Auto Engineer is a tool designed to automate the Software Development Life Cycle (SDLC) by building production-grade applications with a combination of human and AI agents. It offers a plugin-based architecture that allows users to install only the necessary functionality for their projects. The tool guides users through key stages including Flow Modeling, IA Generation, Deterministic Scaffolding, AI Coding & Testing Loop, and Comprehensive Quality Checks. Auto Engineer follows a command/event-driven architecture and provides a modular plugin system for specific functionalities. It supports TypeScript with strict typing throughout and includes a built-in message bus server with a web dashboard for monitoring commands and events.

LLM Context is a tool designed to assist developers in quickly injecting relevant content from code/text projects into Large Language Model chat interfaces. It leverages `.gitignore` patterns for smart file selection and offers a streamlined clipboard workflow using the command line. The tool also provides direct integration with Large Language Models through the Model Context Protocol (MCP). LLM Context is optimized for code repositories and collections of text/markdown/html documents, making it suitable for developers working on projects that fit within an LLM's context window. The tool is under active development and aims to enhance AI-assisted development workflows by harnessing the power of Large Language Models.

Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.

A sophisticated multi-agent configuration system for Claude Code that provides specialized agents and command templates to accelerate code review, refactoring, security audits, tech-lead-guidance, and UX evaluations. It offers essential commands, directory structure details, agent system overview, command templates, usage patterns, collaboration philosophy, sync management, advanced usage guidelines, and FAQ. The tool aims to streamline development workflows, enhance code quality, and facilitate collaboration between developers and AI agents.

Sim is a platform that allows users to build and deploy AI agent workflows quickly and easily. It provides cloud-hosted and self-hosted options, along with support for local AI models. Users can set up the application using Docker Compose, Dev Containers, or manual setup with PostgreSQL and pgvector extension. The platform utilizes technologies like Next.js, Bun, PostgreSQL with Drizzle ORM, Better Auth for authentication, Shadcn and Tailwind CSS for UI, Zustand for state management, ReactFlow for flow editor, Fumadocs for documentation, Turborepo for monorepo management, Socket.io for real-time communication, and Trigger.dev for background jobs.

Gonzo is a powerful, real-time log analysis terminal UI tool inspired by k9s. It allows users to analyze log streams with beautiful charts, AI-powered insights, and advanced filtering directly from the terminal. The tool provides features like live streaming log processing, OTLP support, interactive dashboard with real-time charts, advanced filtering options including regex support, and AI-powered insights such as pattern detection, anomaly analysis, and root cause suggestions. Users can also configure AI models from providers like OpenAI, LM Studio, and Ollama for intelligent log analysis. Gonzo is built with Bubble Tea, Lipgloss, Cobra, Viper, and OpenTelemetry, following a clean architecture with separate modules for TUI, log analysis, frequency tracking, OTLP handling, and AI integration.

CrewAI-GUI is a Node-Based Frontend tool designed to revolutionize AI workflow creation. It empowers users to design complex AI agent interactions through an intuitive drag-and-drop interface, export designs to JSON for modularity and reusability, and supports both GPT-4 API and Ollama for flexible AI backend. The tool ensures cross-platform compatibility, allowing users to create AI workflows on Windows, Linux, or macOS efficiently.

Orra is a tool for building production-ready multi-agent applications that handle complex real-world interactions. It coordinates tasks across existing stack, agents, and tools run as services using intelligent reasoning. With features like smart pre-evaluated execution plans, domain grounding, durable execution, and automatic service health monitoring, Orra enables users to go fast with tools as services and revert state to handle failures. It provides real-time status tracking and webhook result delivery, making it ideal for developers looking to move beyond simple crews and agents.

R2R (RAG to Riches) is a fast and efficient framework for serving high-quality Retrieval-Augmented Generation (RAG) to end users. The framework is designed with customizable pipelines and a feature-rich FastAPI implementation, enabling developers to quickly deploy and scale RAG-based applications. R2R was conceived to bridge the gap between local LLM experimentation and scalable production solutions. **R2R is to LangChain/LlamaIndex what NextJS is to React**. A JavaScript client for R2R deployments can be found here. ### Key Features * **🚀 Deploy** : Instantly launch production-ready RAG pipelines with streaming capabilities. * **🧩 Customize** : Tailor your pipeline with intuitive configuration files. * **🔌 Extend** : Enhance your pipeline with custom code integrations. * **⚖️ Autoscale** : Scale your pipeline effortlessly in the cloud using SciPhi. * **🤖 OSS** : Benefit from a framework developed by the open-source community, designed to simplify RAG deployment.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

AgentScope is a multi-agent platform designed to empower developers to build multi-agent applications with large-scale models. It features three high-level capabilities: Easy-to-Use, High Robustness, and Actor-Based Distribution. AgentScope provides a list of `ModelWrapper` to support both local model services and third-party model APIs, including OpenAI API, DashScope API, Gemini API, and ollama. It also enables developers to rapidly deploy local model services using libraries such as ollama (CPU inference), Flask + Transformers, Flask + ModelScope, FastChat, and vllm. AgentScope supports various services, including Web Search, Data Query, Retrieval, Code Execution, File Operation, and Text Processing. Example applications include Conversation, Game, and Distribution. AgentScope is released under Apache License 2.0 and welcomes contributions.

RLAMA is a powerful AI-driven question-answering tool that seamlessly integrates with local Ollama models. It enables users to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems tailored to their documentation needs. RLAMA follows a clean architecture pattern with clear separation of concerns, focusing on lightweight and portable RAG capabilities with minimal dependencies. The tool processes documents, generates embeddings, stores RAG systems locally, and provides contextually-informed responses to user queries. Supported document formats include text, code, and various document types, with troubleshooting steps available for common issues like Ollama accessibility, text extraction problems, and relevance of answers.

ScaBench is a comprehensive framework designed for evaluating security analysis tools and AI agents on real-world smart contract vulnerabilities. It provides curated datasets from recent audits and official tooling for consistent evaluation. The tool includes features such as curated datasets from Code4rena, Cantina, and Sherlock audits, a baseline runner for security analysis, a scoring tool for evaluating findings, a report generator for HTML reports with visualizations, and pipeline automation for complete workflow execution. Users can access curated datasets, generate new datasets, download project source code, run security analysis using LLMs, and evaluate tool findings against benchmarks using LLM matching. The tool enforces strict matching policies to ensure accurate evaluation results.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

SG-Nav is an online 3D scene graph prompting tool designed for LLM-based zero-shot object navigation. It proposes a framework that constructs an online 3D scene graph to prompt LLMs, allowing direct application to various scenes and categories without the need for training.

ChatGPT API Faucet is a frontend project for the public platform ChatGPT API Faucet, inspired by the crypto project MultiFaucet. It allows developers in the AI ecosystem to claim $1.00 for free every 24 hours. The program is developed using the Next.js framework and React library, with key components like _app.tsx for initializing pages, index.tsx for main modifications, and Layout.tsx for defining layout components. Users can deploy the project by installing dependencies, building the project, starting the project, configuring reverse proxies or using port:IP access, and running a development server. The tool also supports token balance queries and is related to projects like one-api, ChatGPT-Cost-Calculator, and Poe.Monster. It is licensed under the MIT license.

Auto Engineer is a tool designed to automate the Software Development Life Cycle (SDLC) by building production-grade applications with a combination of human and AI agents. It offers a plugin-based architecture that allows users to install only the necessary functionality for their projects. The tool guides users through key stages including Flow Modeling, IA Generation, Deterministic Scaffolding, AI Coding & Testing Loop, and Comprehensive Quality Checks. Auto Engineer follows a command/event-driven architecture and provides a modular plugin system for specific functionalities. It supports TypeScript with strict typing throughout and includes a built-in message bus server with a web dashboard for monitoring commands and events.

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.