Embedding API Integration Guide

Direct answer

Use POST https://api2.laozhang.ai/v1/embeddings to convert text or a text array into vectors. Filter for Embeddings models in the catalog, then validate default dimensions, optional dimension reduction, batch ordering, and billing with the current API key. Do not generalize one OpenAI model’s dimension rules to every provider model. This page was last verified on September 2, 2026.

Minimal request

curl "https://api2.laozhang.ai/v1/embeddings" \
  -H "Authorization: Bearer $LAOZHANG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "A short text for validating the embedding endpoint"
  }'

Python:

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["LAOZHANG_API_KEY"],
    base_url="https://api2.laozhang.ai/v1",
)

response = client.embeddings.create(
    model="text-embedding-3-small",
    input=["First text", "Second text"],
)

vectors = [item.embedding for item in response.data]
print([len(vector) for vector in vectors])

The example model appears in the current catalog, but account permission and price still require a console check.

Acceptance items

Item	Acceptance method
Model ID	Copy from the console and send a minimal request
Default dimensions	Check `len(data[0].embedding)`
`dimensions`	Use only when explicitly documented or tested for the model
Batch input	Check `data[].index` and input ordering
Empty or oversized input	Confirm the error and whether usage is charged
Usage	Compare with call logs and the model’s billing unit

Usage boundaries

Vector dimensions and semantic spaces from different models are not interchangeable.
Rebuild the index after changing embedding models.
Dimension reduction can affect recall and requires offline evaluation.
Batch size, input length, and rate limits require testing.
Match vector database normalization and distance functions to the selected model.

Essentials

Text APIs

Video Generation APIs

Image Generation APIs

AI Understanding

Embedding API Integration Guide

Direct answer

Minimal request

Acceptance items

Usage boundaries

​Direct answer

​Minimal request

​Acceptance items

​Usage boundaries

​Related documentation

Direct answer

Minimal request

Acceptance items

Usage boundaries

Related documentation