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CodeProject.AI-Server
CodeProject.AI Server is a self contained service that software developers can include in, and distribute with, their applications in order to augment their apps with the power of AI.
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A standalone, self-hosted, fast, free and Open Source Artificial Intelligence microserver for any
platform, any language. It can be installed locally, required no off-device or out of network data
transfer, and is easy to use.
Supported Platforms
Windows
macOS
macOS arm64
Ubuntu / Debian
Raspberry Pi arm64
Docker
Visual Studio2019+
Visual StudioCode
Why
AI programming is something every single developer should be aware of. We wanted a fun project we could use to help teach developers and get them involved in AI. We'll be using CodeProject.AI as a focus for articles and exploration to make it fun and painless to learn AI programming.
We got sick of fighting versions and libraries and models and being blocked by tiny annoying things every step of the way. So we put put this together so we could save you the frustration. We'll take care of the housekeeping, you focus on the code.
We also got sick of needing to sign up to potentially expensive services for AI functionality. This is something we need, and by sharing maybe you can use it too, and hopefully add your own modules and improvements along the way.
On the dashboard, top and centre, is a link to the CodeProject.AI Explorer. Open that and play!
2: Running and debugging the code
Clone the CodeProject.AI-Server repository.
Make sure you have Visual Studio Code or Visual Studio 2019+ installed.
Run the setup script in /devops/install
Optionally pull all CodeProject.AI Modules by running the clone_repos script in /devops/install
Debug the front-end server application (see notes below, but it's easy)
How do I use it in my application?
Here's an example of using the API for scene detection using a simple JavaScript call:
<html>
<body>
Detect the scene in this file: <input id="image" type="file" />
<input type="button" value="Detect Scene" onclick="detectScene(image)" />
<script>
function detectScene(fileChooser) {
var formData = new FormData();
formData.append('image', fileChooser.files[0]);
fetch('http://localhost:32168/v1/vision/detect/scene', {
method: "POST",
body: formData
})
.then(response => {
if (response.ok) response.json().then(data => {
console.log(`Scene is ${data.label}, ${data.confidence} confidence`)
});
});
}
</script>
</body>
</html>
You can include the CodeProject.AI installer (or just a link to the latest version of the installer) in your own apps and installers and voila, you have an AI enabled app.
What does it include?
CodeProject.AI includes
A HTTP REST API Server. The server listens for requests from other apps, passes them to the backend analysis services for processing, and then passes the results back to the caller. It runs as a simple self contained web service on your device.
Backend Analysis services. The brains of the operation is in the analysis services sitting behind the front end API. All processing of data is done on the current machine. No calls to the cloud and no data leaving the device.
The Source Code, naturally.
What can it do?
It can run any AI module your imagination and patience can create. Current modules include
Generative AI: LLMs for text generation, Text-to-image, and multi-modal LLMs (eg "tell me what's in this picture")
Object Detection in images, including using custom models
Faces detection and recognition images
Scene recognition represented in an image
Remove a background from an image
Blur a background from an image
Enhance the resolution of an image
Pull out the most important sentences in text to generate a text summary
Prove sentiment analysis on text
Sound Classification
We will be constantly expanding the feature list.
Our Goals
To promote AI development and inspire the AI developer community to dive in and have a go. AI is here, it's in demand, and it's a huge paradigm change in the industry. Whether you like AI or not, developers owe it to themselves to experiment in and familiarise themselves with the technology. This is CodeProject.AI: a demonstration, an explorer, a learning tool, and a library and service that can be used out of the box.
To make AI development easy. It's not that AI development is that hard. It's that there are so, so many options. Our architecture is designed to allow any AI implementation to find a home in our system, and for our service to be callable from any language.
To focus on core use-cases. We're deliberately not a solution for everyone. Instead we're a solution for common day-to-day needs. We will be adding dozens of modules and scores of AI capabilities to our system, but our goal is always clarity and simplicity over a 100% solution.
To tap the expertise of the Developer Community. We're not experts but we know a developer or two out there who are. The true power of CodeProject.AI comes from the contributions and improvements from our AI community.
Supported Development Environments
This current release works best with Visual Studio Code on Windows 10+. Ubuntu 22.04+, Debian and macOS (both Intel and Apple Silicon). Visual Studio 2019+ support is included for Windows 10+.
The current release provides support for CPU on each platform, DirectML on Windows, CUDA on Windows and Linux, support for Apple Silicon GPUs, RockChip NPUs and Coral.AI TPUs. Support depends on the module itself.
