Delphi GenAI - Optimized OpenAI Integration

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NEW:

GetIt current version: 1.4.0
Changelog v1.4.3 updated on January 11, 2026
Provider Support and OpenAI API Compatibility
Local model support via LM Studio (OpenAI-compatible server)
Deep Research
Videos using SORA

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Introduction
Documentation Overview
Tips for using the tutorial effectively
Local model support via LM Studio
GenAI functional coverage
Provider Support and OpenAI API Compatibility
Quick Start Guide
- Responses vs. Chat Completions
Tips and tricks
Deprecated
Contributing
License

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Introduction

Built with Delphi 12 Community Edition (v12.1 Patch 1)
The wrapper itself is MIT-licensed.
You can compile and test it free of charge with Delphi CE; any recent commercial Delphi edition works as well.

DelphiGenAI is a full OpenAI wrapper for Delphi, covering the entire platform: text, vision, audio, image generation, video (Sora-2), embeddings, conversations, containers, and the latest v1/responses agentic workflows. It offers a unified interface with sync/async/await support across major Delphi platforms, making it easy to leverage modern multimodal and tool-based AI capabilities in Delphi applications.

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[!IMPORTANT]

This is an unofficial library. OpenAI does not provide any official library for Delphi. This repository contains Delphi implementation over OpenAI public API.

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Documentation Overview

Comprehensive Project Documentation Reference

Changelog
About this project
Detailed documentation with synchronous and asynchronous examples is located in the guides folder.

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Tips for using the tutorial effectively

Obtain an API Key

To initialize the API instance, you need to obtain an API key from OpenAI

Once you have a token, you can initialize IGenAI interface, which is an entry point to the API.

[!NOTE]

//uses GenAI, GenAI.Types;

//Declare 
//  Client: IGenAI;

 // Cloud clients
 Client := TGenAIFactory.CreateInstance(openAI_api_key);


 // Local client (LM Studio – OpenAI compatible server)
 Client := TGenAIFactory.CreateLMSInstance; // default: http://127.0.0.1:1234/v1

 // or
 //Client := TGenAIFactory.CreateLMSInstance('http://192.168.1.10:1234');

 Client := TGenAIFactory.CreateGeminiInstance(gemini_api_key);

To streamline the use of the API wrapper, the process for declaring units has been simplified. Regardless of which methods you use, you only need to reference the following two core units: GenAI and GenAI.Types.

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[!TIP] To effectively use the examples in this tutorial, particularly when working with asynchronous methods, it is recommended to define the client interfaces with the broadest possible scope. For optimal implementation, these clients should be declared in the application's OnCreate method.

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Code examples

The OpenAI API lets you plug advanced models into your applications and production workflows in just a few lines of code. Once billing is enabled on your account, your API keys become active and you can start making requests — including your first call to the chat endpoint within seconds.

Synchronous code example
Asynchronous code example

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Synchronous code example

//uses GenAI, GenAI.Types, GenAI.Tutorial.VCL;

  var API_Key := 'OPENAI_API_KEY';
  var Client := TGenAIFactory.CreateInstance(API_KEY);

  var Value := Client.Responses.Create(
    procedure (Params: TResponsesParams)
    begin
      Params
        .Model('gpt-4.1-mini')
        .Input('What is the difference between a mathematician and a physicist?')
        .Store(False);  // Response not stored
    end);
  try
    for var Item in Value.Output do
      for var SubItem in Item.Content do
        Memo1.Text := SubItem.Text;
  finally
    Value.Free;
  end;

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Asynchronous code example

//uses GenAI, GenAI.Types, GenAI.Tutorial.VCL;

var Client: IGenAI;

procedure TForm1.Test;
begin
  var API_Key := 'OPENAI_API_KEY';
  Client := TGenAIFactory.CreateInstance(API_KEY);

  Client.Responses.AsynCreate(
    procedure (Params: TResponsesParams)
    begin
      Params
        .Model('gpt-4.1-mini')
        .Input('What is the difference between a mathematician and a physicist?')
        .Store(False);  // Response not stored
    end,
    function : TAsynResponse
    begin
      Result.OnStart :=
        procedure (Sender: TObject)
        begin
          Memo1.Lines.Text := 'Please wait...';
        end;

      Result.OnSuccess :=
        procedure (Sender: TObject; Value: TResponse)
        begin
          for var Item in Value.Output do
            for var SubItem in Item.Content do
              Memo1.Text := SubItem.Text;
        end;

      Result.OnError :=
        procedure (Sender: TObject; Error: string)
        begin
          Memo1.Lines.Text := Error;
        end;
    end);
end;

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Strategies for quickly using the code examples

To streamline the implementation of the code examples provided in this tutorial, two support units have been included in the source code: GenAI.Tutorial.VCL and GenAI.Tutorial.FMX Based on the platform selected for testing the provided examples, you will need to initialize either the TVCLTutorialHub or TFMXTutorialHub class within the application's OnCreate event, as illustrated below:

[!IMPORTANT] In this repository, you will find in the sample folder two ZIP archives, each containing a template to easily test all the code examples provided in this tutorial. Extract the VCL or FMX version depending on your target platform for testing. Next, add the path to the DelphiGenAI library in your project’s options, then copy and paste the code examples for immediate execution.

These two archives are designed to fully leverage the TutorialHub middleware and enable rapid upskilling with DelphiGenAI.

VCL support with TutorialHUB: TestGenAI_VCL.zip
FMX support with TutorialHUB: TestGenAI_FMX.zip

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Use file2knowledge

This project, built with DelphiGenAI , allows you to consult GenAI documentation and code in order to streamline and accelerate your upskilling.

GenAI functional coverage

Below, the table succinctly summarizes all OpenAI endpoints supported by the GenAI.

DelphiGenAI

Install / Use

README

Delphi GenAI - Optimized OpenAI Integration

NEW:

Introduction

Documentation Overview

Tips for using the tutorial effectively

Obtain an API Key

Code examples

Synchronous code example

Asynchronous code example

Strategies for quickly using the code examples

Use file2knowledge

GenAI functional coverage