This project provide a rest API for gym. The aim is to provide a simple way to build and test RL algorithms in other languages than python.
Stay tunned for the first client that uses this: scala-gym
- Running it locally:
➜ gym-server git:(master) ✗ pip install -r requirements.txt
➜ gym-server git:(master) ✗ ./start.shPull the image form docker hub: flaviotruzzi/gym-server:latest
Running: docker run -p 5000:5000 -p 8000:8000 -it flaviotruzzi/gym-server:latest
- Install docker.
- Build docker image with:
➜ gym-server git:(master) ✗ docker build -t gym-server:latest .➜ gym-server git:(master) ✗ curl http://localhost:5000/v1/help{
"v1": {
"/v1/envs/<instance_id>/info": {
"doc": "Expose useful information, such as: action_space, and observation_space.\n :return:",
"methods": "HEAD,OPTIONS,GET"
},
"/v1/envs/<instance_id>/monitor/close/": {
"doc": "Stop monitoring.\n :param instance_id:\n :return:",
"methods": "POST,OPTIONS"
},
"/v1/envs/<instance_id>/monitor/start/": {
"doc": "Start monitoring. Accept json with the following format:\n {\n 'force': true,\n 'resume: false\n }\n :param instance_id:\n :return:",
"methods": "POST,OPTIONS"
},
"/v1/envs/<instance_id>/reset/": {
"doc": "Reset environment. Accept json to say if it should render or not.\n\n {\n \"render\": false\n }\n\n :param instance_id:\n :return: first observation",
"methods": "POST,OPTIONS"
},
"/v1/envs/<instance_id>/step/": {
"doc": "Execute given action.\n\n Accept json with the following format:\n {\n 'action': 0,\n 'render': true\n }\n\n The API assumes that action is an integer. Render can be set to expose the rendered image. Render is optional.\n\n :param instance_id:\n :param action: Integer value representing the action.\n :return: json with environment response.",
"methods": "POST,OPTIONS"
},
"/v1/envs/<instance_id>/upload/": {
"doc": ":param instance_id:\n :return:",
"methods": "POST,OPTIONS"
},
"/v1/envs/create/": {
"doc": "Create Environment. Accept a json with the following format:\n {\n 'environment': 'CartPole-v0'\n }\n\n :return: json with instance_id of the environment",
"methods": "POST,OPTIONS"
},
"/v1/help": {
"doc": ":return: Friendly start message.",
"methods": "HEAD,OPTIONS,GET"
}
}
}%Create an Environment, return the instance id.
➜ gym-server git:(master) ✗ curl -H "Content-Type: application/json" \
-XPOST http://localhost:5000/v1/envs/create/ \
-d '{"environment": "CartPole-v0"}'{
"instance_id": "ce2dbb50"
}%Reset the environment, and generate an image of the current state.
➜ gym-server git:(master) ✗ curl -XPOST -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/reset/ \
-d '{"render": true}'{
"observation": {
"observation": [
0.005304555907637974,
0.03223077653449176,
-0.04756061105355254,
-0.03335494425626853
],
"render": "successfully rendered: 1.png"
}
}%Execute one step passing an action.
➜ gym-server git:(master) ✗ curl -XPOST -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/step/ \
-d '{"action": 1}'{
"done": false,
"info": {},
"observation": [
0.0059491714383278094,
0.22800135862141657,
-0.048227709938677914,
-0.3406563021698157
],
"reward": 1.0
}%The artifacts generated through the monitor are available through port 8000.
Start monitoring.
➜ gym-server git:(master) ✗ curl -XPOST -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/monitor/start/ \
-d '{"force": false, "resume": false}'
{
"message": true
}%Stop monitoring.
➜ gym-server git:(master) ✗ curl -XPOST -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/monitor/stop/
{
"message": true
}%Upload results stored by the monitoring.
➜ gym-server git:(master) ✗ curl -XPOST -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/upload/ -d \
'{
"algorithm_id": "my_id",
"writeup": "http://mygist",
"api_key": "my_apikey",
"ignore_open_monitors": true
}'
{
"message": true
}%Provide some information about the environment, such as, action space and observation space.
➜ gym-server git:(master) ✗ curl -XGET -H "Content-Type: application/json" \
http://localhost:5000/v1/envs/ce2dbb50/info
{
"action_space": "Discrete(2)",
"observation_space": {
"high": [
2.4,
Infinity,
0.41887902047863906,
Infinity
],
"low": [
-2.4,
-Infinity,
-0.41887902047863906,
-Infinity
],
"shape": [
4
]
}
}%The images generated are available at: http://localhost:8000/ce2dbb50/rendered/
The files of your simulation are available at: http://localhost:8000/ce2dbb50/simulation/
You can also access http://localhost:8000/render.html?instance_id=ce2dbb50, this is updated every 500ms showing the last generated image.
Note that all ips depends where your docker is running or if you are running it locally.
- Provide API for getting statistics of simulation
- Provide clients:
- - scala (in progress)
- - python
- - java
- - go
- - want another one? You can also contribute ;)
- Ideas? Create an issue!
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request :D
- @catherio: idea of EnvironmentManager, and most of its implementation. Also a lot of influence on the API.