by HewlettPackard · Agent Tool · ★ 89
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LLM Agentic Tool Mesh Welcome to LLM Agentic Tool Mesh, a pioneering initiative by HPE aimed at democratizing Generative Artificial Intelligence (Gen AI). Our vision is to make Gen AI accessible and beneficial to a broader audience, enabling users from various backgrounds to leverage cutting-edge Gen AI technology effortlessly. The project consists of two main components: Athon (agentic-python library): A Python library that provides the core functions and abstractions required to build agentic applications. It serves as the foundation for creating, orchestrating, and managing Gen AI agents and workflows. Agentic Tool Mesh Platform: A service-based platform built on top of the agentic-python library. It offers a complete ecosystem of tools, APIs, and infrastructure needed to deploy, operate, and scale Gen AI-driven applications in real-world environments. Together, these components form a flexible and extensible framework for building next-generation AI solutions with minimal friction.
| Stars | 89 |
| Forks | 10 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69.1289025342386/100 |
| Open Issues | 22 |
| Last Updated | 2025-10-13 |
| Created | 2024-11-07 |
| Platforms | python |
| Est. Tokens | ~378k |
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llmesh is LLM Agentic Tool Mesh Platform is an innovative platform designed to streamline and enhance the use of AI in various applications. It serves as a central hub to orchestrate 'Intelligent Plugins,' opti. It is categorized as a Agent Tool with 89 GitHub stars.
llmesh is primarily written in Python. It covers topics such as agentic-tool-platform, athon, hpe.
You can find installation instructions and usage details in the llmesh GitHub repository at github.com/HewlettPackard/llmesh. The project has 89 stars and 10 forks, indicating an active community.
llmesh is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to llmesh on Agent Skills Hub include claude-skills-marketplace, tutor-skills, lenny-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.