ListModelsData
Example Usage
typescript
import { ListModelsData } from "@meetkai/mka1/models/operations";
let value: ListModelsData = {
id: "<id>",
object: "model",
created: 675851,
ownedBy: "<value>",
modelType: "embeddings",
inputModalities: [
"<value 1>",
],
outputModalities: [
"<value 1>",
"<value 2>",
],
parameterCount: 233742,
activeParameterCount: 833434,
releaseDate: null,
capabilities: {
supportsTemperature: false,
supportsTopP: false,
},
};Fields
| Field | Type | Required | Description |
|---|---|---|---|
id | string | ✔️ | N/A |
object | "model" | ✔️ | N/A |
created | number | ✔️ | N/A |
ownedBy | string | ✔️ | N/A |
modelType | operations.ListModelsModelType | ✔️ | N/A |
inputModalities | string[] | ✔️ | Modalities this model accepts as input, mirroring the registry's capabilities.modalities.input (e.g. ["text", "image"]). Clients use it to decide whether an attachment — an image, audio clip, or video — can be sent to this model at all. |
outputModalities | string[] | ✔️ | Modalities this model can produce, mirroring the registry's capabilities.modalities.output. Unconstrained strings rather than a closed enum so a new registry modality reaches clients without a breaking schema change. |
parameterCount | number | ✔️ | Total parameter count of the weights behind this model, mirroring the registry's modelCard.parameterCount. Null when the registry does not record one (closed-weight API models, or entries nobody has filled in yet). |
activeParameterCount | number | ✔️ | Parameters active per token for mixture-of-experts models, mirroring the registry's modelCard.activeParameterCount. Null for dense models and whenever unrecorded. |
releaseDate | RFCDate | ✔️ | Public release date of the model as an ISO calendar date (YYYY-MM-DD), mirroring the registry's modelCard.releaseDate. Null when unrecorded. |
capabilities | operations.ListModelsCapabilities | ✔️ | Curated public sampling capabilities for this model. |