Awesome GitHub RepositoriesData Visualization Tools

Twenty is a headless customer relationship management framework that enables developers to build, version, and deploy custom business applications using code. By utilizing a declarative approach to data modeling, the platform allows for the definition of custom objects, fields, and complex relationships directly within the source code. This schema-driven architecture automatically generates corresponding REST and GraphQL APIs, ensuring that data structures and interface components remain synchronized across development and production environments. The platform distinguishes itself through a m

Metabase is a business intelligence platform designed to connect to various storage systems and relational databases for data exploration, visualization, and reporting. It provides a centralized environment where users can build queries through a graphical interface or raw code, transforming raw information into interactive dashboards and charts. The platform is built to support self-service analytics, allowing non-technical team members to extract insights without requiring deep knowledge of database syntax. The platform distinguishes itself through a metadata-driven modeling layer that abst

Dokploy is a self-hosted platform-as-a-service designed to simplify the deployment and management of containerized applications and databases. It provides a centralized control plane that decouples administrative management from application workloads, allowing users to oversee infrastructure across multiple server nodes through a unified web interface or a command-line tool. The platform distinguishes itself through an extensive library of pre-configured application templates, enabling the rapid deployment of databases, identity providers, and various productivity or development tools. It sup

This project is a curated directory of resources, extensions, and themes designed to extend the functionality of the Visual Studio Code editor. It serves as a comprehensive index for developers seeking to enhance their coding environment, offering a structured collection of community-driven tools that streamline development workflows and improve editor productivity. The directory distinguishes itself by organizing a vast ecosystem of plugins into logical categories, ranging from language-specific intelligence and version control integrations to advanced productivity utilities. It highlights t

This application is a desktop utility for managing, editing, and visualizing local database files. It provides a graphical interface for executing SQL queries, designing database structures, and performing routine maintenance tasks on data stores. The software distinguishes itself through its support for encrypted database files, allowing users to manage password-protected data using modular cryptographic extensions. It also offers built-in tools for data analysis, enabling the generation of graphical charts and plots directly from query results to identify trends within datasets. Beyond its

Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea

MMPose is a PyTorch-based pose estimation toolbox and deep learning training pipeline designed for detecting 2D and 3D keypoints on humans, animals, and faces. It serves as a computer vision model zoo and a framework for both 2D pose estimation and 3D pose lifting. The project is distinguished by its modular architecture and extensibility, employing a registry-based system and hierarchical configurations to allow for custom algorithm integration and model pipeline customization. It supports diverse estimation paradigms, including top-down, bottom-up, and two-stage pose lifting workflows. The

ClearML is a comprehensive MLOps platform designed to manage the end-to-end machine learning lifecycle, from initial experimentation to production deployment. It provides a suite of integrated tools including a pipeline orchestrator for automating workflows, an experiment tracking tool for logging hyperparameters and metrics, and a metadata-driven data versioning system for managing large-scale datasets and model artifacts. The platform is distinguished by its advanced compute management and serving capabilities. It features a GPU compute manager that supports fractional resource slicing and

ClearML is a comprehensive MLOps platform designed to manage the entire machine learning lifecycle. It functions as an experiment tracking tool, a data versioning system, and a pipeline orchestrator, while providing infrastructure for GPU cluster management and model serving. The platform is distinguished by its ability to handle hybrid-cloud compute scheduling and fractional GPU allocation, allowing multiple workloads to share a single hardware accelerator. It employs a metadata-based approach to data versioning, using virtual views to track large datasets and artifacts without duplicating r

charts.css is a CSS-driven framework designed to transform semantic HTML into accessible data visualizations without relying on JavaScript. It functions as a charting library that uses standard HTML structures, such as tables and lists, to render graphs while maintaining full compatibility with screen readers. The project distinguishes itself by using CSS variables to map numeric data to visual dimensions and utility classes to control chart types and layouts. It supports a wide range of visual styles, including 3D effects, reflection effects, and customized color palettes integrated via a br

MMDetection3D is an open-source toolbox for 3D perception, providing a unified framework for detecting and segmenting objects in three-dimensional environments. It supports a range of core tasks including monocular 3D object detection from single camera images, LiDAR-based 3D object detection from raw point clouds, and multi-modal fusion that combines camera images with LiDAR data. The toolbox also covers point cloud semantic segmentation, assigning class labels to every point in a scan for scene understanding. The project distinguishes itself through a config-driven pipeline that orchestrate

vue-chartjs is a component library that wraps Chart.js chart types as reusable Vue components, integrating the charting library into Vue's component model. It provides reactive props binding so that charts automatically redraw when data or options change, and exposes the underlying Chart.js instance via template refs for direct programmatic access. The library also forwards Chart.js interaction events like clicks and hovers to Vue component event handlers, and applies ARIA labels to chart elements for screen reader support. The library distinguishes itself by offering typed Vue components for

Giskard लार्ज लैंग्वेज मॉडल्स (LLMs) और AI एजेंट्स के लिए एक इवैल्यूएशन फ्रेमवर्क, टेस्टिंग लाइब्रेरी और क्वालिटी मॉनिटरिंग सिस्टम है। यह मॉडल के प्रदर्शन और विश्वसनीयता को मापने के लिए एक टूलकिट के रूप में कार्य करता है, जो RAG (retrieval-augmented generation) पाइपलाइन्स को वैलिडेट करने के लिए विशेष क्षमताएं प्रदान करता है। यह प्रोजेक्ट अपने ऑटोमेटेड रेड टीमिंग टूल और सिक्योरिटी स्कैनर के माध्यम से खुद को अलग बनाता है, जिसे कमजोरियों, प्रॉम्प्ट इंजेक्शन और सुरक्षा जोखिमों की पहचान करने के लिए डिज़ाइन किया गया है। यह मॉडल की मजबूती को मापने और जानकारी लीक होने का पता लगाने के लिए एडवर्सरियल प्रोबिंग और सिंथेटिक एज केस जनरेशन का उपयोग करता है। यह प्लेटफॉर्म तथ्यात्मक सटीकता और मतिभ्रम (hallucination) का पता लगाने, तर्क और लॉजिक बेंचमार्किंग, और बायस डिटेक्शन जैसी व्यापक क्षमताएं प्रदान करता है। यह रिग्रेशन टेस्टिंग, RAG कंपोनेंट असेसमेंट और नॉलेज बेस से टेस्ट केस जनरेट करने के लिए टूल्स प्रदान करता है। सिस्टम में सहयोगी टीम वर्कस्पेस, रोल-आधारित एक्सेस कंट्रोल और समय के साथ प्रदर्शन में गिरावट की निगरानी के लिए शेड्यूल्ड इवैल्यूएशन पाइपलाइन्स जैसी मैनेजमेंट सुविधाएं शामिल हैं।

Argilla is a collaborative AI feedback tool and data curation management system. It serves as a human-in-the-loop dataset platform designed to coordinate workforce annotators and domain experts in labeling, rating, and refining data samples for machine learning projects. The platform focuses on large language model dataset curation and reinforcement learning from human feedback workflows. It provides a shared workspace for integrating human expertise into AI development to validate model outputs and correct data errors. The system manages the end-to-end machine learning data pipeline, includ

This project is a deep learning implementation of the RetinaNet architecture for detecting and classifying objects within images. Built as a Keras object detection framework and a TensorFlow computer vision tool, it provides a complete neural network implementation based on the RetinaNet paper. The framework includes specialized components such as a Feature Pyramid Network and a focal loss function to handle object detection. It features a configurable backbone architecture and anchor-based bounding boxes to predict object locations across varying scales and aspect ratios. The toolset covers

This project is a Model Context Protocol server that enables large language models to generate and render data visualizations, charts, and diagrams. It functions as a toolset for AI assistants to transform raw data into professional visual representations. The server utilizes an intelligent selection layer to determine the most effective visualization format based on the provided data. It supports remote rendering via external HTTP services and provides the flexibility to route requests to self-hosted rendering endpoints for private network environments. Capabilities cover a wide range of da