OpenAI for Workers AI is a simple, quick, and dirty implementation of OpenAI's API on Cloudflare's new Workers AI platform. It allows developers to use the OpenAI SDKs with the new LLMs without having to rewrite all of their code. The API currently supports completions, chat completions, audio transcription, embeddings, audio translation, and image generation. It is not production ready but will be semi-regularly updated with new features as they roll out to Workers AI.

Smartcat is a CLI interface that brings language models into the Unix ecosystem, allowing power users to leverage the capabilities of LLMs in their daily workflows. It features a minimalist design, seamless integration with terminal and editor workflows, and customizable prompts for specific tasks. Smartcat currently supports OpenAI, Mistral AI, and Anthropic APIs, providing access to a range of language models. With its ability to manipulate file and text streams, integrate with editors, and offer configurable settings, Smartcat empowers users to automate tasks, enhance code quality, and explore creative possibilities.

llamafile is a tool that enables users to distribute and run Large Language Models (LLMs) with a single file. It combines llama.cpp with Cosmopolitan Libc to create a framework that simplifies the complexity of LLMs into a single-file executable called a 'llamafile'. Users can run these executable files locally on most computers without the need for installation, making open LLMs more accessible to developers and end users. llamafile also provides example llamafiles for various LLM models, allowing users to try out different LLMs locally. The tool supports multiple CPU microarchitectures, CPU architectures, and operating systems, making it versatile and easy to use.

RayLLM (formerly known as Aviary) is an LLM serving solution that makes it easy to deploy and manage a variety of open source LLMs, built on Ray Serve. It provides an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. RayLLM supports Transformer models hosted on Hugging Face Hub or present on local disk. It simplifies the deployment of multiple LLMs, the addition of new LLMs, and offers unique autoscaling support, including scale-to-zero. RayLLM fully supports multi-GPU & multi-node model deployments and offers high performance features like continuous batching, quantization and streaming. It provides a REST API that is similar to OpenAI's to make it easy to migrate and cross test them. RayLLM supports multiple LLM backends out of the box, including vLLM and TensorRT-LLM.

PythonAI is an open-source AI Assistant designed for the Raspberry Pi by Kevin McAleer. The project aims to enhance the capabilities of the Raspberry Pi by providing features such as conversation history, a conversation API, a web interface, a skills framework using plugin technology, and an event framework for adding functionality via plugins. The tool utilizes the Vosk offline library for speech-to-text conversion and offers a simple skills framework for easy implementation of new skills. Users can create new skills by adding Python files to the 'skills' folder and updating the 'skills.json' file. PythonAI is designed to be easy to read, maintain, and extend, making it a valuable tool for Raspberry Pi enthusiasts looking to build AI applications.

AI-Horde-Worker is a repository containing the original reference implementation for a worker that turns your graphics card(s) into a worker for the AI Horde. It allows users to generate or alchemize images for others. The repository provides instructions for setting up the worker on Windows and Linux, updating the worker code, running with multiple GPUs, and stopping the worker. Users can configure the worker using a WebUI to connect to the horde with their username and API key. The repository also includes information on model usage and running the Docker container with specified environment variables.

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.

The AI client 99 is designed for Neovim users to streamline requests to AI and limit them to restricted areas. It supports visual, search, and debug functionalities. Users must have a supported AI CLI installed such as opencode, claude, or cursor-agent. The tool allows for configuration of completions, referencing rules and files to add context to requests. 99 supports multiple AI CLI backends and providers. Users can report bugs by providing full running debug logs and are advised not to request features directly. Known usability issues include long function definition problems, duplication of comment definitions in lua and jsdoc, visual selection sending the whole file, occasional issues with auto-complete, and potential errors with 'export function' prompts.

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.

AlwaysReddy is a simple LLM assistant with no UI that you interact with entirely using hotkeys. It can easily read from or write to your clipboard, and voice chat with you via TTS and STT. Here are some of the things you can use AlwaysReddy for: - Explain a new concept to AlwaysReddy and have it save the concept (in roughly your words) into a note. - Ask AlwaysReddy "What is X called?" when you know how to roughly describe something but can't remember what it is called. - Have AlwaysReddy proofread the text in your clipboard before you send it. - Ask AlwaysReddy "From the comments in my clipboard, what do the r/LocalLLaMA users think of X?" - Quickly list what you have done today and get AlwaysReddy to write a journal entry to your clipboard before you shutdown the computer for the day.

The Bard API is a Python package that returns responses from Google Bard through the value of a cookie. It is an unofficial API that operates through reverse-engineering, utilizing cookie values to interact with Google Bard for users struggling with frequent authentication problems or unable to authenticate via Google Authentication. The Bard API is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore, using it for any other purposes is strongly discouraged. If you have access to a reliable official PaLM-2 API or Google Generative AI API, replace the provided response with the corresponding official code. Check out https://github.com/dsdanielpark/Bard-API/issues/262.

Civitai is a platform where people can share their stable diffusion models (textual inversions, hypernetworks, aesthetic gradients, VAEs, and any other crazy stuff people do to customize their AI generations), collaborate with others to improve them, and learn from each other's work. The platform allows users to create an account, upload their models, and browse models that have been shared by others. Users can also leave comments and feedback on each other's models to facilitate collaboration and knowledge sharing.

MultiPL-E is a system for translating unit test-driven neural code generation benchmarks to new languages. It is part of the BigCode Code Generation LM Harness and allows for evaluating Code LLMs using various benchmarks. The tool supports multiple versions with improvements and new language additions, providing a scalable and polyglot approach to benchmarking neural code generation. Users can access a tutorial for direct usage and explore the dataset of translated prompts on the Hugging Face Hub.

Call GPT is a voice application that utilizes Deepgram for Speech to Text, elevenlabs for Text to Speech, and OpenAI for GPT prompt completion. It allows users to chat with ChatGPT on the phone, providing better transcription, understanding, and speaking capabilities than traditional IVR systems. The app returns responses with low latency, allows user interruptions, maintains chat history, and enables GPT to call external tools. It coordinates data flow between Deepgram, OpenAI, ElevenLabs, and Twilio Media Streams, enhancing voice interactions.

Claude.vim is a Vim plugin that integrates Claude, an AI pair programmer, into your Vim workflow. It allows you to chat with Claude about what to build or how to debug problems, and Claude offers opinions, proposes modifications, or even writes code. The plugin provides a chat/instruction-centric interface optimized for human collaboration, with killer features like access to chat history and vimdiff interface. It can refactor code, modify or extend selected pieces of code, execute complex tasks by reading documentation, cloning git repositories, and more. Note that it is early alpha software and expected to rapidly evolve.

AIAC is a library and command line tool to generate Infrastructure as Code (IaC) templates, configurations, utilities, queries, and more via LLM providers such as OpenAI, Amazon Bedrock, and Ollama. Users can define multiple 'backends' targeting different LLM providers and environments using a simple configuration file. The tool allows users to ask a model to generate templates for different scenarios and composes an appropriate request to the selected provider, storing the resulting code to a file and/or printing it to standard output.

LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Curated Transformers is a transformer library for PyTorch that provides state-of-the-art models composed of reusable components. It supports various transformer architectures, including encoders like ALBERT, BERT, and RoBERTa, and decoders like Falcon, Llama, and MPT. The library emphasizes consistent type annotations, minimal dependencies, and ease of use for education and research. It has been production-tested by Explosion and will be the default transformer implementation in spaCy 3.7.

Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.

**bert4torch** is a high-level framework for training and deploying transformer models in PyTorch. It provides a simple and efficient API for building, training, and evaluating transformer models, and supports a wide range of pre-trained models, including BERT, RoBERTa, ALBERT, XLNet, and GPT-2. bert4torch also includes a number of useful features, such as data loading, tokenization, and model evaluation. It is a powerful and versatile tool for natural language processing tasks.

This is a production-grade knowledge Q&A chatbot implementation based on AWS services and the LangChain framework, with optimizations at various stages. It supports flexible configuration and plugging of vector models and large language models. The front and back ends are separated, making it easy to integrate with IM tools (such as Feishu).

OpenAI for Workers AI is a simple, quick, and dirty implementation of OpenAI's API on Cloudflare's new Workers AI platform. It allows developers to use the OpenAI SDKs with the new LLMs without having to rewrite all of their code. The API currently supports completions, chat completions, audio transcription, embeddings, audio translation, and image generation. It is not production ready but will be semi-regularly updated with new features as they roll out to Workers AI.

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

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.