Showing 4 open source projects for "local"

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  • 1
    agentsview

    agentsview

    Local-first session intelligence and analytics for coding agents

    agentsview is a local-first analytics and session browser for developers using AI coding agents. It indexes conversations from tools like Claude Code, Codex, Gemini CLI, Cursor, OpenHands, and many other agent systems. The project lets users browse, search, and analyze coding-agent activity without creating an account or sending session content to a hosted service.
    Downloads: 5 This Week
    Last Update:
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  • 2
    Mods

    Mods

    AI on the command line

    ...The project is useful for summarizing logs, rewriting text, formatting data, generating Markdown, producing JSON, and analyzing command output without leaving the shell. It works well with local LLMs and hosted providers, which gives users flexibility depending on privacy, cost, and performance needs. Mods fits naturally into Unix-style workflows because it can read from standard input and produce output that other commands can continue processing. Its main value is bringing practical AI assistance into everyday terminal automation.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Crush

    Crush

    The glamourous AI CLI coding agent for your favourite terminal 💘

    Crush is a next-generation, terminal-based AI coding assistant developed by Charm, designed to seamlessly integrate with your tools, workflows, and preferred LLMs. It provides developers with an intuitive, session-based experience where multiple contexts can be managed across projects. With flexible model switching, Crush allows you to change providers mid-session while retaining conversation history. It enhances productivity by combining LSP (Language Server Protocol) support with...
    Downloads: 2 This Week
    Last Update:
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  • 4
    Kite

    Kite

    Primary Kite repo, private bits replaced with XXXXXXX

    ...We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs available for running larger jobs and for testing our cloud services. We bundle a lot of pre-computed datasets & machine learning models into the Kite app through the use of a custom filemap & encoding on top of go-bindata. The data, located in kite-go/client/datadeps, is kept in Git-LFS.
    Downloads: 6 This Week
    Last Update:
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