text-embedding-3-small

A highly efficient embedding model that provides excellent performance for most use cases at a fraction of the cost of larger models.

Key Features

• 1536 Dimensions: Default embedding size (adjustable)
• 8191 Max Tokens: Large input capacity
• Cost Effective: Lower price than text-embedding-3-large
• Fast: Optimized for high-throughput applications

API Usage

Note: This model uses the /v1/embeddings endpoint, not /v1/chat/completions.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.ohmygpt.com/v1",
    api_key="your-api-key",
)

response = client.embeddings.create(
    model="text-embedding-3-small",
    input="The quick brown fox jumps over the lazy dog",
)

embedding = response.data[0].embedding
print(f"Embedding dimension: {len(embedding)}")

Batch Embedding

You can embed multiple texts in a single request:

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

for i, item in enumerate(response.data):
    print(f"Document {i}: {len(item.embedding)} dimensions")

Reducing Dimensions

You can request smaller embeddings to save storage:

response = client.embeddings.create(
    model="text-embedding-3-small",
    input="Hello world",
    dimensions=512,  # Reduce from 1536 to 512
)

Use Cases