SimAI is the industry's first full-stack, high-precision simulator for AI large-scale training. It provides detailed modeling and simulation of the entire LLM training process, encompassing framework, collective communication, network layers, and more. This comprehensive approach offers end-to-end performance data, enabling researchers to analyze training process details, evaluate time consumption of AI tasks under specific conditions, and assess performance gains from various algorithmic optimizations.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

Unoplat-CodeConfluence is a universal code context engine that aims to extract, understand, and provide precise code context across repositories tied through domains. It combines deterministic code grammar with state-of-the-art LLM pipelines to achieve human-like understanding of codebases in minutes. The tool offers smart summarization, graph-based embedding, enhanced onboarding, graph-based intelligence, deep dependency insights, and seamless integration with existing development tools and workflows. It provides a precise context API for knowledge engine and AI coding assistants, enabling reliable code understanding through bottom-up code summarization, graph-based querying, and deep package and dependency analysis.

ERNIE 4.5 is a family of large-scale multimodal models with 10 distinct variants, including Mixture-of-Experts (MoE) models with 47B and 3B active parameters. The models feature a novel heterogeneous modality structure supporting parameter sharing across modalities while allowing dedicated parameters for each individual modality. Trained with optimal efficiency using PaddlePaddle deep learning framework, ERNIE 4.5 models achieve state-of-the-art performance across text and multimodal benchmarks, enhancing multimodal understanding without compromising performance on text-related tasks. The open-source development toolkits for ERNIE 4.5 offer industrial-grade capabilities, resource-efficient training and inference workflows, and multi-hardware compatibility.

Parallax is a fully decentralized inference engine developed by Gradient. It allows users to build their own AI cluster for model inference across distributed nodes with varying configurations and physical locations. Core features include hosting local LLM on personal devices, cross-platform support, pipeline parallel model sharding, paged KV cache management, continuous batching for Mac, dynamic request scheduling, and routing for high performance. The backend architecture includes P2P communication powered by Lattica, GPU backend powered by SGLang and vLLM, and MAC backend powered by MLX LM.

EvoAgentX is an open-source framework for building, evaluating, and evolving LLM-based agents or agentic workflows in an automated, modular, and goal-driven manner. It enables developers and researchers to move beyond static prompt chaining or manual workflow orchestration by introducing a self-evolving agent ecosystem. The framework includes features such as agent workflow autoconstruction, built-in evaluation, self-evolution engine, plug-and-play compatibility, comprehensive built-in tools, memory module support, and human-in-the-loop interactions.

Agents Towards Production is an open-source playbook for building production-ready GenAI agents that scale from prototype to enterprise. Tutorials cover stateful workflows, vector memory, real-time web search APIs, Docker deployment, FastAPI endpoints, security guardrails, GPU scaling, browser automation, fine-tuning, multi-agent coordination, observability, evaluation, and UI development.

Xorbits Inference (Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy and serve your or state-of-the-art built-in models using just a single command. Whether you are a researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full potential of cutting-edge AI models.

RAI is a framework designed to bring general multi-agent system capabilities to robots, enhancing human interactivity, flexibility in problem-solving, and out-of-the-box AI features. It supports multi-modalities, incorporates an advanced database for agent memory, provides ROS 2-oriented tooling, and offers a comprehensive task/mission orchestrator. The framework includes features such as voice interaction, customizable robot identity, camera sensor access, reasoning through ROS logs, and integration with LangChain for AI tools. RAI aims to support various AI vendors, improve human-robot interaction, provide an SDK for developers, and offer a user interface for configuration.

BeeAI Framework is a versatile tool for building production-ready multi-agent systems. It offers flexibility in orchestrating agents, seamless integration with various models and tools, and production-grade controls for scaling. The framework supports Python and TypeScript libraries, enabling users to implement simple to complex multi-agent patterns, connect with AI services, and optimize token usage and resource management.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

KubeSphere is a distributed operating system for cloud-native application management, using Kubernetes as its kernel. It provides a plug-and-play architecture, allowing third-party applications to be seamlessly integrated into its ecosystem. KubeSphere is also a multi-tenant container platform with full-stack automated IT operation and streamlined DevOps workflows. It provides developer-friendly wizard web UI, helping enterprises to build out a more robust and feature-rich platform, which includes most common functionalities needed for enterprise Kubernetes strategy.

Vision Agents is an open-source project by Stream that provides building blocks for creating intelligent, low-latency video experiences powered by custom models and infrastructure. It offers multi-modal AI agents that watch, listen, and understand video in real-time. The project includes SDKs for various platforms and integrates with popular AI services like Gemini and OpenAI. Vision Agents can be used for tasks such as sports coaching, security camera systems with package theft detection, and building invisible assistants for various applications. The project aims to simplify the development of real-time vision AI applications by providing a range of processors, integrations, and out-of-the-box features.

Nuitrack™ is an ultimate 3D body tracking solution developed by 3DiVi Inc. It enables body motion analytics applications for virtually any widespread depth sensors and hardware platforms, supporting a wide range of applications from real-time gesture recognition on embedded platforms to large-scale multisensor analytical systems. Nuitrack provides highly-sophisticated 3D skeletal tracking, basic facial analysis, hand tracking, and gesture recognition APIs for UI control. It offers two skeletal tracking engines: classical for embedded hardware and AI for complex poses, providing a human-centric spatial understanding tool for natural and intelligent user engagement.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

LLM4AD is an open-source Python-based platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). It provides unified interfaces for methods, tasks, and LLMs, along with features like evaluation acceleration, secure evaluation, logs, GUI support, and more. The platform was originally developed for optimization tasks but is versatile enough to be used in other areas such as machine learning, science discovery, game theory, and engineering design. It offers various search methods and algorithm design tasks across different domains. LLM4AD supports remote LLM API, local HuggingFace LLM deployment, and custom LLM interfaces. The project is licensed under the MIT License and welcomes contributions, collaborations, and issue reports.

SimAI is the industry's first full-stack, high-precision simulator for AI large-scale training. It provides detailed modeling and simulation of the entire LLM training process, encompassing framework, collective communication, network layers, and more. This comprehensive approach offers end-to-end performance data, enabling researchers to analyze training process details, evaluate time consumption of AI tasks under specific conditions, and assess performance gains from various algorithmic optimizations.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

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.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.