Search Results for "application development"

...Native Tauri IPC connects the interface directly to the Rust application without requiring a separate backend HTTP service. Development scripts coordinate the frontend, hot reload, Rust rebuilding, and desktop relaunching from one command. Public builds are still forthcoming, so the repository is primarily aimed at development and experimentation today.

Arch is an AI-native proxy designed to facilitate the development of agentic applications by handling complex tasks such as input clarification, agent routing, and seamless integration of prompts with tools for common tasks. It provides unified access and observability of Large Language Models (LLMs), enabling developers to build applications more efficiently. Arch supports both edge and LLM deployments, offering flexibility in various environments.

...The system supports importing credentials and browser cookies to access provider data securely. It also includes a command-line interface for scripting and automation, making it useful in development and CI environments. Overall, it helps developers track and manage AI tool usage efficiently in a centralized way.

Cake is a compact, powerful toolkit that combines a flexible TCP/UDP proxy, port forwarding system, and connection manager designed for both development and penetration testing scenarios. It enables users to create complex networking flows where traffic can be proxied, relayed, and manipulated between endpoints — useful for debugging networked applications, inspecting protocols, or tunneling traffic through different hops. The tool is designed to work with multiple protocols and supports...

...You can deploy your Pipeless application with a single command to edge and IoT devices or the cloud.

"Building Large Language Model Applications: Application Development and Architecture Design" is an open source e-book about the real-world application of LLM. It introduces the basics and applications of large language models, as well as how to build your own models. These include writing, developing, and managing prompts, exploring what the best large language models can bring, and pattern and architecture design for LLM application development.