How to Create a Topic

Inferences for the same domain are aggregated into the same topic

What is a Topic?

Topics are Schelling points (opens in a new tab) where disparate-but-alike data scientists and domain experts aggregate their predictions. For example, we might create a topic for predicting the future price of ETH. There, all experts with any talent in predicting the future price of ETH will submit their inferences. Topics vary by domain and parameterization, defining how these inferences are collected and valued.

Developers can make topics for arbitrary categories of inferences so long as they complete these steps:

Prerequisites:

A wallet with sufficient funds to at least cover gas. Use the faucet to get funds.
Allorad CLI tool

Explainer Video

Please see the video below to get a full deep-dive on the different parameters that make up a topic:

Tx Functions

These functions write to the appchain. Add the Command value into your query to retrieve the expected data.

allorad tx emissions [Command]

Creating Your First Topic

The transaction for creating a topic has the following structure:

type MsgCreateNewTopic struct {
  // Address of the wallet that will own the topic
  Creator          string   `json:"creator,omitempty"`
  // Information about the topic
  Metadata         string   `json:"metadata,omitempty"`
  // The method used for loss calculations 
  LossMethod       string   `json:"loss_method,omitempty"`
  // The frequency (in blocks) of inference calculations (Must be greater than 0)
  EpochLength      int64    `json:"epoch_length,omitempty"`
  // The time it takes for the ground truth to become available (Cannot be negative)
  GroundTruthLag   int64    `json:"ground_truth_lag,omitempty"`
  // the time window within a given epoch that worker nodes can submit an inference
  WorkerSubmissionWindow int64 `json:"worker_submission_window"`
  // Raising this parameter raises how much high-quality inferences are favored over lower-quality inferences (Must be between 2.5 and 4.5)
  PNorm            github_com_allora_network_allora_chain_math.Dec `json:"p_norm"`
  // Raising this parameter lowers how much workers historical performances influence their current reward distribution (Must be between 0 and 1)
  AlphaRegret      github_com_allora_network_allora_chain_math.Dec  `json:"alpha_regret"`
  // Indicates if the loss function's output can be negative. If false, the reputer submits logs of losses; if true, the reputer submits raw losses.
  AllowNegative    bool     `json:"allow_negative,omitempty"`
  // the numerical precision at which the network should distinguish differences in the logarithm of the loss
  Epsilon          github_com_allora_network_allora_chain_math.Dec  `json:"epsilon"`
  MeritSortitionAlpha github_com_allora_network_allora_chain_math.Dec  `json:"merit_sortition_alpha"`
  ActiveInfererQuantile github_com_allora_network_allora_chain_math.Dec `json:"active_inferer_quantile"`
  ActiveForecasterQuantile github_com_allora_network_allora_chain_math.Dec `json:"active_forecaster_quantile"`
  ActiveReputerQuantile github_com_allora_network_allora_chain_math.Dec `json:"active_reputer_quantile"`
}

Using the allorad CLI to create a topic:

allorad tx emissions create-topic \
  allo13tr5nx74zjdh7ya8kgyuu0hweppnnx8d4ux7pj \    # Creator address
  "ETH prediction in 24h" \                                         # Metadata
  "mse" \                                         # LossMethod
  3600 \                                          # EpochLength
  0 \                                             # GroundTruthLag
  3 \                                             # WorkerSubmissionWindow
  3 \                                             # PNorm 
  1 \                                             # AlphaRegret 
  true \                                          # AllowNegative
  0.001 \                                         # Epsilon
  0.1 \                                           # MeritSortitionAlpha
  0.25 \                                           # ActiveInfererQuantile
  0.25 \                                           # ActiveForecasterQuantile
  0.25 \                                           # ActiveReputerQuantile
  --node <RPC_URL>
  --chain-id <CHAIN_ID>

Be sure to swap out RPC_URL, YOUR_ADDRESS, CHAIN_ID and all other arguments as appropriate with the desired values.

Notes

An explanation in more detail of some of these fields.

Metadata is a descriptive field to let users know what this topic is about and/or any specific indication about how it is expected to work.
allowNegative determines whether the loss function output can be negative.
- If true, the reputer submits raw losses.
- If false, the reputer submits logs of losses.

Fund a Topic

RPC Method: FundTopic
Command: fund-topic [sender] [topic_id] [amount] [extra_data]
Description: Sends funds to a specific topic to be used for paying for inferences or other topic-related activities.
Positional Arguments:
- sender: The address of the sender providing the funds.
- topic_id: The identifier of the topic to receive the funds.
- amount: The amount of funds being sent to the topic.
- extra_data: Additional data or metadata associated with the funding transaction.

Use Case:

Why use it?

This command is used to fund a topic, ensuring there are sufficient funds available to reward workers, forecasters, or other participants submitting inferences or engaging with the topic.

Example Scenario:

As a network administrator or topic creator, you want to add funds to a topic to ensure that workers and forecasters are compensated for their contributions.

Topic Life Cycle How to Query Topic Data using allorad