Engine API

To run the engine without the app, use these commands:

cd engine && uv run dmlx serve --port 8642
curl -s localhost:8642/v1/images/generations -H 'content-type: application/json' \
  -d '{"prompt":"a rowboat on a lake at dawn","size":"1024x1024"}' | jq '.dmlx'

Method	Path	Notes
POST	/v1/images/generations	OpenAI-compatible; stream: true returns server-sent events
POST	/v1/images/edits	multipart (OpenAI style) or JSON with source_id / reference_ids
POST	/v1/workflows	workflow with validation and capability checks; supports streaming
POST	/v1/workflows/route	what to do with a chat message; "plan": true asks the agent
GET	/v1/capabilities	operations and input limits of each model
POST	/v1/prompts/compile	prompt enhancement preview
POST	/v1/uploads	stores an image and gives an id for later references
GET	/v1/results/{id} · /meta	PNG with the prompt and seed in the file · its metadata
GET/DELETE	/v1/jobs/{id} · /events	status · cancel · events
POST	/v1/jobs/{id}/retry	runs a failed workflow again from the failed step
GET	/v1/models	catalog with downloaded / loaded state
POST	/admin/models/{id}/pull · load · unload	download, pin, free
GET	/admin/memory	memory budget, pressure, loaded parts
GET/POST	/admin/prompt-assistant · /select · /pull	agent models: status, select, download

Events: queued, plan, loading{component}, encoding, step{step,total}, decoding, image{result_id}, done{result_ids, report}, error{code,message}, cancelled.

Configuration

The app sets these values in Settings → Intelligence. If you use the engine without the app, set these environment variables.

Variable	Use
DMLX_PROMPT_ASSISTANT_MODEL	Agent model id (for example, ministral-3-3b-instruct-2512-4bit)
DMLX_PROMPT_ASSISTANT=off	Sets the agent to off
DMLX_ROUTER_BASE_URL, DMLX_ROUTER_MODEL, DMLX_ROUTER_API_KEY, DMLX_ROUTER_TIMEOUT	Routes messages without the agent, through any OpenAI-compatible chat server (HTTPS, or HTTP on loopback)
DMLX_ROUTER_PROVIDER=local-llm, DMLX_LOCAL_LLM_MODEL_PATH, DMLX_LOCAL_LLM_REVISION	Routes messages without the agent, through a local Qwen checkpoint (“Local Qwen MLX” in the app)
DMLX_PROMPT_BASE_URL, DMLX_PROMPT_MODEL, DMLX_PROMPT_API_KEY, DMLX_PROMPT_TIMEOUT	Prompt enhancement through an OpenAI-compatible server

If you set API keys in the app, the app keeps them in the macOS Keychain. When the agent plans, the engine also does a check of its answer. The images that the answer names must exist. An edit must use 1–3 images. The answer can use only workflows that an installed model can run. If the answer is still not valid after one retry, the app asks the user and does not guess.