Document classification with AI Embeddings API
Build production-ready document classification features using the AI Embeddings API from Helix-API. This guide covers setup, integration, and best practices.
Why Use AI Embeddings API for Document classification?
Production Ready
Battle-tested API with consistent response format and error handling.
Low Latency
Built-in caching and optimized infrastructure for fast responses.
Easy Integration
Standard REST API with OpenAPI spec. Works with any language or framework.
Free to Start
Start with the free tier on RapidAPI. Scale when you're ready.
Quick Start
document-classification.js
// Document classification with AI Embeddings API
const response = await fetch(
"https://ai-embeddings-by-helix-api.p.rapidapi.com/embed",
{
method: "POST",
headers: {
"X-RapidAPI-Key": "YOUR_API_KEY",
"X-RapidAPI-Host": "ai-embeddings-by-helix-api.p.rapidapi.com"
}
}
);
const { status, data } = await response.json();
console.log("Document classification result:", data);Available Endpoints
POST
/embedGenerate embeddings for text(s)
POST
/similarityCompute cosine similarity between texts
GET
/modelsList available models
Other Use Cases for AI Embeddings API
Semantic searchRAG pipelinesRecommendation enginesDuplicate detectionContent clusteringFAQ matching enginePlagiarism detectionResume-to-job matchingCustomer support ticket routingProduct similarity searchLegal case law matchingKnowledge graph constructionEmail intent classificationChatbot context retrievalAcademic citation matchingCode snippet searchNews article deduplicationFeedback theme extractionAnomaly detection in text logs