OpenAiEmbeddingModel.ts

OpenAiEmbeddingModel.ts overview

The OpenAiEmbeddingModel module adapts OpenAI-compatible embeddings endpoints to Effect’s embedding model service. It sends embedding requests through OpenAiClient, exposes constructors for layers and AiModel values, supports scoped request configuration overrides, and checks that the provider 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
• context
  • Config (class)
• layers
  • layer
• models
  • Model (type alias)

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configuration

withConfigOverride

Provides scoped request config overrides for OpenAI-compatible embedding model operations.

When to use

Use to apply embedding request options to one effect without changing the model’s default configuration.

Details

The overrides are merged with any existing Config service for the duration of the supplied effect. Fields in overrides take precedence over existing config, and the helper supports both effect.pipe(withConfigOverride(overrides)) and withConfigOverride(effect, overrides).

See

• Config for available OpenAI-compatible embedding request configuration fields

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-compatible embedding model service backed by OpenAiClient.

When to use

Use when you need to build or provide an EmbeddingModel service directly from an existing OpenAiClient.

Details

The service sends embedding requests through OpenAiClient.createEmbedding. Request config is merged as the selected model, constructor config, then scoped Config, so scoped overrides take precedence. Provider usage prompt_tokens is exposed as usage.inputTokens.

Gotchas

Provider responses must contain one numeric vector for every requested input with unique, in-range index values; otherwise embedding operations fail with AiError.InvalidOutputError.

See

• model for the higher-level AiModel descriptor that also provides EmbeddingModel.Dimensions
• layer for providing the service as a Layer
• withConfigOverride for scoping embedding request overrides

Signature

declare const make: (args_0: {
  readonly model: string
  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-compatible embedding model with its configured vector dimensions.

When to use

Use to provide an OpenAI-compatible 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,
  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

context

Config (class)

Context service for OpenAI embedding model configuration.

When to use

Use when you need to provide shared default request options for OpenAI-compatible embedding operations through the Effect context, such as dimensions, encoding_format, or user.

Details

The service stores the embedding request payload without input. Requests combine the selected model, layer or constructor config, and scoped context config, with scoped context config taking precedence.

See

• withConfigOverride for scoping embedding request overrides

Signature

declare class Config

Source

Since v4.0.0

layers

layer

Creates a layer for an OpenAI-compatible embedding model service.

When to use

Use when composing application layers and you want an OpenAI-compatible embeddings endpoint to satisfy EmbeddingModel.EmbeddingModel while supplying OpenAiClient from another layer.

See

• make for constructing the embedding model service effectfully
• model for creating an AiModel with configured dimensions

Signature

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

Source

Since v4.0.0

models

Model (type alias)

A model identifier accepted by an OpenAI-compatible embeddings endpoint.

Signature

type Model = string

Source

Since v4.0.0