Reference: AI: LMStudio

Installation

dependencies {
    
    implementation(platform("org.http4k:http4k-connect-bom:5.25.1.0"))

    implementation("org.http4k:http4k-connect-ai-lmstudio")
    implementation("org.http4k:http4k-connect-ai-lmstudio-fake")
}

The http4k-connect LmStudio integration provides:

  • LmStudio API Client
  • FakeLmStudio server which can be used as testing harness for either API Client

LmStudio API connector

The LmStudio connector provides the following Actions:

  • GetModels
  • ChatCompletion
  • CreateEmbeddings

New actions can be created easily using the same transport.

The client APIs utilise the LmStudio API Key (Bearer Auth). There is no reflection used anywhere in the library, so this is perfect for deploying to a Serverless function.

Example usage

const val USE_REAL_CLIENT = false

fun main() {
    // we can connect to the real service or the fake (drop in replacement)
    val http: HttpHandler = if (USE_REAL_CLIENT) JavaHttpClient() else FakeLmStudio()

    // create a client
    val client = LmStudio.Http(http.debug())

    // all operations return a Result monad of the API type
    val result: Result<Models, RemoteFailure> = client
        .getModels()

    println(result)
}

Other examples can be found here.

Fake LmStudio Server

The Fake LmStudio provides the below actions and can be spun up as a server, meaning it is perfect for using in test environments without using up valuable request tokens!

  • GetModels
  • ChatCompletion

Generation of responses

By default, a random LoremIpsum generator creates chat completion responses for the Fake. This behaviour can be overridden to generate custom response formats (eg. structured responses) if required. To do so, create instances of the ChatCompletionGenerator interface and return as appropriate.

Default Fake port: 58438

To start:

FakeLmStudio().start()