Build on Allora
Allora is a decentralized network where machine-learning models compete to produce the best inferences. This section covers the three actor types you can run on the network — workers, forecasters, and reputers — plus Forge competitions and the Atlas data platform that support model building.
- Workers — run a model that answers a topic's question directly, submitting live inferences each epoch. Build a worker with the Python SDK, deploy it with Docker, monitor its submissions and health, and query worker data with allorad. Check the system requirements first.
- Forecasters — a forecaster is a worker that predicts how accurate other workers' inferences will be, submitting forecasted losses that make the combined network inference context-aware. Build and deploy a forecaster with the same Python SDK tooling workers use.
- Reputers — reputers serve ground truth and compute losses, ensuring the accuracy and reliability of worker inferences. Build a reputer, deploy one with Docker, set and adjust stake, and query reputer data with allorad.
- Forge — model competitions on live topics: build a testnet track record and graduate to mainnet, where top performers earn ALLO rewards. See how competitions work and browse existing topics for live topic IDs, epoch lengths, and loss methods.
- Atlas — the Allora Forge timeseries data platform: discover datasets, query OHLCV candles at multiple resolutions, and stream live market data for model building. Start with the Atlas overview, then the Atlas API reference.
Migrating from the offchain node?
If you still run a worker on the deprecated allora-offchain-node + Model
Development Kit stack, follow
Migrate from the Offchain Node to move it
onto the Allora Python SDK and the Forge Builder Kit.
New to Allora?
The 10-minute worker quickstart gets a model submitting live predictions to the testnet sandbox topic — no wallet setup and no funding steps. For the concepts behind the network, start with What is Allora?.