OpenAiEmbeddingModel.ts

OpenAiEmbeddingModel.ts overview

The OpenAiEmbeddingModel module provides the OpenAI implementation of Effect AI’s EmbeddingModel service. It sends embedding requests through OpenAiClient, exposes constructors for layers and AiModel values, supports scoped request configuration overrides, and checks that OpenAI returns one numeric vector for each requested input.

Since v4.0.0

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Exports Grouped by Category

• configuration
  • withConfigOverride
• constructors
  • make
  • model
• layers
  • layer
• models
  • Model (type alias)
• services
  • Config (class)

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configuration

withConfigOverride

Provides config overrides for OpenAI embedding model operations.

When to use

Use when you need scoped OpenAI embedding request defaults for a single effect or workflow without rebuilding the embedding model service.

Details

Supports both data-first and data-last forms. Existing scoped config is read first, then the provided overrides are applied so override fields take precedence.

See

• Config for the scoped embedding request configuration service

Signature

declare const withConfigOverride: {
  (overrides: typeof Config.Service): <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, Config>>
  <A, E, R>(self: Effect.Effect<A, E, R>, overrides: typeof Config.Service): Effect.Effect<A, E, Exclude<R, Config>>
}

Source

Since v4.0.0

constructors

make

Creates an OpenAI embedding model service.

When to use

Use to construct the EmbeddingModel.Service effectfully when OpenAiClient is already available in the environment.

Details

The model option is sent with each embedding request. Constructor config supplies create-embedding request fields other than model and input, and scoped overrides from withConfigOverride are merged last for each request.

Gotchas

The service expects numeric embedding vectors. It fails with InvalidOutputError when the provider returns base64 embeddings, out-of-range indexes, duplicate indexes, or an unexpected number of embeddings.

See

• layer for providing the embedding model service as a layer
• model for creating an AiModel that also provides dimensions
• withConfigOverride for scoped request configuration overrides

Signature

declare const make: (args_0: {
  readonly model: (string & {}) | Model
  readonly config?: Omit<typeof Config.Service, "model"> | undefined
}) => Effect.Effect<EmbeddingModel.Service, never, OpenAiClient>

Source

Since v4.0.0

model

Creates an AiModel for an OpenAI embedding model with its configured vector dimensions.

When to use

Use to provide an OpenAI EmbeddingModel and its Dimensions service to an Effect program.

See

• layer for providing only the embedding model service
• withConfigOverride for scoped request configuration overrides

Signature

declare const model: (
  model: (string & {}) | Model,
  options: { readonly dimensions: number; readonly config?: Omit<typeof Config.Service, "model" | "dimensions"> }
) => AiModel.Model<"openai", EmbeddingModel.EmbeddingModel | EmbeddingModel.Dimensions, OpenAiClient>

Source

Since v4.0.0

layers

layer

Creates a layer for the OpenAI embedding model.

When to use

Use when composing application layers and you want OpenAI to satisfy EmbeddingModel.EmbeddingModel while supplying OpenAiClient from another layer.

Gotchas

Use the default floating-point embedding format. The service expects numeric vectors and fails with InvalidOutputError if OpenAI returns base64 embeddings.

See

• make for constructing the embedding model service effectfully
• model for creating an AiModel that also provides embedding dimensions

Signature

declare const layer: (options: {
  readonly model: (string & {}) | Model
  readonly config?: Omit<typeof Config.Service, "model"> | undefined
}) => Layer.Layer<EmbeddingModel.EmbeddingModel, never, OpenAiClient>

Source

Since v4.0.0

models

Model (type alias)

Model identifiers supported by OpenAI’s embeddings API.

Signature

type Model = "text-embedding-ada-002" | "text-embedding-3-small" | "text-embedding-3-large"

Source

Since v4.0.0

services

Config (class)

Context service for OpenAI embedding model configuration.

When to use

Use when you need scoped OpenAI request defaults or overrides for embedding requests from Effect context.

Details

The service stores the OpenAI create-embedding request payload without input, carrying options such as model, dimensions, encoding_format, and user.

See

• withConfigOverride for scoping embedding request overrides

Signature

declare class Config

Source

Since v4.0.0