OpenAI Kotlin API client is a Kotlin client for OpenAI's API with multiplatform and coroutines capabilities. It allows users to interact with OpenAI's API using Kotlin programming language. The client supports various features such as models, chat, images, embeddings, files, fine-tuning, moderations, audio, assistants, threads, messages, and runs. It also provides guides on getting started, chat & function call, file source guide, and assistants. Sample apps are available for reference, and troubleshooting guides are provided for common issues. The project is open-source and licensed under the MIT license, allowing contributions from the community.

AutoDocs by Sita is a tool designed to automate documentation for any repository. It parses the repository using tree-sitter and SCIP, constructs a code dependency graph, and generates repository-wide, dependency-aware documentation and summaries. It provides a FastAPI backend for ingestion/search and a Next.js web UI for chat and exploration. Additionally, it includes an MCP server for deep search capabilities. The tool aims to simplify the process of generating accurate and high-signal documentation for codebases.

Fast MCP is a Ruby gem that simplifies the integration of AI models with your Ruby applications. It provides a clean implementation of the Model Context Protocol, eliminating complex communication protocols, integration challenges, and compatibility issues. With Fast MCP, you can easily connect AI models to your servers, share data resources, choose from multiple transports, integrate with frameworks like Rails and Sinatra, and secure your AI-powered endpoints. The gem also offers real-time updates and authentication support, making AI integration a seamless experience for developers.

Fragments is an open-source tool that leverages Anthropic's Claude Artifacts, Vercel v0, and GPT Engineer. It is powered by E2B Sandbox SDK and Code Interpreter SDK, allowing secure execution of AI-generated code. The tool is based on Next.js 14, shadcn/ui, TailwindCSS, and Vercel AI SDK. Users can stream in the UI, install packages from npm and pip, and add custom stacks and LLM providers. Fragments enables users to build web apps with Python interpreter, Next.js, Vue.js, Streamlit, and Gradio, utilizing providers like OpenAI, Anthropic, Google AI, and more.

AirCasting is a platform for gathering, visualizing, and sharing environmental data. It aims to provide a central hub for environmental data, making it easier for people to access and use this information to make informed decisions about their environment.

SnipKit is a CLI tool designed to manage snippets efficiently, allowing users to execute saved scripts or generate new ones with the help of AI directly from the terminal. It supports loading snippets from various sources, parameter substitution, different parameter types, themes, and customization options. The tool includes an interactive chat-style interface called SnipKit Assistant for generating parameterized scripts. Users can also work with different AI providers like OpenAI, Anthropic, Google Gemini, and more. SnipKit aims to streamline script execution and script generation workflows for developers and users who frequently work with code snippets.

Context7 is a powerful tool for analyzing and visualizing data in various formats. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With advanced features such as data filtering, aggregation, and customization, Context7 is suitable for both beginners and experienced data analysts. The tool supports a wide range of data sources and formats, making it versatile for different use cases. Whether you are working on exploratory data analysis, data visualization, or data storytelling, Context7 can help you uncover valuable insights and communicate your findings effectively.

Agentic Company Researcher is a multi-agent tool that generates comprehensive company research reports by utilizing a pipeline of AI agents to gather, curate, and synthesize information from various sources. It features multi-source research, AI-powered content filtering, real-time progress streaming, dual model architecture, modern React frontend, and modular architecture. The tool follows an agentic framework with specialized research and processing nodes, leverages separate models for content generation, uses a content curation system for relevance scoring and document processing, and implements a real-time communication system via WebSocket connections. Users can set up the tool quickly using the provided setup script or manually, and it can also be deployed using Docker and Docker Compose. The application can be used for local development and deployed to various cloud platforms like AWS Elastic Beanstalk, Docker, Heroku, and Google Cloud Run.

Backend.AI Web UI is a user-friendly web and app interface designed to make AI accessible for end-users, DevOps, and SysAdmins. It provides features for session management, inference service management, pipeline management, storage management, node management, statistics, configurations, license checking, plugins, help & manuals, kernel management, user management, keypair management, manager settings, proxy mode support, service information, and integration with the Backend.AI Web Server. The tool supports various devices, offers a built-in websocket proxy feature, and allows for versatile usage across different platforms. Users can easily manage resources, run environment-supported apps, access a web-based terminal, use Visual Studio Code editor, manage experiments, set up autoscaling, manage pipelines, handle storage, monitor nodes, view statistics, configure settings, and more.

AutoAgent is a fully-automated and zero-code framework that enables users to create and deploy LLM agents through natural language alone. It is a top performer on the GAIA Benchmark, equipped with a native self-managing vector database, and allows for easy creation of tools, agents, and workflows without any coding. AutoAgent seamlessly integrates with a wide range of LLMs and supports both function-calling and ReAct interaction modes. It is designed to be dynamic, extensible, customized, and lightweight, serving as a personal AI assistant.

LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.

AI Artifacts is an open source tool that replicates Anthropic's Artifacts UI in the Claude chat app. It utilizes E2B's Code Interpreter SDK and Core SDK for secure AI code execution in a cloud sandbox environment. Users can run AI-generated code in various languages such as Python, JavaScript, R, and Nextjs apps. The tool also supports running AI-generated Python in Jupyter notebook, Next.js apps, and Streamlit apps. Additionally, it offers integration with Vercel AI SDK for tool calling and streaming responses from the model.

Pebblo enables developers to safely load data and promote their Gen AI app to deployment without worrying about the organization’s compliance and security requirements. The project identifies semantic topics and entities found in the loaded data and summarizes them on the UI or a PDF report.

Graphiti is a framework for building and querying temporally-aware knowledge graphs, tailored for AI agents in dynamic environments. It continuously integrates user interactions, structured and unstructured data, and external information into a coherent, queryable graph. The framework supports incremental data updates, efficient retrieval, and precise historical queries without complete graph recomputation, making it suitable for developing interactive, context-aware AI applications.

Recommendarr is a tool that generates personalized TV show and movie recommendations based on your Sonarr, Radarr, Plex, and Jellyfin libraries using AI. It offers AI-powered recommendations, media server integration, flexible AI support, watch history analysis, customization options, and dark/light mode toggle. Users can connect their media libraries and watch history services, configure AI service settings, and get personalized recommendations based on genre, language, and mood/vibe preferences. The tool works with any OpenAI-compatible API and offers various recommended models for different cost options and performance levels. It provides personalized suggestions, detailed information, filter options, watch history analysis, and one-click adding of recommended content to Sonarr/Radarr.

The OpenAIApi Plugin provides access to the OpenAI API in Unreal Engine, allowing users to generate images, transcribe speech, and power NPCs using advanced AI models. It offers blueprint nodes for making API calls, setting parameters, and accessing completion values. Users can authenticate using an API key directly or as an environment variable. The plugin supports various tasks such as generating images, transcribing speech, and interacting with NPCs through chat endpoints.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.

Run Vercel AI package on React Native, Expo, Web and Universal apps. Currently React Native fetch API does not support streaming which is used as a default on Vercel AI. This package enables you to use AI library on React Native but the best usage is when used on Expo universal native apps. On mobile you get back responses without streaming with the same API of `useChat` and `useCompletion` and on web it will fallback to `ai/react`

LLamaSharp is a cross-platform library to run 🦙LLaMA/LLaVA model (and others) on your local device. Based on llama.cpp, inference with LLamaSharp is efficient on both CPU and GPU. With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.

GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs and any GPU. Note that your CPU needs to support AVX or AVX2 instructions. Learn more in the documentation. A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. Nomic AI supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models.

ChatGPT Telegram Bot is a Telegram bot that provides a smooth AI experience. It supports both Azure OpenAI and native OpenAI, and offers real-time (streaming) response to AI, with a faster and smoother experience. The bot also has 15 preset bot identities that can be quickly switched, and supports custom bot identities to meet personalized needs. Additionally, it supports clearing the contents of the chat with a single click, and restarting the conversation at any time. The bot also supports native Telegram bot button support, making it easy and intuitive to implement required functions. User level division is also supported, with different levels enjoying different single session token numbers, context numbers, and session frequencies. The bot supports English and Chinese on UI, and is containerized for easy deployment.

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.

Agnaistic is an AI roleplay chat tool that allows users to interact with personalized characters using their favorite AI services. It supports multiple AI services, persona schema formats, and features such as group conversations, user authentication, and memory/lore books. Agnaistic can be self-hosted or run using Docker, and it provides a range of customization options through its settings.json file. The tool is designed to be user-friendly and accessible, making it suitable for both casual users and developers.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.