Symposium2023

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What is Symposium2023

Symposium2023 is a project developed by geoffsmith82, aiming to empower Delphi users by integrating AI technology into their applications. This initiative was initially presented at the ADUG Symposium in 2023 and has since been expanded to showcase the vast capabilities of AI. The core of this project is to provide generalized interfaces for various AI models, making them easily accessible and usable for different applications. From translating languages to voice recognition, and generating images from text, Symposium2023 enables Delphi developers to explore and implement AI technologies without deep technical expertise in AI.

How to Use Symposium2023

To use Symposium2023, Delphi programmers can explore the example programs provided within the project. Each example serves as a demonstration of how AI can be integrated into Delphi applications. Users are encouraged to experiment with different AI models, following the leading advancements or adapting based on cost and preferences. The project supports a wide range of AI functionalities, from text-to-speech and language translation to image generation and voice recognition.

To get started, users need to set up the necessary API keys for the cloud services they wish to use. This involves accessing the developer consoles of providers like Google, Microsoft Azure, and OpenAI, among others. Once the APIs are configured, users can test the functionalities through the provided example programs.

Key Features of Symposium2023

Symposium2023 offers a comprehensive suite of features designed to make AI integration seamless for Delphi developers:

Generalized AI Interfaces: Supports various AI models and providers, allowing easy swapping and experimentation.
Example Programs: Demonstrations include ChatGPT integration, language translation, voice recognition, image generation, and more.
Vendor Flexibility: Avoids vendor lock-in by supporting multiple providers, such as Google, Amazon, Microsoft Azure, and others.
AI Functionalities:
- Language Translation: Efficiently translates between languages using cloud APIs.
- Voice Recognition and Transcription: Converts speech to text in real-time or from audio files.
- Text-to-Speech: Utilizes various APIs to offer different voices and accents.
- Image Generation: Creates images from textual descriptions using AI models.
- Data Processing: Extracts and formats data from documents like invoices into machine-readable formats.
Customization and Expansion: Encourages users to explore and implement additional AI capabilities, such as using embeddings for data search or integrating Python AI libraries with Delphi.

By providing these tools and examples, Symposium2023 aims to lower the barrier for Delphi developers to incorporate advanced AI technologies into their applications, enhancing functionality and user engagement.

Source code and Documentation for my ADUG Symposium Talk presented on the 28th of April 2023. I have since added to and continue to enhance the code to further demonstrate capabilities of AI, adding things that wasn't available at the time. The goal of this project is to enable delphi users to be able to use AI technology in their applications. There are many different types of AI and thousands of different models. This project is working on creating generalized interfaces to the different types of AI models and make them easily accessible. Artificial intelligence (AI) is an interdisciplinary field that combines computer science, mathematics, and cognitive psychology to create intelligent systems capable of performing complex tasks. Its rapid advancements have led to a wide array of applications demonstrating AI's versatility. Language translation is one such application, where AI-powered tools efficiently translate between languages, simplifying tasks like translating software programs for global audiences. AI also excels in human-like conversations, with interactive applications that understand and respond to human language naturally. Voice recognition and real-time speech-to-text allow conversion and seamless voice-based interactions, making AI-driven applications more accessible and user-friendly. In creative and artistic domains, AI can generate images based on textual descriptions, showcasing its capacity to understand and produce visual content. AI's computer vision capabilities enable it to accurately recognize faces and other objects in photographs and documents, illustrating its potential in visual recognition tasks and diverse applications like security and automation. AI's ability to analyze and process data, and generate comprehensive reports highlights its value in various domains. Furthermore, AI-powered tools can transcribe audio files into written text, making transcription tasks more efficient and accurate. The example programs below is an attempt to demonstrate the capabilities available to Delphi programmers today. I have worked on creating generic API's so that different providers can be swapped in or out to:

experiment
follow the current leading AI model
make it easy to change based on price
avoid vendor lockin
or for any other reason.

ChatGPT Prompts

Some Example GPT Prompts

Presentation Slides from Original 2023 ADUG Symposium

AI and ChatGPT

Example programs

ChatGPTAction
Simple Server app that can be added to a ChatGPT GPT action to allow your computer to write delphi code. See AI Generated Delphi for some example programs created with ChatGPTAction.
EmbeddingsDemo
- Simple demo showing how Embeddings work
Talk
Program demonstrating calling various Text to Speech API's and the different voices available (FMX)
Translate
- translates between languages using the various cloud API's.
- Simplify translating Delphi programs when using Delphi's built-in multi language resource support.
DelphiChatGPT
- write questions to ChatGPT and have it speak the answer. image
FaceDetection
- Detect faces in a photo. image
Weather
- Query the weather forcast for Bendigo from the bureau of meteorology generate a paragraph or two and read it out image
TranscribeAudio
Upload a audio file and have it translated via a cloud speech to text api.
VoiceRecognition
convert speech to text in real-time straight from your microphone, feed it to OpenAI's GPT and have the response read back to you. image
Image generation
generate an image using text that you provide using OpenAI's DALLE-2 and DALLE-3 API.
ProcessInvoice
from a pdf invoice extract out the important details and format as a machine readable JSON string
TestAPIs
- A project to test out the different API's and the functionality of the API's

Project Supports LLM Features

| Feature | GPT-4o | Azure OpenAI Service | Groq | xAI's Grok | Anthropic's Claude | Google's Gemini | | Vision Support | Yes | Yes | Yes | Yes | Yes | No* | | Function Calling | Yes | Yes | Yes | Yes | Yes | No* | *Feature not currently supported/implementated

Questions / Need Help?

Create an issue and I will respond to it.

Providers Used/Available

Google - Text to Speech, LLM, Translate
Microsoft Azure - Text to Speech, GPT, Translate
Amazon - Text to Speech, Translate
Anthropic claude-3-opus, claude-3-sonnet and claude-3-haiku, supporting one of largest context windows currently available (200k tokens)
X.AI grok-beta LLM
Replicate access a wide range of models
Huggingface access a wide range of models
ElevenLabs Text to Speech and Voice Cloning
OpenAI Text to Speech, Whisper Voice Recognition, DALLE-2, DALLE-3 Image Generation, GPT4 LLM
AssemblyAI Voice Recognition
DeepGram Voice Recognition
Rev.AI Voice Recognition
Conqui-ai Run a variaty of text to speech models locally from a docker container
CodeProject-Ai Local Face Detection.

Getting the projects working

Each of the cloud API's need to have been setup in their respective developer consoles.
Run the TestAPIs project and select the Settings->API Keys... menu item. Add the api for the providers you want to use.
If you're not using a particular provider you don't need a key for it.

Questions about code and how to set things up

Please feel free to raise issues about any questions you have about the code. I know there is a lot to this project and lots to setup, so I would like to improve the documentation to make it easy for everyone to use all the parts of this project.

Potential future areas of research/study

Using Embeddings to search large datasets
Using Python4Delphi to be able to call various Python AI libraries from Delphi.

TensorFlow.Delphi
whisper.cpp Voice Recognition
llama.cpp
llama-pas
Bing Image Creator
Bing
RDOpenAI Delphi implementation of ChatGPT - an event based component
ChatGPT OpenAI ChatGPT
DelphiOpenAI a Delphi Library for OpenAI
ChatGPTPluginForLazarus An OpenAI (ChatGPT) plug-in for Lazarus IDE.
ChatGPT a Firemonkey ChatGPT interface written in Delphi.
AI-Playground-DesktopClient A Firemonkey Language model playground to access languages models like StableLM, ChatGPT, and more.
AI-Code-Translator Use GPT to translate between programming languages
TOpenALPR Open Source Number Plate recognition
PgVector PgVector allows storing and querying of Vectors/Embeddings in an SQL database
CommonVoice Public dataset of recordings for Voice Recognition
Huggingface
Open-Assistant

External Libraries required to build projects

ICS 9.0 or from the GetIt package manager built into Delphi. - For Voice recognition
landgraf-dev/aws-sdk-delphi AWS SDK
DelphiMVCFramework for ChatGPTAction

Tools used to create example projects

Fiddler
XML Data Binder in Delphi

How to Use

To use the Symposium2023, follow these steps:

Visit https://github.com/geoffsmith82/Symposium2023https://github.com/geoffs...
Follow the setup instructions to create an account (if required)
Connect the MCP server to your Claude Desktop application
Start using Symposium2023 capabilities within your Claude conversations

Additional Information

Created

March 17, 2023

Company

geoffsmith82

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