MCPJungle is a self-hosted MCP Gateway for private AI agents, serving as a registry for Model Context Protocol Servers. Developers use it to manage servers and tools centrally, while clients discover and consume tools from a single 'Gateway' MCP Server. Suitable for developers using MCP Clients like Claude & Cursor, building production-grade AI Agents, and organizations managing client-server interactions. The tool allows quick start, installation, usage, server and client setup, connection to Claude and Cursor, enabling/disabling tools, managing tool groups, authentication, enterprise features like access control and OpenTelemetry metrics. Limitations include lack of long-running connections to servers and no support for OAuth flow. Contributions are welcome.

AIAC is a library and command line tool to generate Infrastructure as Code (IaC) templates, configurations, utilities, queries, and more via LLM providers such as OpenAI, Amazon Bedrock, and Ollama. Users can define multiple 'backends' targeting different LLM providers and environments using a simple configuration file. The tool allows users to ask a model to generate templates for different scenarios and composes an appropriate request to the selected provider, storing the resulting code to a file and/or printing it to standard output.

This repository provides an easy-to-use solution for running inference servers on Slurm-managed computing clusters using vLLM. All scripts in this repository run natively on the Vector Institute cluster environment. Users can deploy models as Slurm jobs, check server status and performance metrics, and shut down models. The repository also supports launching custom models with specific configurations. Additionally, users can send inference requests and set up an SSH tunnel to run inference from a local device.

The Slack Bot is a tool designed to enhance the workflow of development teams by integrating with Jenkins, GitHub, GitLab, and Jira. It allows for custom commands, macros, crons, and project-specific commands to be implemented easily. Users can interact with the bot through Slack messages, execute commands, and monitor job progress. The bot supports features like starting and monitoring Jenkins jobs, tracking pull requests, querying Jira information, creating buttons for interactions, generating images with DALL-E, playing quiz games, checking weather, defining custom commands, and more. Configuration is managed via YAML files, allowing users to set up credentials for external services, define custom commands, schedule cron jobs, and configure VCS systems like Bitbucket for automated branch lookup in Jenkins triggers.

Magic CLI is a command line utility that leverages Large Language Models (LLMs) to enhance command line efficiency. It is inspired by projects like Amazon Q and GitHub Copilot for CLI. The tool allows users to suggest commands, search across command history, and generate commands for specific tasks using local or remote LLM providers. Magic CLI also provides configuration options for LLM selection and response generation. The project is still in early development, so users should expect breaking changes and bugs.

VectorFlow is an open source, high throughput, fault tolerant vector embedding pipeline. It provides a simple API endpoint for ingesting large volumes of raw data, processing, and storing or returning the vectors quickly and reliably. The tool supports text-based files like TXT, PDF, HTML, and DOCX, and can be run locally with Kubernetes in production. VectorFlow offers functionalities like embedding documents, running chunking schemas, custom chunking, and integrating with vector databases like Pinecone, Qdrant, and Weaviate. It enforces a standardized schema for uploading data to a vector store and supports features like raw embeddings webhook, chunk validation webhook, S3 endpoint, and telemetry. The tool can be used with the Python client and provides detailed instructions for running and testing the functionalities.

Loz is a command-line tool that integrates AI capabilities with Unix tools, enabling users to execute system commands and utilize Unix pipes. It supports multiple LLM services like OpenAI API, Microsoft Copilot, and Ollama. Users can run Linux commands based on natural language prompts, enhance Git commit formatting, and interact with the tool in safe mode. Loz can process input from other command-line tools through Unix pipes and automatically generate Git commit messages. It provides features like chat history access, configurable LLM settings, and contribution opportunities.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

Smartcat is a CLI interface that brings language models into the Unix ecosystem, allowing power users to leverage the capabilities of LLMs in their daily workflows. It features a minimalist design, seamless integration with terminal and editor workflows, and customizable prompts for specific tasks. Smartcat currently supports OpenAI, Mistral AI, and Anthropic APIs, providing access to a range of language models. With its ability to manipulate file and text streams, integrate with editors, and offer configurable settings, Smartcat empowers users to automate tasks, enhance code quality, and explore creative possibilities.

HASH is a self-building, open-source database which grows, structures and checks itself. With it, we're creating a platform for decision-making, which helps you integrate, understand and use data in a variety of different ways.

RayLLM (formerly known as Aviary) is an LLM serving solution that makes it easy to deploy and manage a variety of open source LLMs, built on Ray Serve. It provides an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. RayLLM supports Transformer models hosted on Hugging Face Hub or present on local disk. It simplifies the deployment of multiple LLMs, the addition of new LLMs, and offers unique autoscaling support, including scale-to-zero. RayLLM fully supports multi-GPU & multi-node model deployments and offers high performance features like continuous batching, quantization and streaming. It provides a REST API that is similar to OpenAI's to make it easy to migrate and cross test them. RayLLM supports multiple LLM backends out of the box, including vLLM and TensorRT-LLM.

A Seamless Slurm-Native Solution for HPC-Based Services. This repository contains the stand-alone web interface of Chat AI, which can be set up independently to act as a wrapper for an OpenAI-compatible API endpoint. It consists of two Docker containers, 'front' and 'back', providing a ReactJS app served by ViteJS and a wrapper for message requests to prevent CORS errors. Configuration files allow setting port numbers, backend paths, models, user data, default conversation settings, and more. The 'back' service interacts with an OpenAI-compatible API endpoint using configurable attributes in 'back.json'. Customization options include creating a path for available models and setting the 'modelsPath' in 'front.json'. Acknowledgements to contributors and the Chat AI community are included.

Vectara Answer is a sample app for Vectara-powered Summarized Semantic Search (or question-answering) with advanced configuration options. For examples of what you can build with Vectara Answer, check out Ask News, LegalAid, or any of the other demo applications.

Claude Debugs For You is an MCP Server and VS Code extension that enables interactive debugging and evaluation of expressions with Claude or other LLM models. It is language-agnostic, requiring debugger console support and a valid launch.json for debugging in VSCode. Users can download the extension from releases or VS Code Marketplace, install it, and access commands through the status menu item 'Claude Debugs For You'. The tool supports debugging setups using stdio or /sse, and users can follow specific setup instructions depending on their configuration. Once set up, users can debug their code by interacting with the tool, which provides suggestions and fixes for identified issues.

Laragenie is an AI chatbot designed to understand and assist developers with their codebases. It runs on the command line from a Laravel app, helping developers onboard to new projects, understand codebases, and provide daily support. Laragenie accelerates workflow and collaboration by indexing files and directories, allowing users to ask questions and receive AI-generated responses. It supports OpenAI and Pinecone for processing and indexing data, making it a versatile tool for any repo in any language.

This repository, safety-tooling, is designed to be shared across various AI Safety projects. It provides an LLM API with a common interface for OpenAI, Anthropic, and Google models. The aim is to facilitate collaboration among AI Safety researchers, especially those with limited software engineering backgrounds, by offering a platform for contributing to a larger codebase. The repo can be used as a git submodule for easy collaboration and updates. It also supports pip installation for convenience. The repository includes features for installation, secrets management, linting, formatting, Redis configuration, testing, dependency management, inference, finetuning, API usage tracking, and various utilities for data processing and experimentation.

MCPJungle is a self-hosted MCP Gateway for private AI agents, serving as a registry for Model Context Protocol Servers. Developers use it to manage servers and tools centrally, while clients discover and consume tools from a single 'Gateway' MCP Server. Suitable for developers using MCP Clients like Claude & Cursor, building production-grade AI Agents, and organizations managing client-server interactions. The tool allows quick start, installation, usage, server and client setup, connection to Claude and Cursor, enabling/disabling tools, managing tool groups, authentication, enterprise features like access control and OpenTelemetry metrics. Limitations include lack of long-running connections to servers and no support for OAuth flow. Contributions are welcome.

Octelium is a free and open source, self-hosted, unified zero trust secure access platform that operates as a modern zero-config remote access VPN, a comprehensive Zero Trust Network Access (ZTNA)/BeyondCorp platform, an ngrok/Cloudflare Tunnel alternative, an API gateway, an AI/LLM gateway, a PaaS-like platform, a Kubernetes gateway/ingress, and a homelab infrastructure. It provides scalable zero trust architecture for identity-based, application-layer aware secure access via private client-based access over WireGuard/QUIC tunnels and public clientless access, with context-aware access control. Octelium offers dynamic secretless access, fine-grained access control, identity-based routing, continuous strong authentication, OpenTelemetry-native auditing, passwordless SSH, effortless deployment of containerized applications, centralized management, and more. It is open source, designed for self-hosting, and provides a commercial license option for businesses.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.