7 repositorios
Utilities for transitioning AI agents from prototypes to production environments.
Distinguishing note: Focuses on the deployment lifecycle of agents specifically.
Explore 7 awesome GitHub repositories matching artificial intelligence & ml · Agent Deployment Tools. Refine with filters or upvote what's useful.
Auto-GPT is an autonomous agent framework that uses large language models to decompose complex goals and execute multi-step tasks without human intervention. It functions as a workflow automation tool that chains language model tasks and manages memory to achieve specific objectives. The project features a visual agent designer that allows users to define behaviors and goals by connecting functional blocks through a graphical interface. It employs a vector database memory system to recall information across different sessions and a sliding-window buffer for immediate short-term context. The
Ships utilities for transitioning autonomous agents from local prototypes to scalable production triggers.
Launches agents using a server that provides automatic request validation and tracing for rapid production deployment.
This project is a comprehensive framework for developing, orchestrating, and deploying autonomous agents. It provides a structured environment for building agents that utilize reasoning loops to perform multi-step tasks, manage state through graph-based workflows, and interact with external tools. By mapping unstructured model outputs into typed schemas, the framework ensures reliable integration with downstream application logic. The platform distinguishes itself through a focus on production-grade reliability and security. It incorporates hybrid memory systems that combine vector embeddings
Provides utilities for transitioning AI agents from development prototypes to scalable production environments.
This project provides a collection of reference implementations, architectural patterns, and SDK samples for building autonomous agents using large language models. It serves as a multi-language framework for implementing and deploying specialized AI agents across diverse programming environments. The system centers on an orchestration framework that combines deterministic code with adaptive reasoning through structured graph workflows. It utilizes schema-driven integration to connect agents with third-party applications and diverse AI models. The development lifecycle is supported by toolki
Implements utilities for transitioning AI agents from initial local prototypes to production environments.
ChaosBlade is an open-source chaos engineering platform that injects faults into applications, containers, Kubernetes clusters, and host systems to test resilience. It functions as a multi-layer fault injection tool, capable of disrupting system resources, Java, C++, NodeJS, and Golang applications, Docker containers, and Kubernetes pods and nodes from a single interface. The platform distinguishes itself through its architecture, which defines chaos experiments as Kubernetes Custom Resource Definitions for native cluster integration, and supports multiple fault injection mechanisms including
Deploys chaos engineering agents and tools onto hosts or Kubernetes clusters without manual setup.
Ottomator-agents is a framework for building and deploying autonomous AI agents using structured workflow files and source code. It serves as a declarative deployment tool and workflow orchestrator that translates static configuration files into executable sequences of AI agent tasks and logic flows. The system utilizes manifest-driven instantiation and template-driven deployment to create functional agent identities by populating source code templates with user-specified parameters. It incorporates a modular skill system that equips agents with discrete, reusable source code units and toolse
Provides utilities for instantiating and transitioning AI agents from prototypes to functional deployments.
OpenGpt is an agent orchestration platform and multimodal interface designed for building and deploying specialized AI personas. It allows users to create task-oriented agents with custom system prompts and behavioral constraints to automate professional, creative, and technical workflows. The project features a prompt engineering workflow that transforms simple user inputs into structured instructions to improve model accuracy. It integrates retrieval-augmented generation by connecting vector databases to the chat interface, enabling context-aware responses from private datasets. The platfo
Provides utilities for transitioning AI agents from prototypes to production environments for specialized tasks.