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TypeScript Types

The Endee TypeScript SDK includes comprehensive type definitions for full type safety and excellent IDE support.

Importing Types

import type {
  VectorItem,
  QueryOptions,
  QueryResult,
  CreateIndexOptions,
  IndexInfo,
  IndexDescription,
  SpaceType
} from "endee";

Type Definitions

SpaceType

Distance metric used for similarity calculations.

type SpaceType = "cosine" | "l2" | "ip";
ValueDescription
cosineCosine similarity (recommended for text embeddings)
l2Euclidean distance
ipInner product (dot product)

CreateIndexOptions

Options for creating a new index.

interface CreateIndexOptions {
  name: string;            // Unique index name
  dimension: number;       // Vector dimensionality
  spaceType?: SpaceType;   // Distance metric (default: cosine)
  M?: number;              // Graph connectivity (default: 16)
  efCon?: number;          // Construction parameter (default: 128)
  useFp16?: boolean;       // Half-precision storage (default: true)
  version?: number;        // Index version
}

VectorItem

Structure for upserting vectors.

interface VectorItem {
  id: string;                       // Unique vector ID
  vector: number[];                 // Vector embedding
  meta?: Record<string, unknown>;   // Optional metadata
  filter?: Record<string, unknown>; // Optional filter fields
}

QueryOptions

Options for querying the index.

interface QueryOptions {
  vector: number[];                        // Query vector
  topK?: number;                           // Number of results
  filter?: Record<string, unknown> | null; // Optional filter
  ef?: number;                             // Search quality parameter
  includeVectors?: boolean;                // Include vectors in results
  log?: boolean;                           // Enable logging
}

QueryResult

Structure of query results.

interface QueryResult {
  id: string;                       // Vector ID
  similarity: number;               // Similarity score
  distance: number;                 // Distance value
  meta?: Record<string, unknown>;   // Metadata (if stored)
  filter?: Record<string, unknown>; // Filter fields (if stored)
  norm?: number;                    // Vector norm
  vector?: number[];                // Vector data (if includeVectors=true)
}

IndexInfo

Index information returned when listing indexes.

interface IndexInfo {
  name: string;            // Index name
  space_type: SpaceType;   // Distance metric
  dimension: number;       // Vector dimension
  total_elements?: number; // Total number of vectors
  use_fp16?: boolean;      // Half-precision enabled
  M?: number;              // Graph connectivity
  checksum?: string;       // Index checksum
  lib_token?: string;      // Library token
}

IndexDescription

Index statistics and configuration from describe().

interface IndexDescription {
  name: string;          // Index name
  space_type: SpaceType; // Distance metric
  dimension: number;     // Vector dimension
  count: number;         // Number of vectors stored
  precision: string;     // Storage precision
  M: number;             // Graph connectivity
}

Usage Example

import { Endee } from "endee";
import type { VectorItem, QueryOptions, QueryResult } from "endee";
 
const endee = new Endee("user_id:api_token:region");
const index = await endee.getIndex("my_index");
 
// Typed vector item
const vectors: VectorItem[] = [
  {
    id: "doc1",
    vector: [0.1, 0.2, 0.3],
    meta: { title: "Document 1" },
    filter: { category: "reference" }
  }
];
 
await index.upsert(vectors);
 
// Typed query options
const options: QueryOptions = {
  vector: [0.1, 0.2, 0.3],
  topK: 10,
  includeVectors: true
};
 
// Typed results
const results: QueryResult[] = await index.query(options);
 
// Access result fields
for (const result of results) {
  console.log(`ID: ${result.id}`);
  console.log(`Similarity: ${result.similarity}`);
  console.log(`Distance: ${result.distance}`);
}
UsageQuickstart