Skip to main content
Glama

@arizeai/phoenix-mcp

Official
by Arize-ai
logDocumentAnnotations.ts2.15 kB
import { createClient } from "../client"; import { ClientFn } from "../types/core"; import { DocumentAnnotation, toDocumentAnnotationData } from "./types"; /** * Parameters to log multiple document annotations */ export interface LogDocumentAnnotationsParams extends ClientFn { /** * The document annotations to log */ documentAnnotations: DocumentAnnotation[]; /** * If true, the request will be fulfilled synchronously and return the annotation IDs. * If false, the request will be processed asynchronously and return null. * @default false */ sync?: boolean; } /** * Log multiple document annotations in a single request. * * Each annotation can be of type "LLM", "CODE", or "HUMAN" and can include a label, score, explanation, and metadata. * At least one of label, score, or explanation must be provided for each annotation. * * @param params - The parameters to log document annotations * @returns The IDs of the created annotations * * @example * ```ts * const results = await logDocumentAnnotations({ * documentAnnotations: [ * { * spanId: "123abc", * documentPosition: 0, * name: "relevance_score", * label: "relevant", * score: 0.95, * annotatorKind: "LLM", * explanation: "Document is highly relevant to the query", * metadata: { * model: "gpt-4" * } * }, * { * spanId: "123abc", * documentPosition: 1, * name: "relevance_score", * label: "somewhat_relevant", * score: 0.6, * annotatorKind: "LLM" * } * ] * }); * ``` */ export async function logDocumentAnnotations({ client: _client, documentAnnotations, sync = false, }: LogDocumentAnnotationsParams): Promise<{ id: string }[]> { const client = _client ?? createClient(); const { data, error } = await client.POST("/v1/document_annotations", { params: { query: { sync }, }, body: { data: documentAnnotations.map(toDocumentAnnotationData), }, }); if (error) { throw new Error(`Failed to log document annotations: ${error}`); } return data?.data || []; }

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Arize-ai/phoenix'

If you have feedback or need assistance with the MCP directory API, please join our Discord server