Awesome GitHub RepositoriesGraph Execution Tracing

Ivy is a machine learning framework transpiler and model converter designed to ensure deep learning portability. It serves as a tool for migrating source code and models between different deep learning frameworks while maintaining original functionality. The system enables cross-framework model portability by translating model weights, architectures, and source code. It uses abstract syntax tree based transpilation and computational graph tracing to capture execution flows and rewrite high-level logic into target framework code. The project covers model interoperability through weight-layout

Eino is an AI agent development kit and LLM application framework designed for building autonomous agents and orchestrating complex language model workflows. It serves as a multi-agent orchestration engine and workflow orchestrator, providing a graph-based execution model to route data between models, tools, and retrievers. The framework distinguishes itself through a robust set of multi-agent coordination patterns, including supervisor-led management, sequential flows, and autonomous reasoning loops like ReAct. It features advanced agent execution controls such as active turn preemption, che

This project is a Java-based framework integration that provides an AI agent runtime, a graph-based AI workflow engine, and an LLM orchestration framework for Spring applications. It enables the development of stateful autonomous agents and the implementation of retrieval-augmented generation systems using document processing and vector databases. The framework distinguishes itself through a graph-based workflow runtime for designing complex AI pipelines with conditional routing and persistent state. It supports multi-agent orchestration via service-discovery coordination and provides human-i

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

Unit ist ein visuelles Programmiersystem und eine graphbasierte integrierte Entwicklungsumgebung, die dazu verwendet wird, funktionale Software durch das Verbinden von Zustandsautomaten und primitiven Operationen zu erstellen. Es dient als knotenbasierter Logik-Editor und Zustandsautomaten-Orchestrator, der visuelle Programmspezifikationen in eigenständige JavaScript-Dateien für das Deployment als statische Websites umwandelt. Das System zeichnet sich durch einen visuellen Compiler aus, der Programm-Bundles in aktive Websites rendern und bidirektionale Graph-Inspektionen durchführen kann, wodurch eine live gerenderte Anwendung für Debugging-Zwecke in ihren ursprünglichen visuellen Graphen zurückverwandelt werden kann. Es verwendet einen räumlichen Arbeitsbereich, in dem Low-Level-System-APIs in wiederverwendbare Zustandsautomaten gekapselt werden, um eine konsistente Bibliothek funktionaler Einheiten zu schaffen. Die Plattform deckt ein breites Spektrum an Fähigkeiten ab, einschließlich graphbasierter Logikkomposition mit pin-basiertem Datenrouting, rekursiver Subgraph-Verschachtelung und manueller JSON-Datenerstellung. Sie bietet zudem Tools für Projekt-Serialisierung, Hierarchie-Navigation zwischen Eltern- und Kindknoten sowie eine finale Rendering-Vorschau, um die Ausgabe eines Graphen zu betrachten.