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make name public and export types for rendering #540

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Merged
merged 1 commit into from
Apr 18, 2025
Merged

make name public and export types for rendering #540

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8 changes: 7 additions & 1 deletion src/main.ts
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Expand Up @@ -199,7 +199,13 @@ export { GantryClient, type Gantry } from './components/gantry';
*/
export * as gantryApi from './gen/component/gantry/v1/gantry_pb';

export { MLModelClient, type MLModel } from './services/ml-model';
export {
MLModelClient,
type MLModel,
type Metadata,
type TensorInfo,
type FlatTensors,
} from './services/ml-model';

export { MotorClient, type Motor } from './components/motor';
/**
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3 changes: 2 additions & 1 deletion src/services/ml-model/client.ts
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Expand Up @@ -10,8 +10,9 @@ import { MLModelService } from '../../gen/service/mlmodel/v1/mlmodel_connect';

export class MLModelClient implements MLModel {
private client: PromiseClient<typeof MLModelService>;
private readonly name: string;
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Interesting. Not sure why it was private to begin with

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Normally this would be caught because we would extend Resource which requires name to be public. But the MLModelService does not implement the doCommand, which is a requirement for a Resource. So the type-checker didn't yell at me when I missed it last time.

private readonly options: Options;

public readonly name: string;
public callOptions: CallOptions = { headers: {} as Record<string, string> };

constructor(client: RobotClient, name: string, options: Options = {}) {
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2 changes: 1 addition & 1 deletion src/services/ml-model/index.ts
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@@ -1,2 +1,2 @@
export type { MLModel, FlatTensors } from './ml-model';
export type { MLModel, Metadata, FlatTensors, TensorInfo } from './ml-model';
export { MLModelClient } from './client';
2 changes: 2 additions & 0 deletions src/services/ml-model/ml-model.ts
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@@ -1,6 +1,8 @@
import type { Struct } from '@bufbuild/protobuf';
import type * as mlModelAPI from '../../gen/service/mlmodel/v1/mlmodel_pb';

export type Metadata = mlModelAPI.Metadata;
export type TensorInfo = mlModelAPI.TensorInfo;
export type FlatTensors = mlModelAPI.FlatTensors;

export interface MLModel {
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