Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

TEN Agent is an open-source multimodal agent powered by the world’s first real-time multimodal framework, TEN Framework. It offers high-performance real-time multimodal interactions, multi-language and multi-platform support, edge-cloud integration, flexibility beyond model limitations, and real-time agent state management. Users can easily build complex AI applications through drag-and-drop programming, integrating audio-visual tools, databases, RAG, and more.

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.

MaxKB is a knowledge base Q&A system based on the LLM large language model. MaxKB = Max Knowledge Base, which aims to become the most powerful brain of the enterprise.

Free-one-api is a tool that allows access to all LLM reverse engineering libraries in a standard OpenAI API format. It supports automatic load balancing, Web UI, stream mode, multiple LLM reverse libraries, heartbeat detection mechanism, automatic disabling of unavailable channels, and runtime log recording. The tool is designed to work with the 'one-api' project and 'songquanpeng/one-api' for accessing official interfaces of various LLMs (paid). Contributors are needed to test adapters, find new reverse engineering libraries, and submit PRs.

Awesome Agents is a curated list of open source AI agents designed for various tasks such as private interactions with documents, chat implementations, autonomous research, human-behavior simulation, code generation, HR queries, domain-specific research, and more. The agents leverage Large Language Models (LLMs) and other generative AI technologies to provide solutions for complex tasks and projects. The repository includes a diverse range of agents for different use cases, from conversational chatbots to AI coding engines, and from autonomous HR assistants to vision task solvers.

L3AGI is an open-source tool that enables AI Assistants to collaborate together as effectively as human teams. It provides a robust set of functionalities that empower users to design, supervise, and execute both autonomous AI Assistants and Teams of Assistants. Key features include the ability to create and manage Teams of AI Assistants, design and oversee standalone AI Assistants, equip AI Assistants with the ability to retain and recall information, connect AI Assistants to an array of data sources for efficient information retrieval and processing, and employ curated sets of tools for specific tasks. L3AGI also offers a user-friendly interface, APIs for integration with other systems, and a vibrant community for support and collaboration.

The Ultralytics YOLO iOS App GitHub repository offers an advanced object detection tool leveraging YOLOv8 models for iOS devices. Users can transform their devices into intelligent detection tools to explore the world in a new and exciting way. The app provides real-time detection capabilities with multiple AI models to choose from, ranging from 'nano' to 'x-large'. Contributors are welcome to participate in this open-source project, and licensing options include AGPL-3.0 for open-source use and an Enterprise License for commercial integration. Users can easily set up the app by following the provided steps, including cloning the repository, adding YOLOv8 models, and running the app on their iOS devices.

Koko-aio shader is an all-in-one CRT shader tool that can be configured with various parameters to run on different GPUs. It aims to provide visual parameters to make monitors look similar to CRT displays without simulating their internal behavior. The tool includes features such as color corrections, B/W display colorization, antialiasing, noise effects, deconvergence, blurring/sharpening, interlacing, phosphor glow, and more. It also supports ambient lighting, vignette, integer scaling, and various image effects. Koko-aio is designed to enhance the visual experience of low-res content on high-resolution displays.

Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

Chat-xiuliu is a bidirectional voice assistant powered by ChatGPT, capable of accessing the internet, executing code, reading/writing files, and supporting GPT-4V's image recognition feature. It can also call DALL·E 3 to generate images. The project is a fork from a background of a virtual cat girl named Xiuliu, with removed live chat interaction and added voice input. It can receive questions from microphone or interface, answer them vocally, upload images and PDFs, process tasks through function calls, remember conversation content, search the web, generate images using DALL·E 3, read/write local files, execute JavaScript code in a sandbox, open local files or web pages, customize the cat girl's speaking style, save conversation screenshots, and support Azure OpenAI and other API endpoints in openai format. It also supports setting proxies and various AI models like GPT-4, GPT-3.5, and DALL·E 3.

Postiz is an ultimate AI social media scheduling tool that offers everything you need to manage your social media posts, build an audience, capture leads, and grow your business. It allows you to schedule posts with AI features, measure work with analytics, collaborate with team members, and invite others to comment and schedule posts. The tech stack includes NX (Monorepo), NextJS (React), NestJS, Prisma, Redis, and Resend for email notifications.

ComfyUI for Photoshop is a plugin that integrates with an AI-powered image generation system to enhance the Photoshop experience with features like unlimited generative fill, customizable back-end, AI-powered artistry, and one-click transformation. The plugin requires a minimum of 6GB graphics memory and 12GB RAM. Users can install the plugin and set up the ComfyUI workflow using provided links and files. Additionally, specific files like Check points, Loras, and Detailer Lora are required for different functionalities. Support and contributions are encouraged through GitHub.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

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.