Configuration

Whether you start Label Studio via label-studio executable or server.py script directly, it reads server configuration settings from config.json file located inside the project directory.
You can modify this file, or create your own and pass it to Label Studio.

python server.py -c your_config.json

Server options

label_config

label_config configures UI for the Label tool.

"label_config": "../examples/chatbot/config.xml"

input_path

input_path for tasks: it can be a file or a directory. In the case of the directory, it reads all the files and creates a list of tasks.

"input_path": "./input/tasks.json"

output_dir

output_dir is used to store completions (labeling results) in JSON format. output_dir will be created automatically. Each task is mapped to a corresponding completion JSON file.

"output_dir": "./output"

Example: task a.json and b.json consist of 3 tasks and there will be 6 completion files in output_dir:

input/a.json = [{"text": "0"}, {"text": "1"}, {"text": "2"}]
input/b.json = [{"text": "3"}, {"text": "4"}, {"text": "5"}]

output/0.json = {"completions": [{"result": [...]}], "task": {"text": "0"}}  # a.json
output/1.json = {"completions": [{"result": [...]}], "task": {"text": "1"}}  # a.json
output/2.json = {"completions": [{"result": [...]}], "task": {"text": "2"}}  # a.json
output/3.json = {"completions": [{"result": [...]}], "task": {"text": "3"}}  # b.json
output/4.json = {"completions": [{"result": [...]}], "task": {"text": "4"}}  # b.json
output/5.json = {"completions": [{"result": [...]}], "task": {"text": "5"}}  # b.json

instruction

instruction Shows the instruction to a person who makes labeling

"instruction": "Type something to label experts!"

build_path

build_path points to the directory with JS, CSS and other media from the app

"editor": {
  "build_path": "../build/static",
  "debug": false,
  "interfaces": [
    "basic",
    "panel",
    "submit",
    "submit:load",
    "side-column",
    "submit:skip",
    "submit:check-empty",
    "predictions:hide"
  ],
}

title

title name of your service for the web

"title": "Label Studio",

port

Server port

"port": 8200

debug

Running web server in debug mode.

"debug": true,

ml_backend

Specify settings to integrate machine learning backend.

url

URL where ML backend serves, e.g. "http://localhost:9090"

model_name

Model name that is used to identify and store a trained model.

logger