A quickstart for the trader agent for AI prediction markets on Gnosis at https://github.com/valory-xyz/trader
- Windows 10/11: WSL2 / Git BASH
- Mac ARM / Intel
- Linux
- Raspberry Pi 4
Ensure your machine satisfies the requirements:
- Python
==3.10
- Poetry
>=1.4.0
- Docker Engine
<25.0.0
- Docker Compose
- You need xDAI on Gnosis Chain in one of your wallets.
- You need an RPC for your agent instance. We recommend Nodies RPC.
Clone this repository locally and execute:
chmod +x run_service.sh
./run_service.sh
Answer 'No' when prompted:
Do you want to use staking in this service? (yes/no): n
⚠️ Warning
The code within this repository is provided without any warranties. It is important to note that the code has not been audited for potential security vulnerabilities. Using this code could potentially lead to loss of funds, compromised data, or asset risk. Exercise caution and use this code at your own risk. Please refer to the LICENSE file for details about the terms and conditions.
Before you proceed, ensure you have at least 20 OLAS on Gnosis Chain. For more information on staking, checkout the following blogpost.
Clone this repository locally and execute:
chmod +x run_service.sh
./run_service.sh
Answer 'Yes' when prompted:
Do you want to use staking in this service? (yes/no): y
Find below a diagram of the possible status a service can be in the Alpine staking program:
Services can become staked by invoking the stake()
contract method, where service parameters and deposit amounts are verified. Staked services can call the checkpoint()
method at regular intervals, ensuring liveness checks and calculating staking incentives. In case a service remains inactive beyond the specified maxAllowedInactivity
time, it faces eviction from the staking program, ceasing to accrue additional rewards. Staked or evicted services can unstaked by calling the unstake()
contract method. They can do so after minStakingDuration
has passed or if no more staking rewards are available.
Notes:
- Staking is currently in a testing phase, so the number of trader agents that can be staked might be limited.
- In the Alpine staking program services are evicted after accumulating 2 consecutive checkpoints without meeting the activity threshold.
- Currently, the minimum staking time is approximately 3 days. In particular, a service cannot be unstaked during the minimum staking period.
Once the command has completed, i.e. the service is running, you can see the live logs with:
docker logs trader_abci_0 --follow
To stop your agent, use:
./stop_service.sh
Agent runners are recommended to create a backup of the relevant secret key material.
-
Use the
trades
command to display information about placed trades by a given address:cd trader; poetry run python ../trades.py --creator YOUR_SAFE_ADDRESS; cd ..
Or restrict the search to specific dates by defining the "from" and "to" dates:
cd trader; poetry run python ../trades.py --creator YOUR_SAFE_ADDRESS --from-date 2023-08-15:03:50:00 --to-date 2023-08-20:13:45:00; cd ..
-
Use the
report
command to display a summary of the service status:cd trader; poetry run python ../report.py; cd ..
-
Use this command to investigate your agent's logs:
cd trader; poetry run autonomy analyse logs --from-dir trader_service/abci_build/persistent_data/logs/ --agent aea_0 --reset-db; cd ..
For example, inspect the state transitions using this command:
cd trader; poetry run autonomy analyse logs --from-dir trader_service/abci_build/persistent_data/logs/ --agent aea_0 --fsm --reset-db; cd ..
This will output the different state transitions of your agent per period, for example:
For more options on the above command run:
cd trader; poetry run autonomy analyse logs --help; cd ..
or take a look at the command documentation.
Simply pull the latest script:
git pull origin
Remove the existing trader folder:
rm -rf trader
Then continue above with "Run the script".
⚠️ Warning
The code within this repository is provided without any warranties. It is important to note that the code has not been audited for potential security vulnerabilities.If you are updating the password for your key files, it is strongly advised to create a backup of the old configuration (located in the
./trader_runner
folder) before proceeding. This backup should be retained until you can verify that the changes are functioning as expected. For instance, run the service multiple times to ensure there are no issues with the new password before discarding the backup.
If you have started you script specifying a password to protect your key files, you can change it by running the following command:
cd trader; poetry run python ../scripts/change_keys_json_password.py ../.trader_runner --current_password <current_password> --new_password <new_password>; cd ..
This will change the password in the following files:
.trader_runner/keys.json
.trader_runner/operator_keys.json
.trader_runner/agent_pkey.txt
.trader_runner/operator_pkey.txt
If your key files are not encrypted, you must not use the --current-password
argument. If you want to remove the password protection of your key files,
you must not specify the --new-password
argument.
In Docker Desktop make sure that in Settings -> Advanced
the following boxes are ticked
We provide some hints to have your Windows system ready to run the agent. The instructions below have been tested in Windows 11.
Execute the following steps in a PowerShell terminal:
-
Install Git and Git Bash:
winget install --id Git.Git -e --source winget
-
Install Python 3.10:
winget install Python.Python.3.10
-
Close and re-open the PowerShell terminal.
-
Install Poetry:
curl.exe -sSL https://install.python-poetry.org | python -
-
Add Poetry to your user's path:
$existingUserPath = (Get-Item -Path HKCU:\Environment).GetValue("PATH", $null, "DoNotExpandEnvironmentNames") $newUserPath = "$existingUserPath;$Env:APPDATA\Python\Scripts" [System.Environment]::SetEnvironmentVariable("Path", $newUserPath, "User")
-
Install Docker Desktop:
winget install -e --id Docker.DockerDesktop
-
Log out of your Windows session and then log back in.
-
Open Docker Desktop and leave it opened in the background.
Now, open a Git Bash terminal and follow the instructions in the "Run the script" section as well as the subsequent sections. You might need to install Microsoft Visual C++ 14.0 or greater.
This chapter is for advanced users who want to further customize the trader agent's behaviour without changing the underlying trading logic.
This script automatically sets some default weights to the agent's policy as a warm start to help convergence and improve tool selection. These data were obtained after many days of running the service and are set here. As a result, the current weights are always deleted and replaced by this strategy which is considered to boost the initial performance of the service.
However, you may have found better performing policy weights and would like to remove this logic.
It can easily be done, by removing this method call,
here,
in order to set your own custom warm start.
Setting your own custom weights can be done by editing the corresponding files in .trader_runner
.
Moreover, you may store your current policy as a backup before editing those files, using the following set of commands:
cp ".trader_runner/available_tools_store.json" ".trader_runner/available_tools_store_$(date +"%d-%m-%Y")".json
cp ".trader_runner/policy_store.json" ".trader_runner/policy_store_$(date +"%d-%m-%Y")".json
cp ".trader_runner/utilized_tools.json" ".trader_runner/utilized_tools_$(date +"%d-%m-%Y")".json
Sometimes, a mech tool might temporarily return invalid results.
As a result, the service would end up performing mech calls without being able to use the response.
Assuming that this tool has a large reward rate in the policy weights,
the service might end up spending a considerable amount of xDAI before adjusting the tool's reward rate,
without making any progress.
If a tool is temporarily misbehaving, you could use an environment variable in order to exclude it.
This environment variable is defined
here
and can be overriden by setting it anywhere in the run_service.sh
script with a new value, e.g.:
IRRELEVANT_TOOLS=["some-misbehaving-tool", "openai-text-davinci-002", "openai-text-davinci-003", "openai-gpt-3.5-turbo", "openai-gpt-4", "stabilityai-stable-diffusion-v1-5", "stabilityai-stable-diffusion-xl-beta-v2-2-2", "stabilityai-stable-diffusion-512-v2-1", "stabilityai-stable-diffusion-768-v2-1"]
When executed for the first time, the run_service.sh
script creates a number of Gnosis chain accounts:
- one EOA account will be used as the service owner and agent operator,
- one EOA account will be used for the trading agent, and
- one smart contract account corresponds to a Safe wallet with a single owner (the agent account).
The addresses and private keys of the EOA accounts (plus some additional configuration) are stored within the folder .trader_runner
. In order to avoid losing your assets, back up this folder in a safe place, and do not publish or share its contents with unauthorized parties.
You can gain access to the assets of your service as follows:
-
Ensure that your service is stopped by running
stop_service.sh
. -
Ensure that you have a hot wallet (e.g., MetaMask) installed and set up in your browser.
-
Import the two EOAs accounts using the private keys. In MetaMask, select "Add account or hardware wallet" → "Import account" → "Select Type: Private Key", and enter the private key of the owner/operator EOA account (located in
.trader_runner/operator_pkey.txt
): -
Repeat the same process with the agent EOA account (private key located in
.trader_runner/agent_pkey.json
).
Now, you have full access through the hot wallet to the EOAs addresses associated to your service and you can transfer their assets to any other address. You can also manage the assets of the service Safe through the DApp https://app.safe.global/, using the address located in the file .trader_runner/service_safe_address.txt
.
If you wish to terminate your on-chain service (and receive back the staking/bonding funds to your owner/operator address in case your service is staked) execute:
./stop_service.sh
./terminate_on_chain_service.sh
When updating the service, you may need to re-run the script if you obtain any of the following error messages:
Error: Service unbonding failed with following error; ChainTimeoutError(Timed out when waiting for transaction to go through)
Error: Component mint failed with following error; ChainTimeoutError(Timed out when waiting for transaction to go through)
Error: Service activation failed with following error; ChainTimeoutError(Timed out when waiting for transaction to go through)
Error: Service deployment failed with following error; ChainTimeoutError(Timed out when waiting for transaction to go through)
Error: Service terminatation failed with following error; ChainInteractionError({'code': -32010, 'message': 'AlreadyKnown'})