables (and ~/.env), talks directly to the OpenAI SDK, and uses raw terminal escapes for its interface. If you want to understand or modify how it works, you read one file. That's the whole pitch.

It's built to survive the rough edges of self-hosted and open models: if the server doesn't support native tool-calling, it falls back to parsing <tool_call>…</tool_call> tags out of the model's text. If the server streams a separate reasoning_content field (MiniMax-M3, DeepSeek-R1, etc.), it renders that as a dim "thinking" block above the answer. It degrades gracefully rather than demanding a perfect server.

pip install openai
export MINION_BASE_URL=http://localhost:8080/v1
export MINION_MODEL=your-model-name
export MINION_API_KEY=sk-noop        # any string; local servers ignore it
python minion.py

If MINION_MODEL is unset, minion asks the server what it's serving.

If you'd rather have a minion command on your $PATH, install from this repo:

pip install -e .

That registers a minion console script pointing at this checkout — edits you make here are picked up immediately. Use pip install . (no -e) for a non-editable install instead.

minion reads configuration from environment variables, and automatically loads ~/.env at startup (so you don't have to export things in every terminal).

MINION_BASE_URL=http://localhost:8080/v1
MINION_MODEL=your-model-name
MINION_API_KEY=sk-noop

Define named endpoints and switch between them at runtime:

MINION_SOURCES=local,zai

MINION_SOURCE_LOCAL_BASE_URL=http://localhost:8080/v1
MINION_SOURCE_LOCAL_API_KEY=sk-noop

MINION_SOURCE_ZAI_BASE_URL=https://api.z.ai/api/paas/v4
MINION_SOURCE_ZAI_API_KEY=$zai_test         # $name = look up a key from env / ~/.env
MINION_SOURCE_ZAI_MODEL=glm-x-preview

See sources.example.env for a full annotated example. Switch at runtime with /source [name]. The conversation context is preserved across switches (use /reset if you want a clean slate).

The prompt is a multi-line editor with a framed box:

• Enter submits; Alt+Enter or Ctrl+J inserts a newline
• Paste (bracketed-paste) inserts text verbatim, including newlines
• Up/Down navigate history; Left/Right move within the line
• Home/End jump to line start/end; Ctrl+U clears; Ctrl+C cancels
• Long lines word-wrap inside the box

Falls back to plain input() when stdin/stdout isn't a TTY.

Press Esc at any point during generation to stop the model and drop back to the prompt. The stream is closed, partial output is discarded, and a synthetic "you were interrupted" note is appended to context so the model knows what happened. In-flight tool calls (e.g. a running run_bash) are not cancelled — they run to completion. Ctrl+C kills the whole process if you need a hard stop.

Every write / edit / bash call is risk-classified by a single cheap model call before it runs. Levels: low (read-only or trivially reversible), medium (modifies state but contained/reversible), high (destructive, hard to reverse, or broad scope). The threshold is the minimum level that requires approval:

The risk assessment is shown in brackets next to the prompt, so you have context for the decision:

allow rm -rf /tmp/foo? [risk: HIGH — recursive force delete in /tmp] [Y/n/esc]

At the prompt, press:

• Y (or Enter) to approve
• n to deny — the model is told the action was refused and can adapt
• Esc to stop the turn and drop back to the chat input so you can add more guidance. The escaped action is recorded as cancelled; if the model emitted multiple tool calls, any remaining ones are marked skipped so the context stays valid. A note is left so the model knows you pulled it back.

Auto-allowed calls print a one-liner:

↳ auto-allow [low] ls -la (read-only listing)

YOLO mode skips the classifier entirely. If the classifier call fails or returns garbage, the action defaults to high (always prompts) so it errs on the side of asking.

Every chat is automatically saved to ~/.minion/sessions/ (override with MINION_HOME or MINION_SESSIONS_DIR) — one JSON file per session holding the exact message array the model sees plus a little metadata (id, title, description, source, cwd, timestamps). Files are plain JSON and human-readable/greppable.

• Auto-save happens after every model turn, so a crash or accidental close never loses your work. On Ctrl-D / Ctrl-C exit a grey resume with: minion --resume <id> hint is printed so you can pick right back up.
• The title is auto-derived from your first message; set a custom one with /save <title>.
• A short id (the 6-hex suffix) is shown in listings and accepted by --resume / /resume, so minion --resume deadbe works without typing the full timestamp.
• A model-generated description refreshes every MINION_SESSION_DESC_REFRESH turns (default 6; 0 disables) and appears as a dim subtitle under each session in minion sessions / /sessions — it tracks the current task rather than freezing on the first message.
• Resume a session at startup with minion --resume <target> or mid-chat with /resume <target>. A target is a number from /sessions, a short id, a full session id, a unique id prefix, or an exact title. Bare minion --resume resumes your most recent session.
• On resume, the full conversation history is printed as a one-line-per- message recap (color-coded by role, tool calls shown as → name(...)) so you immediately re-orient on what the chat was about.
• Discover saved sessions from the shell with minion sessions (prints and exits — no REPL). Add a substring query to filter: minion sessions refactor matches titles, descriptions, and ids.
• A resumed session reselects the source (endpoint + model) it was started on, so it lands on the same backend it was talking to.
• /sessions <n> shows the full transcript of a past session inline.
• /reset starts a fresh session (it does not overwrite the old one).

$ minion sessions              # browse recent sessions, then exit
$ minion sessions refactor     # filter to sessions mentioning "refactor"
$ minion --resume 1            # resume the most recent session
$ minion --resume deadbe       # resume by short id
$ minion --resume implement    # resume the session titled "implement…"

This is a deliberately lightweight take on session persistence — inspired by how Hermes (hermes_state.py) stores sessions, but flat JSON files instead of SQLite, since minion is a single local agent rather than a multi-platform gateway.

Reasoning models sometimes spin in place — they keep saying "let me implement…" without actually doing anything. minion counts those "ready to act" phrases during the reasoning phase and, after MINION_REASONING_LOOP_SIGNALS (default 10) of them, cuts the stream and nudges the model to take a concrete action. Set the env var to 0 to disable, or lower it (e.g. 5) for a more aggressive cut.

At startup (and after a /source / /yolo / /approval switch) minion prints a one-line banner showing the model name, active source, approval mode, and endpoint. The banner is printed into the normal scrollback — there's no pinned/scroll-region status bar, so terminal scrollback works normally and every line of output stays visible.

(An earlier version pinned a status bar at row 1 using a DECSTBM scroll region, like tmux/vim. It was removed because it broke terminal scrollback — lines scrolling off the top of the region never entered the scrollback buffer, so the chat became unscrollable in a plain terminal.)

Every request and streamed SSE chunk is appended to llamacpp.log next to the script (JSONL). Useful for debugging what the model actually saw and returned.

minion was developed using the following models:

• minion (eating its own dog food)
• GLM 5.2 (Z.ai) (Open Weights coming soon!)
• MiniMax-M3 (MiniMax)