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@arizeai/phoenix-client

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import invariant from "tiny-invariant"; import { createClient } from "../client.js"; import { DATASET_UPLOAD_EXAMPLE_IDS } from "../constants/serverRequirements.js"; import { ensureServerCapability } from "../utils/serverVersionUtils.js"; /** * Create a dataset with the given examples. * * If a dataset with the same name already exists, it is updated to match the * provided examples. Re-running with the same inputs is a no-op. * * @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 async function createDataset({ client: _client, name, description, examples, }) { const client = _client || createClient(); const inputs = examples.map((example) => example.input); const outputs = examples.map((example) => example?.output ?? {}); // Treat null as an empty object const metadata = examples.map((example) => example?.metadata ?? {}); const splits = examples.map((example) => example?.splits !== undefined ? example.splits : null); // Extract span IDs from examples, preserving null/undefined as null const spanIds = examples.map((example) => example?.spanId ?? null); // Only include span_ids in the request if at least one example has a span ID const hasSpanIds = spanIds.some((id) => id !== null); // Extract example IDs from examples, preserving null/undefined as null const exampleIds = examples.map((example) => example?.id ?? null); // Only include example_ids in the request if at least one example has an ID const hasExampleIds = exampleIds.some((id) => id !== null); const post = (action) => client.POST("/v1/datasets/upload", { params: { query: { // TODO: parameterize this sync: true, }, }, body: { name, description, action, inputs, outputs, metadata, splits, ...(hasSpanIds ? { span_ids: spanIds } : {}), ...(hasExampleIds ? { example_ids: exampleIds } : {}), }, }); if (hasExampleIds) { await ensureServerCapability({ client, requirement: DATASET_UPLOAD_EXAMPLE_IDS, }); } let createDatasetResponse = await post("update"); if (isUnsupportedUpdateActionResponse(createDatasetResponse)) { warnUpdateFallback(); createDatasetResponse = await post("create"); } invariant(createDatasetResponse.data?.data, "Failed to create dataset"); const datasetId = createDatasetResponse.data.data.dataset_id; return { datasetId, }; } function isUnsupportedUpdateActionResponse(result) { if (result.response?.status !== 422) return false; const body = typeof result.error === "string" ? result.error : JSON.stringify(result.error ?? ""); return (body.includes("Invalid dateset action") || body.includes("Invalid dataset action")); } function warnUpdateFallback() { // eslint-disable-next-line no-console console.warn("Phoenix server does not support declarative update semantics. " + "Upgrade to Phoenix v15 or later."); } //# sourceMappingURL=createDataset.js.map