Awesome GitHub RepositoriesAPI Request Execution from CLI

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

LXD is a unified platform for managing both system containers and virtual machines through a single REST API and command-line interface. It provides a programmatic HTTP interface for controlling the full lifecycle of instances, enabling automation and integration with external tools. The system runs unprivileged containers with per-instance UID/GID mappings, seccomp filters, and AppArmor profiles for kernel-level isolation, while supporting multiple storage backends including directory, Btrfs, LVM, ZFS, Ceph, LINSTOR, and TrueNAS through a unified driver interface. The platform distinguishes

ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself

ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented

Evans ist ein gRPC-Client und API-Explorer, der für das Testen, Debuggen und Automatisieren von Remote Procedure Calls entwickelt wurde. Er fungiert als interaktiver Client und zustandsloses Kommandozeilen-Utility für die Ausführung von gRPC-Methoden und die Inspektion von Remote-Server-API-Oberflächen. Das Tool bietet spezialisierte Unterstützung für das gRPC-Web-Protokoll, um die Kommunikation mit Web-basierten Implementierungen zu erleichtern. Es ermöglicht die Entdeckung von Diensten und Nachrichtenstrukturen durch Server-Reflection oder Definitionsdateien und unterstützt das Management von Unary-, Client-Side-, Server-Side- und bidirektionalen Streaming-Kommunikationen. Das Projekt deckt das Request-Management durch benutzerdefinierte Metadaten-Header und die Handhabung komplexer Feldtypen wie Arrays, Enums und Base64-kodierte Bytes ab. Es nutzt JSON-basierte Repräsentationen für Ein- und Ausgaben, um maschinenlesbare Ergebnisse und Datei-basierte Request-Automatisierung zu ermöglichen.

Thunder Client is a REST API client extension for VS Code that functions as an HTTP request manager, testing tool, and mocking workspace. It allows users to send requests, organize them into collections, and manage API configurations directly within the editor. The project distinguishes itself through a command-line interface for executing automated test suites in CI/CD pipelines and a Git-based synchronization system for sharing request collections and environment configurations across teams. It also incorporates artificial intelligence to automate the conversion of API scripts during migrat