DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

Easy Dataset is a specialized application designed to streamline the creation of fine-tuning datasets for Large Language Models (LLMs). It offers an intuitive interface for uploading domain-specific files, intelligently splitting content, generating questions, and producing high-quality training data for model fine-tuning. With Easy Dataset, users can transform domain knowledge into structured datasets compatible with all OpenAI-format compatible LLM APIs, making the fine-tuning process accessible and efficient.

GPUStack is an open-source GPU cluster manager designed for running large language models (LLMs). It supports a wide variety of hardware, scales with GPU inventory, offers lightweight Python package with minimal dependencies, provides OpenAI-compatible APIs, simplifies user and API key management, enables GPU metrics monitoring, and facilitates token usage and rate metrics tracking. The tool is suitable for managing GPU clusters efficiently and effectively.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

pgvecto.rs is a Postgres extension written in Rust that provides vector similarity search functions. It offers ultra-low-latency, high-precision vector search capabilities, including sparse vector search and full-text search. With complete SQL support, async indexing, and easy data management, it simplifies data handling. The extension supports various data types like FP16/INT8, binary vectors, and Matryoshka embeddings. It ensures system performance with production-ready features, high availability, and resource efficiency. Security and permissions are managed through easy access control. The tool allows users to create tables with vector columns, insert vector data, and calculate distances between vectors using different operators. It also supports half-precision floating-point numbers for better performance and memory usage optimization.

DeepMesh is an auto-regressive artist-mesh creation tool that utilizes reinforcement learning to generate high-quality meshes conditioned on a given point cloud. It offers pretrained weights and allows users to generate obj/ply files based on specific input parameters. The tool has been tested on Ubuntu 22 with CUDA 11.8 and supports A100, A800, and A6000 GPUs. Users can clone the repository, create a conda environment, install pretrained model weights, and use command line inference to generate meshes.

ZO2 (Zeroth-Order Offloading) is an innovative framework designed to enhance the fine-tuning of large language models (LLMs) using zeroth-order (ZO) optimization techniques and advanced offloading technologies. It is tailored for setups with limited GPU memory, enabling the fine-tuning of models with over 175 billion parameters on single GPUs with as little as 18GB of memory. ZO2 optimizes CPU offloading, incorporates dynamic scheduling, and has the capability to handle very large models efficiently without extra time costs or accuracy losses.

HuixiangDou is a **group chat** assistant based on LLM (Large Language Model). Advantages: 1. Design a two-stage pipeline of rejection and response to cope with group chat scenario, answer user questions without message flooding, see arxiv2401.08772 2. Low cost, requiring only 1.5GB memory and no need for training 3. Offers a complete suite of Web, Android, and pipeline source code, which is industrial-grade and commercially viable Check out the scenes in which HuixiangDou are running and join WeChat Group to try AI assistant inside. If this helps you, please give it a star ⭐

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

Inferable is an open source platform that helps users build reliable LLM-powered agentic automations at scale. It offers a managed agent runtime, durable tool calling, zero network configuration, multiple language support, and is fully open source under the MIT license. Users can define functions, register them with Inferable, and create runs that utilize these functions to automate tasks. The platform supports Node.js/TypeScript, Go, .NET, and React, and provides SDKs, core services, and bootstrap templates for various languages.

MarkLLM is an open-source toolkit designed for watermarking technologies within large language models (LLMs). It simplifies access, understanding, and assessment of watermarking technologies, supporting various algorithms, visualization tools, and evaluation modules. The toolkit aids researchers and the community in ensuring the authenticity and origin of machine-generated text.

SuperAgentX is a lightweight open-source AI framework designed for multi-agent applications with Artificial General Intelligence (AGI) capabilities. It offers goal-oriented multi-agents with retry mechanisms, easy deployment through WebSocket, RESTful API, and IO console interfaces, streamlined architecture with no major dependencies, contextual memory using SQL + Vector databases, flexible LLM configuration supporting various Gen AI models, and extendable handlers for integration with diverse APIs and data sources. It aims to accelerate the development of AGI by providing a powerful platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.

Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.

Auto-News is an automatic news aggregator tool that utilizes Large Language Models (LLM) to pull information from various sources such as Tweets, RSS feeds, YouTube videos, web articles, Reddit, and journal notes. The tool aims to help users efficiently read and filter content based on personal interests, providing a unified reading experience and organizing information effectively. It features feed aggregation with summarization, transcript generation for videos and articles, noise reduction, task organization, and deep dive topic exploration. The tool supports multiple LLM backends, offers weekly top-k aggregations, and can be deployed on Linux/MacOS using docker-compose or Kubernetes.

ChatTTS is a generative speech model optimized for dialogue scenarios, providing natural and expressive speech synthesis with fine-grained control over prosodic features. It supports multiple speakers and surpasses most open-source TTS models in terms of prosody. The model is trained with 100,000+ hours of Chinese and English audio data, and the open-source version on HuggingFace is a 40,000-hour pre-trained model without SFT. The roadmap includes open-sourcing additional features like VQ encoder, multi-emotion control, and streaming audio generation. The tool is intended for academic and research use only, with precautions taken to limit potential misuse.

GPTSwarm is a graph-based framework for LLM-based agents that enables the creation of LLM-based agents from graphs and facilitates the customized and automatic self-organization of agent swarms with self-improvement capabilities. The library includes components for domain-specific operations, graph-related functions, LLM backend selection, memory management, and optimization algorithms to enhance agent performance and swarm efficiency. Users can quickly run predefined swarms or utilize tools like the file analyzer. GPTSwarm supports local LM inference via LM Studio, allowing users to run with a local LLM model. The framework has been accepted by ICML2024 and offers advanced features for experimentation and customization.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

DBeaver is a free multi-platform database tool designed for developers, SQL programmers, database administrators, and analysts. It offers a wide range of features including schema editor, SQL editor, data editor, AI integration, ER diagrams, data export/import/migration, SQL execution plans, database administration tools, database dashboards, Spatial data viewer, proxy and SSH tunnelling, custom database drivers editor, etc. It supports over 100 database drivers out of the box and is compatible with any database that has a JDBC or ODBC driver. DBeaver also supports smart AI completion and code generation with OpenAI or Copilot.

Spice is a portable runtime written in Rust that offers developers a unified SQL interface to materialize, accelerate, and query data from any database, data warehouse, or data lake. It connects, fuses, and delivers data to applications, machine-learning models, and AI-backends, functioning as an application-specific, tier-optimized Database CDN. Built with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. Spice makes it fast and easy to query data from one or more sources using SQL, co-locating a managed dataset with applications or machine learning models, and accelerating it with Arrow in-memory, SQLite/DuckDB, or attached PostgreSQL for fast, high-concurrency, low-latency queries.

LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.