Configuration

VibeBot uses Limnoria's registry for all configuration. See the Limnoria configuration documentation for how the registry works in general.

Set values from IRC with:

@config plugins.LLM.<settingName> <value>

View a current value by omitting the value. Channel-overridable settings also accept a per-channel form:

@config channel #channel plugins.LLM.<settingName> <value>

Scope in the tables below means: channel settings accept per-channel overrides; global settings apply everywhere.

A new default in a release does not change a running bot

Limnoria writes the whole registry to bot.conf when the bot shuts down, so every setting the bot has ever loaded exists there as an explicit line. That line wins over the default shipped in a later release.

So when an upgrade changes a Default in the tables below, the new value applies to fresh installs only. An existing deployment keeps whatever was persisted, silently and with no error — the feature simply behaves as it did before.

To adopt a new default, set it explicitly with @config (which writes through the registry), or stop the bot, edit bot.conf, and start it again. Editing bot.conf while the bot runs does not work: the next shutdown flush overwrites it.

Verify by reading back the value with @config plugins.LLM.<settingName> — a green deploy and a quiet log do not prove the new value took effect.

API keys

API keys are not part of the Limnoria registry. They come from environment variables, one per provider, read at the point each provider call is made and selected by the provider of the model being called — not by which command or channel triggered the call. The old assistantApiKey / codeApiKey / imageApiKey / searchApiKey registry settings were removed, not deprecated: @config on them now errors.

Variable	Provider
XAI_API_KEY	xAI (Grok)
GEMINI_API_KEY	Google Gemini
OPENAI_API_KEY	OpenAI
ANTHROPIC_API_KEY	Anthropic (Claude)

Any other provider LiteLLM recognises — vertex_ai, openrouter, azure, bedrock, and so on — resolves to no key from this plugin, so LiteLLM falls back to that provider's own native credentials: Application Default Credentials, IAM, or its own environment variables. With the defaults, a fresh install needs ANTHROPIC_API_KEY for chat and @code, XAI_API_KEY for search and @draw (the default imageModel is xai/grok-imagine-image).

Running on local models

A local server (Ollama, vLLM, LM Studio) takes no key from this plugin. Set its address in the env file and pick models with the matching LiteLLM prefix:

Server	Env variable	Model prefix
Ollama	OLLAMA_API_BASE=http://host:11434	ollama_chat/<model>
vLLM	HOSTED_VLLM_API_BASE=http://host:8000/v1	hosted_vllm/<model>
LM Studio	LM_STUDIO_API_BASE=http://host:1234/v1	lm_studio/<model>

@config channel #chan supybot.plugins.LLM.assistantModel ollama_chat/qwen3:14b

Don't use openai/<model> with OPENAI_API_BASE for a local server. That redirects every OpenAI call in the bot and sends OPENAI_API_KEY to your box.

The chat path calls tools, so the local model must support function calling. Each role has its own model setting (assistantModel, searchModel, codeModel, memoryModel, verseModel and the rest under Model selection). Any role left on a hosted provider still sends its requests there. That matters when you turn off privacyOptInOnly: keep every model a channel uses local, or overheard lines can still reach a hosted provider.

Opting in to Vertex AI

Vertex AI is not the default, but it remains a supported imageModel (and general model) choice for anyone who wants it — for example to bill image generation to a separate GCP project. Credentials (ADC, IAM) are enough for authentication, but LiteLLM's Vertex Imagen path separately requires the project and region, and it fails closed with vertex_project and vertex_location are required for Vertex AI if they are missing:

Variable	Required	Notes
VERTEXAI_PROJECT	Yes	Your GCP project ID
VERTEXAI_LOCATION	Yes	Region, e.g. us-central1. VERTEX_LOCATION also works as a fallback name

Vertex AI takes no bearer key from this plugin — no VERTEX_AI_API_KEY exists; it authenticates through ADC and IAM only.

Drawing against a self-hosted endpoint

imageApiBase points @draw at any OpenAI-shaped /v1/images/generations endpoint — including the same box @animate uses, which serves images as well as video. Set it and three things change: the request carries an api_base, it authenticates with ANIMATE_API_KEY instead of the provider key imageModel's name would imply, and imageSteps/imageSize ride along in the request body. Leave it empty and nothing changes; the hosted provider path is untouched.

@config channel #chan supybot.plugins.LLM.imageApiBase http://host:port/v1
@config channel #chan supybot.plugins.LLM.imageModel openai//path/to/model
@config channel #chan supybot.plugins.LLM.imageSteps 8
@config channel #chan supybot.plugins.LLM.imageSize 1024x576

The openai/ prefix tells LiteLLM which wire format to speak; everything after it is the model name your server expects, which is why a filesystem path with slashes in it is fine.

Two things to weigh before switching a busy channel over:

• Steps are the whole latency budget. Measured against the reference box at 1024x576 on an idle server: 8 steps ≈ 32 seconds, 25 steps ≈ 94 seconds. Compare a hosted provider answering in a few seconds. Raise drawTimeout (default 120) to cover whatever you pick, or draws will fall into the stash-and-deliver-later path.
• A busy box is much slower than an idle one. That server runs jobs concurrently rather than queueing, so a draw submitted while clips are rendering can take well over twice as long, and every other job on the box slows down too.

Spend is recorded as $0.00, which is accurate for your own hardware — and unlike an unpriced hosted model, it does not log the "no price in IMAGE_COST_PER_IMAGE" warning, so that warning still means what it says.

Falling back when a provider refuses

The same endpoint can sit behind a hosted provider instead of replacing it. Set imageFallbackApiBase and a refusal on content grounds is redrawn against your own box rather than reaching the user as an error:

@config channel #chan supybot.plugins.LLM.imageFallbackApiBase http://host:port/v1
@config channel #chan supybot.plugins.LLM.imageFallbackModel openai//path/to/model
@config channel #chan supybot.plugins.LLM.imageFallbackSteps 8
@config channel #chan supybot.plugins.LLM.imageFallbackSize 1024x576

The fallback is sent the original prompt, never a safety rewrite. A rewrite exists to talk a filter around, and an endpoint with no filter has nothing to be talked around — so the picture that arrives is the one that was asked for, and it carries no 🔁 marker because nothing was reworded.

This interacts with drawAutoRewriteMax (default 1), and the two orderings buy different things:

drawAutoRewriteMax	What a refused prompt does
1 (default)	Rewrites once and redraws on the provider. If that is refused too, the fallback draws the original. Fast when it works, but the user gets a softened version of their request, and the rewrite costs a second billed call
0	Skips rewriting and goes straight to the fallback. Slower per refusal (a self-hosted draw is tens of seconds), free, and faithful to what was asked

Refusals are still recorded either way. A recovered draw carries its blocked_attempts through to the usage table, so the refusal rate stays measurable, and the fallback logs image_fallback_served at WARNING so you can count how often it earns its keep.

If the fallback also fails — refused again, misconfigured, or the box is down — the user gets the original refusal message. Which of two backends disappointed them is not something they asked about.

Video generation

@animate talks to a self-hosted vLLM video server rather than a LiteLLM provider, so it needs both halves of its own credential and stays off until it has them:

Setting	Where	Notes
ANIMATE_API_KEY	Environment	Bearer token for the video server. Covered by log redaction like every other *_API_KEY
animateApiUrl	Registry	Base URL, e.g. http://videohost:14205 — no trailing /v1. Empty (the default) disables @animate and hides the generate_video tool

With either half missing the command returns a configuration error and the tool never reaches the model, so it cannot promise a clip the bot has no way to render.

@animate never sends the words the user typed. A planner turn rewrites the ask into a script the video server can render, so the usage row records both: prompt holds the request and rendered_prompt holds what was submitted. Every other command leaves rendered_prompt empty. Rows written before this landed have it empty too — the rendered wording was only ever held in pending_tasks, which is cleared as each clip is delivered.

Copy .env.example to ~/.config/vibebot/env and set the variables there; the systemd unit passes that file to the container with --env-file (see Installation). A model whose provider has no key configured fails with an error naming the missing variable, for example no API key configured for provider 'xai' (set XAI_API_KEY).

Model selection

Models follow LiteLLM's provider/model format. Model names are validated against LiteLLM's known providers; the bot rejects unrecognised names and suggests alternatives.

Setting	Scope	Default	Description
assistantModel	channel	anthropic/claude-haiku-5-5	All assistant text and tool work: chat, planner, memory, reminders, scheduled tasks. Needs vision support if users paste image URLs
refusalFallbackModel	channel	xai/grok-4-1-fast-non-reasoning	Re-runs a chat turn once when its model refuses: a policy refusal that survives its one retry, or a provider refusal error. The fallback gets the original request without the refusal. Empty turns it off. Skipped when the turn already runs on this model, when its provider has no key, or when a tool that changes something (a reminder, an image, a memory) already worked this turn, since the re-run would repeat it. Its cost books at xai/grok-4.3 rates, the model behind the alias
codeModel	channel	anthropic/claude-haiku-5-5	The code-generation one-shot behind @code and the generate_code tool. The @code planner loop itself runs on assistantModel
imageModel	channel	xai/grok-imagine-image	Model for @draw
imageApiBase	channel	empty	Draw against an OpenAI-shaped endpoint of your own instead of the provider imageModel names — see Drawing against a self-hosted endpoint
imageSteps	channel	0	Denoising steps for a self-hosted endpoint. 0 lets the server choose. Ignored unless imageApiBase is set
imageSize	channel	empty	Output geometry as WxH for a self-hosted endpoint. Ignored unless imageApiBase is set
imageFallbackApiBase	channel	empty	Endpoint to redraw against when the primary provider refuses a prompt — see Falling back when a provider refuses
imageFallbackModel	channel	empty	Model for imageFallbackApiBase. A plain string, not a validated model name
imageFallbackSteps	channel	0	Denoising steps for the fallback endpoint
imageFallbackSize	channel	empty	Output geometry as WxH for the fallback endpoint
searchModel	channel	xai/grok-4.3	Model for web search and URL fetch. Falls back to assistantModel. Only xAI and Gemini models search; any other provider answers from its own knowledge. GitHub links skip it: they are read through GitHub's API. A request can run at most three searches
memoryModel	channel	empty	Model for the memory extraction that runs after every reply. Falls back to assistantModel. A flash-lite class model is enough
subjectResearchEnabled	channel	True	Research the real people, places and events a @draw or @animate request names before the planner writes the prompt — see Subject research
subjectResearchModel	channel	empty	Model for the subject-research pre-stage. Falls back to searchModel, then assistantModel
verseModel	channel	empty	Model for verse-mode replies. Falls back to assistantModel. Set this when the assistant model is a terse reasoning model that writes poor prose
verseCompactionModel	global	anthropic/claude-haiku-5-5	Cheap model for the daily verse compaction job. Unlike the channel model keys this one is a plain string, so a misspelled model name is accepted at @config time and only fails when the nightly job runs

Channel overrides let different channels run different models:

@config channel #dev plugins.LLM.assistantModel anthropic/claude-sonnet-4-20250514
@config channel #casual plugins.LLM.assistantModel anthropic/claude-haiku-5-5

Subject research

Image and video generators know nothing by name. @animate renders a bare "Churchill" as nothing at all, or as the word printed across the frame, and @draw is little better — which is why both commands run a planner turn that rewrites the request before the generator ever sees it. The planner is told to keep the name the user typed and put a description of the subject beside it, but for a real person or a real event it has nothing to build that description from: the verse canon block covers characters the channel invented, not people the world already contains.

subjectResearchEnabled (on by default) closes that gap with one grounded completion in front of the planner. It identifies the real subjects the request names, looks up how each actually looks, and layers the answer onto the planner's prompt. A request that names nobody real — "a slow aerial shot over a pine forest" — comes back with nothing and adds nothing to the prompt.

The cost is one extra call and a few seconds. @animate hides that behind a render measured at 135 seconds; @draw does not, so @draw gets visibly slower with this on. The typing indicator covers the wait. The usage table records research costs under the command name dossier, separately from the planner's own row, because the two run on different models.

Only the dash-prefixed fact lines the research prompt asks for are kept, and only those that end in a (source: …) tag. A model that declines the question, or wraps its answer in commentary, contributes nothing rather than contributing its refusal to the next model's prompt. The source tag guards the other failure: asked about a name that exists nowhere, a grounded model guesses an appearance from the words in it rather than answering NONE, and a guess has nothing to cite. The tag is stripped before the line reaches the planner.

subjectResearchModel picks the model. Left empty it falls back to searchModel and then assistantModel, which in most deployments means the researcher is a different provider from the planner. Set it when the search model is more reticent about describing real people than the generator downstream is.

System prompts

System prompts define the bot's personality and constraints. Both are channel-overridable.

Setting	Description
assistantSystemPrompt	Personality and constraints for all assistant work. Verse mode layers scene context on top of this prompt rather than replacing it
codeSystemPrompt	Instructions for @code output format

Both defaults carry constraints worth keeping: assistantSystemPrompt holds replies to one to three lines of plain text with no markdown, and codeSystemPrompt keeps the code body in the tool's URL rather than in the channel. Read the shipped text before you replace it — @config default plugins.LLM.assistantSystemPrompt — because a replacement drops those constraints with it.

Example: give a channel a specialised personality:

@config channel #python plugins.LLM.assistantSystemPrompt You are a Python expert. Answer with Python examples. Be concise.

Verse

The verse is the per-channel world model. See The verse for concepts and operation; this table is the key reference.

Setting	Scope	Default	Description
verseEnabled	channel	False	Main switch. When off, verse commands are unavailable and no events are recorded
verseTriggerRegex	channel	\bverse\b	Case-insensitive pattern that marks a message as a canon reference, alongside entity mentions. A match grounds the reply in canon and, for an avatar holder, turns it into a prose tale. It does not enter roleplay mode; that needs @rp. Empty disables the keyword signal
verseRoleplayStickyTtlSeconds	channel	900	Sliding inactivity timeout for sticky @rp on roleplay. Each in-character turn refreshes it. 0 never expires
verseChatRecordEnabled	channel	False	Let an opted-in avatar's ordinary chat turn call verse_record. Off keeps canon growing only during roleplay
verseEventRetentionDays	channel	30	Events older than this are eligible for compaction. 0 disables compaction for the channel
verseAutoEntityRetireDays	channel	14	Days without a mention before auto-created non-player characters (NPCs) retire. 0 disables the sweep. Pinned entities are exempt
verseAutoEntityMaxNamesPerCall	channel	8	Cap on the actors array in one verse_record call
verseRosterMaxChars	channel	4000	Character cap on the canon-roster block in the verse system prompt
verseStyleExemplars	channel	[]	Curated style exemplars injected into the verse prompt. Populate offline with the taste miner
verseReactionCaptureEnabled	channel	True	Capture IRCv3 emoji reactions to verse lines as an offline approval signal
verseCompactionDailyAt	global	03:00	Local HH:MM time for the daily compaction sweep. Empty falls back to 03:00. A malformed value does not — it defers the next run by an hour, each time, and logs a warning
verseCompactionMinKeepEvents	global	20	Verses with fewer total events are skipped by compaction

Storybook

These caps cover both illustrated-page paths: the verse_storybook tool on verse turns, and the standalone @story command. @story needs no verse — it is gated like @draw, on llm.draw plus an authenticated account — so these limits still bind in a channel where verseEnabled is False. The verse prefix is historical; renaming the keys would orphan existing bot.conf values.

Setting	Scope	Default	Description
verseStorybookEnabled	channel	False	Expose the verse_storybook tool on verse turns. It does not gate @story
verseStorybookMaxImages	channel	5	Cap on illustrations per storybook
verseStorybookMaxPerTurn	channel	1	Cap on storybooks per verse turn. Tool-only; @story does not read it
verseStorybookCooldownSeconds	channel	300	Per-account cooldown between storybooks
verseStorybookDailyImageCap	channel	30	Registered but not yet enforced — there is no per-account daily image count to check it against
verseStorybookMaxChars	channel	6000	Character cap on the storybook body
verseStorybookImageTimeout	channel	45	Seconds to wait for each illustration

Turning verseStorybookEnabled off does not stop image costs on its own, because @story still runs. What bounds them today is verseStorybookMaxImages per page and the per-account cooldown between pages, not the daily cap.

Memory

Setting	Scope	Default	Description
memoryEnabled	channel	True	Enable automatic memory extraction
memoryMaxPerUser	global	50	Cap on durable memories per user
memoryCleanupInterval	global	3	Extraction passes between cleanup runs. 0 disables
memoryPromotionThreshold	global	2	Mentions a candidate fact needs before promotion. 1 restores single-stage saving
memoryCandidateTTLDays	global	14	Days an unreinforced candidate survives. 0 disables pruning

See Memory promotion for how the two-stage pipeline works.

Conversation context

Setting	Scope	Default	Description
contextEnabled	channel	True	Enable conversation context
contextMaxMessages	channel	20	Messages kept in per-user history
contextTimeoutMinutes	channel	5	Clear context after this much inactivity
privacyOptInOnly	channel	True	Send only lines addressed to the bot to the provider. Set False to track every channel message as context and let irc_lookup read the channel's server history (kind=history, up to 100 lines) for "what did I miss". Those lines go to whichever provider serves the channel's models. See Running on local models
channelContextMaxMessages	channel	10	Messages in the shared channel context

Rate limiting

Rate limits follow the pattern {command}{tier}RateLimitCount and {command}{tier}RateLimitWindow for the commands ask, code, draw, story, and animate. All rate-limit settings are global. See Rate limiting and security for tiers, defaults, and the observe-only switch enforceRateLimits.

Bot-to-bot loops

Two bots that answer each other never get bored, so replies to another bot are capped.

Setting	Scope	Default	Description
botLoopReplyLimit	channel	3	Consecutive replies to one bot before the bot goes quiet. 0 disables the guard
botLoopWindow	channel	300	Seconds of quiet after which that bot's count resets
botLoopHostSuffixes	global	Bot.AfterNET.Org	Host suffixes the network reserves for bots. Matched case-insensitively against the sender's host. A sender matched here, or one with the +B mode, cannot address the bot by replying to its lines. A full host works too, for a bot on a user host

A nick counts as a bot only when the network says so, by either of two signals. AfterNET advertises BOT=B and marks flagged users in the WHOX status field, which is where the bot reads it — six nicks carry it today, long-running service bots among them. Anyone unflagged is treated as a person and is never capped, and a human addressing the bot clears the counts in that channel, so a conversation someone has joined is never cut short. Only addressed lines reset it: what people say during a bot loop is commentary on the noise ("wtf", "jesus"), and treating that as a reset would license three more replies after every such line.

The +B mode is opt-in, and the bot most likely to loop with yours may not set it — grok answers on Hxz from grok.Bot.AfterNET.Org. So the sender's host counts too: AfterNET only issues *.Bot.AfterNET.Org to registered bots, and across a full day of channel logs the only nicks on one were grok, grook5, and vibebot itself. The host is checked first because it is free and decides on the very first line, with no WHO round trip.

Because skipAutoWhoOnJoin suppresses the WHO on join, the flag is fetched on demand: the first time an unknown nick addresses the bot, a WHO goes out for that nick and the answer is cached for an hour. That first line is always answered — the guard fails open, so the worst case is one extra reply, never a silenced user. A bot that never sets +B is invisible to this and will not be capped.

Web and HTTP output

Setting	Scope	Default	Description
httpRoot	global	empty	Filesystem path for output files. Empty keeps them under Limnoria's data/web/llm/ and serves them from its built-in HTTP server. Setting it unhooks that server — an external server such as nginx must serve the path, and httpUrlBase must be set to match, or every generated link 404s
httpUrlBase	global	empty	Public base URL for output files. Empty uses Limnoria's publicUrl plus /llm; if publicUrl is also unset the bot falls back to http://localhost:<http port>/llm, which nobody off the host can open
imageUploadUrl	global	empty	External image host for generated images. Empty stores them locally
helpUrl	global	https://rdrake.github.io/vibebot-v8/	URL shown in help output
longReplyTeaserMaxChars	channel	220	Characters in the one-line teaser for long replies saved as HTML
multilineMaxLines	channel	3	Replies that wrap to at most this many IRC lines go inline as one IRCv3 draft/multiline batch instead of a teaser and link. Needs supybot.protocols.irc.experimentalExtensions. 0 turns it off
fileCleanupAge	global	720	Delete output files older than this many hours (30 days)
fileCleanupMax	global	1000	Cap on files kept in the output directory

Offloading images to an external host

Set imageUploadUrl to an uploader that takes a multipart POST on the images[] field and answers with JSON:

{"results": [{"success": true, "filePath": "/img/img_abc123.png"}]}

Generated images then live on that host instead of under httpRoot, and storybook pages embed the absolute URL. Pages themselves (answers, code, stories) still come from your own HTTP server, so this offloads bandwidth rather than replacing it.

Every failure falls back to local storage: endpoint unreachable, upload rejected, image over 10 MB, or a reply naming a URL that is not an image on the configured host. An outage costs a slower draw, nothing more.

paste.boxlabs.uk/img/ is an externally operated uploader, the host this contract follows, and it needs no key. Ask the host's owner before pointing the bot at somebody else's uploader.

Limnoria tool bridge

Setting	Scope	Default	Description
bridgeEnabled	channel	False	Expose loaded Limnoria plugin commands to the LLM as a tool
bridgeAllowedPlugins	channel	empty	Plugin allowlist. Empty uses the curated read-safe default set
bridgeAllowMutating	channel	False	Expose state-changing commands through the bridge
bridgeScheduledTaskLimit	channel	5	Active scheduled LLM tasks per creator per channel. 0 disables scheduling
bridgeDebugInChannel	channel	False	Append a bridge-call debug footer to replies
ircLookupEnabled	channel	True	Advertise the irc_lookup tool (live LIST, NAMES, WHOIS, WHO, topic, network info, CTCP) to chat. Its history kind also needs privacyOptInOnly off. @channels and @names work regardless
memeModel	channel	anthropic/claude-haiku-5-5	Model that picks a template and writes captions when @meme (or make_meme's brief) names no template the catalog knows. It opens on a short list (the 40 most popular templates plus up to 20 sharing a word with the request, about 5K prompt tokens) and can call a search_templates tool up to twice to reach the rest of the catalog. No search: one call, about 5K tokens, 2 s. Each search is another round trip: about 12K tokens and 4 s with one, 19K and 6 s with two. Under $0.003 on Haiku either way. Empty falls back to assistantModel; grok-4-1-fast copies the template's example captions instead of writing new ones
memeEditModel	global	xai/grok-imagine-image	Image model for the picker's draw (and make_meme's). Templates with picture slots get one generated picture per slot (/v1/images/generations), masked into the blank; other templates send the captioned meme to /v1/images/edits. xai/ only. About $0.02 per picture, refusals billed too
memeEnabled	channel	True	False refuses @meme and hides the make_meme tool from chat
memeAliases	global	tyrone=yallgot biggums=yallgot chappelle=yallgot	Extra template names, name=id or name=https://image. An id target adds the name as a keyword on that template; a URL target adds a two-caption template drawn on that image. Hyphens for spaces in the name

See Tuning and monitoring for the bridge's security model and the scheduled-task tool.

Status pages

Setting	Scope	Default	Description
statusPageUrls	global	Claude=https://status.claude.com GitHub=https://www.githubstatus.com OpenAI=https://status.openai.com	Space-separated status pages to poll and announce — both Atlassian Statuspage and incident.io pages work — each written as Name=url or as a bare url, which takes its host as its name. Names are 1-32 chars of [A-Za-z0-9._-], case-insensitively unique across this key and statusQueryablePages, and are what the model uses to ask about one service. Unusable entries are dropped with a warning and the rest survive; at most 5 are polled
statusQueryablePages	global	empty	Same Name=url grammar as statusPageUrls, for pages the bot can be asked about but never polls or announces — the long tail like Cloudflare or AWS, where polling forever to answer an occasional question is the wrong trade. Fetched lazily on request and cached for 5 minutes, with a failure backoff. An entry naming the same page as a statusPageUrls entry is dropped, whatever its name — that page is already reachable, polled, as the fresher entry. At most 20
statusAnnounce	channel	False	Announce incidents from every configured statusPageUrls page in this channel as they open and again as they resolve. statusQueryablePages pages never announce, no matter how this is set

check_service_status is on the model's tool surface whenever either key holds at least one page. An empty statusPageUrls no longer removes the tool by itself — only polling and announcing stop; a non-empty statusQueryablePages keeps the tool available for on-request lookups.

See Tuning and monitoring for the polling rotation, staleness, and the RSS cutover order.

Aurora

Setting	Scope	Default	Description
auroraEnabled	channel	True	Give the chat model the aurora tool: NOAA aurora probability, solar wind, Kp, darkness, and cloud cover for a named place
auroraAnnounce	channel	False	Announce G3+ storm watches and sustained storm conditions in this channel. Works without auroraEnabled
auroraAnnouncePlaces	channel	empty	Optional space-separated places for this channel's announcements; _ stands for a space, as in Sault_Ste._Marie. Adds cloud cover for them and holds a storm line until one is dark. A place that matches nothing is skipped (warned once in the log)

The tool reads NOAA SWPC (services.swpc.noaa.gov) and Open-Meteo (geocoding-api.open-meteo.com, api.open-meteo.com). No API keys are needed. The tool and the announcer share one cache: solar wind for 2 minutes, aurora probability for 10 minutes, storm alerts for 5 minutes, the Kp forecast for 3 hours, cloud cover for 1 hour per place (a 5-day forecast), and place lookups for 24 hours (misses for 1 hour). A failed fetch is not cached. See Aurora.

Announcements go to every channel with auroraAnnounce on; set auroraAnnouncePlaces to add cloud cover and hold storm alerts until it is dark there. The bot checks every 5 minutes and posts two kinds of line, both fixed templates with no model rewrite:

• Storm watch: when NOAA's newest geomagnetic storm watch puts a UTC day at G3 or higher. A re-issued watch at the same level is not announced again; a rise (G3 to G4) is. With places set, the line adds "Clouds night of ": the mean over each place's remaining dark hours in the local night that overlaps that UTC day most, or the next night if that one is already over.
• Storm conditions: once per episode of Bz at or below -10 nT for most of 3 hours. With places set, the line waits until at least one of them is dark, and cloud figures are the mean over the next 3 hours; without places it goes out at once with no cloud figures. A place that matches nothing is skipped (warned once in the log); if a lookup service outage stops every place resolving, the storm line waits for the next check.

The first check after a restart, and the first check after a channel turns announcements on, only records what is already in effect; nothing already running is announced. A channel whose send fails is retried on the next check. If no channel announces, nothing is fetched.

Reminders and scheduled tasks

Setting	Scope	Default	Description
pendingTasksEnabled	channel	False	Advertise set_reminder and schedule_llm_task to the model, so natural-language scheduling works. Off by default: the schemas and their rules cost roughly 1,100 prompt tokens on every completion in the channel

The @remind command and the firing of reminders and tasks already created work regardless. This key only controls whether the model can create reminders and scheduled tasks from plain language. Listing and cancelling are not on the chat tool surface at any setting: users reach both their reminders and their scheduled tasks with @remind list, del and clear.

Timeouts and retries

When an API call times out, the bot retries in the background for a bounded window.

Setting	Scope	Default	Description
timeout	global	30	Timeout for LLM API calls, in seconds
drawTimeout	global	120	Timeout for image generation. 0 uses the global timeout
askExpiry	global	60	Seconds to keep retrying a timed-out @ask. 0 disables
codeExpiry	global	60	Seconds to keep retrying a timed-out @code. 0 disables
drawExpiry	global	60	Seconds to keep retrying a timed-out @draw. 0 disables

Draw behaviour

Setting	Scope	Default	Description
drawEnabled	channel	True	False refuses @draw and hides the generate_image tool from chat. The tool is also hidden when imageModel's provider has no key
drawAutoRewriteMax	channel	1	Automatic prompt rewordings when a safety filter blocks a request. 0 disables. Each rewording costs a second billed image call on top of the refused one, and every recovery observed in prod landed on the first attempt, so raising this mostly buys repeat refusals of a prompt that was never going to pass
drawContextMaxAgeSeconds	channel	60	Pass conversation context to draw requests only when the last activity is this recent. 0 always starts fresh

Animate behaviour

@animate renders on a self-hosted video box (see Video generation for the credential). Generation is asynchronous: the command submits a job and returns, and the pending-task poller publishes the clip when it lands, so a bot restart mid-render does not lose the video. The box renders one clip at a time, so the queue is capped (animateMaxPendingPerUser, animateMaxPending) and @renders lets users and admins inspect or clear it.

Setting	Scope	Default	Description
animateEnabled	channel	True	False refuses @animate and hides the generate_video tool from chat. Both are off everywhere until the video box is configured
animateSteps	channel	25	Denoising steps, and the dominant cost knob — latency is roughly linear in it. Measured on the reference box at 1280x704: a four-second clip took 68s at 25 steps and 171s at 50; at 25 steps a seven-second clip took 135s
animateSize	channel	1280x704	Output resolution. Must be a geometry the loaded model supports
animateDuration	channel	7	Clip length in seconds. The whole clip is exclusive GPU time, so raising it slows every queued request behind it. Also watch the file size: a 7s clip measured 8.87 MB, leaving about 1 MB under the uploader's 10 MB ceiling, and a clip over it falls back to local storage instead of imageUploadUrl
animateAudio	channel	True	Generate a soundtrack with the video. False requests silent video
animateModel	channel	empty	Model to request. Empty sends no model field, letting a single-model box pick its own — usually right
animateFlowShift	global	12	Flow-matching shift for the video sampler
animateAudioFlowShift	global	3	Flow-matching shift for the audio track. Ignored when animateAudio is off
animateTimeout	global	60	Timeout for individual HTTP calls to the video server. Not the generation budget — that is animateExpiry
animateExpiry	global	1800	Seconds to keep polling a submitted job before reporting it expired. Generous on purpose: a queued job can wait a long time before it starts
animateMaxPendingPerUser	global	2	How many clips one person may have waiting to render at once. A request past this is refused before anything is submitted. Owner and admin are exempt. 0 disables the per-user cap
animateMaxPending	global	6	How many clips may be waiting to render across the whole bot. The box renders one at a time, so this bounds the longest wait anyone is promised. Applies to everyone. 0 disables
animateRenderSeconds	global	135	Seconds one clip takes to render at the configured size, duration and steps. Only used to estimate the wait quoted when a clip is queued; measure it on the box after changing animateDuration or animateSteps

Clips are published to imageUploadUrl when one is configured — the reference host accepts MP4 on the same images[] field and files it as vid_*.mp4 — and fall back to local storage otherwise, including when a clip exceeds the 10 MB upload ceiling.

Other settings

Setting	Scope	Default	Description
maxPromptLength	global	10000	Longest accepted user prompt, in characters
commandPrefixes	global	. @	Space-separated prefixes sanitised in output to prevent IRC command injection. The default covers both the conventional . and VibeBot's own @
databasePath	global	empty	Path to the SQLite database. Empty uses data/LLM.db
logLevel	global	WARNING	Plugin log level: DEBUG, INFO, WARNING, ERROR, CRITICAL
metaMaxSteps	global	12	Cap on tool-call round trips per assistant turn. Stops runaway tool loops
maxConcurrentLLMCalls	global	16	Cap on simultaneous outbound LLM calls across all surfaces
skipAutoWhoOnJoin	global	True	Skip Limnoria's automatic WHO on join when the account-tag and extended-join capabilities are active
enforceRateLimits	global	True	Enforce rate limits. False tracks and logs without blocking