27 Repos
Systems that propagate database changes to connected clients instantly to ensure user interfaces reflect the current state without manual refreshing.
Explore 27 awesome GitHub repositories matching data & databases · Real-Time. Refine with filters or upvote what's useful.
Pocketbase is a backend-as-a-service platform that provides a self-contained, single-binary server for building full-stack applications. It integrates a relational database, authentication, and file storage into one executable process, eliminating the need for external infrastructure or complex server management. The platform distinguishes itself through an embedded database engine that runs directly within the application process and a reactive communication layer that pushes live updates to connected clients. By monitoring internal transaction logs, it synchronizes data across multiple user
Streams database modifications to connected clients instantly to ensure user interfaces remain synchronized with current state.
Refine is a React-based framework for building data-intensive internal tools, admin panels, and B2B applications. It functions as a data-driven UI library and a headless admin panel generator that connects frontends to external backend services using standardized logic for state management and network request handling. The project decouples business logic from the presentation layer, allowing any custom design system or interface library to be applied to the application. It includes a CRUD application generator that automatically creates user interfaces for managing records based on the struc
Ensures application state reflects backend changes instantly through real-time data synchronization.
Apollo is a microservice configuration management system and dynamic configuration center. It serves as a centralized platform for storing, distributing, and syncing application settings across distributed environments to maintain consistency across various clusters. The system distinguishes itself through a dynamic configuration orchestrator that supports real-time updates to connected applications, eliminating the need for manual service restarts. It features a grayscale configuration deployment tool for rolling out changes to a small subset of service instances and a version control system
Propagates configuration changes to connected clients instantly to ensure the system reflects the current state without restarts.
Storm is an automated research platform that coordinates multiple language model agents to conduct internet-based information gathering and generate structured, citation-backed articles. The system functions as a modular framework that grounds generated content in real-time web data, ensuring that all outputs are verifiable and evidence-based. The platform distinguishes itself through a multi-agent discourse orchestrator that simulates expert dialogues to refine information discovery. By utilizing hierarchical concept mapping, the system organizes retrieved data into dynamic structures, allow
Connects language models to live internet data to ensure generated content is verifiable and evidence-based.
React-admin is a framework for building data-driven administrative interfaces that connect to REST or GraphQL backends. It provides a comprehensive suite of tools for managing the full lifecycle of administrative applications, including resource-oriented routing, declarative form scaffolding, and context-driven state management. By utilizing a modular adapter-based architecture, the framework abstracts backend communication, allowing developers to build consistent CRUD interfaces that handle data fetching, authentication, and synchronization automatically. The project distinguishes itself thr
Reflects live backend updates in the user interface using pub-sub mechanisms to keep dashboards current without manual refreshes.
This project is a high-performance, lightweight C graphics library designed for creating interactive user interfaces on resource-constrained embedded hardware. It functions as a comprehensive framework that provides a widget toolkit, a rendering engine, and hardware-agnostic drivers to support the development of graphical displays on microcontrollers and embedded systems. The framework distinguishes itself through a flexible, object-oriented widget hierarchy and a declarative layout engine that supports responsive design patterns like flexbox and grid systems. It enables developers to synchro
Connects graphics engines to real-time operating systems to handle task scheduling and hardware abstraction.
The Gemini Cookbook is a comprehensive collection of implementation patterns, code samples, and development guides designed for building applications with Google Gemini models. It serves as a central resource for developers to integrate multimodal generative artificial intelligence into their software, providing the necessary frameworks to manage model interactions, stateful workflows, and structured data extraction. The repository distinguishes itself by offering specialized toolkits for autonomous agent orchestration, enabling the construction of agents that can execute code, browse the web
Integrates real-time geographical data into model outputs to provide location-aware answers based on current place information.
Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic. The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ
Integrates execution results and tool outputs with conversation history to ensure agents learn from past actions.
OpenMetadata is an enterprise data catalog, metadata platform, and governance suite that functions as a knowledge graph for data assets. It serves as an AI-ready metadata layer, providing governed context and organizational memory to large language model agents via the Model Context Protocol. The platform distinguishes itself by capturing institutional knowledge, linking conversations, decisions, and remediation notes directly to data assets to preserve tribal knowledge. It integrates AI agents to automate metadata governance, such as suggesting descriptions and identifying sensitive data thr
Provides business context grounding to make technical assets discoverable and understandable for users and AI.
Planning with files is an enterprise knowledge graph platform designed to transform unstructured organizational data into a searchable, interconnected network. By utilizing a graph-based retrieval-augmented generation engine, the system grounds language model outputs in verified internal data, ensuring that responses are explainable, traceable, and free from hallucinations. The platform distinguishes itself through a focus on data sovereignty and secure, private infrastructure deployment. It enables organizations to maintain full control over sensitive information by processing data locally o
Grounds language models in verified internal data to ensure generated responses are accurate and trustworthy.
This project is a multi-model database system designed to store and manage information as documents, graphs, and key-value pairs within a single engine. It functions as a graph database and knowledge graph platform, providing the infrastructure to build, query, and visualize structured data models. By integrating vector search capabilities, the system serves as a vector database that supports retrieval-augmented generation for artificial intelligence applications. The platform distinguishes itself through a unified query language that allows users to perform document lookups, graph traversals
Supplies large language models with verified enterprise context through graph retrieval and vector search.
DataHub is a metadata management platform designed to unify technical, operational, and business context across diverse data ecosystems. By utilizing a graph-based metadata model and an event-driven ingestion architecture, it creates a centralized source of truth that maps complex data relationships, lineage, and ownership. This foundational framework enables organizations to maintain a synchronized view of their data landscape, supporting both human-led discovery and automated data operations. The platform distinguishes itself through its focus on grounding artificial intelligence and autono
Supplies AI agents with verified business definitions and lineage to ensure grounded, trustworthy insights.
F Prime ist ein komponentenbasiertes Framework für die Entwicklung und Bereitstellung von Embedded- und Raumfahrtsoftware. Es bietet eine modulare Architektur, die Softwarelogik von Kommunikationsschnittstellen entkoppelt und es Entwicklern ermöglicht, Systemstrukturen über eine domänenspezifische Modellierungssprache zu definieren. Dieser modellbasierte Ansatz ermöglicht eine automatisierte Codegenerierung, die Konsistenz über komplexe Systemtopologien hinweg gewährleistet und gleichzeitig strikte Schnittstellenverträge zwischen Softwaremodulen aufrechterhält. Das Framework zeichnet sich durch sein integriertes Build-System und eine Suite für Bodendatenoperationen aus. Es automatisiert den gesamten Lebenszyklus von Embedded-Software, von der Cross-Kompilierung und dem Abhängigkeitsmanagement bis hin zur Generierung von Telemetrie- und Befehlsschnittstellen. Durch die Bereitstellung einer einheitlichen Umgebung für Onboard-Flugsoftware und bodengestützte Überwachung erleichtert es die nahtlose Integration, das Testen sowie die Steuerung und Überwachung verteilter Embedded-Systeme über verschiedene Hardwareplattformen hinweg. Über die Kernarchitektur hinaus enthält das Projekt umfassende Werkzeuge für die Systembeobachtbarkeit, einschließlich Echtzeit-Telemetrie-Visualisierung, Ereignisprotokollierung und diagnostischer Tracing-Funktionen. Es unterstützt eine breite Palette von Bereitstellungsszenarien, von Bare-Metal-Umgebungen bis hin zu Echtzeitbetriebssystemen, und bietet Mechanismen für Speicherverwaltung, zustandsgesteuerte Verhaltensmodellierung und asynchrone Aufgabenausführung. Das Projekt wird als C++-Repository mit umfangreicher Dokumentation und Build-System-Unterstützung für die plattformübergreifende Entwicklung gepflegt.
Executes custom external processes alongside the ground data system to integrate new user interfaces or data processors.
This project is a plugin framework and agentic workflow library designed to connect large language models to professional toolstacks. It provides a system for integrating language models with external data warehouses, CRMs, and other enterprise software to retrieve and manipulate real-time business data. The framework enables the automation of specialized professional tasks through a file-based plugin definition system. It allows for the customization of domain expertise and plugin behavior to align with internal company processes, supported by an enterprise data connector that links models t
Captures business details and tool connections to provide organizational context for agentic workflows.
This project is a browser extension and toolset designed to integrate real-time web search results and extracted page content into large language model prompts. It functions as a web search integrator and content parser that feeds current internet data into conversational AI interfaces to ensure responses are grounded in evidence. The system includes a prompt template manager for storing and executing pre-defined structures that trigger automated web crawls. It enables deep research workflows by performing comprehensive searches to generate detailed responses supported by citations and links
Inserts real-time web search results into the prompt context to ground AI reasoning with current evidence.
Genkit is an open-source framework for building AI-powered applications. It provides a unified interface for connecting to hundreds of generative AI models from multiple providers, enabling text, image, audio, and video generation through a single API. The framework structures multi-step AI interactions—including chat, retrieval-augmented generation, tool use, and agentic workflows—as composable, traceable flows with built-in streaming and state management. The framework distinguishes itself through a comprehensive developer toolkit that includes a command-line interface and a local developer
Provides location-aware answers by integrating maps data into the model's context.
Dieses Projekt ist ein Wissensdatenbank-Plugin und RAG-Kontextmanager, der eine lokale Vektordatenbank-Schnittstelle nutzt, um semantische Suche und Beziehungsmapping zu ermöglichen. Es transformiert Text in numerische Vektoren, um semantisch verwandte Notizen und Auszüge basierend auf konzeptioneller Bedeutung statt nur nach Schlüsselwortübereinstimmungen zu finden. Das System zeichnet sich durch einen semantischen Graph-Visualisierer aus, der Notizen in Clustern abbildet, um konzeptionelle Verbindungen aufzudecken. Es verfügt zudem über einen Kontextmanager, der lokale Notizen und Auszüge in wiederverwendbare Pakete bündeln kann, um fundierte Faktenbasen für Konversationen mit großen Sprachmodellen bereitzustellen. Das Tool deckt eine breite Palette an Funktionen ab, darunter die Abfrage von natürlichsprachlichem Wissen, die automatisierte Workflow-Ausführung für die Notizerstellung und die Möglichkeit, Prompts zwischen lokalen und Cloud-basierten KI-Modellen zu routen. Es bietet verschiedene Discovery-Schnittstellen, wie z. B. Inline-Indikatoren für verwandte Inhalte und ein Fußzeilen-Panel zum Einblenden ähnlicher Dokumente während des Bearbeitungsprozesses.
Grounds AI responses using content from a local index of documents and notes.
Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for
Retrieves grounded answers from verified source material across large repositories to ensure accurate technical information.
Deep research ist ein automatisiertes System zur Forschungsgenerierung, das große Sprachmodelle und Websuchmaschinen nutzt, um umfassende Berichte und Deep-Dive-Analysen zu komplexen Themen zu synthetisieren. Es kombiniert Echtzeit-Websuchergebnisse mit hochgeladenen lokalen Dokumenten, um generierte Inhalte auf spezifischen Fakten zu fundieren. Das System verwendet einen iterativen Forschungsworkflow, um Berichte durch einen schrittweisen Prozess des Bearbeitens, Aktualisierens und Neustartens spezifischer Forschungsphasen zu verfeinern. Es kann unstrukturierte Berichtsdaten in Wissensgraph-Visualisierungen umwandeln, um Beziehungen zwischen verschiedenen Erkenntnissen abzubilden und die Struktur eines Forschungsprojekts zu organisieren. Zu den Funktionsbereichen gehören die Integration mehrerer KI-Modelle und Suchmaschinen, die Verwendung spezialisierter Vorlagen zur Definition des Forschungsumfangs sowie die Verwaltung der Forschungshistorie. Das System unterstützt zudem das Model Context Protocol, um Forschungsfähigkeiten und Datenströme mit externen Tools zu verbinden.
Grounds AI generated reports in specific factual data from a combination of local documents and web search.
DocSearch ist ein integriertes Toolset zum Hinzufügen von Suchfunktionen zu Dokumentations-Websites. Es bietet eine JavaScript- und React-Suchschnittstelle zum Einbetten von Autocomplete-Suchleisten, einen dedizierten Web-Crawler zum Extrahieren und Synchronisieren von Website-Inhalten in einen durchsuchbaren Index sowie ein Überwachungssystem zur Verfolgung von Benutzeranfragen und Interaktionsereignissen. Das Projekt zeichnet sich durch die Einbindung eines KI-Konversationsassistenten aus, der auf Retrieval-Augmented Generation basiert. Dieser Assistent stützt ein Large Language Model auf einen spezifischen Dokumentationsindex, um faktische Antworten zu liefern, mit konfigurierbaren System-Prompts zur Verhaltensanpassung und Domänenbeschränkungen, um zu steuern, wo der Assistent aktiv bleibt. Das System deckt ein breites Spektrum an operativen Fähigkeiten ab, einschließlich automatisierter Crawl-Zeitplanung, Überprüfung der Domäneninhaberschaft und Manipulation von Suchergebnissen durch Filtern und Scoping. Die Benutzeroberfläche ist durch vordefinierte Themes, lokalisierte Textüberschreibungen und komponentenbasierte Ergebnistemplating hochgradig anpassbar. Die Suchschnittstelle kann als eingebettete Eingabe, Modal oder persistentes Seitenpanel bereitgestellt werden.
Restricts the language model to a specific search index to ensure answers are based exclusively on internal documentation.