Embarcadero’s SimpleChatWithDownload sample demonstrates how to build a complete local AI chat application in Delphi that can download a model, load it with llama.cpp, and start chatting—all from a native Delphi interface.
Built on top of the llama-cpp-delphi project, the sample shows how to integrate local LLMs directly into Delphi applications without relying on cloud APIs or external AI services. Developers can ship AI-powered applications that run entirely on the user’s machine while taking advantage of llama.cpp’s broad hardware acceleration support.
The sample demonstrates:
- Downloading GGUF models from within the application
- Running local LLMs with llama.cpp
- Native Delphi chat interfaces
- Streaming AI conversations
- Local-first AI workflows
- Offline AI deployment
- CPU and GPU accelerated inference
Because it uses llama.cpp, the same application architecture can work with a wide range of open-weight models including Llama, Mistral, DeepSeek, Qwen, and other GGUF-compatible models. The underlying runtime supports Windows, Linux, and macOS, with acceleration options including CUDA, Vulkan, Metal, HIP, and more depending on the target platform.
For Delphi developers looking to add private, offline AI capabilities to their applications, SimpleChatWithDownload provides a practical starting point for building ChatGPT-style experiences powered entirely by local models.
