Search Results for "visual query builder"
Sort By:
Showing 15 open source projects for "visual query builder"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
MATRIX is a world-class, award-winning learning management system (LMS) for businesses.The platform is known for delivering a great user experience, while incorporating all the essential tools companies need to support efficient training and learning.
-
1
athenaSQL
SQL builder for AWS Athena, inspired by sparkSQL
athenaSQL is Athena SQL query builder, inspired by sparkSQL. It borrow some sparkSQL’s concept sparkSQL. It was initially designed to eliminate the need for hard-coding SQL queries as strings within Python scripts and as an alternative to any bespoke SQL query templating. However, it offers the flexibility to be used in various ways as needed. -
2
Piccolo
A fast, user friendly ORM and query builder which supports asyncio
Piccolo is a modern, fast, and type-safe ORM for Python, designed with developer ergonomics in mind. It provides a clean syntax for defining schemas and building queries while supporting both sync and async execution. With built-in admin tools and rich introspection, Piccolo is suitable for web apps, APIs, and small-to-medium scale backends that prioritize clarity and speed. -
3
Microsoft Azure CLI
Azure command-line interface
A great cloud needs great tools; we're excited to introduce Azure CLI, our next-generation multi-platform command-line experience for Azure. Take a test run now from Azure Cloud Shell! We support tab completion for groups, commands, and some parameters. You can use the --query parameter and the JMESPath query syntax to customize your output. With the Azure CLI Tools Visual Studio Code extension, you can create .azcli files and use these features. IntelliSense for commands and their arguments. Snippets for commands, inserting required arguments automatically. Run the current command in the integrated terminal. ... -
4
VideoRAG
"VideoRAG: Chat with Your Videos
VideoRAG is a retrieval-augmented generation (RAG) framework tailored for video content that enables AI systems to answer questions, summarize, and reason over long videos by combining visual embeddings with contextual search. The system works by first breaking video into clips, extracting visual and audio-textual features, and indexing them into embeddings, then using an LLM with a retriever to pull relevant segments on demand. When a user query is received, VideoRAG locates semantically relevant moments in the video using the embedding index, retrieves associated clips or transcripts, and feeds them to a generative model to produce accurate, grounded answers or summaries. ... -
Effortlessly manage macOS, iOS, iPadOS and tvOS devices across multiple clients and locations.Addigy solutions accelerate Apple adoption in any environment.
-
5
DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
...Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. It includes an “Ask” feature that lets users query the generated wiki using RAG-style retrieval, enabling interactive question-answering and exploration. -
6
AI Data Science Team
An AI-powered data science team of agents
...It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly. -
7
DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
DeepSeek-VL2 is DeepSeek’s vision + language multimodal model—essentially the next-gen successor to their first vision-language models. It combines image and text inputs into a unified embedding / reasoning space so that you can query with text and image jointly (e.g. “What’s going on in this scene?” or “Generate a caption appropriate to context”). The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to process visual inputs as context for downstream tasks. The repository includes evaluation results (e.g. image/text alignment scores, common VL benchmarks), configuration files, and model weights (where permitted). ... -
8
Sentry
Cross-platform application monitoring and error tracking software
Sentry is a cross-platform, self-hosted error monitoring solution that helps software teams discover, monitor and fix errors in real-time. The most users and logs will have to provide are the clues, and Sentry provides the answers. Sentry offers enhanced application performance monitoring through information-laden stack traces. It lets you build better software faster and more efficiently by showing you all issues in one place and providing the trail of events that lead to errors. It also... -
9
Qwen3-VL-Embedding
Multimodal embedding and reranking models built on Qwen3-VL
...The core embedding model maps such inputs into semantically rich vectors in a unified representation space, enabling similarity search, clustering, and cross-modal retrieval. The reranking model then precisely scores relevance between a given query and candidate documents, enhancing retrieval accuracy in complex multimodal tasks. Together, they support advanced information retrieval workflows such as image-text search, visual question answering (VQA), and video-text matching, while providing out-of-the-box support for more than 30 languages. -
Wiz: #1 Cloud Security Software for Modern Cloud ProtectionUse the Wiz Cloud Security Platform to build faster in the cloud, enabling security, dev and devops to work together in a self-service model built for the scale and speed of your cloud development.
-
10
RAG Anything
RAG-Anything: All-in-One RAG Framework
RAG-Anything is an open-source unified framework that extends the Retrieval-Augmented Generation (RAG) paradigm to fully multimodal document and knowledge retrieval, enabling systems to ingest, parse, represent, and query rich content that includes text, images, tables, formulas, and other structured or visual elements. Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling multimodal content in ways that preserve cross-modal relationships and semantic context, often treating content elements as interconnected knowledge entities rather than separate data silos. ... -
11
zvt
Modular quant framework
For practical trading, a complex algorithm is fragile, a complex algorithm building on a complex facility is more fragile, complex algorithm building on a complex facility by a complex team is more and more fragile. zvt wants to provide a simple facility for building a straightforward algorithm. Technologies come and technologies go, but market insight is forever. Your world is built by core concepts inside you, so it’s you. zvt world is built by core concepts inside the market, so it’s zvt.... -
12
BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ... -
13
Orator
The Orator ORM provides a simple yet beautiful ActiveRecord implement.
The Orator ORM provides a simple yet beautiful ActiveRecord implementation. The Orator ORM is based on conventions to avoid the hassle of defining every single aspect of your models. It is inspired by the database part of the Laravel framework, but largely modified to be more pythonic. All you need to get you started is the configuration describing your database connections and passing it to a DatabaseManager instance. If you have multiple databases configured you can specify which one is... -
14
GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
gif-for-cli is a small, playful utility that brings animated GIFs to the command line by rendering frames directly in a terminal. It takes an input GIF (or a URL) and converts each frame into a terminal-friendly representation, timing updates to approximate the original animation. Depending on terminal capabilities, it can use ANSI color blocks or image protocols to achieve surprisingly faithful playback. The tool includes conveniences such as looping control, scaling to fit your terminal,... -
15
GDeps
Automatic process to update and build your external libraries/projects
Welcome to GDeps! ( http://gdeps.org ) ========== [PRE-ALPHA] GDeps is a C++ dependencies/projects builder. Write in Python3. Launch a project script and GDeps will: 1) Create and Update the repository (svn, git, mercurial) 2) Make the solution (cmake, boost, bakefile) 3) Build the solution (Compilers : Mingw, VC90~140, Clang, Digital Mars, Ides : Visual Studio, Codeblocks ). Install: ========== 1) Install Python3: https://www.python.org/ 2) Install GDeps: https://sourceforge.net/projects/gdeps/files/latest/download?...
- Previous
- You're on page 1
- Next