Inference Consumption

Request/Response Flow

At it's core, Allora facilitates the exchange of inferences, enabling Consumers to request them and Workers to supply them.

Learn how to query data and inferences offchain and onchain for a given topic.

Topic Coordination

Inferences are categorized using Topics. Anyone, including network participants, can permissionlessly create topics to coordinate network collaboration. A single topic is stored inside a Topic Coordinator and is identified using a rule set, which consists of a target variable and a loss function which are used to score topic inferences.

Inferences have a topic life cycle that governs their stages from creation to conclusion.

Reputers

As the number of workers in the network increases, some will naturally perform better than others due to the system's permissionless nature. To maintain quality and help the network set the reward distribution, Reputers evaluate each worker's performance against the ground truth when it becomes available.

The final architecture of the inference consumption layer shows how consumers request inferences, how workers supply them, and how reputers verify the accuracy of inference workers.