IEKit

IEKit The Impact Evaluator Kit (IEKit) is an enhanced version of the CoordinationKit, which leverages Ceramic streams to automate the tracking and rewarding of users' contributions on the ecosystem. We provide a demo agent service based on the IEKit which is designed to track contributions in the form of Twitter mentions of the Autonolas DAO (@autonolas). Generic scores can be also read from a Ceramic stream. The demo service implements three main features:

Monitor for new users' registrations. Reads registered users both from tweets that contain the #olas hashtag and also from a Ceramic stream that contains user data like discord ids and wallet addresses.
Monitor for users' contributions. The service periodically scans for new mentions of @autonolas on Twitter and updates to the scores stream, and increments and updates the score of the corresponding user.
Update the badge of users according to their score. To access the badge image associated to a user's NFT, the metadata URI associated to it is redirected to an agent in the service. Upon reading the concrete NFT from the request, the service provides the IPFS address of the image, which is updated periodically in relation to the user's score.

The demo service uses dedicated Ceramic streams as a persistent solution to store users' scores and registration metadata. The service demonstrates the applicability of the IEKit to build a particular use case, but of course, the IEKit is modular by design and can be adapted to a range of custom impact evaluators.

Demo

Important

This section is under active development - please report issues in the Autonolas Discord.

In order to run a local demo service based on the IEKit:

Set up your system to work with the Open Autonomy framework. We recommend that you use these commands:

mkdir your_workspace && cd your_workspace
touch Pipfile && pipenv --python 3.10 && pipenv shell

pipenv install open-autonomy[all]==0.14.6
autonomy init --remote --ipfs --reset --author=your_name

Fetch the IEKit.

autonomy fetch valory/impact_evaluator:0.1.0:bafybeifckp2jegwhbacpowlutgxzwcihe3gy4srzxzfele4xmyulmj4i4a --service

Build the Docker image of the service agents

cd impact_evaluator
autonomy build-image

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

Example of a keys.json file

WARNING: Use this file for testing purposes only. Never use the keys or addresses provided in this example in a production environment or for personal use.

[
  {
      "address": "0x15d34AAf54267DB7D7c367839AAf71A00a2C6A65",
      "private_key": "0x47e179ec197488593b187f80a00eb0da91f1b9d0b13f8733639f19c30a34926a"
  },
  {
      "address": "0x9965507D1a55bcC2695C58ba16FB37d819B0A4dc",
      "private_key": "0x8b3a350cf5c34c9194ca85829a2df0ec3153be0318b5e2d3348e872092edffba"
  },
  {
      "address": "0x976EA74026E726554dB657fA54763abd0C3a0aa9",
      "private_key": "0x92db14e403b83dfe3df233f83dfa3a0d7096f21ca9b0d6d6b8d88b2b4ec1564e"
  },
  {
      "address": "0x14dC79964da2C08b23698B3D3cc7Ca32193d9955",
      "private_key": "0x4bbbf85ce3377467afe5d46f804f221813b2bb87f24d81f60f1fcdbf7cbf4356"
  }
]

Prepare the environment and build the service deployment.

Create Twitter API Authentication Tokens and an OpenAI API key.
Create a Ceramic Decentralized Identity (DID) using Glaze.
Using the DID created in the previous step, create three empty Ceramic streams. The service will optionally read generic scores from the first one and will write scores to the second one. The third one will store some tool configurations. Alternatively, the create_streams.py script from the IEKit repo can be used to create some dummy streams.
Create an API key for Infura or your preferred provider. You will need both Ethereum and Gnosis Chain RPCs.
Deploy a Safe on Gnosis chain and set your agents as the owners so they can interact with it. The service will send Mech requests using the Safe. Alternatively, use Olas protocol frontend to mint the service, and a Safe will be automatically deployed for you.

Create an .env file with the required environment variables, modifying its values to your needs.

ETHEREUM_LEDGER_CHAIN_ID=1
GNOSIS_LEDGER_CHAIN_ID=100
DYNAMIC_CONTRIBUTION_CONTRACT_ADDRESS=0x02C26437B292D86c5F4F21bbCcE0771948274f84
CERAMIC_DID_STR=z6MkszfuezSP8ftgHRhMr8AX8uyTjtKpcia4bP19TBgmhEPs
CERAMIC_DID_SEED=9a683e9b21777b5b159974c35c4766bc0c4522855aefc8de30876dbaa252f179
RESET_PAUSE_DURATION=30
CERAMIC_API_BASE=https://ceramic-clay.3boxlabs.com/
EARLIEST_BLOCK_TO_MONITOR=16097553
RESET_TENDERMINT_AFTER=5
TWITTER_SEARCH_ARGS=query=%23OlasNetwork&tweet.fields=author_id,created_at,conversation_id&user.fields=name&expansions=author_id&max_results=100&since_id={since_id}
MAX_POINTS_PER_PERIOD=5000
USE_ACN=false
TWITTER_TWEETS_ARGS=tweet.fields=author_id,created_at,conversation_id&user.fields=name&expansions=author_id&max_results=10&start_time={start_time}
DEFAULT_CHAIN_ID=gnosis
USE_STAGING_API=true
TWITTER_API_BASE=https://api.twitter.com/
TWITTER_MENTIONS_ENDPOINT=twitter/2/users/1/mentions?
TWITTER_SEARCH_ENDPOINT=twitter/2/tweets/search/recent?
MECH_CONTRACT_ADDRESS=0x77af31De935740567Cf4fF1986D04B2c964A786a
STAGING_API_TWITTER=http://host.docker.internal:5000/twitter/create_tweet
TRANSACTION_SERVICE_URL=https://safe-transaction-goerli.safe.global/api/v1/messages/{message_hash}/
WVEOLAS_ADDRESS=0xa2AA89938805836077aB0724f335142da7A27085
USE_TERMINATION=false
POINTS_TO_IMAGE_HASHES='{"0":"bafybeiabtdl53v2a3irrgrg7eujzffjallpymli763wvhv6gceurfmcemm","100":"bafybeid46w6yzbehir7ackcnsyuasdkun5aq7jnckt4sknvmiewpph776q","50000":"bafybeigbxlwzljbxnlwteupmt6c6k7k2m4bbhunvxxa53dc7niuedilnr4","100000":"bafybeiawxpq4mqckbau3mjwzd3ic2o7ywlhp6zqo7jnaft26zeqm3xsjjy","150000":"bafybeie6k53dupf7rf6622rzfxu3dmlv36hytqrmzs5yrilxwcrlhrml2m"}'

# Fill in the following variables
# -------------------------------

# RPCS
ETHEREUM_LEDGER_RPC=
GNOSIS_LEDGER_RPC=

# Agent addresses and Safe. Agents must be owners of the safe, which is used for Mech interactions.
ALL_PARTICIPANTS='["<agent_address>","<agent_address>","<agent_address>"."<agent_address>"]'
SAFE_CONTRACT_ADDRESS=

# The following var contains multiple secrets: Orbis context, dids, and multiple Twitter and OpenAI tokens
TWITTER_API_BEARER_TOKEN=
OPENAI_API_KEY_0=
CENTAUR_ID_TO_SECRETS='{"1":{"orbis":{"context":"","did_seed":"9a683e9b21777b5b159974c35c4766bc0c4522855aefc8de30876dbaa252f179","did_str":"z6MkszfuezSP8ftgHRhMr8AX8uyTjtKpcia4bP19TBgmhEPs"},"twitter":{"consumer_key":"<your_consumer_key>","consumer_secret":"<your_consumer_secret>","access_token":"<your_access_token>","access_secret":"<your_access_secret>"}}}'

# Ceramic streams (use the create_streams.py script to create some dummy streams)
CERAMIC_DB_STREAM_ID=
CENTAURS_STREAM_ID=
MANUAL_POINTS_STREAM_ID=

and export them:

export $(grep -v '^#' .env | xargs)

Copy the keys.json file inside the service's folder.
Build the service deployment.
```
autonomy deploy build keys.json -ltm
```

Run the service.
```
cd abci_build
autonomy deploy run
```
You can cancel the local execution at any time by pressing Ctrl+C.
Check that the service is running. Open a separate terminal and execute the command below. You should see the service transitioning along different states.
```
docker logs -f impactevaluator_abci_0 | grep -E 'Entered|round is done'
```

You can try some examples on how to curl the service endpoints from inside one of the agent containers. For example:

# Get the metadata for the token with id=1
curl localhost:8000/1 | jq

# Output
{
  "title": "Autonolas Contribute Badges",
  "name": "Badge 1",
  "description": "This NFT recognizes the contributions made by the holder to the Autonolas Community.",
  "image": "ipfs://bafybeiabtdl53v2a3irrgrg7eujzffjallpymli763wvhv6gceurfmcemm",
  "attributes": []
}

# Get the service health status
curl localhost:8000/healthcheck | jq

# Output
{
  "seconds_since_last_reset": 15.812911033630371,
  "healthy": true,
  "seconds_until_next_update": -5.812911033630371
}

Build

Fork the IEKit repository.
Make the necessary adjustments to tailor the service to your needs. This could include:
- Adjust configuration parameters (e.g., in the service.yaml file).
- Expand the service finite-state machine with your custom states.
Run your service as detailed above.

Looking for help building your own?

Refer to the Autonolas Discord community, or consider ecosystem services like Valory Propel for the fastest way to get your first autonomous service in production.