Kodit is a Code Indexing MCP Server that connects AI coding assistants to external codebases, providing accurate and up-to-date code snippets. It improves AI-assisted coding by offering canonical examples, indexing local and public codebases, integrating with AI coding assistants, enabling keyword and semantic search, and supporting OpenAI-compatible or custom APIs/models. Kodit helps engineers working with AI-powered coding assistants by providing relevant examples to reduce errors and hallucinations.

HAI Code Generator is a cutting-edge tool designed to simplify and automate task execution while enhancing code generation workflows. Leveraging Specif AI, it streamlines processes like task execution, file identification, and code documentation through intelligent automation and AI-driven capabilities. Built on Cline's powerful foundation for AI-assisted development, HAI Code Generator boosts productivity and precision by automating task execution and integrating file management capabilities. It combines intelligent file indexing, context generation, and LLM-driven automation to minimize manual effort and ensure task accuracy. Perfect for developers and teams aiming to enhance their workflows.

ECA (Editor Code Assistant) is a free and open-source editor-agnostic tool designed to link Language Model Machines (LLMs) with editors for AI pair programming. It provides a protocol for any editor to integrate, offering a seamless user experience. The tool allows for single configuration across different editors, features a chat interface for collaboration, supports multiple LLM models, and enhances code editing with context details. ECA aims to simplify the integration of LLMs with editors, focusing on improving the user experience and productivity in coding tasks.

Magic is an open-source all-in-one AI productivity platform designed to help enterprises quickly build and deploy AI applications, aiming for a 100x increase in productivity. It consists of various AI products and infrastructure tools, such as Super Magic, Magic IM, Magic Flow, and more. Super Magic is a general-purpose AI Agent for complex task scenarios, while Magic Flow is a visual AI workflow orchestration system. Magic IM is an enterprise-grade AI Agent conversation system for internal knowledge management. Teamshare OS is a collaborative office platform integrating AI capabilities. The platform provides cloud services, enterprise solutions, and a self-hosted community edition for users to leverage its features.

Kaizen is an open-source project that helps teams ensure quality in their software delivery by providing a suite of tools for code review, test generation, and end-to-end testing. It integrates with your existing code repositories and workflows, allowing you to streamline your software development process. Kaizen generates comprehensive end-to-end tests, provides UI testing and review, and automates code review with insightful feedback. The file structure includes components for API server, logic, actors, generators, LLM integrations, documentation, and sample code. Getting started involves installing the Kaizen package, generating tests for websites, and executing tests. The tool also runs an API server for GitHub App actions. Contributions are welcome under the AGPL License.

AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.

CodeGate is a local gateway that enhances the safety of AI coding assistants by ensuring AI-generated recommendations adhere to best practices, safeguarding code integrity, and protecting individual privacy. Developed by Stacklok, CodeGate allows users to confidently leverage AI in their development workflow without compromising security or productivity. It works seamlessly with coding assistants, providing real-time security analysis of AI suggestions. CodeGate is designed with privacy at its core, keeping all data on the user's machine and offering complete control over data.

ChatFAQ is an open-source comprehensive platform for creating a wide variety of chatbots: generic ones, business-trained, or even capable of redirecting requests to human operators. It includes a specialized NLP/NLG engine based on a RAG architecture and customized chat widgets, ensuring a tailored experience for users and avoiding vendor lock-in.

CORE is an open-source unified, persistent memory layer for all AI tools, allowing developers to maintain context across different tools like Cursor, ChatGPT, and Claude. It aims to solve the issue of context switching and information loss between sessions by creating a knowledge graph that remembers conversations, decisions, and insights. With features like unified memory, temporal knowledge graph, browser extension, chat with memory, auto-sync from apps, and MCP integration hub, CORE provides a seamless experience for managing and recalling context. The tool's ingestion pipeline captures evolving context through normalization, extraction, resolution, and graph integration, resulting in a dynamic memory that grows and changes with the user. When recalling from memory, CORE utilizes search, re-ranking, filtering, and output to provide relevant and contextual answers. Security measures include data encryption, authentication, access control, and vulnerability reporting.

TaskingAI brings Firebase's simplicity to **AI-native app development**. The platform enables the creation of GPTs-like multi-tenant applications using a wide range of LLMs from various providers. It features distinct, modular functions such as Inference, Retrieval, Assistant, and Tool, seamlessly integrated to enhance the development process. TaskingAI’s cohesive design ensures an efficient, intelligent, and user-friendly experience in AI application development.

Dapr Agents is a developer framework for building production-grade resilient AI agent systems that operate at scale. It enables software developers to create AI agents that reason, act, and collaborate using Large Language Models (LLMs), while providing built-in observability and stateful workflow execution to ensure agentic workflows complete successfully. The framework is scalable, efficient, Kubernetes-native, data-driven, secure, observable, vendor-neutral, and open source. It offers features like scalable workflows, cost-effective AI adoption, data-centric AI agents, accelerated development, integrated security and reliability, built-in messaging and state infrastructure, and vendor-neutral and open source support. Dapr Agents is designed to simplify the development of AI applications and workflows by providing a comprehensive API surface and seamless integration with various data sources and services.

The AI Platform Engineering repository provides a collection of tools and resources for building and deploying AI models. It includes libraries for data preprocessing, model training, and model serving. The repository also contains example code and tutorials to help users get started with AI development. Whether you are a beginner or an experienced AI engineer, this repository offers valuable insights and best practices to streamline your AI projects.

The Conversation Knowledge Mining Solution Accelerator enables customers to leverage intelligence to uncover insights, relationships, and patterns from conversational data. It empowers users to gain valuable knowledge and drive targeted business impact by utilizing Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and Azure Search for topic modeling, key phrase extraction, speech-to-text transcription, and interactive chat experiences.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

LLM Workflow Engine (LWE) is a powerful command-line interface (CLI) and workflow manager for large language models (LLMs) like ChatGPT and GPT4. It allows users to interact with LLMs directly from their terminal, making it easy to automate tasks and build complex workflows. LWE supports the official ChatGPT API, providing access to all supported models through your OpenAI account. Additionally, it features a simple plugin architecture that enables users to extend its functionality and integrate with other LLMs. LWE also offers a Python API for integrating LLM capabilities into Python scripts. Notable projects built using the original ChatGPT Wrapper, which LWE evolved from, include bookast, ChatGPT.el, ChatGPT Reddit Bot, Smarty GPT, ChatGPTify, and selection-to-chatgpt.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

Kodit is a Code Indexing MCP Server that connects AI coding assistants to external codebases, providing accurate and up-to-date code snippets. It improves AI-assisted coding by offering canonical examples, indexing local and public codebases, integrating with AI coding assistants, enabling keyword and semantic search, and supporting OpenAI-compatible or custom APIs/models. Kodit helps engineers working with AI-powered coding assistants by providing relevant examples to reduce errors and hallucinations.

r2ai is a tool designed to run a language model locally without internet access. It can be used to entertain users or assist in answering questions related to radare2 or reverse engineering. The tool allows users to prompt the language model, index large codebases, slurp file contents, embed the output of an r2 command, define different system-level assistant roles, set environment variables, and more. It is accessible as an r2lang-python plugin and can be scripted from various languages. Users can use different models, adjust query templates dynamically, load multiple models, and make them communicate with each other.

ChunkHound is a modern tool for transforming your codebase into a searchable knowledge base for AI assistants. It utilizes semantic search via the cAST algorithm and regex search, integrating with AI assistants through the Model Context Protocol (MCP). With features like cAST Algorithm, Multi-Hop Semantic Search, Regex search, and support for 22 languages, ChunkHound offers a local-first approach to code analysis and discovery. It provides intelligent code discovery, universal language support, and real-time indexing capabilities, making it a powerful tool for developers looking to enhance their coding experience.

**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.