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@arizeai/phoenix-client

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import type { ClientFn } from "../types/core"; import type { Example } from "../types/datasets"; export type CreateDatasetParams = ClientFn & { /** * The name of the dataset */ name: string; /** * The description of the dataset */ description: string; /** * The examples to create in the dataset */ examples: Example[]; }; export type CreateDatasetResponse = { datasetId: string; }; /** * Create a new dataset with examples. * * @experimental this interface may change in the future * * @param params - The parameters for creating the dataset * @param params.client - Optional Phoenix client instance * @param params.name - The name of the dataset * @param params.description - The description of the dataset * @param params.examples - The examples to create in the dataset. Each example can include: * - `input`: Required input data for the example * - `output`: Optional expected output data * - `metadata`: Optional metadata for the example * - `splits`: Optional split assignment (string, array of strings, or null) * - `spanId`: Optional OpenTelemetry span ID to link the example back to its source span * * @returns A promise that resolves to the created dataset ID * * @example * ```ts * // Create a dataset with span links * const { datasetId } = await createDataset({ * name: "qa-dataset", * description: "Q&A examples from traces", * examples: [ * { * input: { question: "What is AI?" }, * output: { answer: "Artificial Intelligence is..." }, * spanId: "abc123def456" // Links to the source span * }, * { * input: { question: "Explain ML" }, * output: { answer: "Machine Learning is..." }, * spanId: "789ghi012jkl" * } * ] * }); * ``` */ export declare function createDataset({ client: _client, name, description, examples, }: CreateDatasetParams): Promise<CreateDatasetResponse>; //# sourceMappingURL=createDataset.d.ts.map