Entirely-in-browser, fully private LLM chatbot supporting Llama 3, Mistral and other open source models. Fully private = No conversation data ever leaves your computer. Runs in the browser = No server needed and no install needed! Works offline. Easy-to-use interface on par with ChatGPT, but for open source LLMs. System requirements include a modern browser with WebGPU support. Supported models include TinyLlama-1.1B-Chat-v0.4-q4f32_1-1k, Llama-3-8B-Instruct-q4f16_1, Phi1.5-q4f16_1-1k, and Mistral-7B-Instruct-v0.2-q4f16_1. Looking for contributors to improve the interface, support more models, speed up initial model loading time, and fix bugs.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

Athina is an open-source library designed to help engineers improve the reliability and performance of Large Language Models (LLMs) through eval-driven development. It offers plug-and-play preset evals for catching and preventing bad outputs, measuring model performance, running experiments, A/B testing models, detecting regressions, and monitoring production data. Athina provides a solution to the flaws in current LLM developer workflows by offering rapid experimentation, customizable evaluators, integrated dashboard, consistent metrics, historical record tracking, and easy setup. It includes preset evaluators for RAG applications and summarization accuracy, as well as the ability to write custom evals. Athina's evals can run on both development and production environments, providing consistent metrics and removing the need for manual infrastructure setup.

DXOS is an open-source platform that offers Composer, an extensible app platform for developers to organize and sync their knowledge across devices. It enables real-time or offline collaboration with others, emphasizing a local-first and private approach. The DXOS SDK facilitates peer-to-peer collaboration for local-first apps without relying on central sync servers.

Tegon is an open-source AI-First issue tracking tool designed for engineering teams. It aims to simplify task management by leveraging AI and integrations to automate task creation, prioritize tasks, and enhance bug resolution. Tegon offers features like issues tracking, automatic title generation, AI-generated labels and assignees, custom views, and upcoming features like sprints and task prioritization. It integrates with GitHub, Slack, and Sentry to streamline issue tracking processes. Tegon also plans to introduce AI Agents like PR Agent and Bug Agent to enhance product management and bug resolution. Contributions are welcome, and the product is licensed under the MIT License.

Bedrock Engineer is an AI assistant for software development tasks powered by Amazon Bedrock. It combines large language models with file system operations and web search functionality to support development processes. The autonomous AI agent provides interactive chat, file system operations, web search, project structure management, code analysis, code generation, data analysis, agent and tool customization, chat history management, and multi-language support. Users can select agents, customize them, select tools, and customize tools. The tool also includes a website generator for React.js, Vue.js, Svelte.js, and Vanilla.js, with support for inline styling, Tailwind.css, and Material UI. Users can connect to design system data sources and generate AWS Step Functions ASL definitions.

WebLLM Chat is a private AI chat interface that combines WebLLM with a user-friendly design, leveraging WebGPU to run large language models natively in your browser. It offers browser-native AI experience with WebGPU acceleration, guaranteed privacy as all data processing happens locally, offline accessibility, user-friendly interface with markdown support, and open-source customization. The project aims to democratize AI technology by making powerful tools accessible directly to end-users, enhancing the chatting experience and broadening the scope for deployment of self-hosted and customizable language models.

LangWatch is a monitoring and analytics platform designed to track, visualize, and analyze interactions with Large Language Models (LLMs). It offers real-time telemetry to optimize LLM cost and latency, a user-friendly interface for deep insights into LLM behavior, user analytics for engagement metrics, detailed debugging capabilities, and guardrails to monitor LLM outputs for issues like PII leaks and toxic language. The platform supports OpenAI and LangChain integrations, simplifying the process of tracing LLM calls and generating API keys for usage. LangWatch also provides documentation for easy integration and self-hosting options for interested users.

InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.

Nebula is an advanced, AI-powered penetration testing tool designed for cybersecurity professionals, ethical hackers, and developers. It integrates state-of-the-art AI models into the command-line interface, automating vulnerability assessments and enhancing security workflows with real-time insights and automated note-taking. Nebula revolutionizes penetration testing by providing AI-driven insights, enhanced tool integration, AI-assisted note-taking, and manual note-taking features. It also supports any tool that can be invoked from the CLI, making it a versatile and powerful tool for cybersecurity tasks.

Twinny is a free and open-source AI code completion plugin for Visual Studio Code and compatible editors. It integrates with various tools and frameworks, including Ollama, llama.cpp, oobabooga/text-generation-webui, LM Studio, LiteLLM, and Open WebUI. Twinny offers features such as fill-in-the-middle code completion, chat with AI about your code, customizable API endpoints, and support for single or multiline fill-in-middle completions. It is easy to install via the Visual Studio Code extensions marketplace and provides a range of customization options. Twinny supports both online and offline operation and conforms to the OpenAI API standard.

FreeGenius AI is an ambitious project offering a comprehensive suite of AI solutions that mirror the capabilities of LetMeDoIt AI. It is designed to engage in intuitive conversations, execute codes, provide up-to-date information, and perform various tasks. The tool is free, customizable, and provides access to real-time data and device information. It aims to support offline and online backends, open-source large language models, and optional API keys. Users can use FreeGenius AI for tasks like generating tweets, analyzing audio, searching financial data, checking weather, and creating maps.

RK3588 is a flagship 8K SoC chip by Rockchip, integrating Cortex-A76 and Cortex-A55 cores with NEON coprocessor for 8K video codec. This repository curates resources for developing with RK3588, including official resources, RKNN models, projects, development boards, documentation, tools, and sample code.

Project Miyagi showcases Microsoft's Copilot Stack in an envisioning workshop aimed at designing, developing, and deploying enterprise-grade intelligent apps. By exploring both generative and traditional ML use cases, Miyagi offers an experiential approach to developing AI-infused product experiences that enhance productivity and enable hyper-personalization. Additionally, the workshop introduces traditional software engineers to emerging design patterns in prompt engineering, such as chain-of-thought and retrieval-augmentation, as well as to techniques like vectorization for long-term memory, fine-tuning of OSS models, agent-like orchestration, and plugins or tools for augmenting and grounding LLMs.

This repository serves as the website for the Introduction to Data-Centric AI class. It contains lab assignments and resources for the course. Users can contribute by opening issues or submitting pull requests. The website can be built locally using Docker and Jekyll. The design is based on Missing Semester. All contents, including source code, lecture notes, and videos, are licensed under CC BY-NC-SA 4.0.

Entirely-in-browser, fully private LLM chatbot supporting Llama 3, Mistral and other open source models. Fully private = No conversation data ever leaves your computer. Runs in the browser = No server needed and no install needed! Works offline. Easy-to-use interface on par with ChatGPT, but for open source LLMs. System requirements include a modern browser with WebGPU support. Supported models include TinyLlama-1.1B-Chat-v0.4-q4f32_1-1k, Llama-3-8B-Instruct-q4f16_1, Phi1.5-q4f16_1-1k, and Mistral-7B-Instruct-v0.2-q4f16_1. Looking for contributors to improve the interface, support more models, speed up initial model loading time, and fix bugs.

Glide is a cloud-native LLM gateway that provides a unified REST API for accessing various large language models (LLMs) from different providers. It handles LLMOps tasks such as model failover, caching, key management, and more, making it easy to integrate LLMs into applications. Glide supports popular LLM providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock (Titan), Cohere, Google Gemini, OctoML, and Ollama. It offers high availability, performance, and observability, and provides SDKs for Python and NodeJS to simplify integration.

Easy, fast, and cheap pretrain, finetune, serving for everyone

Agents-Flex is a LLM Application Framework like LangChain base on Java. It provides a set of tools and components for building LLM applications, including LLM Visit, Prompt and Prompt Template Loader, Function Calling Definer, Invoker and Running, Memory, Embedding, Vector Storage, Resource Loaders, Document, Splitter, Loader, Parser, LLMs Chain, and Agents Chain.

ShellGPT is a tool that allows users to chat with a large language model (LLM) in the terminal. It can be used for various purposes such as generating shell commands, telling stories, and interacting with Linux terminal. The tool provides different modes of usage including direct mode for asking questions, REPL mode for chatting with LLM, and TUI mode tailored for inferring shell commands. Users can customize the tool by setting up different language model backends such as Ollama or using OpenAI compatible API endpoints. Additionally, ShellGPT comes with built-in system contents for general questions, correcting typos, generating URL slugs, programming questions, shell command inference, and git commit message generation. Users can define their own content or share customized contents in the discuss section.

Open-LLM-VTuber is a project in early stages of development that allows users to interact with Large Language Models (LLM) using voice commands and receive responses through a Live2D talking face. The project aims to provide a minimum viable prototype for offline use on macOS, Linux, and Windows, with features like long-term memory using MemGPT, customizable LLM backends, speech recognition, and text-to-speech providers. Users can configure the project to chat with LLMs, choose different backend services, and utilize Live2D models for visual representation. The project supports perpetual chat, offline operation, and GPU acceleration on macOS, addressing limitations of existing solutions on macOS.

The demo-chatbot repository contains a simple app to chat with an LLM, allowing users to create any LLM Inference Web Apps using Python. The app utilizes OpenAI's GPT-4 API to generate responses to user messages, with the flexibility to switch to other APIs or models. The repository includes a tutorial in the Taipy documentation for creating the app. Users need an OpenAI account with an active API key to run the app by cloning the repository, installing dependencies, setting up the API key in a .env file, and running the main.py file.

UMbreLLa is a tool designed for deploying Large Language Models (LLMs) for personal agents. It combines offloading, speculative decoding, and quantization to optimize single-user LLM deployment scenarios. With UMbreLLa, 70B-level models can achieve performance comparable to human reading speed on an RTX 4070Ti, delivering exceptional efficiency and responsiveness, especially for coding tasks. The tool supports deploying models on various GPUs and offers features like code completion and CLI/Gradio chatbots. Users can configure the LLM engine for optimal performance based on their hardware setup.

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.