Learning Service

A service to learn about Olas agents and Open Autonomy.

System requirements

• Python >=3.10
• Tendermint ==0.34.19
• IPFS node ==0.6.0
• Pip
• Poetry
• Docker Engine
• Docker Compose
• Set Docker permissions so you can run containers as non-root user

Run you own agent

Get the code

1. Clone this repo:

   git clone git@github.com:valory-xyz/academy-learning-service-template.git
   

2. Create the virtual environment:

   cd academy-learning-service
   poetry shell
   poetry install
   

3. Sync packages:

   autonomy packages sync --update-packages
   

Prepare the data

1. Prepare a keys.json file containing wallet address and the private key for each of the four agents.

   autonomy generate-key ethereum -n 4
   

2. Prepare a ethereum_private_key.txt file containing one of the private keys from keys.json. Ensure that there is no newline at the end.

3. Deploy a Safe on Gnosis (it's free) and set your agent addresses as signers. Set the signature threshold to 3 out of 4.

4. Create a Tenderly account and from your dashboard create a fork of Gnosis chain (virtual testnet).

5. From Tenderly, fund your agents and Safe with a small amount of xDAI, i.e. $0.02 each.

6. Make a copy of the env file:

   cp sample.env .env
   

7. Fill in the required environment variables in .env. These variables are: ALL_PARTICIPANTS, GNOSIS_LEDGER_RPC, COINGECKO_API_KEY and SAFE_CONTRACT_ADDRESS. You will need to get a Coingecko. Set GNOSIS_LEDGER_RPC to your Tenderly fork Admin RPC.

Run a single agent

1. Verify that ALL_PARTICIPANTS in .env contains only 1 address.

2. Run the agent:

   bash run_agent.sh
   

Run the service (4 agents)

1. Check that Docker is running:

   docker
   

2. Verify that ALL_PARTICIPANTS in .env contains 4 addresses.

3. Run the service:

   bash run_service.sh
   

4. Look at the service logs for one of the agents (on another terminal):

   docker logs -f learningservice_abci_0