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.

Tiledesk Design Studio is an open-source, no-code development platform for creating chatbots and conversational apps. It offers a user-friendly, drag-and-drop interface with pre-ready actions and integrations. The platform combines the power of LLM/GPT AI with a flexible 'graph' approach for creating conversations and automations with ease. Users can automate customer conversations, prototype conversations, integrate ChatGPT, enhance user experience with multimedia, provide personalized product recommendations, set conditions, use random replies, connect to other tools like HubSpot CRM, integrate with WhatsApp, send emails, and seamlessly enhance existing setups.

Podman AI Lab is an open source extension for Podman Desktop designed to work with Large Language Models (LLMs) on a local environment. It features a recipe catalog with common AI use cases, a curated set of open source models, and a playground for learning, prototyping, and experimentation. Users can quickly and easily get started bringing AI into their applications without depending on external infrastructure, ensuring data privacy and security.

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.

Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. It provides an intuitive UI Workflow Editor, event-driven & scheduled workflows, multiple flow controls, built-in code editor supporting Java, JavaScript, Python, and Ruby, rich component ecosystem, extendable with custom connectors, AI-ready with built-in AI components, developer-ready to expose workflows as APIs, version control friendly, self-hosted, scalable, and resilient. It allows users to build and visualize workflows, automate tasks across SaaS apps, internal APIs, and databases, and handle millions of workflows with high availability and fault tolerance.

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

Twinny is a free and private AI extension for Visual Studio Code that offers AI-based code completion and code discussion features. It provides real-time code suggestions, function explanations, test generation, refactoring requests, and more. Twinny operates both online and offline, supports customizable API endpoints, conforms to OpenAI API standards, and offers various customization options for prompt templates, API providers, model names, and more. It is compatible with multiple APIs and allows users to accept code solutions directly in the editor, create new documents from code blocks, and copy generated code solution blocks. Twinny is open-source under the MIT license and welcomes contributions from the community.

ServerlessLLM is a fast, affordable, and easy-to-use library designed for multi-LLM serving, optimized for environments with limited GPU resources. It supports loading various leading LLM inference libraries, achieving fast load times, and reducing model switching overhead. The library facilitates easy deployment via Ray Cluster and Kubernetes, integrates with the OpenAI Query API, and is actively maintained by contributors.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

ZetaForge is an open-source AI platform designed for rapid development of advanced AI and AGI pipelines. It allows users to assemble reusable, customizable, and containerized Blocks into highly visual AI Pipelines, enabling rapid experimentation and collaboration. With ZetaForge, users can work with AI technologies in any programming language, easily modify and update AI pipelines, dive into the code whenever needed, utilize community-driven blocks and pipelines, and share their own creations. The platform aims to accelerate the development and deployment of advanced AI solutions through its user-friendly interface and community support.

KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.

OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.

ShortGPT is a powerful framework for automating content creation, simplifying video creation, footage sourcing, voiceover synthesis, and editing tasks. It offers features like automated editing framework, scripts and prompts, voiceover support in multiple languages, caption generation, asset sourcing, and persistency of editing variables. The tool is designed for youtube automation, Tiktok creativity program automation, and offers customization options for efficient and creative content creation.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

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.

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.

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.