allora/README.md

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# Basic Price Prediction Node
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This repository provides an example [Allora network](https://docs.allora.network/) worker node, designed to offer price predictions. The primary objective is to demonstrate the use of a basic inference model running within a dedicated container, showcasing its integration with the Allora network infrastructure to contribute valuable inferences.
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## Components
- **Worker**: The node that publishes inferences to the Allora chain.
- **Inference**: A container that conducts inferences, maintains the model state, and responds to internal inference requests via a Flask application. This node operates with a basic linear regression model for price predictions.
- **Updater**: A cron-like container designed to update the inference node's data by daily fetching the latest market information from the data provider, ensuring the model stays current with new market trends.
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Check the `docker-compose.yml` file for the detailed setup of each component.
## Docker-Compose Setup
A complete working example is provided in the `docker-compose.yml` file.
### Steps to Setup
1. **Clone the Repository**
2. **Copy and Populate Model Configuration environment file**
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Copy the example .env.example file and populate it with your variables:
```sh
cp .env.example .env
```
Here are the currently accepted configurations:
- TOKEN
Must be one in ['ETH','SOL','BTC','BNB','ARB'].
Note: if you are using `Binance` as the data provider, any token could be used.
If you are using Coingecko, you should add its `coin_id` in the [token_map here](https://github.com/allora-network/basic-coin-prediction-node/blob/main/updater.py#L107). Find [more info here](https://docs.coingecko.com/reference/simple-price) and the [list here](https://docs.google.com/spreadsheets/d/1wTTuxXt8n9q7C4NDXqQpI3wpKu1_5bGVmP9Xz0XGSyU/edit?usp=sharing).
- TRAINING_DAYS
Must be an `int` >= 1.
Represents how many days of historical data to use.
- TIMEFRAME
This should be in this form: `10m`, `1h`, `1d`, etc.
Note: For Coingecko, Data granularity (candle's body) is automatic - [see here](https://docs.coingecko.com/reference/coins-id-ohlc). To avoid downsampling, it is recommanded to use with Coingecko:
- TIMEFRAME >= 30m if TRAINING_DAYS <= 2
- TIMEFRAME >= 4h if TRAINING_DAYS <= 30
- TIMEFRAME >= 4d if TRAINING_DAYS >= 31
- MODEL
Must be one in ['LinearRegression','SVR','KernelRidge','BayesianRidge'].
You can easily add support for any other models by [adding it here](https://github.com/allora-network/basic-coin-prediction-node/blob/main/model.py#L133).
- REGION
Must be `EU` or `US` - it is used for the Binance API.
- DATA_PROVIDER
Must be `Binance` or `Coingecko`. Feel free to add support for other data providers to personalize your model!
- CG_API_KEY
This is your `Coingecko` API key, if you've set `DATA_PROVIDER=coingecko`.
3. **Copy and Populate Worker Configuration**
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Copy the example configuration file and populate it with your variables:
```sh
cp config.example.json config.json
```
4. **Initialize Worker**
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Run the following commands from the project's root directory to initialize the worker:
```sh
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chmod +x init.config
./init.config
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```
These commands will:
- Automatically create Allora keys for your worker.
- Export the needed variables from the created account to be used by the worker node, bundle them with your provided `config.json`, and pass them to the node as environment variables.
5. **Faucet Your Worker Node**
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You can find the offchain worker node's address in `./worker-data/env_file` under `ALLORA_OFFCHAIN_ACCOUNT_ADDRESS`. [Add faucet funds](https://docs.allora.network/devs/get-started/setup-wallet#add-faucet-funds) to your worker's wallet before starting it.
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6. **Start the Services**
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Run the following command to start the worker node, inference, and updater nodes:
```sh
docker compose up --build
```
To confirm that the worker successfully sends the inferences to the chain, look for the following log:
```
{"level":"debug","msg":"Send Worker Data to chain","txHash":<tx-hash>,"time":<timestamp>,"message":"Success"}
```
## Testing Inference Only
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This setup allows you to develop your model without the need to bring up the offchain worker or the updater. To test the inference model only:
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1. Run the following command to start the inference node:
```sh
docker compose up --build inference
```
Wait for the initial data load.
2. Send requests to the inference model. For example, request ETH price inferences:
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```sh
curl http://127.0.0.1:8000/inference/ETH
```
Expected response:
```json
{"value":"2564.021586281073"}
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```
3. Update the node's internal state (download pricing data, train, and update the model):
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```sh
curl http://127.0.0.1:8000/update
```
Expected response:
```sh
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0
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```