Text Embedding 3 Small
OpenAI's compact embedding model. 1536 dimensions, great for semantic search and RAG.
Examples
See what Text Embedding 3 Small can generate
Semantic Search
Input:
"How to deploy a Node.js app to production"
Similar matches:
Deploying Node applications to cloud servers
94%Setting up a Node.js production environment
89%Node.js deployment best practices and CI/CD
85%Document Clustering
Input:
"Machine learning model training techniques"
Similar matches:
Deep learning optimization and hyperparameter tuning
91%Neural network training strategies for beginners
87%Supervised learning algorithms and model evaluation
83%Pricing
API Integration
Use our OpenAI-compatible API to integrate Text Embedding 3 Small into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
const vectors = await rw.run("text-embedding-3-small", "Hello world", { type: "embed" });
console.log(vectors[0].length); // embedding dimensions
// Or use the embed() method for full control
const res = await rw.embed("text-embedding-3-small", ["Hello", "World"]);
for (const item of res.data) {
console.log(item.embedding.length);
}Start using Text Embedding 3 Small today
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