openai

OpenAI Embedding for Eino

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Introduction

This is an OpenAI Embedding component implementation for Eino, which implements the Embedder interface and seamlessly integrates into Eino's embedding system to provide text vectorization capabilities. It supports both OpenAI API and Azure OpenAI Service.

Features

• Implements github.com/cloudwego/eino/components/embedding.Embedder interface
• Easy integration into Eino workflows
• Support for both OpenAI and Azure OpenAI Service
• Support for multiple OpenAI embedding models
• Configurable encoding format (float or base64)
• Configurable output dimensions for text-embedding-3 models
• Built-in callback support in Eino
• Configurable timeout and HTTP client settings

Installation

go get github.com/cloudwego/eino-ext/components/embedding/openai

Quick Start

Using OpenAI API

package main

import (
	"context"
	"log"
	"time"

	"github.com/cloudwego/eino-ext/components/embedding/openai"
)

func main() {
	ctx := context.Background()

	embedder, err := openai.NewEmbedder(ctx, &openai.EmbeddingConfig{
		APIKey:  "your-openai-api-key",
		Model:   "text-embedding-3-small",
		Timeout: 30 * time.Second,
	})
	if err != nil {
		log.Fatalf("NewEmbedder of openai error: %v", err)
		return
	}

	vectors, err := embedder.EmbedStrings(ctx, []string{"hello", "how are you"})
	if err != nil {
		log.Fatalf("EmbedStrings of OpenAI failed, err=%v", err)
	}

	log.Printf("vectors : %v", vectors)
}

Using Azure OpenAI Service

package main

import (
	"context"
	"log"
	"time"

	"github.com/cloudwego/eino-ext/components/embedding/openai"
)

func main() {
	ctx := context.Background()

	embedder, err := openai.NewEmbedder(ctx, &openai.EmbeddingConfig{
		APIKey:     "your-azure-api-key",
		ByAzure:    true,
		BaseURL:    "https://{YOUR_RESOURCE_NAME}.openai.azure.com",
		APIVersion: "2024-02-01",
		Model:      "text-embedding-3-small",
		Timeout:    30 * time.Second,
	})
	if err != nil {
		log.Fatalf("NewEmbedder of openai error: %v", err)
		return
	}

	vectors, err := embedder.EmbedStrings(ctx, []string{"hello", "how are you"})
	if err != nil {
		log.Fatalf("EmbedStrings of OpenAI failed, err=%v", err)
	}

	log.Printf("vectors : %v", vectors)
}

Configuration

The embedder can be configured through the EmbeddingConfig structure:

type EmbeddingConfig struct {
    // Timeout specifies the maximum duration to wait for API responses
    // If HTTPClient is set, Timeout will not be used.
    // Optional. Default: no timeout
    Timeout time.Duration `json:"timeout"`

    // HTTPClient specifies the client to send HTTP requests.
    // If HTTPClient is set, Timeout will not be used.
    // Optional. Default &http.Client{Timeout: Timeout}
    HTTPClient *http.Client `json:"http_client"`

    // APIKey is your authentication key
    // Use OpenAI API key or Azure API key depending on the service
    // Required
    APIKey string `json:"api_key"`

    // ByAzure indicates whether to use Azure OpenAI Service
    // Optional. Default: false
    ByAzure bool `json:"by_azure"`

    // BaseURL is the Azure OpenAI endpoint URL (only for Azure)
    // Format: https://{YOUR_RESOURCE_NAME}.openai.azure.com
    // Required for Azure
    BaseURL string `json:"base_url"`

    // APIVersion specifies the Azure OpenAI API version (only for Azure)
    // Required for Azure
    APIVersion string `json:"api_version"`

    // Model specifies the ID of the model to use for embedding generation
    // Required
    Model string `json:"model"`

    // EncodingFormat specifies the format of the embeddings output
    // Optional. Default: EmbeddingEncodingFormatFloat
    EncodingFormat *EmbeddingEncodingFormat `json:"encoding_format,omitempty"`

    // Dimensions specifies the number of dimensions the resulting output embeddings should have
    // Only supported in text-embedding-3 and later models
    // Optional
    Dimensions *int `json:"dimensions,omitempty"`

    // User is a unique identifier representing your end-user
    // Optional. Helps OpenAI monitor and detect abuse
    User *string `json:"user,omitempty"`
}

Encoding Formats

The embedder supports two encoding formats:

• EmbeddingEncodingFormatFloat: Returns embeddings as floating-point arrays (default)
• EmbeddingEncodingFormatBase64: Returns embeddings as base64-encoded strings

Available Models

OpenAI supports several embedding models:

• text-embedding-3-small: Latest small embedding model with improved performance
• text-embedding-3-large: Latest large embedding model with highest quality
• text-embedding-ada-002: Previous generation embedding model

The text-embedding-3-small and text-embedding-3-large models support the Dimensions parameter for configurable output dimensions.

Azure OpenAI Service

To use Azure OpenAI Service, you need to:

1. Set ByAzure to true
2. Provide your Azure resource URL in BaseURL (format: https://{YOUR_RESOURCE_NAME}.openai.azure.com)
3. Specify the API version in APIVersion
4. Use your Azure API key in APIKey

For more details about Azure OpenAI Service, see the Azure documentation.

Examples

See the following examples for more usage:

• Text Embedding

API Reference

For more details about OpenAI's embedding API, please refer to:

• OpenAI Embeddings API Documentation

License

This component is licensed under the Apache License 2.0. See the LICENSE file for details.