RepoAgent is an AI framework that transforms any code repository into an interactive knowledge base. It indexes source files, functions, classes, and documentation into a vector store, enabling fast retrieval and context-aware responses. Developers can ask natural language questions about code functionality, architecture, or dependencies. It supports automated code summarization, documentation generation, and test case creation by integrating with LLMs. RepoAgent also analyzes issues, pull requests, and commit history to provide insights on code quality and potential bugs. Its modular design allows customization of retrieval pipelines, model selection, and output formatting. By embedding directly into CI/CD pipelines or IDEs, RepoAgent streamlines development, reduces onboarding time, and boosts team productivity.

AutoCode is an AI-powered software development tool that automates the code generation process. By leveraging advanced AI technology, it allows users to create, manage, and deploy applications more efficiently. Users can generate code snippets based on specific instructions, reduce coding errors, and improve productivity across multiple programming languages, simplifying the development workflow and enabling quicker deployment of functionality.

Super-Agent-Party allows developers to define a Party object where individual AI agents perform distinct roles such as planning, researching, drafting, and reviewing. Each agent can be configured with custom prompts, tools, and model parameters. The framework manages message routing and shared context, enabling agents to collaborate in real time on subtasks. It supports plugin integration for third-party services, flexible agent orchestration strategies, and error handling routines. With an intuitive API, users can dynamically add or remove agents, chain workflows, and visualize agent interactions. Built on Node.js and compatible with major cloud providers, Super-Agent-Party streamlines the development of scalable, maintainable AI multi-agent systems for automation, content generation, data analysis, and more.

TypedAI delivers a developer-centric library that wraps large language models in strongly typed TypeScript abstractions. You define input and output schemas to validate data at compile time, create reusable prompt templates, and handle streaming or batch responses. It supports function calling patterns to connect AI outputs with backend logic, and integrates with popular LLM providers like OpenAI, Anthropic, and Azure. With built-in error handling and logging, TypedAI helps you ship robust AI features—chat interfaces, document summarization, code generation, and custom agents—without sacrificing type safety or developer productivity.