Build stateful agents that manage their own memory and continue working across long-running interactions.
MemoryNanobot
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
Persistent context and long-running agents
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Nanobotv0.3.5
From the release notes
🐈 nanobot v0.3.5 brings the workbench to the terminal — and makes conversations easier to continue across the browser, terminal, and chat apps. The headline is one agent, more places to work. Run nanobot for the native terminal client or nanobot webui for the browser. Both use the same gateway and saved WebSocket conversations. Terminal sessions can be resumed, forked, inspected, and detached without building a separate agent runtime. The browser workbench has grown around real multitasking: grouped conversation panes, temporary chats, persistent sidebar ordering, session mentions, a skills marketplace, portable Agent Plugins, and browser OAuth for remote MCP servers. Automations now have task and calendar views, clearer scheduling controls, and per-run replies. Mobile composition, settings, context charts, app logos, and branded mentions received another round of focused polish. The other story is continuity you can inspect. Context usage and compaction are visible, interrupted work has clearer recovery controls, and session history is more durable across pagination, reconnects, and upgrades. This release also tightens attachment, process, workspace, and email-authentication boundaries. Please read the upgrade notes before replacing an existing installation. Highlights A native terminal workbench — Start with nanobot, switch sessions, paste supported clipboard images, complete app and skill references, inspect context and file diffs, queue follow-ups, and use /detach to leave the gateway running. Browser conversations side by side — Arrange up to four topics in resizable groups, keep sidebar ordering, drag saved sessions into mentions, and use temporary chats when you do not want a persistent topic. Automations that are easier to manage — Switch between task and calendar views, inspect run replies, and adjust schedules with clearer controls. Editing a job preserves pending executions; deleting one no longer leaves navigation blocked. Visible context and steadier long sessions — Per-round token/cache charts, context-compaction progress, paged history search, cumulative summaries, and file-read deduplication scoped to the actual model context. Apps and skills with clearer identities — SkillHub discovery, portable Agent Plugins, remote MCP OAuth and token refresh, visible connection failures, and consistent app logos and brand names in chat. A better small-screen experience — Home-screen installation through PWA support, narrower composer controls, draggable context sheets, touch-friendly chart details, and settings navigation that matches its opening direction. Broader model and search choices — DeepSeek Responses and V4 vision support, Eden AI and OrcaRouter gateways, AnySearch, online OAuth model catalogs, and more resilient provider fallback and Responses-history handling. More reliable channels and runtime boundaries — Rich Telegram streaming, improved Feishu onboarding, safer QQ attachments, trusted email authentication results, o
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