@arizeai/phoenix-client/dist/esm/experiments/runExperiment.d.ts

A client for the Phoenix API

import { type DiagLogLevel, NodeTracerProvider } from "@arizeai/phoenix-otel";
import { type PhoenixClient } from "../client.js";
import { AnnotatorKind } from "../types/annotations.js";
import { ClientFn } from "../types/core.js";
import { DatasetSelector } from "../types/datasets.js";
import type { Evaluator, ExperimentEvaluatorLike, ExperimentTask, RanExperiment } from "../types/experiments.js";
import { type Logger } from "../types/logger.js";
/**
 * Parameters for running an experiment.
 *
 * @experimental This feature is not complete, and will change in the future.
 */
export type RunExperimentParams = ClientFn & {
    /**
     * An optional name for the experiment.
     * Defaults to the dataset name + a timestamp
     */
    experimentName?: string;
    /**
     * The description of the experiment
     */
    experimentDescription?: string;
    /**
     * Experiment metadata
     * E.x. modelName
     */
    experimentMetadata?: Record<string, unknown>;
    /**
     * The dataset to run the experiment on
     */
    dataset: DatasetSelector;
    /**
     * The task to run
     */
    task: ExperimentTask;
    /**
     * The evaluators to use
     */
    evaluators?: ExperimentEvaluatorLike[];
    /**
     * The logger to use
     */
    logger?: Logger;
    /**
     * Whether to record the experiment results
     */
    record?: boolean;
    /**
     * The number of dataset examples to run in parallel
     */
    concurrency?: number;
    /**
     * Whether or not to run the experiment as a dry run. If a number is privided, n examples will be run.
     * @default false
     */
    dryRun?: number | boolean;
    /**
     * Whether to set the global tracer provider when running the task.
     * If set to false, a locally scoped tracer will be created but will not get registered.
     * This may cause certain spans to not be picked up by Phoenix. Notably libraries like the AI SDK that leverage the global tracer.
     * @default true
     */
    setGlobalTracerProvider?: boolean;
    /**
     * Number of times to repeat each dataset example
     * @default 1
     */
    repetitions?: number;
    useBatchSpanProcessor?: boolean;
    /**
     * Log level to set for the default DiagConsoleLogger when tracing.
     * Omit to disable default diag logging, or to bring your own.
     */
    diagLogLevel?: DiagLogLevel;
};
/**
 * Runs an experiment using a given set of dataset of examples.
 *
 *   An experiment is a user-defined task that runs on each example in a dataset. The results from
 *   each experiment can be evaluated using any number of evaluators to measure the behavior of the
 *   task. The experiment and evaluation results are stored in the Phoenix database for comparison
 *   and analysis.
 *
 *   A `task` is either a sync or async function that returns a JSON serializable
 *   output. If the `task` is a function of one argument then that argument will be bound to the
 *   `input` field of the dataset example. Alternatively, the `task` can be a function of any
 *   combination of specific argument names that will be bound to special values:
 *
 *   - `input`: The input field of the dataset example
 *   - `expected`: The expected or reference output of the dataset example
 *   - `reference`: An alias for `expected`
 *   - `metadata`: Metadata associated with the dataset example
 *   - `example`: The dataset `Example` object with all associated fields
 *
 * @example
 * ```ts
 * import { asEvaluator, runExperiment } from "@phoenix/client/experiments";
 *
 * const experiment = await runExperiment({
 *   dataset: "my-dataset",
 *   task: async (example) => example.input,
 *   evaluators: [
 *     asEvaluator({ name: "my-evaluator", kind: "CODE", evaluate: async (params) => params.output }),
 *   ],
 * });
 * ```
 */
export declare function runExperiment({ experimentName, experimentDescription, experimentMetadata, client: _client, dataset: datasetSelector, task, evaluators, logger, record, concurrency, dryRun, setGlobalTracerProvider, repetitions, useBatchSpanProcessor, diagLogLevel, }: RunExperimentParams): Promise<RanExperiment>;
/**
 * Evaluate an experiment.
 *
 * @experimental This feature is not complete, and will change in the future.
 */
export declare function evaluateExperiment({ experiment, evaluators, client: _client, logger, concurrency, dryRun, setGlobalTracerProvider, useBatchSpanProcessor, tracerProvider: paramsTracerProvider, diagLogLevel, }: {
    /**
     * The experiment to evaluate
     **/
    experiment: RanExperiment;
    /** The evaluators to use */
    evaluators: ExperimentEvaluatorLike[];
    /** The client to use */
    client?: PhoenixClient;
    /** The logger to use */
    logger?: Logger;
    /** The number of evaluators to run in parallel */
    concurrency?: number;
    /**
     * Whether to run the evaluation as a dry run
     * If a number is provided, the evaluation will be run for the first n runs
     * @default false
     * */
    dryRun?: boolean | number;
    /**
     * Whether to set the global tracer provider when running the evaluators
     * @default true
     */
    setGlobalTracerProvider?: boolean;
    /**
     * Whether to use batching for the span processor.
     * @default true
     */
    useBatchSpanProcessor?: boolean;
    /**
     * The tracer provider to use. If set, the other parameters will be ignored and the passed tracer provider will get used
     * Intended as a pass-through from runExperiment
     */
    tracerProvider?: NodeTracerProvider | null;
    /**
     * Log level to set for the default DiagConsoleLogger when tracing.
     * Omit to disable default diag logging, or to bring your own.
     */
    diagLogLevel?: DiagLogLevel;
}): Promise<RanExperiment>;
/**
 * Wrap an evaluator function in an object with a name property.
 *
 * @experimental This feature is not complete, and will change in the future.
 *
 * @param params - The parameters for creating the evaluator
 * @param params.name - The name of the evaluator.
 * @param params.kind - The kind of evaluator (e.g., "CODE", "LLM")
 * @param params.evaluate - The evaluator function.
 * @returns The evaluator object.
 * @deprecated use asExperimentEvaluator instead
 */
export declare function asEvaluator({ name, kind, evaluate, }: {
    name: string;
    kind: AnnotatorKind;
    evaluate: Evaluator["evaluate"];
}): Evaluator;
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