Savvy is a CLI tool that simplifies the creation, sharing, and running of runbooks directly from the terminal. It can generate runbooks using AI or commands provided by the user. The tool allows users to easily create runbooks for various tasks, share them, and run them automatically. Savvy also provides features like explaining commands and troubleshooting errors in a user-friendly manner. It supports creating runbooks from shell history, sharing runbooks, and running runbooks seamlessly from the terminal.

Ultravox is a fast multimodal Language Model (LLM) that can understand both text and human speech in real-time without the need for a separate Audio Speech Recognition (ASR) stage. By extending Meta's Llama 3 model with a multimodal projector, Ultravox converts audio directly into a high-dimensional space used by Llama 3, enabling quick responses and potential understanding of paralinguistic cues like timing and emotion in human speech. The current version (v0.3) has impressive speed metrics and aims for further enhancements. Ultravox currently converts audio to streaming text and plans to emit speech tokens for direct audio conversion. The tool is open for collaboration to enhance this functionality.

OpenUI is a tool designed to simplify the process of building UI components by allowing users to describe UI using their imagination and see it rendered live. It supports converting HTML to React, Svelte, Web Components, etc. The tool is open source and aims to make UI development fun, fast, and flexible. It integrates with various AI services like OpenAI, Groq, Gemini, Anthropic, Cohere, and Mistral, providing users with the flexibility to use different models. OpenUI also supports LiteLLM for connecting to various LLM services and allows users to create custom proxy configs. The tool can be run locally using Docker or Python, and it offers a development environment for quick setup and testing.

pyrfuniverse is a python package used to interact with RFUniverse simulation environment. It is developed with reference to ML-Agents and produce new features. The package allows users to work with RFUniverse for simulation purposes, providing tools and functionalities to interact with the environment and create new features.

This repository provides a tool for AI voice cloning, allowing users to generate synthetic speech that closely resembles a target speaker's voice. The tool is designed to be user-friendly and accessible, with a graphical user interface that guides users through the process of training a voice model and generating synthetic speech. The tool also includes a variety of features that allow users to customize the generated speech, such as the pitch, volume, and speaking rate. Overall, this tool is a valuable resource for anyone interested in creating realistic and engaging synthetic speech.

WebCraftifyAI is a software aid that makes it easy to create and build web pages and content. It is designed to be user-friendly and accessible to people of all skill levels. With WebCraftifyAI, you can quickly and easily create professional-looking websites without having to learn complex coding or design skills.

Mentat is an AI tool designed to assist with coding tasks directly from the command line. It combines human creativity with computer-like processing to help users understand new codebases, add new features, and refactor existing code. Unlike other tools, Mentat coordinates edits across multiple locations and files, with the context of the project already in mind. The tool aims to enhance the coding experience by providing seamless assistance and improving edit quality.

Concierge is a versatile automation tool designed to streamline repetitive tasks and workflows. It provides a user-friendly interface for creating custom automation scripts without the need for extensive coding knowledge. With Concierge, users can automate various tasks across different platforms and applications, increasing efficiency and productivity. The tool offers a wide range of pre-built automation templates and allows users to customize and schedule their automation processes. Concierge is suitable for individuals and businesses looking to automate routine tasks and improve overall workflow efficiency.

AIOStreams is a versatile tool that combines streams from various addons into one platform, offering extensive customization options. Users can change result formats, filter results by various criteria, remove duplicates, prioritize services, sort results, specify size limits, and more. The tool scrapes results from selected addons, applies user configurations, and presents the results in a unified manner. It simplifies the process of finding and accessing desired content from multiple sources, enhancing user experience and efficiency.

Feeds Fun is a self-hosted news reader tool that automatically assigns tags to news entries. Users can create rules to score news based on tags, filter and sort news as needed, and track read news. The tool offers multi/single-user support, feeds management, and various features for personalized news consumption. Users can access the tool's backend as the ffun package on PyPI and the frontend as the feeds-fun package on NPM. Feeds Fun requires setting up OpenAI or Gemini API keys for full tag generation capabilities. The tool uses tag processors to detect tags for news entries, with options for simple and complex processors. Feeds Fun primarily relies on LLM tag processors from OpenAI and Google for tag generation.

Micro Agent is an AI tool designed to write and fix code for users by generating code that passes specified tests or matches design screenshots. It aims to streamline the code generation process by leveraging AI capabilities to iterate and improve code until desired outcomes are achieved. The tool focuses on test-driven development and provides interactive features for user feedback. Micro Agent is not intended to be a comprehensive development tool but rather a specialized agent for code generation and iteration.

AgentGenesis is an open-source web app that provides customizable Gen AI code snippets for building custom RAG flows and AI agents. Users can easily copy and paste components into their applications, modify the code as needed, and build on top of it. The tool aims to simplify the development process by offering pre-built code snippets that can be integrated seamlessly into projects without the need for npm installation. AgentGenesis encourages contributions, positive feedback, and support from the community to enhance and grow the project.

Discord-AI-Selfbot is a Python-based Discord selfbot that uses the `discord.py-self` library to automatically respond to messages mentioning its trigger word using Groq API's Llama-3 model. It functions as a normal Discord bot on a real Discord account, enabling interactions in DMs, servers, and group chats without needing to invite a bot. The selfbot comes with features like custom AI instructions, free LLM model usage, mention and reply recognition, message handling, channel-specific responses, and a psychoanalysis command to analyze user messages for insights on personality.

WebWhiz is an open-source tool that allows users to train ChatGPT on website data to build AI chatbots for customer queries. It offers easy integration, data-specific responses, regular data updates, no-code builder, chatbot customization, fine-tuning, and offline messaging. Users can create and train chatbots in a few simple steps by entering their website URL, automatically fetching and preparing training data, training ChatGPT, and embedding the chatbot on their website. WebWhiz can crawl websites monthly, collect text data and metadata, and process text data using tokens. Users can train custom data, but bringing custom open AI keys is not yet supported. The tool has no limitations on context size but may limit the number of pages based on the chosen plan. WebWhiz SDK is available on NPM, CDNs, and GitHub, and users can self-host it using Docker or manual setup involving MongoDB, Redis, Node, Python, and environment variables setup. For any issues, users can contact [email protected].

Seer is a service that provides AI capabilities to Sentry by running inference on Sentry issues and providing user insights. It is currently in early development and not yet compatible with self-hosted Sentry instances. The tool requires access to internal Sentry resources and is intended for internal Sentry employees. Users can set up the environment, download model artifacts, integrate with local Sentry, run evaluations for Autofix AI agent, and deploy to a sandbox staging environment. Development commands include applying database migrations, creating new migrations, running tests, and more. The tool also supports VCRs for recording and replaying HTTP requests.

This repository provides a tool to create an AI chatbot clone of yourself using your WhatsApp chats as training data. It utilizes the Torchtune library for finetuning and inference. The code includes preprocessing of WhatsApp chats, finetuning models, and chatting with the AI clone via a command-line interface. Supported models are Llama3-8B-Instruct and Mistral-7B-Instruct-v0.2. Hardware requirements include approximately 16 GB vRAM for QLoRa Llama3 finetuning with a 4k context length. The repository addresses common issues like adjusting parameters for training and preprocessing non-English chats.

Savvy is a CLI tool that simplifies the creation, sharing, and running of runbooks directly from the terminal. It can generate runbooks using AI or commands provided by the user. The tool allows users to easily create runbooks for various tasks, share them, and run them automatically. Savvy also provides features like explaining commands and troubleshooting errors in a user-friendly manner. It supports creating runbooks from shell history, sharing runbooks, and running runbooks seamlessly from the terminal.

AirGo is a front and rear end separation, multi user, multi protocol proxy service management system, simple and easy to use. It supports vless, vmess, shadowsocks, and hysteria2.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

The 'llm-code-interpreter' repository is a deprecated plugin that provides a code interpreter on steroids for ChatGPT by E2B. It gives ChatGPT access to a sandboxed cloud environment with capabilities like running any code, accessing Linux OS, installing programs, using filesystem, running processes, and accessing the internet. The plugin exposes commands to run shell commands, read files, and write files, enabling various possibilities such as running different languages, installing programs, starting servers, deploying websites, and more. It is powered by the E2B API and is designed for agents to freely experiment within a sandboxed environment.

Pezzo is a fully cloud-native and open-source LLMOps platform that allows users to observe and monitor AI operations, troubleshoot issues, save costs and latency, collaborate, manage prompts, and deliver AI changes instantly. It supports various clients for prompt management, observability, and caching. Users can run the full Pezzo stack locally using Docker Compose, with prerequisites including Node.js 18+, Docker, and a GraphQL Language Feature Support VSCode Extension. Contributions are welcome, and the source code is available under the Apache 2.0 License.

Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It implements dataset abstraction, scalable cache runtime, automated data operations, elasticity and scheduling, and is runtime platform agnostic. Key concepts include Dataset and Runtime. Prerequisites include Kubernetes version > 1.16, Golang 1.18+, and Helm 3. The tool offers features like accelerating remote file accessing, machine learning, accelerating PVC, preloading dataset, and on-the-fly dataset cache scaling. Contributions are welcomed, and the project is under the Apache 2.0 license with a vendor-neutral approach.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.