AgentMark offers a comprehensive framework for developing, testing, and evaluating AI agents, abstracting the complexities of prompt engineering and agent workflows. It targets developers seeking a structured approach to building AI applications, enabling multimodal output generation, robust testing with datasets and evals, and rapid iteration through a CLI and SDK integrations. The primary benefit is a unified system for managing the AI agent lifecycle, from prompt design to performance assessment.

How It Works

AgentMark utilizes a unique .prompt.mdx file format, incorporating a JSX-like syntax for defining prompts with logic, conditionals, loops, props, and filter functions. It supports multimodal generation (text, images, speech), file attachments, and structured JSON output via JSON Schema definitions, ensuring type safety with auto-generated TypeScript types. A key architectural choice is its adapter system, which translates prompts for various LLM SDKs (Vercel, Mastra, LlamaIndex, or raw JSON) rather than directly integrating with specific models or providers. This promotes flexibility and interoperability across different AI backends.

Quick Start & Requirements

• Install: npm create agentmark@latest
• Prerequisites: Node.js and npm.
• Running: Use the CLI: agentmark run-prompt your-prompt.prompt.mdx or agentmark run-experiment your-prompt.prompt.mdx.
• SDK Adapters: Vercel AI SDK, Mastra SDK, LlamaIndex SDK, Default (raw JSON).
• Language Support: TypeScript, JavaScript (Python support is "Coming Soon").
• Links: Homepage, Discord, Docs

Highlighted Details

• Multimodal generation capabilities from a single prompt file.
• Type-safe inputs and outputs using JSON Schema and auto-generated TypeScript types.
• JSX-like syntax for embedding logic, conditionals, and dynamic data within prompts.
• Extensible adapter system for seamless integration with various LLM SDKs.

Maintenance & Community

Community support and collaboration are facilitated through a Discord server. Contributions are welcomed via the project's contribution guidelines.

Licensing & Compatibility

The project is licensed under the MIT License, which permits commercial use and modification with minimal restrictions.

Limitations & Caveats

AgentMark does not directly support or interface with LLM providers; it relies entirely on external SDK adapters for model interaction. Python language support is planned but not yet available. The "Cloud Platform" mentioned is a separate, extended offering.