Showing 4 open source projects for "structure"

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    Qwen Code

    Qwen Code

    Qwen Code is a coding agent that lives in the digital world

    Qwen Code is a command-line AI workflow tool designed to enhance developer productivity by leveraging the power of Qwen3-Coder models. Adapted from the Google Gemini CLI, it features an enhanced parser optimized specifically for Qwen-Coder models, enabling deep code understanding and manipulation. The tool supports querying and editing large codebases beyond traditional context limits, making it ideal for modern, complex projects. Qwen Code automates various development workflows, including...
    Downloads: 20 This Week
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  • 2
    LazyCodex

    LazyCodex

    The one and only agent harness for complex codebases

    LazyCodex is an agent harness for using Codex on complex software projects. It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced.
    Downloads: 2 This Week
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  • 3
    Letta Code

    Letta Code

    The memory-first coding agent

    ...Unlike traditional session-based coding tools, Letta Code attaches a long-lived agent to a working directory so that the agent accumulates memory about a project’s structure, preferences, and history, effectively acting as a collaborative partner rather than a stateless helper. Users can initialize and connect the agent to various models, including popular large language models, and issue commands, refactor code, or ask context-aware questions directly in the terminal, with memory retained across multiple interactions.
    Downloads: 2 This Week
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  • 4
    AutoBE

    AutoBE

    AI Vibe Coding Agent of TS backend server

    AutoBE is an AI backend builder that turns natural-language requirements into a working TypeScript backend application. It analyzes what the user wants, creates specifications, designs database structure, defines API documentation, writes end-to-end tests, and generates implementation logic. The project is aimed at moving from prototype to production more quickly while keeping generated code buildable and verifiable. It uses an agentic workflow supported by compiler-friendly checks and test generation, which helps reduce the risk of incomplete AI output. ...
    Downloads: 1 This Week
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