Chital is a native macOS app designed for chatting with Ollama models. It offers low memory usage and fast app launch times, supports multiple chat threads, allows users to switch between different models, provides Markdown support, and automatically summarizes chat thread titles. The app requires macOS 14 Sonoma or above, the installation of Ollama, and at least one downloaded LLM model. Chital is a user-friendly tool that simplifies the process of engaging with Ollama models through chat threads on macOS systems.

Batteries Included is an all-in-one platform for building and running modern applications, simplifying cloud infrastructure complexity. It offers production-ready capabilities through an intuitive interface, focusing on automation, security, and enterprise-grade features. The platform includes databases like PostgreSQL and Redis, AI/ML capabilities with Jupyter notebooks, web services deployment, security features like SSL/TLS management, and monitoring tools like Grafana dashboards. Batteries Included is designed to streamline infrastructure setup and management, allowing users to concentrate on application development without dealing with complex configurations.

SecureAI Tools is a private and secure AI tool that allows users to chat with AI models, chat with documents (PDFs), and run AI models locally. It comes with built-in authentication and user management, making it suitable for family members or coworkers. The tool is self-hosting optimized and provides necessary scripts and docker-compose files for easy setup in under 5 minutes. Users can customize the tool by editing the .env file and enabling GPU support for faster inference. SecureAI Tools also supports remote OpenAI-compatible APIs, with lower hardware requirements for using remote APIs only. The tool's features wishlist includes chat sharing, mobile-friendly UI, and support for more file types and markdown rendering.

Open Roleplay is an open-source alternative to Character.ai. It allows users to create their own AI characters, customize them, and generate images and voices for them. Open Roleplay also supports group chat and automatic translation. The tool is built with Next.js, React.js, Tailwind CSS, Vercel, Convex, and Clerk.

VideoLingo is an all-in-one video translation and localization dubbing tool designed to generate Netflix-level high-quality subtitles. It aims to eliminate stiff machine translation, multiple lines of subtitles, and can even add high-quality dubbing, allowing knowledge from around the world to be shared across language barriers. Through an intuitive Streamlit web interface, the entire process from video link to embedded high-quality bilingual subtitles and even dubbing can be completed with just two clicks, easily creating Netflix-quality localized videos. Key features and functions include using yt-dlp to download videos from Youtube links, using WhisperX for word-level timeline subtitle recognition, using NLP and GPT for subtitle segmentation based on sentence meaning, summarizing intelligent term knowledge base with GPT for context-aware translation, three-step direct translation, reflection, and free translation to eliminate strange machine translation, checking single-line subtitle length and translation quality according to Netflix standards, using GPT-SoVITS for high-quality aligned dubbing, and integrating package for one-click startup and one-click output in streamlit.

LafTools is a privacy-first, self-hosted, fully open source toolbox designed for programmers. It offers a wide range of tools, including code generation, translation, encryption, compression, data analysis, and more. LafTools is highly integrated with a productive UI and supports full GPT-alike functionality. It is available as Docker images and portable edition, with desktop edition support planned for the future.

Trieve is an advanced relevance API for hybrid search, recommendations, and RAG. It offers a range of features including self-hosting, semantic dense vector search, typo tolerant full-text/neural search, sub-sentence highlighting, recommendations, convenient RAG API routes, the ability to bring your own models, hybrid search with cross-encoder re-ranking, recency biasing, tunable popularity-based ranking, filtering, duplicate detection, and grouping. Trieve is designed to be flexible and customizable, allowing users to tailor it to their specific needs. It is also easy to use, with a simple API and well-documented features.

OramaCore is a database designed for AI projects, answer engines, copilots, and search functionalities. It offers features such as a full-text search engine, vector database, LLM interface, and various utilities. The tool is currently under active development and not recommended for production use due to potential API changes. OramaCore aims to provide a comprehensive solution for managing data and enabling advanced AI capabilities in projects.

Skynet is an API server for AI services that wraps several apps and models. It consists of specialized modules that can be enabled or disabled as needed. Users can utilize Skynet for tasks such as summaries and action items with vllm or Ollama, live transcriptions with Faster Whisper via websockets, and RAG Assistant. The tool requires Poetry and Redis for operation. Skynet provides a quickstart guide for both Summaries/Assistant and Live Transcriptions, along with instructions for testing docker changes and running demos. Detailed documentation on configuration, running, building, and monitoring Skynet is available in the docs. Developers can contribute to Skynet by installing the pre-commit hook for linting. Skynet is distributed under the Apache 2.0 License.

Felafax is a framework designed to tune LLaMa3.1 on Google Cloud TPUs for cost efficiency and seamless scaling. It provides a Jupyter notebook for continued-training and fine-tuning open source LLMs using XLA runtime. The goal of Felafax is to simplify running AI workloads on non-NVIDIA hardware such as TPUs, AWS Trainium, AMD GPU, and Intel GPU. It supports various models like LLaMa-3.1 JAX Implementation, LLaMa-3/3.1 PyTorch XLA, and Gemma2 Models optimized for Cloud TPUs with full-precision training support.

React Native ExecuTorch is a framework that allows developers to run AI models on mobile devices using React Native. It bridges the gap between React Native and native platform capabilities, providing high-performance AI model execution without requiring deep knowledge of native code or machine learning internals. The tool supports ready-made models in `.pte` format and offers a Python API for custom models. It is designed to simplify the integration of AI features into React Native apps.

AskUI Vision Agent is a powerful automation framework that enables you and AI agents to control your desktop, mobile, and HMI devices and automate tasks. It supports multiple AI models, multi-platform compatibility, and enterprise-ready features. The tool provides support for Windows, Linux, MacOS, Android, and iOS device automation, single-step UI automation commands, in-background automation on Windows machines, flexible model use, and secure deployment of agents in enterprise environments.

AI-Shifu is an AI-led chat flow tool powered by LLM that provides an interactive and immersive experience for users. It allows users to follow a preset chat flow while being able to ask questions and affect the conversation. The tool can make personalized outputs based on user identity, interests, and preferences, making users feel like they are receiving one-on-one service. It is suitable for education, storytelling, product guides, surveys, and game NPC scenarios.

Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.

This repository provides configuration and scripts for running Ollama LLM server on Apple Silicon Macs in headless mode, optimized for performance and resource usage. It includes features like automatic startup, system resource optimization, external network access, proper logging setup, and SSH-based remote management. Users can customize the Ollama service configuration and enable optional GPU memory optimization and Docker autostart for container applications. The installation process disables unnecessary system services, configures power management, and optimizes for background operation while maintaining Screen Sharing capability for remote management. Performance considerations focus on reducing memory usage, disabling GUI-related services, minimizing background processes, preventing sleep/hibernation, and optimizing for headless operation.

Next AI Draw.io is a next.js web application that integrates AI capabilities with draw.io diagrams. It allows users to create, modify, and enhance diagrams through natural language commands and AI-assisted visualization. Features include LLM-Powered Diagram Creation, Image-Based Diagram Replication, Diagram History, Interactive Chat Interface, and Smart Editing. The application uses Next.js for frontend framework, @ai-sdk/react for chat interface and AI interactions, and react-drawio for diagram representation and manipulation. Diagrams are represented as XML that can be rendered in draw.io, with AI processing commands to generate or modify the XML accordingly.

Elia is a powerful terminal user interface designed for interacting with large language models. It allows users to chat with models like Claude 3, ChatGPT, Llama 3, Phi 3, Mistral, and Gemma. Conversations are stored locally in a SQLite database, ensuring privacy. Users can run local models through 'ollama' without data leaving their machine. Elia offers easy installation with pipx and supports various environment variables for different models. It provides a quick start to launch chats and manage local models. Configuration options are available to customize default models, system prompts, and add new models. Users can import conversations from ChatGPT and wipe the database when needed. Elia aims to enhance user experience in interacting with language models through a user-friendly interface.

Mistral Inference repository contains minimal code to run 7B, 8x7B, and 8x22B models. It provides model download links, installation instructions, and usage guidelines for running models via CLI or Python. The repository also includes information on guardrailing, model platforms, deployment, and references. Users can interact with models through commands like mistral-demo, mistral-chat, and mistral-common. Mistral AI models support function calling and chat interactions for tasks like testing models, chatting with models, and using Codestral as a coding assistant. The repository offers detailed documentation and links to blogs for further information.

LLMFlex is a python package designed for developing AI applications with local Large Language Models (LLMs). It provides classes to load LLM models, embedding models, and vector databases to create AI-powered solutions with prompt engineering and RAG techniques. The package supports multiple LLMs with different generation configurations, embedding toolkits, vector databases, chat memories, prompt templates, custom tools, and a chatbot frontend interface. Users can easily create LLMs, load embeddings toolkit, use tools, chat with models in a Streamlit web app, and serve an OpenAI API with a GGUF model. LLMFlex aims to offer a simple interface for developers to work with LLMs and build private AI solutions using local resources.

MinimalChat is a minimal and lightweight open-source chat application with full mobile PWA support that allows users to interact with various language models, including GPT-4 Omni, Claude Opus, and various Local/Custom Model Endpoints. It focuses on simplicity in setup and usage while being fully featured and highly responsive. The application supports features like fully voiced conversational interactions, multiple language models, markdown support, code syntax highlighting, DALL-E 3 integration, conversation importing/exporting, and responsive layout for mobile use.

Chat with MLX is an all-in-one Chat Playground using Apple MLX on Apple Silicon Macs. It provides privacy-enhanced AI for secure conversations with various models, easy integration of HuggingFace and MLX Compatible Open-Source Models, and comes with default models like Llama-3, Phi-3, Yi, Qwen, Mistral, Codestral, Mixtral, StableLM. The tool is designed for developers and researchers working with machine learning models on Apple Silicon.

Transformer Lab is an app that allows users to experiment with Large Language Models by providing features such as one-click download of popular models, finetuning across different hardware, RLHF and Preference Optimization, working with LLMs across different operating systems, chatting with models, using different inference engines, evaluating models, building datasets for training, calculating embeddings, providing a full REST API, running in the cloud, converting models across platforms, supporting plugins, embedded Monaco code editor, prompt editing, inference logs, all through a simple cross-platform GUI.

ell is a command-line interface for Language Model Models (LLMs) written in Bash. It allows users to interact with LLMs from the terminal, supports piping, context bringing, and chatting with LLMs. Users can also call functions and use templates. The tool requires bash, jq for JSON parsing, curl for HTTPS requests, and perl for PCRE. Configuration involves setting variables for different LLM models and APIs. Usage examples include asking questions, specifying models, recording input/output, running in interactive mode, and using templates. The tool is lightweight, easy to install, and pipe-friendly, making it suitable for interacting with LLMs in a terminal environment.

Ollama-SwiftUI is a user-friendly interface for Ollama.ai created in Swift. It allows seamless chatting with local Large Language Models on Mac. Users can change models mid-conversation, restart conversations, send system prompts, and use multimodal models with image + text. The app supports managing models, including downloading, deleting, and duplicating them. It offers light and dark mode, multiple conversation tabs, and a localized interface in English and Arabic.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.