Showing 4 open source projects for "ai code writer"

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  • 1
    GitNexus

    GitNexus

    Zero-Server Code Intelligence Engine

    ...GitNexus includes a built-in Graph RAG agent that helps users explore and understand complex repositories through intelligent navigation and querying. Because the system runs client-side, it emphasizes privacy and portability without requiring backend infrastructure. Overall, GitNexus is designed for developers, code reviewers, and AI tooling builders who need fast, visual codebase comprehension.
    Downloads: 22 This Week
    Last Update:
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  • 2
    XLSX.jl

    XLSX.jl

    Excel file reader and writer for the Julia language

    XLSX.jl is a Julia package to read and write Excel spreadsheet files. Internally, an Excel XLSX file is just a Zip file with a set of XML files inside. The formats for these XML files are described in the Standard ECMA-376. This package follows the EMCA-376 to parse and generate XLSX files.
    Downloads: 9 This Week
    Last Update:
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  • 3
    Excalidraw MCP

    Excalidraw MCP

    Fast and streamable Excalidraw MCP App

    Excalidraw-MCP is an open-source Model Context Protocol (MCP) application and server that connects the visual power of Excalidraw’s hand-drawn diagram editor with AI-driven workflows, enabling agents like Claude, ChatGPT, VS Code, and other MCP-compatible hosts to generate and manipulate diagrams programmatically. Rather than being just a static whiteboard, Excalidraw-MCP serves diagrams in real time using an MCP backend and streams interactive visual output back to the client, letting AI tools create shapes, connectors, text, and entire diagrams as part of conversational or task-based sessions. ...
    Downloads: 9 This Week
    Last Update:
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  • 4
    Data Formulator

    Data Formulator

    Create rich visualizations with AI

    ...To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data transformation barriers via LLMs' code generation ability. However, these systems do not work well for iterative visualization authoring, because they often require analysts to provide, in a single turn, a text-only prompt that fully describes the complex visualization task to be performed, which is unrealistic to both users and models in many cases. ...
    Downloads: 13 This Week
    Last Update:
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