rlcard-showdown/README.md

8.5 KiB

NOTE: This project is under final tesing. The one in the repo only supports the visualization of some sampled data. The full version will be available soon!

Frontend

Frontend Setup

RLCard-Showdown has separated frontend and backend. The frontend part is built with React and the backend is with Django.

Prerequisite

To set up the frontend part, you should make sure you have Node.js and NPM installed. Normally you just need to manually install Node.js, and the NPM package would be automatically installed together with Node.js for you. Please refer to its official website for installation of Node.js.

You can run the following commands to verify the installation

node -v
npm -v

Install Dependencies

The dependencies can be easily installed with the help of NPM:

git clone https://github.com/datamllab/rlcard-showdown.git
cd rlcard-showdown
npm install

Run Frontend in Development Mode

Run the following command under the project folder to start frontend in development mode.

npm start

The frontend would be started in port 3000 in localhost by default, you can view it by entering http://127.0.0.1:3000/ in the browser.

Config

You will see blank tables on the frontend if you haven't started the backend Django server, or the backend server URL is configured incorrectly.

The default configuration for backend server URL is http://127.0.0.1:8000/, you can also change it in /src/utils/config.js.

Screenshots

Django Server

Server Setup

Install dependencies:

pip install -r requirements.txt

Migrate the databases:

cd server
python manage.py makemigrations
python manage.py migrate

Run server:

python manage.py runserver

The default URL is http://127.0.0.1:8000/

REST API

The definitions of the fields are as follows:

  • eval_num: Integer. The number of evaluation times.
  • name: String. The name of the environment.
  • agent0: String. Model name.
  • agent1: String. Model name.
  • win: Boolean. True if model in the first seat wins.
  • payoff: Float. The payoff of the agent in the first seat.
  • index: Integer. The index of the game of the same environent and same agent. It is in the range [0, eval_num-1]
type Resource Parameters Description
GET tournament/launch eval_num, name Launch tournment on the game. Each pair of models will play eval_num times. Results will be saved in database.
GET tournament/query_game name, index, agent0, agent1, win, payoff, elements_every_page, page_index Query the games with the given parameters
GET tournament/query_payoff name, agent0, agent1, payoff Query the payoffs with the given parameters
GET tournament/query_agent_payoff name, elements_every_page, page_index, Query the payoffs of all the agents
GET tournament/replay name, agent0, agent1, index Return the replay data
POST tournament/upload_agent model(Python file), name, game, entry Upload a model file. name is model ID, entry is the class name of the model
GET tournament/delete_agent name Delete the agent of the given name
GET tournament/list_uploaded__agents game list all the uploaded agents
GET tournament/list_baseline__agents game list all the baseline agents

Example API

API Description
http://127.0.0.1:8000/tournament/launch?eval_num=200&name=leduc-holdem Evaluate on Leduc Holdem with 200 games for each pair of models
http://127.0.0.1:8000/tournament/replay?name=leduc-holdem&agent0=leduc-holdem-rule-v1&agent1=leduc-holdem-cfr&index=3 Obtain the replay data between rule model and CFR model. Obtain the data of the 3rd game
http://127.0.0.1:8000/tournament/query_game&elements_every_page=10&page_index=0 Get all the game data
http://127.0.0.1:8000/tournament/query_game?name=leduc-holdem&elements_every_page=10&page_index=0 Get all the game data of Leduc Holdem
http://127.0.0.1:8000/tournament/query_payoff Get all the payoffs
http://127.0.0.1:8000/tournament/query_payoff?agent0=leduc-holdem-cfr&agent1=leduc-holdem-rule-v1 Get all the payoffs between rule and CFR models
http://127.0.0.1:8000/tournament/query_agent_payoff?name=leduc-holdem&elements_every_page=1&page_index=1 Get the payoffs of all the agents of leduc-holdem
http://127.0.0.1:8000/tournament/list_uploaded_agents?game=leduc-holdem List the uploaded agents of leduc-holdem
http://127.0.0.1:8000/tournament/list_baseline_agents?game=leduc-holdem List the baseline agents of leduc-holdem

Registered Models

Some models have been pre-registered as baselines

Model Game Description
leduc-holdem-random leduc-holdem A random model
leduc-holdem-cfr leduc-holdem Pre-trained CFR model on Leduc Holdem
leduc-holdem-rule-v1 leduc-holdem A rule model that plays greedily
doudizhu-random doudizhu A random model
doudizhu-rule-v1 doudizhu Dou Dizhu rule model

Example of uploading a new model

A example model file is prepared:

cd server/upload_test

Upload the model with curl:

curl -F 'model=@example_model.py' -F "name=leduc-new" -F "entry=LeducHoldemRuleModelV2" -F "game=leduc-holdem" http://127.0.0.1:8000/tournament/upload_agent

Launch the tounament with:

curl 'http://127.0.0.1:8000/tournament/launch?eval_num=200&name=leduc-holdem'

We list the uploaded agent with

curl http://127.0.0.1:8000/tournament/list_uploaded_agents

We can delete the agent with

curl 'http://127.0.0.1:8000/tournament/delete_agent?name=leduc-new'