Open Autonomy is a framework for creating agent services that run as a multi-agent-system and offer enhanced functionalities on-chain. It enables executing complex operations like machine-learning algorithms in a decentralized, trust-minimized, transparent, and robust manner.

Denser Retriever is an enterprise-grade AI retriever designed to streamline AI integration into applications, combining keyword-based searches, vector databases, and machine learning rerankers using xgboost. It provides state-of-the-art accuracy on MTEB Retrieval benchmarking and supports various heterogeneous retrievers for end-to-end applications like chatbots and semantic search.

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

AnythingLLM is a full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

Kiln is an intuitive tool for fine-tuning LLM models, generating synthetic data, and collaborating on datasets. It offers desktop apps for Windows, MacOS, and Linux, zero-code fine-tuning for various models, interactive data generation, and Git-based version control. Users can easily collaborate with QA, PM, and subject matter experts, generate auto-prompts, and work with a wide range of models and providers. The tool is open-source, privacy-first, and supports structured data tasks in JSON format. Kiln is free to use and helps build high-quality AI products with datasets, facilitates collaboration between technical and non-technical teams, allows comparison of models and techniques without code, ensures structured data integrity, and prioritizes user privacy.

Axolotl is a lightweight and efficient tool for managing and analyzing large datasets. It provides a user-friendly interface for data manipulation, visualization, and statistical analysis. With Axolotl, users can easily import, clean, and explore data to gain valuable insights and make informed decisions. The tool supports various data formats and offers a wide range of functions for data processing and modeling. Whether you are a data scientist, researcher, or business analyst, Axolotl can help streamline your data workflows and enhance your data analysis capabilities.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

PySpur is a graph-based editor designed for LLM (Large Language Models) workflows. It offers modular building blocks, node-level debugging, and performance evaluation. The tool is easy to hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies. Users can quickly set up PySpur by cloning the repository, creating a .env file, starting docker services, and accessing the portal. PySpur can also work with local models served using Ollama, with steps provided for configuration. The roadmap includes features like canvas, async/batch execution, support for Ollama, new nodes, pipeline optimization, templates, code compilation, multimodal support, and more.

biniou is a self-hosted webui for various GenAI (generative artificial intelligence) tasks. It allows users to generate multimedia content using AI models and chatbots on their own computer, even without a dedicated GPU. The tool can work offline once deployed and required models are downloaded. It offers a wide range of features for text, image, audio, video, and 3D object generation and modification. Users can easily manage the tool through a control panel within the webui, with support for various operating systems and CUDA optimization. biniou is powered by Huggingface and Gradio, providing a cross-platform solution for AI content generation.

LLM Interface is an npm module that streamlines interactions with various Large Language Model (LLM) providers in Node.js applications. It offers a unified interface for switching between providers and models, supporting 36 providers and hundreds of models. Features include chat completion, streaming, error handling, extensibility, response caching, retries, JSON output, and repair. The package relies on npm packages like axios, @google/generative-ai, dotenv, jsonrepair, and loglevel. Installation is done via npm, and usage involves sending prompts to LLM providers. Tests can be run using npm test. Contributions are welcome under the MIT License.

Windows-Use is a powerful automation agent that interacts directly with the Windows OS at the GUI layer. It bridges the gap between AI agents and Windows to perform tasks such as opening apps, clicking buttons, typing, executing shell commands, and capturing UI state without relying on traditional computer vision models. It enables any large language model (LLM) to perform computer automation instead of relying on specific models for it.

assistant-ui is a set of React components for AI chat, providing wide model provider support out of the box and the ability to integrate custom APIs. It includes integrations with Langchain, Vercel AI SDK, TailwindCSS, shadcn-ui, react-markdown, react-syntax-highlighter, React Hook Form, and more. The tool allows users to quickly create AI chat applications with pre-configured templates and easy setup steps.

Sunshine-AIO is an all-in-one step-by-step guide to set up Sunshine with all necessary tools for Windows users. It provides a dedicated display for game streaming, virtual monitor switching, automatic resolution adjustment, resource-saving features, game launcher integration, and stream management. The project aims to evolve into an AIO tool as it progresses, welcoming contributions from users.

PankoGPT is an AI companion platform that allows users to easily create and deploy custom AI companions on messaging platforms like WhatsApp, Discord, and Telegram. Users can customize companion behavior, configure settings, and equip companions with various tools without the need for coding. The platform aims to provide contextual understanding and user-friendly interface for creating companions that respond based on context and offer configurable tools for enhanced capabilities. Planned features include expanded functionality, pre-built skills, and optimization for better performance.

Pipeshub-ai is a versatile tool for automating data pipelines in AI projects. It provides a user-friendly interface to design, deploy, and monitor complex data workflows, enabling seamless integration of various AI models and data sources. With Pipeshub-ai, users can easily create end-to-end pipelines for tasks such as data preprocessing, model training, and inference, streamlining the AI development process and improving productivity. The tool supports integration with popular AI frameworks and cloud services, making it suitable for both beginners and experienced AI practitioners.

Archestra is an enterprise-grade platform that enables non-technical users to safely leverage AI agents and MCP servers. It provides a secure runtime environment for AI interactions with sandboxing, resource controls, and prompt injection prevention. The platform supports MCP Protocol and is designed with a local-first architecture, enterprise-level security, and extensible tool system.

Open Autonomy is a framework for creating agent services that run as a multi-agent-system and offer enhanced functionalities on-chain. It enables executing complex operations like machine-learning algorithms in a decentralized, trust-minimized, transparent, and robust manner.

LLM-Subtrans is an open source subtitle translator that utilizes LLMs as a translation service. It supports translating subtitles between any language pairs supported by the language model. The application offers multiple subtitle formats support through a pluggable system, including .srt, .ssa/.ass, and .vtt files. Users can choose to use the packaged release for easy usage or install from source for more control over the setup. The tool requires an active internet connection as subtitles are sent to translation service providers' servers for translation.

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.