Showing 4 open source projects for "memory"

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  • 1
    Letta Code

    Letta Code

    The memory-first coding agent

    Letta Code is a memory-first CLI coding agent built on the Letta platform that offers developers a persistent AI assistant capable of learning and improving over time rather than resetting state each session, giving agents a sense of continuity and context across coding tasks. 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. ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    ByteRover CLI

    ByteRover CLI

    The portable memory layer for autonomous coding agents

    ...ByteRover is useful when agents need persistent context instead of starting from scratch every time they enter a project. Its main value is making agent memory more structured, shareable, and practical across teams, tools, and long-running development workflows.
    Downloads: 2 This Week
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  • 3
    DeepSeek-Reasonix

    DeepSeek-Reasonix

    DeepSeek-native AI coding agent for your terminal

    ...Reasonix includes a coding mode with filesystem and shell tools, a lighter chat mode, one-shot task execution, health checks, session utilities, and project-scoped memory. It supports reviewed SEARCH/REPLACE edits, plan mode, MCP servers, web search, hooks, skills, semantic indexing, transcript replay, event logs, and cost or cache tracking. The project is especially useful for developers who want an open, terminal-first coding agent optimized for DeepSeek’s cache mechanics. It also includes a prerelease desktop client for users who prefer a GUI over the same agent loop.
    Downloads: 44 This Week
    Last Update:
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  • 4
    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. LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. ...
    Downloads: 3 This Week
    Last Update:
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