Showing 3 open source projects for "simple chat"

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  • 1
    NanoClaw

    NanoClaw

    A lightweight alternative to Clawdbot / OpenClaw

    ...It runs agent execution inside Apple containers to provide strong isolation boundaries, so individual chats and actions can be sandboxed with tighter filesystem and process separation than a typical single-process bot. The project connects directly to WhatsApp, letting you deploy an assistant that can chat in a familiar interface while still supporting real agent behaviors instead of simple call-and-response prompts. It includes memory so the assistant can retain important context across interactions, enabling more consistent follow-through on ongoing tasks. It also supports scheduled jobs, making it suitable for recurring reminders, periodic automations, and timed workflows without needing an external orchestrator.
    Downloads: 47 This Week
    Last Update:
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  • 2
    nanobot

    nanobot

    🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw

    nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to...
    Downloads: 3 This Week
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  • 3
    Build Your Own OpenClaw

    Build Your Own OpenClaw

    A step-by-step guide to build your own AI agent

    Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. ...
    Downloads: 0 This Week
    Last Update:
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