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7 repositorios

Awesome GitHub RepositoriesAgent Deployment Tools

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.

Awesome Agent Deployment Tools GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • significant-gravitas/auto-gptAvatar de Significant-Gravitas

    Significant-Gravitas/Auto-GPT

    184,987Ver en GitHub↗

    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.

    Python
    Ver en GitHub↗184,987
  • mlflow/mlflowAvatar de mlflow

    mlflow/mlflow

    26,554Ver en GitHub↗

    Launches agents using a server that provides automatic request validation and tracing for rapid production deployment.

    Pythonagentopsagentsai
    Ver en GitHub↗26,554
  • nirdiamant/agents-towards-productionAvatar de NirDiamant

    NirDiamant/agents-towards-production

    17,375Ver en GitHub↗

    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.

    Jupyter Notebookagentagent-frameworkagents
    Ver en GitHub↗17,375
  • google/adk-samplesAvatar de google

    google/adk-samples

    8,476Ver en GitHub↗

    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.

    Pythonadkagent-samplesagents
    Ver en GitHub↗8,476
  • chaosblade-io/chaosbladeAvatar de chaosblade-io

    chaosblade-io/chaosblade

    6,355Ver en GitHub↗

    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.

    Pythonalibabachaos-engineeringchaos-testing
    Ver en GitHub↗6,355
  • coleam00/ottomator-agentsAvatar de coleam00

    coleam00/ottomator-agents

    5,359Ver en GitHub↗

    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.

    Python
    Ver en GitHub↗5,359
  • futantan/opengptAvatar de futantan

    futantan/OpenGpt

    3,902Ver en GitHub↗

    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.

    TypeScript
    Ver en GitHub↗3,902
  1. Home
  2. Artificial Intelligence & ML
  3. Agent Deployment Tools

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  • Chaos Engineering Agent DeploymentsDeploys chaos engineering agents and tools onto hosts or Kubernetes clusters without manual setup. **Distinct from Agent Deployment Tools:** Distinct from Agent Deployment Tools: focuses on chaos engineering agents specifically, not general AI agent deployment.