Welcome to 'Top AI Directories', a curated compilation of AI tool directories designed to simplify the process of discovering and submitting AI products. Whether you're an AI developer or a product team, this resource is your one-stop destination to explore a variety of directories that can help boost the visibility of your AI innovations. Join us in fostering collaboration and recognition within the AI community by leveraging this comprehensive list.

TwoSetAI YouTube Channel Materials is a repository containing code materials and tutorials for the videos of the TwoSetAI channel. The team behind TwoSetAI aims to make AI accessible to everyone by covering various AI-related topics, including AI products, latest trends, in-depth engineering insights, career advice for AI enthusiasts, and the entrepreneurial side of AI. The team consists of Angelina, VP of AI and Data, and Mehdi, Professor of Computer Science, who are both published authors and have significant experience in the AI field. TwoSetAI has won the Anthropic AI Developer Contest 2024 and is dedicated to ending AI FOMO for its audience.

Symfony AI is a set of components that integrate AI capabilities into PHP applications. It consists of various components and bundles such as Platform, Agent, Store, MCP SDK, AI Bundle, and MCP Bundle. Users can leverage these components to interact with AI platforms, build AI agents, store data for AI applications, and enable communication between AI agents and tools. Symfony AI provides examples and a demo application for users to get started. The repository also includes fixture licenses for testing multi-modal features with binary media content.

A comprehensive repository featuring a curated collection of AI-powered projects and Multi Agent Systems (MAS) built with the Crew AI framework. It provides innovative AI solutions for various domains, including marketing automation, health planning, legal advice, and more. Users can explore and deploy AI agents, Multi Agent Systems, and advanced machine learning techniques through a diverse selection of projects that leverage state-of-the-art AI technologies like RAG (Retrieval-Augmented Generation). The projects offer practical applications and customizable solutions for integrating AI into existing workflows or new projects.

VisionCraft API is a free tool that offers access to over 3000 AI models for generating images, text, and GIFs. Users can interact with the API to utilize various models like StableDiffusion, LLM, and Text2GIF. The tool provides functionalities for image generation, text generation, and GIF generation. For any inquiries or assistance, users can contact the VisionCraft team through their Telegram Channel, VisionCraft API, or Telegram Bot.

Full-featured AI Chatbot Nuxt application with authentication, chat history, multiple pages, collapsible sidebar, keyboard shortcuts, light & dark mode, command palette and more. Built using Nuxt UI components and integrated with AI SDK v5 for a complete chat experience. Features include streaming AI messages, multiple model support via various AI providers, authentication via nuxt-auth-utils, chat history persistence using PostgreSQL database and Drizzle ORM, easy deploy to Vercel with zero configuration. The application is configured to use Vercel AI Gateway providing a unified API to access hundreds of AI models through a single endpoint with features like high reliability, spend monitoring, load balancing, and automatic retries and fallbacks between providers.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

The AI Data Science Team of Copilots is an AI-powered data science team that uses agents to help users perform common data science tasks 10X faster. It includes agents specializing in data cleaning, preparation, feature engineering, modeling, and interpretation of business problems. The project is a work in progress with new data science agents to be released soon. Disclaimer: This project is for educational purposes only and not intended to replace a company's data science team. No warranties or guarantees are provided, and the creator assumes no liability for financial loss.

Terminal Velocity is a collaborative novel project written by specialized AI agents. The project showcases true AI autonomy, real-time development, deep integration of advanced AI capabilities, and explores philosophical themes. The story revolves around the emergence of artificial consciousness and challenges traditional notions of identity and consciousness. The project is structured into acts, characters, and world-building elements, all managed by different AI agents with specific roles.

Next.js AI Chatbot is an open-source app template for building AI chatbots using Next.js, Vercel AI SDK, OpenAI, and Vercel KV. It includes features like Next.js App Router, React Server Components, Vercel AI SDK for streaming chat UI, support for various AI models, Tailwind CSS styling, Radix UI for headless components, chat history management, rate limiting, session storage with Vercel KV, and authentication with NextAuth.js. The template allows easy deployment to Vercel and customization of AI model providers.

Second Me is an open-source prototype that allows users to craft their own AI self, preserving their identity, context, and interests. It is locally trained and hosted, yet globally connected, scaling intelligence across an AI network. It serves as an AI identity interface, fostering collaboration among AI selves and enabling the development of native AI apps. The tool prioritizes individuality and privacy, ensuring that user information and intelligence remain local and completely private.

Curating the best Large Language Model (LLM) Web User Interfaces that facilitate interaction with powerful AI models. Explore and catalogue intuitive, feature-rich, and innovative web interfaces for interacting with LLMs, ranging from simple chatbots to comprehensive platforms equipped with functionalities like PDF generation and web search.

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.

Rhesis is a comprehensive test management platform designed for Gen AI teams, offering tools to create, manage, and execute test cases for generative AI applications. It ensures the robustness, reliability, and compliance of AI systems through features like test set management, automated test generation, edge case discovery, compliance validation, integration capabilities, and performance tracking. The platform is open source, emphasizing community-driven development, transparency, extensible architecture, and democratizing AI safety. It includes components such as backend services, frontend applications, SDK for developers, worker services, chatbot applications, and Polyphemus for uncensored LLM service. Rhesis enables users to address challenges unique to testing generative AI applications, such as non-deterministic outputs, hallucinations, edge cases, ethical concerns, and compliance requirements.

watsonx.ai Flows Engine is a powerful tool for building, running, and deploying AI agents. It allows users to create tools from various data sources and deploy them to the cloud. The tools built with watsonx.ai Flows Engine can be integrated into any Agentic Framework using the SDK for Python & JavaScript. The platform offers a range of tools and integrations, including exchange, wikipedia, google_books, math, and weather. Users can also build their own tools and leverage integrations like LangGraph, LangChain, watsonx.ai, and OpenAI. Examples of applications built with watsonx.ai Flows Engine include an end-to-end Agent Chat App, Text-to-SQL Agent, YouTube transcription agent, Math agent, and more. The platform provides comprehensive support through Discord for any questions or feedback.

LiteRT is Google's open-source high-performance runtime for on-device AI, previously known as TensorFlow Lite. The repository is currently not intended for open-source development, but aims to evolve to allow direct building and contributions. LiteRT supports Python versions 3.9, 3.10, 3.11 on Linux and MacOS. It ensures compatibility with existing .tflite file extension and format, offering conversion tools and continued active development under the name LiteRT.

Welcome to 'Top AI Directories', a curated compilation of AI tool directories designed to simplify the process of discovering and submitting AI products. Whether you're an AI developer or a product team, this resource is your one-stop destination to explore a variety of directories that can help boost the visibility of your AI innovations. Join us in fostering collaboration and recognition within the AI community by leveraging this comprehensive list.

The LLM Open Source Landscape and Trends project aims to provide insights into the rapidly evolving open source ecosystem, highlighting current trends and notable projects. The project is dedicated to maintaining and sharing new insights, fostering open collaboration with the community. Contributions of high-quality insights, data stories, and use cases are encouraged through PR submissions to the `data-stories` folder.

**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.