agentmark
Markdown for the AI era
Stars: 228
AgentMark is a tool designed to make it easy for developers to develop, test, and evaluate AI Agents. It combines Markdown syntax with JSX components to create reliable Agents. The tool seamlessly integrates with SDKs, offering comprehensive tooling such as full type safety, unified prompt configuration, syntax highlighting, loops and conditionals, custom SDK adapters, and support for text, object, image, and speech generation across multiple model providers.
README:
Markdown for the AI Era. Develop, test, and evalaute your AI Agents.
AgentMark makes it easy for developers to develop, test, and evaluate Agents.
AgentMark makes prompt engineering intuitive by combining familiar Markdown syntax with JSX components, allowing developers to focus on creating reliable Agents. AgentMark seamlessly integrates with your favorite SDK's using our adapters, and currently works in TypeScript and JavaScript, with Python support coming soon.
AgentMark comes with comprehensive tooling included—featuring full type safety, unified prompt configuration, syntax highlighting, loops and conditionals, custom SDK adapters, and support for text, object, image, and speech generation across multiple model providers, even when they don't support native structured output APIs.
AgentMark prompt file example for generating text
| Feature | Description |
|---|---|
| Multimodal Generation | Generate text, objects, images, and speech from a single prompt file, supporting a wide range of model capabilities. |
| Tools and Agents | Extend prompts with custom tools and agentic workflows, enabling API calls, calculations, and multi-step reasoning. |
| File Attachments | Attach images and files to prompts for tasks like image analysis, document processing, and more. |
| Type Safety | Ensure reliable, type-checked inputs and outputs for prompts using JSON Schema and auto-generated TypeScript types. |
| Conditionals, Loops, Props, Filter Functions | Add logic, dynamic data, and transformations to your prompts with powerful JSX-like syntax. |
| CLI for running/testing | Run, test, and debug prompts directly from the command line or your editor for rapid iteration. |
Get started by first initializing your AgentMark app.
npx @agentmark/cli init
We offer a few ways to run prompts with AgentMark.
- Use our AgentMark CLI:
Run .prompt.mdx files directly from the command line using our CLI. This is the quickest way to test and execute your prompts.
# Run a prompt with test props (default)
npx @agentmark/cli run-prompt your-prompt.prompt.mdx
# Run a prompt with a dataset
npx @agentmark/cli run-prompt your-prompt.prompt.mdx -i dataset
- Run AgentMark files with your favorite SDK
AgentMark doesn't support any models or calling any LLM providers. Instead, we format the input of your prompt through an adapter to match the input of the SDK you're using.
| Adapter | Description |
|---|---|
| Vercel (Recommended) | The Vercel AI SDK. |
| Default | Turns prompts into raw JSON, adapt manually to your needs |
| Custom | Allows a user to create their own AgentMark adapter to custom adapter format. |
| Mastra (Coming Soon) | Coming soon, we'll support the Mastra SDK |
Want to add support for another adapter? Open an issue.
We plan on providing support for AgentMark across a variety of languages.
| Language | Support Status |
|---|---|
| TypeScript | ✅ Supported |
| JavaScript | ✅ Supported |
| Python | |
| Others | Need something else? Open an issue |
AgentMark Studio supports type safety out of the box. Read more about it here.
We welcome contributions! Please check out our contribution guidelines for more information.
Join our community to collaborate, ask questions, and stay updated:
This project is licensed under the MIT License.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for agentmark
Similar Open Source Tools
agentmark
AgentMark is a tool designed to make it easy for developers to develop, test, and evaluate AI Agents. It combines Markdown syntax with JSX components to create reliable Agents. The tool seamlessly integrates with SDKs, offering comprehensive tooling such as full type safety, unified prompt configuration, syntax highlighting, loops and conditionals, custom SDK adapters, and support for text, object, image, and speech generation across multiple model providers.
bedrock-engineer
Bedrock Engineer is an autonomous software development agent application that utilizes Amazon Bedrock. It allows users to customize, create/edit files, execute commands, search the web, use a knowledge base, utilize multi-agents, generate images, and more. The tool provides an interactive chat interface with AI agents, file system operations, web search capabilities, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select and customize agents, choose from various tools like file system operations, web search, Amazon Bedrock integration, and system command execution. Additionally, the tool offers features for website generation, connecting to design system data sources, AWS Step Functions ASL definition generation, diagram creation using natural language descriptions, and multi-language support.
open-assistant-api
Open Assistant API is an open-source, self-hosted AI intelligent assistant API compatible with the official OpenAI interface. It supports integration with more commercial and private models, R2R RAG engine, internet search, custom functions, built-in tools, code interpreter, multimodal support, LLM support, and message streaming output. Users can deploy the service locally and expand existing features. The API provides user isolation based on tokens for SaaS deployment requirements and allows integration of various tools to enhance its capability to connect with the external world.
super-agent-party
A 3D AI desktop companion with endless possibilities! This repository provides a platform for enhancing the LLM API without code modification, supporting seamless integration of various functionalities such as knowledge bases, real-time networking, multimodal capabilities, automation, and deep thinking control. It offers one-click deployment to multiple terminals, ecological tool interconnection, standardized interface opening, and compatibility across all platforms. Users can deploy the tool on Windows, macOS, Linux, or Docker, and access features like intelligent agent deployment, VRM desktop pets, Tavern character cards, QQ bot deployment, and developer-friendly interfaces. The tool supports multi-service providers, extensive tool integration, and ComfyUI workflows. Hardware requirements are minimal, making it suitable for various deployment scenarios.
NeMo-Agent-Toolkit
NVIDIA NeMo Agent toolkit is a flexible, lightweight, and unifying library that allows you to easily connect existing enterprise agents to data sources and tools across any framework. It is framework agnostic, promotes reusability, enables rapid development, provides profiling capabilities, offers observability features, includes an evaluation system, features a user interface for interaction, and supports the Model Context Protocol (MCP). With NeMo Agent toolkit, users can move quickly, experiment freely, and ensure reliability across all agent-driven projects.
bedrock-engineer
Bedrock Engineer is an AI assistant for software development tasks powered by Amazon Bedrock. It combines large language models with file system operations and web search functionality to support development processes. The autonomous AI agent provides interactive chat, file system operations, web search, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select agents, customize them, select tools, and customize tools. The tool also includes a website generator for React.js, Vue.js, Svelte.js, and Vanilla.js, with support for inline styling, Tailwind.css, and Material UI. Users can connect to design system data sources and generate AWS Step Functions ASL definitions.
video-search-and-summarization
The NVIDIA AI Blueprint for Video Search and Summarization is a repository showcasing video search and summarization agent with NVIDIA NIM microservices. It enables industries to make better decisions faster by providing insightful, accurate, and interactive video analytics AI agents. These agents can perform tasks like video summarization and visual question-answering, unlocking new application possibilities. The repository includes software components like NIM microservices, ingestion pipeline, and CA-RAG module, offering a comprehensive solution for analyzing and summarizing large volumes of video data. The target audience includes video analysts, IT engineers, and GenAI developers who can benefit from the blueprint's 1-click deployment steps, easy-to-manage configurations, and customization options. The repository structure overview includes directories for deployment, source code, and training notebooks, along with documentation for detailed instructions. Hardware requirements vary based on deployment topology and dependencies like VLM and LLM, with different deployment methods such as Launchable Deployment, Docker Compose Deployment, and Helm Chart Deployment provided for various use cases.
bytechef
ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. It provides an intuitive UI Workflow Editor, event-driven & scheduled workflows, multiple flow controls, built-in code editor supporting Java, JavaScript, Python, and Ruby, rich component ecosystem, extendable with custom connectors, AI-ready with built-in AI components, developer-ready to expose workflows as APIs, version control friendly, self-hosted, scalable, and resilient. It allows users to build and visualize workflows, automate tasks across SaaS apps, internal APIs, and databases, and handle millions of workflows with high availability and fault tolerance.
coze-studio
Coze Studio is an all-in-one AI agent development tool that offers the most convenient AI agent development environment, from development to deployment. It provides core technologies for AI agent development, complete app templates, and build frameworks. Coze Studio aims to simplify creating, debugging, and deploying AI agents through visual design and build tools, enabling powerful AI app development and customized business logic. The tool is developed using Golang for the backend, React + TypeScript for the frontend, and follows microservices architecture based on domain-driven design principles.
posthog
PostHog is an all-in-one, open source platform for building successful products. It provides tools for product analytics, web analytics, session replays, feature flags, experiments, error tracking, surveys, data warehouse, data pipelines, LLM analytics, and workflows. Users can get started with a generous free tier, self-host the platform, or use PostHog Cloud. The platform supports various SDKs and libraries for popular languages and frameworks, making it versatile and easy to integrate. PostHog is suitable for teams looking to understand user behavior, improve product performance, and automate actions or messages to users.
buildel
Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.
5ire
5ire is a cross-platform desktop client that integrates a local knowledge base for multilingual vectorization, supports parsing and vectorization of various document formats, offers usage analytics to track API spending, provides a prompts library for creating and organizing prompts with variable support, allows bookmarking of conversations, and enables quick keyword searches across conversations. It is licensed under the GNU General Public License version 3.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
katib
Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is the project which is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom Resources with out of the box support for Kubeflow Training Operator, Argo Workflows, Tekton Pipelines and many more.
uusec-waf
UUSEC WAF is an industrial grade free, high-performance, and highly scalable web application and API security protection product that supports AI and semantic engines. It provides intelligent 0-day defense, ultimate CDN acceleration, powerful proactive defense, advanced semantic engine, and advanced rule engine. With features like machine learning technology, cache cleaning, dual layer defense, semantic analysis, and Lua script rule writing, UUSEC WAF offers comprehensive website protection with three-layer defense functions at traffic, system, and runtime layers.
ChatGPT-Shortcut
ChatGPT Shortcut is an AI tool designed to maximize efficiency and productivity by providing a concise list of AI instructions. Users can easily find prompts suitable for various scenarios, boosting productivity and work efficiency. The tool offers one-click prompts, optimization for non-English languages, prompt saving and sharing, and a community voting system. It includes a browser extension compatible with Chrome, Edge, Firefox, and other Chromium-based browsers, as well as a Tampermonkey script for custom domain use. The tool is open-source, allowing users to modify the website's nomenclature, usage directives, and prompts for different languages.
For similar tasks
HPT
Hyper-Pretrained Transformers (HPT) is a novel multimodal LLM framework from HyperGAI, trained for vision-language models capable of understanding both textual and visual inputs. The repository contains the open-source implementation of inference code to reproduce the evaluation results of HPT Air on different benchmarks. HPT has achieved competitive results with state-of-the-art models on various multimodal LLM benchmarks. It offers models like HPT 1.5 Air and HPT 1.0 Air, providing efficient solutions for vision-and-language tasks.
learnopencv
LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.
spark-free-api
Spark AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, AI drawing support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository includes multiple free-api projects for various AI services. Users can access the API for tasks such as chat completions, AI drawing, document interpretation, image analysis, and ssoSessionId live checking. The project also provides guidelines for deployment using Docker, Docker-compose, Render, Vercel, and native deployment methods. It recommends using custom clients for faster and simpler access to the free-api series projects.
mlx-vlm
MLX-VLM is a package designed for running Vision LLMs on Mac systems using MLX. It provides a convenient way to install and utilize the package for processing large language models related to vision tasks. The tool simplifies the process of running LLMs on Mac computers, offering a seamless experience for users interested in leveraging MLX for vision-related projects.
clarifai-python-grpc
This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.
horde-worker-reGen
This repository provides the latest implementation for the AI Horde Worker, allowing users to utilize their graphics card(s) to generate, post-process, or analyze images for others. It offers a platform where users can create images and earn 'kudos' in return, granting priority for their own image generations. The repository includes important details for setup, recommendations for system configurations, instructions for installation on Windows and Linux, basic usage guidelines, and information on updating the AI Horde Worker. Users can also run the worker with multiple GPUs and receive notifications for updates through Discord. Additionally, the repository contains models that are licensed under the CreativeML OpenRAIL License.
geospy
Geospy is a Python tool that utilizes Graylark's AI-powered geolocation service to determine the location where photos were taken. It allows users to analyze images and retrieve information such as country, city, explanation, coordinates, and Google Maps links. The tool provides a seamless way to integrate geolocation services into various projects and applications.
Awesome-Colorful-LLM
Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.
For similar jobs
promptflow
**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
deepeval
DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.
MegaDetector
MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".
leapfrogai
LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.
llava-docker
This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.
carrot
The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.
TrustLLM
TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.
AI-YinMei
AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.

