6 Repos
Implementation of custom Python scripts within visual node-based automation systems.
Distinct from Node Execution Logic: Specifically covers the execution of Python within a node-graph context rather than general application logic
Explore 6 awesome GitHub repositories matching user interface & experience · Python Logic Execution. Refine with filters or upvote what's useful.
Promptflow ist ein Entwicklungs-Framework und Orchestrator für den Aufbau von Anwendungen, die auf Large Language Models basieren. Es fungiert als Tool-Suite für das Design, die Orchestrierung und das Deployment von KI-Workflows, indem Prompts, benutzerdefinierter Python-Code und Sprachmodelle zu ausführbaren Sequenzen verknüpft werden. Das Projekt zeichnet sich durch einen visuellen KI-Workflow-Designer aus, der die Erstellung von gerichteten azyklischen Graphen (DAGs) aus Logik-Knoten ermöglicht. Es bietet eine dedizierte Prompt-Engineering-Umgebung für Versionierung und Vergleich von Templates sowie zustandsbehaftetes Execution-Tracing, um Funktionsaufrufe und Variablenwerte für schrittweises Debugging aufzuzeichnen. Die Plattform deckt ein breites Funktionsspektrum ab, einschließlich Retrieval Augmented Generation (RAG) via Vektordatenbank-Lookups und metrikgesteuerte Evaluierungspipelines für Batch-Tests und Qualitätssicherung. Sie deckt den gesamten Lebenszyklus von der Entwicklung bis zur Produktion ab, durch containerisiertes Deployment, Workflow-Endpoint-Serving und sicheres Verbindungsmanagement für API-Anmeldedaten. Ein Command-Line-Interface (CLI) und ein SDK für Workflow-Validierung und Integration in automatisierte CI/CD-Pipelines sind enthalten.
Allows the integration of custom Python functions to process data and call APIs within a workflow.
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
Enables AI models to write and run Python code for calculations and logic during response generation.
Ryven is a flow-based programming framework and visual scripting editor for Python. It provides a node-based graphical interface for designing and executing logic by connecting discrete functional nodes to build executable data pipelines. The system functions as an extensible visual logic tool, allowing for the development of custom Python nodes and the integration of interactive GUI widgets to expand scripting capabilities. It includes a node graph engine that supports both visual editing and headless execution, enabling scripts to run without a graphical user interface. The platform covers
Provides a node-based graphical interface for designing and executing flow-based logic using Python.
WebGAL is a web-native development environment designed for the creation and publication of interactive narrative games. It provides a browser-based platform that enables users to build visual novels featuring branching dialogue and multimedia assets without requiring manual coding. The platform distinguishes itself through a visual editor that utilizes node-based logic definition to manage narrative flow and scene transitions. It includes specialized tooling for the configuration and integration of animated character models, allowing for the direct implementation of interactive character seq
Translates graphical node connections into executable game logic for narrative branching and scene flow.
n8n-skills is a collection of technical guides and architectural frameworks for designing, building, and deploying automation workflows and AI agents within n8n. It provides a structured approach to creating autonomous agents by combining large language model chains with memory systems and custom toolsets. The project focuses on extending AI capabilities through the development of custom tool functions using structured input schemas and the integration of Model Context Protocol servers. It emphasizes the use of specific architectural patterns to manage webhooks, APIs, and binary data handling
Enables implementation of custom logic within code nodes adhering to standard library limitations.
rgthree-comfy is a collection of custom nodes and interface enhancements designed to automate and organize generative AI workflows within ComfyUI. It provides a specialized toolset for node-based automation, dynamic data routing, and graph management. The project distinguishes itself through a dynamic data router and workflow management tools that enable bulk muting, bypassing, and navigation of complex node graphs via bookmarks and visual labels. It also includes logic and math nodes for evaluating expressions and image processing utilities for side-by-side comparisons and precise cropping.
Implements custom Python script execution within the visual node-graph for dynamic data manipulation and decision logic.