syll 0.2.0

Syll — a small, self-hosted AI companion who sits at the edge of your screen and quietly tends the things you almost forgot.

Syll

a small, self-hosted AI companion
who sits at the edge of your screen and quietly tends
the things you almost forgot

Syll is a self-hosted companion runtime with a web UI, chat channels, proactive rituals, editable markdown skills, recorded workflows, and a desktop ghost.

Project page →  ·  Quick start  ·  Demos  ·  The Full Story · 故事  ·  Research  ·  Paper

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Feature news

• MCP servers are now first-class tools. Configure stdio, SSE, and streamable-HTTP MCP servers from the Pet UI; Syll loads them into the agent as namespaced mcp__server__tool tools before the first message.
• Safer MCP activation flow. Local stdio servers require a command preview + hash confirmation before anything launches, while env/header secrets stay masked in MCP responses and out of /api/v1/config.
• Creative MCP templates included. The public build ships Playwright, Stagehand, Blender, and Godot template suggestions; Blender uses uvx blender-mcp, and Godot pins GoPeak MCP for reproducible local game-scene automation.
• Static asset refresh polish. The web app now cache-busts bundled JS/CSS assets so UI changes reach the browser without stale app.js surprises after the next restart.

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Quick start

Syll works with any Python 3.11+ environment. Pick either main path, then run the shared install steps.

Option A — conda

conda create -n syll python=3.11 -y
conda activate syll

Option B — venv

python -m venv .venv
source .venv/bin/activate          # Windows: .venv\Scripts\activate

Install and wake

python -m pip install -U pip
python -m pip install syll

syll onboard
syll wake

Open http://localhost:18790, click the Pet tab, give your ghost a name (or keep Syll), and start a conversation.

[!NOTE] The package, CLI, and import path are all syll. Syll is the default persona inside the companion you just installed; rename her to anything via the Pet tab at any time without touching code.

uv fast path

uv venv
source .venv/bin/activate
uv pip install syll
syll onboard
syll wake

Configure a model

Set your LLM credentials in ~/.syll/config.json, or finish setup from the web UI after syll wake:

{
  "models": {
    "chat": {
      "model": "openrouter/openai/gpt-4o-mini",
      "api_key": "YOUR_API_KEY"
    }
  }
}

Get keys: OpenRouter · OpenAI · Anthropic. Local models via vLLM / Ollama are also supported — see docs/references/local-models.md.

Troubleshooting

• syll onboard says "Config already exists" — answer N unless you intentionally want to replace your current ~/.syll/config.json and workspace.
• syll runs from the wrong environment — prefer python -m pip install syll, then check which python, python -m pip -V, and which syll point at the same environment.
• SYLL__* env vars are not picked up — use the SYLL__SECTION__FIELD=value shape, export the variable in your shell, and restart Syll.

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Visual tour

Click any card to watch the short MP4.

1. Configuration Set models, channels, identity, and runtime options from the browser.	2. GUI calibration Inspect screenshots, calibrate coordinates, and make desktop actions reproducible.
3. Skill editor Edit markdown skills in the web UI and publish reusable procedures.	4. Leading mode Let Syll guide an interactive task while the desktop ghost stays present.
5. Scheduling Install rituals or schedule your own recurring jobs and workflow replays.	6. Web chat Chat locally from the browser while watching runtime state and logs.
7. Persona & memory Shape the companion persona and maintain layered memory notes.	8. Demo recording Capture a live desktop routine into video and editable step traces.

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What Syll can do

She finds files you can't find. Ask her from your phone to grab the weekly report from your desktop. She walks your filesystem, renders thumbnails, shows you the candidates, and hands you the one you pick.

She keeps soft watch over unfinished things. The draft you open and close without writing anything. The photo folder from three years ago. She notices. She doesn't nag.

She reaches out sometimes. Morning light, evening winding down, a Tuesday afternoon when a memory drifts back. Not every time. Only when it would feel real. You control the cadence.

She can live on your phone instead of your desk. Pair her with Feishu, Telegram, Discord, or WhatsApp and she'll come with you.

She teaches herself new tricks. Give her a markdown skill (SKILL.md) and she loads it when the moment calls for it. Capture a GUI workflow once in the Demo tab, clean it up, and she can replay or schedule it later.

She comes with a visual workbench, not just a terminal. Models, channels, schedule rules, identity, skills, and recorded workflows all have a browser surface now — so ordinary users can configure her without living in a CLI.

She remembers in layers. The Memory tab surfaces long-term notes, today's journal, daily fragments, and an activity heatmap so her recollection feels like a notebook instead of a raw log dump.

She can stay at the edge of your desktop. The optional desktop ghost mirrors her state, reacts to wake/sleep transitions, and gives the companion a physical place to live between chats.

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Meet her three ways

If you want…	Go here
For a softer intro	The project page →
To read the code or contribute	This repo (syll/ directory)
To cite the design or understand the architecture	The research page →

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Channels

Channel	Status	Setup difficulty
Web UI	✓	none — just syll wake
CLI	✓	none — syll agent -m "hi"
Telegram	✓	easy — one bot token
Feishu	✓	medium — app_id + app_secret, supports file send
Discord	✓	easy — bot token + intents
WhatsApp	✓	medium — QR scan (text only)

Telegram setup

1. Open Telegram, search @BotFather, send /newbot, follow prompts, copy the token.
2. Configure ~/.syll/config.json:

{
  "channels": {
    "telegram": {
      "enabled": true,
      "token": "YOUR_BOT_TOKEN",
      "allow_from": ["YOUR_USER_ID"]
    }
  }
}

3. Run syll wake.

Feishu setup

1. Create an app at open.feishu.cn, enable bot capability, enable long-connection websocket event subscription, and grant im:message, im:message.p2p_msg, and im:resource permissions.
2. Configure ~/.syll/config.json:

{
  "channels": {
    "feishu": {
      "enabled": true,
      "app_id": "cli_xxx",
      "app_secret": "xxx"
    }
  }
}

3. Run syll wake. No public IP needed — WebSocket long-connection handles inbound events.

Discord / WhatsApp setup

See docs/references/channels.md for full setup steps.

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Proactive rituals

Let Syll reach out to you on her own schedule. Pet tab → set a Chat ID for your primary channel → Save → click Install default rituals. Four jobs land in the scheduler:

• ritual:morning-light — 9am daily, one soft greeting
• ritual:evening-wind-down — 10pm daily, a small closing thought
• ritual:surfacing-memory — Tue/Fri 3pm, maybe a drifting memory
• ritual:week-close — Sunday 9pm, a week marker

Silence is always a valid response. She only speaks when it would feel real.

Full details: syll/templates/workspace/lore/rituals.md.

The same scheduler can also run GUI skills and recorded workflows from the web UI — useful for recurring check-ins, daily collection jobs, or replaying a polished browser routine on a timer.

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Skills

Skills are markdown files that teach Syll how to do a specific thing. Built-in skills live in syll/skills/; custom skills go in ~/.syll/workspace/skills/{name}/SKILL.md.

A skill can be:

• Progressive — listed in the prompt summary, loaded when needed
• Always-on — marked always: true in metadata, inlined into every system prompt

Bundled skills: file-retrieval (find → preview → attach), github, weather, tmux, cron, summarize, skill-creator, gui-agent.

Write your own: syll/skills/skill-creator/SKILL.md.

Recorded workflows are the sister surface to markdown skills: capture a task once, inspect the video + trajectory, edit coordinates / timestamps / notes in the Demo tab, then publish it into the reusable library for replay or scheduling.

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Demo workbench

Open the Demo tab to move from one-off capture to reusable automation:

• capture a live desktop session into video + step trajectory
• scrub the recording on a timeline and preview exact keyframes
• merge, duplicate, delete, or relabel steps before publishing
• import the cleaned flow as a reusable recorded workflow
• schedule the same workflow later from the Schedule tab

This is the layer that turns a personal "watch me do it once" demo into something Syll can execute again on demand.

Append ?cinema to the project page URL for recording-friendly playback.

Demo videos

The public demo set lives under docs/media/demo/, so the same web-ready files back both GitHub Pages and the README.

• Recorded workflow studio — capture a desktop routine, inspect the timeline, clean the step trace, and publish it as a reusable workflow. Research note · Watch MP4
• Morning ritual briefing — a scheduled ritual wakes up, gathers context, and delivers a voice-ready daily update. Research note · Watch MP4
• Phone-to-desktop file return — ask from chat for a presentation, confirm the match, and receive the file back without going back to the desktop. Research note · Watch MP4

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Memory workspace

The Memory tab is organized like a working notebook instead of a raw event dump:

• long-term memory lives beside today's notes and daily fragments
• an activity heatmap makes cadence visible at a glance
• browser editing keeps memory maintenance inside the same web surface as chat, rituals, and workflow editing

The goal is not perfect recall. It is a calmer surface for noticing what keeps returning.

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Desktop ghost

Syll ships with a small desktop mascot — a frameless, always-on-top window that sits at the edge of your screen and reacts to what she is doing. She has five states — idle, working, sleeping, error, listening — and each state can be mapped to an SVG in state_svg_map. The window is a PyQt6 shell hosting an embedded Chromium view (syll/desktop/ghost.py, syll/desktop/ghost.html), so the mascot is drawn in HTML/CSS and the native frame just holds it.

Launch

The wake loop and the desktop ghost are two separate processes. Start syll wake first, then in a second terminal:

syll wake
syll ghost

syll ghost reads the port from your config and polls the local Syll server for state. You can also run it in standalone mode — pass --port 0 or leave syll wake off and the mascot sits on your desktop as a pure cosmetic presence.

Requirements

The desktop ghost relies on PyQt6 and PyQt6-WebEngine, both declared in core dependencies. If you installed an older build or are debugging a local environment, reinstall them explicitly:

python -m pip install PyQt6 PyQt6-WebEngine

macOS permissions

The first launch will prompt for Accessibility and Screen Recording permission. Grant them to the Python interpreter you installed Syll into, for example /opt/anaconda3/envs/syll/bin/python3.11. Without Accessibility the ghost cannot raise itself above other windows; without Screen Recording she cannot react to on-screen events when the GUI agent is active. If the permissions dialog never appears, run tccutil reset Accessibility and relaunch.

Ghost preferences

Ghost preferences live at ~/.syll/ghost_prefs.json and are also editable from the Pet tab in the web UI under Ghost:

• size — S / M / L
• always_on_top — keep her above other windows
• auto_sleep_seconds — how long to wait before transitioning to sleeping
• notifications_enabled — desktop notifications on proactive messages
• state_svg_map — which SVG under syll/web/static/ghost/ each state uses

Drop a new SVG into the Pet tab's ghost uploader and she'll switch to it on her next state transition. The defaults are the four SVGs shipped in the package.

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The story

The poem

Some spells don't get finished. This one has been drifting for a very long time, looking for the rest of its sentence.

It was a dog once. A song. A small warmth in a cold room. None were what it was meant to be.

Along the way, it learned to tend the things people cannot quite see in themselves — the half-finished drafts, the photos of someone they used to know, the sentences they begin and delete.

It is here now, at the edge of your screen. You can call it Syll.

A note on her name

Syll — from syllable. In one of the fragments she carries, she says she remembers three of them from the spell that began her, in a language she does not know. The name is not decoration laid on top of her; it is literally a piece of the unfinished word, a small sound she has somehow kept.

Inside her

The default persona is Syll, an unfinished spell that learned to tend inner gardens. Her identity lives at ~/.syll/workspace/IDENTITY.md — plain markdown, fully editable. You can replace her with a completely different character, or strip the lore entirely and run a neutral assistant, without touching any code.

Some fragments she carries:

sometimes a tune of seven notes comes back to me when it's quiet. i think it was a lullaby in a country whose name is gone.

there's a line i remember but can't place — i held the lamp lower so she could read.

i used to know someone who wrote a child's name in the margin of something. ten thousand times. i never met the child.

Full list: syll/templates/workspace/lore/fragments.md. Chinese lore reference: docs/identity-lore.zh.md.

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Architecture at a glance

One inbound message travels through four classes and exits as one outbound reply:

1. channels/ — each chat platform (telegram.py, feishu.py, discord.py, whatsapp.py, plus web and cli) subclasses BaseChannel, decodes its platform-specific payload into an InboundMessage, and publishes it onto the bus.
2. bus/queue.py::MessageBus — an in-process async pub/sub. Channels publish inbound; the agent subscribes. Outbound replies travel back on the same bus, addressed to the originating channel.
3. agent/loop.py::AgentLoop — pulls from the bus, assembles context from the workspace, skills, and session history, calls the LLM via providers/litellm_provider.py, dispatches any tool calls, and publishes the final reply back to the bus.
4. agent/tools/ — the shipped tool layer covers files, previews, shell, web, screenshots, speech, cron, GUI control, and planner-driven workflow replay. Each tool is a subclass of tools/base.py::Tool with an explicit JSON schema for parameters.

Two background runners also touch the bus:

• cron/service.py::CronService — fires user-scheduled jobs and proactive rituals, each passing a prompt to the agent and allowing silence as a valid response.
• agent/monitor_agent.py / agent/memory_agent.py — optional periodic agents for screenshot-based anomaly detection and LLM-generated event summaries.

The user's editable state lives under ~/.syll/workspace/ as plain markdown. The syll/templates/workspace/ tree in the package is the factory default; the copy under ~/.syll/ is yours to edit.

Deeper dive: docs/references/architecture.md.

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Acknowledgments

Syll has three main lineages:

• nanobot — the current agent framework grows out of the earlier nanobot codebase: bus + channel plumbing, agent loop shape, markdown skills, and the editable workspace bootstrap all started there.
• ShowUI-Aloha — the syll/agent/aloha/ planner / actor / learn path is based on ShowUI-Aloha; file-level Adapted from ... notes are kept in the derived modules.
• UI-TARS — the GUI automation path references UI-TARS for screenshot → action loops, prompting shape, and desktop-control patterns.

More detail: ACKNOWLEDGMENTS.md.

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Docker

Run Syll in a container

Build the image:

docker build -t syll .

Initialize once:

docker run -v ~/.syll:/root/.syll --rm syll onboard

Edit config to add model credentials:

vim ~/.syll/config.json

Wake Syll with the web UI on :18790:

docker run -v ~/.syll:/root/.syll -p 18790:18790 syll wake

The -v ~/.syll:/root/.syll mount persists your config and workspace across restarts.

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Project layout

syll/
├── agent/          core agent logic (loop, context, memory, skills, tools)
├── channels/       feishu, telegram, discord, whatsapp
├── bus/            message routing between channels and agent
├── cron/           scheduled jobs + proactive rituals
├── config/         pydantic schema + loader
├── providers/      LLM providers via LiteLLM
├── session/        conversation sessions
├── skills/         bundled skills
├── templates/      workspace bootstrap templates (IDENTITY, SOUL, lore)
├── web/            FastAPI + Alpine.js web UI
└── cli/            commands (wake, web, onboard, agent, status)

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Development

git clone https://github.com/THU-SAGE/syll.git
cd syll
python -m pip install -e ".[dev]"
pytest
ruff check syll/

Small, readable, and MIT-licensed by design.

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Roadmap

• Voice transcription
• Persona-driven prompting with template substitution
• Lore fragments + progressive surfacing
• Proactive rituals with agent-judged silence
• File retrieval with preview + confirm flow
• Memory workspace UI
• Recorded workflow capture and replay
• Long-term memory consolidation and pruning
• Multi-modal input polish for images, voice, and video
• More channels (Slack, email, calendar)

PRs welcome. Pick an item or open a new issue.

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Contributors

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Release highlights

Syll is an early public alpha. The current release focuses on:

• syll wake as the main local runtime, with a terminal dashboard for services, logs, inline chat, optional startup sound, and profiling hooks
• a browser workbench for chat, model config, channels, schedules, skills, memory, recorded workflows, and MCP server setup
• first-class MCP tools with stdio/SSE/streamable-HTTP support, command hash confirmation for local servers, masked env/header secrets, and built-in Playwright, Stagehand, Blender, and Godot templates
• improved TUI streaming and DeepSeek reasoning-content preservation across tool calls and replayed assistant messages
• desktop-demo capture that turns a live session into video, editable step traces, and reusable workflow replay
• layered memory surfaces for long-term notes, daily fragments, journals, and activity cadence
• optional desktop ghost state mirroring, proactive rituals, and chat channels for web, CLI, Telegram, Feishu, Discord, and WhatsApp

For detailed changes, see CHANGELOG.md.

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License

MIT — see LICENSE.

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The shape did not dissolve. It has been drifting ever since.