AgenticAppBuilder accelerates AI agent development by providing a one-command CLI to scaffold production-ready applications. It sets up language model configurations, memory backends, tool integrations, and a user interface, enabling developers to focus on custom agent logic. The modular architecture supports extensible toolchains, seamless API key management, and deployment scripts for local or cloud environments, reducing boilerplate and speeding prototyping.

Agents-Deep-Research is designed to streamline the development and testing of autonomous AI agents by offering a modular, extensible codebase. It features a task planning engine that decomposes user-defined goals into sub-tasks, a long-term memory module that stores and retrieves context, and a tool integration layer that allows agents to interact with external APIs and simulated environments. The framework also provides evaluation scripts and benchmarking tools to measure agent performance across diverse scenarios. Built on Python and adaptable to various LLM backends, it enables researchers and developers to rapidly prototype novel agent architectures, conduct reproducible experiments, and compare different planning strategies under controlled conditions.