AIGNE Framework is a functional, composable, TypeScript-first AI agent development framework designed to simplify and accelerate the creation of modern AI applications. It targets developers building scalable AI solutions, offering enhanced development efficiency, type safety, broad AI model support, and flexible workflow patterns.

How It Works

The framework employs a modular design and functional programming principles, ensuring type safety with comprehensive TypeScript definitions. It natively supports multiple AI models (OpenAI, Gemini, Claude, Nova, and extensible) and offers diverse workflow patterns like sequential, concurrent, routing, handoff, reflection, code execution, and group chat. Integration with the Model Context Protocol (MCP) and a secure code execution sandbox enable seamless external system interaction and powerful automation.

Quick Start & Requirements

• Installation: npm install @aigne/core, yarn add @aigne/core, or pnpm add @aigne/core.
• Prerequisites: Node.js version 20.0 or higher.
• Resources: Official documentation and a technical forum are available for support.

Highlighted Details

• Natively supports a wide array of AI models including OpenAI, Gemini, Claude, and Nova, with extensibility.
• Provides flexible workflow patterns such as sequential, concurrent, routing, handoff, reflection, orchestration, code execution, and group chat.
• Features seamless integration with external systems via the Model Context Protocol (MCP).
• Includes a secure sandbox for executing dynamically generated code within workflows.
• Deeply integrated with the Blocklet ecosystem for streamlined development and deployment.

Maintenance & Community

AIGNE is an open-source project actively welcoming community contributions, utilizing release-please for release automation. Support is available through a comprehensive Documentation Center and a Technical Forum for global developer interaction.

Licensing & Compatibility

The project is licensed under the Elastic-2.0 license.

Limitations & Caveats

No specific limitations, alpha status, or known caveats are detailed in the provided README content.