From 61587fddf965a2d823600349c352c4d38ca7576c Mon Sep 17 00:00:00 2001 From: Ryan Randall Date: Thu, 6 Feb 2025 11:50:57 -0500 Subject: [PATCH] Fix: add puzzlet + agentmark Signed-off-by: Ryan Randall --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index c1ec22f..7e844c6 100644 --- a/README.md +++ b/README.md @@ -171,6 +171,7 @@ An awesome & curated list of the best LLMOps tools for developers. | Project | Details | Repository | | ------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- | | [agenta](https://github.com/Agenta-AI/agenta) | The LLMOps platform to build robust LLM apps. Easily experiment and evaluate different prompts, models, and workflows to build robust apps. | ![GitHub Badge](https://img.shields.io/github/stars/Agenta-AI/agenta.svg?style=flat-square) | +| [AgentMark](https://github.com/puzzlet-ai/agentmark) | Type-Safe Markdown-based Agents | ![GitHub Badge](https://img.shields.io/github/stars/Puzzlet-ai/agentmark.svg?style=flat-square) | | [AI studio](https://github.com/missingstudio/ai) | A Reliable Open Source AI studio to build core infrastructure stack for your LLM Applications. It allows you to gain visibility, make your application reliable, and prepare it for production with features such as caching, rate limiting, exponential retry, model fallback, and more. | ![GitHub Badge](https://img.shields.io/github/stars/missingstudio/ai.svg?style=flat-square) | | [Arize-Phoenix](https://github.com/Arize-ai/phoenix) | ML observability for LLMs, vision, language, and tabular models. | ![GitHub Badge](https://img.shields.io/github/stars/Arize-ai/phoenix.svg?style=flat-square) | | [BudgetML](https://github.com/ebhy/budgetml) | Deploy a ML inference service on a budget in less than 10 lines of code. | ![GitHub Badge](https://img.shields.io/github/stars/ebhy/budgetml.svg?style=flat-square) | @@ -220,6 +221,7 @@ An awesome & curated list of the best LLMOps tools for developers. | [PromptSite](https://github.com/dkuang1980/promptsite) | A lightweight Python library for prompt lifecycle management that helps you version control, track, experiment and debug with your LLM prompts with ease. Minimal setup, no servers, databases, or API keys required - works directly with your local filesystem, ideal for data scientists and engineers to easily integrate into existing LLM workflows | | | [Prompteams](https://www.prompteams.com) | Prompt management system. Version, test, collaborate, and retrieve prompts through real-time APIs. Have GitHub style with repos, branches, and commits (and commit history). | | | [prompttools](https://github.com/hegelai/prompttools) | Open-source tools for testing and experimenting with prompts. The core idea is to enable developers to evaluate prompts using familiar interfaces like code and notebooks. In just a few lines of codes, you can test your prompts and parameters across different models (whether you are using OpenAI, Anthropic, or LLaMA models). You can even evaluate the retrieval accuracy of vector databases. | ![GitHub Badge](https://img.shields.io/github/stars/hegelai/prompttools.svg?style=flat-square) | +| [Puzzlet AI](https://www.puzzlet.ai) | The Git-Based LLM Engineering Platform. Achieve more from GenAI: Manage, evaluate, and improve your full-stack LLM application - with version control, type-safety, and local development built-in. | | | [systemprompt.io](https://systemprompt.io) | Systemprompt.io is a Rest API with quality tooling to enable the creation, use and observability of prompts in any AI system. Control every detail of your prompt for a SOTA prompt management experience. | | | [TreeScale](https://treescale.com) | All In One Dev Platform For LLM Apps. Deploy LLM-enhanced APIs seamlessly using tools for prompt optimization, semantic querying, version management, statistical evaluation, and performance tracking. As a part of the developer friendly API implementation TreeScale offers Elastic LLM product, which makes a unified API Endpoint for all major LLM providers and open source models. | | | [TrueFoundry](https://www.truefoundry.com/) | Deploy LLMOps tools like Vector DBs, Embedding server etc on your own Kubernetes (EKS,AKS,GKE,On-prem) Infra including deploying, Fine-tuning, tracking Prompts and serving Open Source LLM Models with full Data Security and Optimal GPU Management. Train and Launch your LLM Application at Production scale with best Software Engineering practices. | |