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Open Source Julia Agentic AI Tools for Linux

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Julia Agentic AI Tools for Linux

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Browse free open source Julia Agentic AI Tools for Linux and projects below. Use the toggles on the left to filter open source Julia Agentic AI Tools for Linux by OS, license, language, programming language, and project status.

  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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  • PeerGFS PEER Software - File Sharing and Collaboration Icon
    PeerGFS PEER Software - File Sharing and Collaboration

    One Solution to Simplify File Management and Orchestration Across Edge, Data Center, and Cloud Storage

    PeerGFS is a software-only solution developed to solve file management/file replication challenges in multi-site, multi-platform, and hybrid multi-cloud environments.
    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
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