[go: up one dir, main page]

R AI Agents for Windows

View 102 business solutions

Browse free open source R AI Agents for Windows and projects below. Use the toggles on the left to filter open source R AI Agents for Windows by OS, license, language, programming language, and project status.

  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • JS7 JobScheduler is an open source workload automation solution. Icon
    JS7 JobScheduler is an open source workload automation solution.

    JS7 offers cross-platform job execution, managed file transfer, complex no-code job dependencies and a real REST API.

    JS7 JobScheduler is an open source workload automation solution. It is used to run executable files, shell scripts etc. and database procedures.
    Learn More
  • 1
    AI-Agent-Host

    AI-Agent-Host

    The AI Agent Host is a module-based development environment.

    The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI Agent Host is built specifically for LangChain, a framework dedicated to developing applications powered by language models. LangChain recognizes that the most powerful and distinctive applications go beyond simply utilizing a language model and strive to be data-aware and agentic. Being data-aware involves connecting a language model to other sources of data, enabling a comprehensive understanding and analysis of information.
    Downloads: 1 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next