Reclaimer

trying to make a framework for this called clusterops.

https://github.com/The-Swarm-Corporation/ClusterOps

Writing clean, maintainable code is an art that takes years to master. This guide presents a philosophy built on six fundamental principles that, when followed consistently, lead to more robust and maintainable software. We'll explore each principle with practical examples in both Python and Rust, demonstrating both good and bad practices.

https://buff.ly/4eZeAlz

Like, repost, and share this with friends!

The Swarms framework was the first ever production-grade multi-agent orchestration framework. OpenAI has stolen our name, code, and methodology. Everything down from the syntax of the agent structure to the swarm class object was tolen from our codebase:

https://github.com/kyegomez/swarms

We plan to seek legal repercussions to pay for the damages done against our name unless openai invests in us.

Our website is swarms.ai and we're pioneering the multi-agent revolution. Share this on all social medias to showcase how OpenAI is stealing and infringing upon their own customers and users.

ClusterOps is an enterprise-grade Python library developed and maintained by the Swarms Team to help you manage and execute agents on specific CPUs and GPUs across clusters. This tool enables advanced CPU and GPU selection, dynamic task allocation, and resource monitoring, making it ideal for high-performance distributed computing environments.

$ pip3 install -U clusterops

To understand the world economy is to grasp the reality that economics is, at its core, built upon the exchange of value. In this essay, we discuss the bedrock of economic systems and how the exchange of value is the heart of all economic systems.

https://buff.ly/3zQR3Eb

MedInsight Pro is an AI-driven agent that streamlines the extraction of actionable insights from medical research. Designed for healthcare professionals, researchers, and innovators, it leverages advanced NLP models (like GPT-4) and integrates with leading data sources such as PubMed and Semantic Scholar. This powerful tool reads and summarizes complex medical papers in real-time, identifying breakthrough treatments, clinical trials, and emerging trends to provide concise and relevant insights.

MedInsight Pro saves time, ensures accuracy, and empowers healthcare leaders to make data-driven decisions based on the latest research, all while offering a user-friendly interface for rapid deployment in enterprise environments.

tickr-agent is an enterprise-ready, scalable Python library for building swarms of financial agents that conduct comprehensive stock analysis and produce insights. Powered by yfinance, loguru for logging, and pydantic for data validation, tickr-agent is designed for businesses that need robust financial data processing, multithreading, and seamless integration with AI-powered models (via OpenAI) to derive actionable insights.

With tickr-agent, you can automate the retrieval of stock market data, perform technical analysis (e.g., RSI, moving averages), and integrate insights into AI-driven workflows. This solution is built to handle real-time data processing, analysis, and reporting at an enterprise scale.

CodeGuardian is an intelligent agent designed to automate the generation of production-grade unit tests for your Python code. It not only creates and runs these tests but also monitors them in real-time, providing you with comprehensive summaries of your code health. With CodeGuardian, you can enhance code reliability, maintainability, and accelerate your development workflow.

Introducing News Agent Swarm

NewsAgent is an enterprise-grade news aggregation agent designed to fetch, query, and summarize news from multiple sources at scale. Built for enterprises, NewsAgent enables you to automate the process of news monitoring, delivering summarized, relevant, and timely news from across the web.

Features:

⎆ Multi-Article Summarization: Efficiently summarizes multiple articles at once, reducing the noise and delivering concise insights

⎆ Smart Query Crafting: Automatically creates optimized queries using an llm to fetch the most relevant news from multiple sources.

⎆ Customizable Sources: Add or remove specific news sources, tailored to your business needs.

https://buff.ly/4dhLIDu

tickr-agent is an enterprise-ready, scalable Python library for building swarms of financial agents that conduct comprehensive stock analysis and produce insights. Powered by yfinance, loguru for logging, and pydantic for data validation, tickr-agent is designed for businesses that need robust financial data processing, multithreading, and seamless integration with AI-powered models (via OpenAI) to derive actionable insights.

Research-Paper-Hive is an intelligent AI-powered application that helps you find and summarize research papers based on your preferences. Whether you're diving into a new research area or looking for papers tailored to specific topics, Research-Paper-Hive uses a swarm of AI agents to streamline your workflow by searching, analyzing, and summarizing relevant research papers for you.

OmniParse is an enterprise-grade solution designed to transform unstructured documents into actionable, structured data with precision and reliability. Whether dealing with invoices, contracts, reports, or any other type of unstructured data, OmniParse is your go-to solution for seamless extraction, processing, and integration into your workflows.

MedInsight Pro is an AI-driven agent that streamlines the extraction of actionable insights from medical research. Designed for healthcare professionals, researchers, and innovators, it leverages advanced NLP models (like GPT-4) and integrates with leading data sources such as PubMed and Semantic Scholar. This powerful tool reads and summarizes complex medical papers in real-time, identifying breakthrough treatments, clinical trials, and emerging trends to provide concise and relevant insights.

One-Click (ETC) Mining Script

-> Automated Setup: Configures the mining environment.

https://github.com/kyegomez/one-click-crypto-mining/

-> GPU Detection: Automatically detects and uses available NVIDIA GPUs.

-> Logging: Logs mining activity and errors for monitoring and troubleshooting.

Announcing the Revolutionary Swarms Memory!

We are thrilled to unveil our latest breakthrough in AI technology – Swarms Memory! This cutting-edge package is set to redefine the landscape of Retrieval-Augmented Generation (RAG) systems, making them easier to use, more reliable, and at the bleeding edge of innovation.

https://github.com/kyegomez/swarms-memory

What's Inside?

-> Pinecone and ChromaDB Integration: Start building with these powerful tools right away.

More Integrations Coming Soon: We're rapidly expanding our capabilities, and new integrations are on the horizon.

Get Started with Python $ pip install swarms-memory

Why Swarms Memory? Experience unparalleled memory management and enhance your AI systems with state-of-the-art technology.

Join the Revolution Check out the repository: https://github.com/kyegomez/swarms-memory

Be Part of the Future We're actively seeking contributors to join our mission. Collaborate with other innovators and shape the future of AI.

Join Our Community Connect with like-minded individuals and stay updated: https://discord.com/servers/agora-999382051935506503

Let's push the boundaries of AI together and create something extraordinary!

Polymorphic Hard Drive Security Protocol (PHDSP) is a cutting-edge AI-based hard drive protection system. Inspired by advanced encryption mechanisms, it continuously monitors your hard drive for unauthorized access and modifications, dynamically rewrites its own code to thwart attacks, and ensures system integrity through self-healing mechanisms.

Full code: https://github.com/kyegomez/zeta/blob...

Join us in this quick and impactful dive into the world of natural language processing (NLP) as we guide you through creating a powerful Language Model using PyTorch, all in just 5 minutes! Whether you're a beginner or an experienced developer, this tutorial is designed to give you a solid foundation in building and training language models with one of the most popular deep learning frameworks available today.

What We'll Cover: - Quick introduction to PyTorch and its fundamental concepts. - Step-by-step guide to building a simple yet effective language model. - Essential training techniques to improve your model's performance. - Tips and tricks for fine-tuning and optimizing your model for real-world applications.

Why PyTorch? PyTorch offers flexibility, ease of use, and a dynamic computational graph that makes it the go-to choice for researchers and developers working on cutting-edge NLP projects.

Shout Out to Zeta! A huge shout out to Zeta, the main framework we're using in this tutorial. Zeta provides an incredible set of tools and functionalities that significantly simplify the process of model development and experimentation. Check out Zeta on GitHub and see how it can supercharge your NLP projects: https://github.com/kyegomez/zeta

Stay Connected! Don't miss out on the conversation and the opportunity to connect with like-minded individuals passionate about AI and machine learning. Join our Discord community here:

/ discord

Looking Forward: - By the end of this video, you'll have a clear understanding of how to create and train a language model with PyTorch. - You'll also be equipped with knowledge on leveraging Zeta for more efficient model training and experimentation.

No prior experience with PyTorch or NLP is required, making this the perfect starting point for anyone curious about diving into the world of AI and machine learning.

Whether you're looking to implement a chatbot, a text generator, or any NLP-driven project, this tutorial will set you on the right path.

Like, Share, and Subscribe for more tutorials, tips, and guides on AI, machine learning, and much more.

#PyTorch #NLP #LanguageModel #MachineLearning #Zeta #ArtificialIntelligence #Tutorial #QuickGuide #Programming #DeepLearning #AICommunity

Announcing, awesome-robotic-foundation-models

An awesome list of Multi-Modal Robotic Foundation Models we're working on at Swarms! Palm-E, RTX, RT-2, and ++ many others.

https://github.com/kyegomez/awesome-robotic-foundation-model...

Lumixion-e1-70k-fncall-qlora Lumixion is the first ever vast array of multi-modal function calling models easily available for usage. This is the first iteration finetuned on 70+ samples with qlora and many other optimizations. https://huggingface.co/AgoraX/Lumixion-e1-70k-fncall-qlora

Swarm of Minecraft Agents Episode 1

https://youtube.com/watch?v=xMAlwazdZbM

Our plan is to deploy thousands of agents into minecraft all collaborating to eventually pave the way into real-world deployment!

Next video will feature 50+ agents!

Powered by Swarms

https://github.com/kyegomez/swarms

Imagine being able to convert a research paper directly into usable code. Sounds like a dream, right? Well, we've turned that dream into reality. With all new new GPT, you can now seamlessly transform AI research papers into code in Pytorch, Jax, Triton, Einops, or any framework of your choice ;)

After building out thousands of neural nets and facing the same annoying bottlenecks of chaotic codebases with no modularity and low performance modules, Zeta needed to be born to enable me and others to quickly prototype, train, and optimize the latest SOTA neural nets and deploy them into production.

Zeta places a radical emphasis on useability, modularity, and performance. Zeta is now currently employed in 100s of models across my github and across others. Get started below and LMK if you want my help building any model, I'm here for you

https://github.com/kyegomez/zeta

I just launched Swarms on ProductHunt

It's a simple python package that enables you to build, deploy, and scale "Swarms" of LLMs, you can get started in 5 lines of code, check it out:

https://producthunt.com/products/swarms

Follow it and pls leave a review if you have tried it

Github: https://github.com/kyegomez/swarms

AutoRT Implementation complete

First ever open source swarm of robots powered by multimodal llms as described in the autort paper.

Any # of agents Plug in robotic action model Each agent comes with [LLM, Long term memory, and tool usage]

https://github.com/kyegomez/AutoRT

The next era of Robotics is here

Announcing HRTX, a Hivemind Multi-Input and Multi-Output Transformer for Robotics.

This can model can process inputs from any number of N robots and output any Z actions across any of those robots.

This model can process input data from any number of robots and then pass them through one single and unified model trained on various hardware and tasks and provide various single or multi-outputs across the robots!

Based on: https://arxiv.org/abs/2402.06580 and RTX

We're actively training this model at Agora and need help with bugs and etc, join us and contribute to open source AI:

https://discord.gg/qqgs6MbYEZ

Introduce yourself [tag me] and then locate the HRTX active project channel