Package: agents-bar
Agents Bar Python ClientThis package is a python client forAgents Barservice.
It isn't supposed to be used in an isolation and you are supposed to have an existing account.
Check the website for more information about the service,
or check theAgents Bar Docsto learn more how to use this client.Quick startThe client allows to communicate with service by wrapping around APIs and coveraging common use patterns.A common usage is replacing your deep reinforcement learning agent with an entity that usesstepandactAPIs for progressing agent and infering action, respectively.
For usage examples as Google Colab checkDoc's quick startlink and for scripts checkexamplesdirectory.For a minimal (almost) working example check this code snippet:fromagents_barimportClient,RemoteAgentfromagents_barimportenvironments# Define client to communicate with https://agents.bar. Make sure it's authenticated.client=Client()# Create an environment. Simple one is "CartPole-v1" from OpenAI gym repo.env_name="CartPole"environments.create(client,config={"name":env_name,"config":{"gym_name":"CartPole-v1"}})# Create an agent. Since environment is discrete we use DQN.agent=RemoteAgent(client,agent_name="CartPoleAgent")agent.create_agent(obs_size=4,action_size=2,agent_model="DQN")# Initiat learning loop. Observe env's state, pass to agent, make a decision (action), execute on env. Repeat.obs=environments.reset(client,env_name)foriterationinrange(10):action=agent.act(obs)out=environments.step(client,env_name,step={"actions":[action],"commit":True})next_obs,reward,done=out.get("observation"),out.get("reward"),done.get("done")agent.step(obs,action,reward,next_obs,done)obs=next_obsSupportAgents Bar Client currently supports manipulation of agents, environments and experimnets.
We also provide an abstraction over agent which allows you to use the agent as an object, the same as you are already using it.The client is intended to be used for easy communication.
Check documentation for all available APIs. In most cases they should be the same as you see inhttps://agents.bar/docs.InstallationPip (Recommended)The latest stable version should always be accessible throughpipasagents-bar. To install locally addagents-barto your dependency file, e.g. requirements.txt, or install it directly usingpip install agents-barGitHub sourceCheckout this package usinggit clone git@github.com:agents-bar/agents-bar-client-python. This will create a new directoryagents-bar-client-python. Go ahead, enter the directory and install the package viapip install -e ..Notewe recommend having a separate python environment for standalone projects, e.g. usingpython -m venvcommand.AuthenticationTo use the client you need to be pass Agents Bar credentials or some proof that you're a user, e.g.access_token. There are a few ways how to authenticate your client.Note: Never store your credentials in places easy accessible by others. This includesgitrepositories that have the slightest chance to leave your computer. Definitely nothing that goes to the GitHub/GitLab.Environment variables (suggested)Currently suggested approach for authentication is to set your token or credentials as environment variables.
The client looks first forAGENTS_BAR_ACCESS_TOKENand uses that as its access token.
You can use this approach if you want to login using a different application with securely stored credentials and temporarily set the access token. Otherwise, you can also set your username and password inAGENTS_BAR_USERNAMEandAGENTS_BAR_PASSWORD, respectively.As an example, in unix, you can set environment variables by usingexportcommand in shellexportAGENTS_BAR_ACCESS_TOKEN=<access_token>
...or...exportAGENTS_BAR_USERNAME=<username>exportAGENTS_BAR_PASSWORD=<password>Instantiating with credentialsTheRemoteClientcan authenticate usingaccess_tokenor credentials (usernameandpassword) provided when instantiating the agent.
Only one of these is required and theaccess_tokenhas priority over credentials pair.
Also, note that directly passed variables have priority over the environment variables.access_token="<access_token>"username="<username>"password="<password>"client=RemoteClient(...,access_token=access_token,username=username,password=password)