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Human Lambdas

Human Lambdas is an open source Human in the Loop platform for anyone to run their own private Mechanical Turk.

How it works

It is designed to provide an all-in-one solution to build, operate and monitor Human in the Loop processes. Its highly flexible, composable and user-friendly UI is designed to enable anyone to easily support all sorts of bespoke manual tasks. Some examples are: data annotation, data cleaning, quality assurance, data extraction, sales research, content moderation, customer operations...

Learn more

• Sample Use Cases
• Documentation
• Manual
• API

Getting Started

We are going to run Human Lambdas on a developer device.

Please ensure you have Docker installed.

mkdir .human_lambdas # create data directory

docker run \
  -p 8000:8000 \
  -it \
  --rm \
  -v $(pwd)/.human_lambdas:/.human_lambdas \
  hlambdas/human-lambdas:v1.0

A shell should eventually start inside the container.

Now initialize a sqlite database in your .human_lambdas dir

human-lambdas initdb

Start the server

human-lambdas up

Human Lambdas is now running against a Sqlite database stored in your working directory.

Check out the server at http://localhost:8000 .

Note: It is best to use incognito or clear cookies if you have used it before without setting a Django SECRET_KEY

Next Try defining your first queue by following this guide.

Run with Docker and Postgres

Human Lambdas requires a database for storing user and task data. When you deploy an instance for your team it is best to use a production-grade database such as Postgres.

You can use a managed Postgres product such as Amazon RDS, or use a Docker container as follows.

When starting your container, pass in authentication details in environment variables.

export POSTGRES_USER=hlambda
export POSTGRES_DB=hlambda
export POSTGRES_PASSWORD=some_password

docker run \
  -p 5432:5432 \
  -e "POSTGRES_USER=$POSTGRES_USER" \
  -e "POSTGRES_PASSWORD=$POSTGRES_PASSWORD" \
  -e "POSTGRES_DB=$POSTGRES_DB" \
  postgres:10

Then initialise your database and start the Human Lambdas server in another container:

export POSTGRES_HOST="host.docker.internal" # Note: This assumes you are trying this out on OS X
export POSTGRES_PORT=5432
export POSTGRES_USER=hlambda
export POSTGRES_DB=hlambda
export POSTGRES_PASSWORD=some_password
docker run \
  -it \
  --rm \
  -e "POSTGRES_HOST=$POSTGRES_HOST" \
  -e "POSTGRES_PORT=$POSTGRES_PORT" \
  -e "POSTGRES_USER=$POSTGRES_USER" \
  -e "POSTGRES_PASSWORD=$POSTGRES_PASSWORD" \
  -e "POSTGRES_DB=$POSTGRES_DB" \
  --entrypoint=bash \
  -p 8000:8000 \
  -v $(pwd)/.human_lambdas:/.human_lambdas \
  hlambdas/human-lambdas:v1.0 \
  -c 'hl initdb && hl up'

Human Lambdas is now available on localhost:8000.

This approach lets you use Human Lambdas in stateless environments such as Google Cloud Run as long as

1. You do not run initdb on startup, as it is not thread-safe
2. You set a single SECRET_KEY environment variable so that all Django Invite/Session tokens work

Directly install Python Package

Requires Python 3.

pip install human-lambdas