Effect-TS/effect @effect/ai@0.8.2

on GitHub

Patch Changes

• #4378 f5e3b1b Thanks @IMax153! - Support non-identified schemas in AiChat.structured and Completions.structured.

  Instead of requiring a Schema with either an identifier or _tag property
  for AI APIs that allow for returning structured outputs, you can now optionally
  pass a correlationId to AiChat.structured and Completions.structured when
  you want to either use a simple schema or inline the schema.

  Example:

  import { Completions } from "@effect/ai"
  import { OpenAiClient, OpenAiCompletions } from "@effect/ai-openai"
  import { NodeHttpClient } from "@effect/platform-node"
  import { Config, Effect, Layer, Schema, String } from "effect"
  
  const OpenAi = OpenAiClient.layerConfig({
    apiKey: Config.redacted("OPENAI_API_KEY")
  }).pipe(Layer.provide(NodeHttpClient.layerUndici))
  
  const Gpt4oCompletions = OpenAiCompletions.layer({
    model: "gpt-4o"
  }).pipe(Layer.provide(OpenAi))
  
  const program = Effect.gen(function* () {
    const completions = yield* Completions.Completions
  
    const CalendarEvent = Schema.Struct({
      name: Schema.String,
      date: Schema.DateFromString,
      participants: Schema.Array(Schema.String)
    })
  
    yield* completions.structured({
      correlationId: "CalendarEvent",
      schema: CalendarEvent,
      input: String.stripMargin(`
        |Extract event information from the following prose:
        |
        |Alice and Bob are going to a science fair on Friday.
      `)
    })
  })
  
  program.pipe(Effect.provide(Gpt4oCompletions), Effect.runPromise)

• #4388 fcf3b7c Thanks @IMax153! - Rename correlationId to toolCallId

• #4389 f089470 Thanks @IMax153! - Add support for GenAI telemetry annotations.

• #4368 a0c85e6 Thanks @IMax153! - Support creation of embeddings from the AI integration packages.

  For example, the following program will create an OpenAI Embeddings service
  that will aggregate all embedding requests received within a 500 millisecond
  window into a single batch.

  import { Embeddings } from "@effect/ai"
  import { OpenAiClient, OpenAiEmbeddings } from "@effect/ai-openai"
  import { NodeHttpClient } from "@effect/platform-node"
  import { Config, Effect, Layer } from "effect"
  
  // Create the OpenAI client
  const OpenAi = OpenAiClient.layerConfig({
    apiKey: Config.redacted("OPENAI_API_KEY")
  }).pipe(Layer.provide(NodeHttpClient.layerUndici))
  
  // Create an embeddings service for the `text-embedding-3-large` model
  const TextEmbeddingsLarge = OpenAiEmbeddings.layerDataLoader({
    model: "text-embedding-3-large",
    window: "500 millis",
    maxBatchSize: 2048
  }).pipe(Layer.provide(OpenAi))
  
  // Use the generic `Embeddings` service interface in your program
  const program = Effect.gen(function* () {
    const embeddings = yield* Embeddings.Embeddings
    const result = yield* embeddings.embed("The input to embed")
  })
  
  // Provide the specific implementation to use
  program.pipe(Effect.provide(TextEmbeddingsLarge), Effect.runPromise)

• Updated dependencies [59b3cfb, 766113c, bb05fb8, 712277f, f269122, 8f6006a, c45b559, 430c846, 7b03057, a9c94c8, 107e6f0, c9175ae, 65c11b9, e386d2f, 9172efb]:

  • @effect/platform@0.75.2
  • effect@3.12.8
  • @effect/experimental@0.39.2