Datasets:

echodict
/

llama.cpp

	<html>

	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1" />
	<meta name="color-scheme" content="light dark">
	<title>llama.cpp - chat</title>

	<style>
	body {
	font-family: system-ui;
	font-size: 90%;
	}

	#container {
	margin: 0em auto;
	display: flex;
	flex-direction: column;
	justify-content: space-between;
	height: 100%;
	}

	main {
	margin: 3px;
	display: flex;
	flex-direction: column;
	justify-content: space-between;
	gap: 1em;

	flex-grow: 1;
	overflow-y: auto;

	border: 1px solid #ccc;
	border-radius: 5px;
	padding: 0.5em;
	}

	body {
	max-width: 600px;
	min-width: 300px;
	line-height: 1.2;
	margin: 0 auto;
	padding: 0 0.5em;
	}

	p {
	overflow-wrap: break-word;
	word-wrap: break-word;
	hyphens: auto;
	margin-top: 0.5em;
	margin-bottom: 0.5em;
	}

	#write form {
	margin: 1em 0 0 0;
	display: flex;
	flex-direction: column;
	gap: 0.5em;
	align-items: stretch;
	}

	.right {
	display: flex;
	flex-direction: row;
	gap: 0.5em;
	justify-content: flex-end;
	}

	fieldset {
	border: none;
	padding: 0;
	margin: 0;
	}

	fieldset.two {
	display: grid;
	grid-template: "a a";
	gap: 1em;
	}

	fieldset.three {
	display: grid;
	grid-template: "a a a";
	gap: 1em;
	}

	details {
	border: 1px solid #aaa;
	border-radius: 4px;
	padding: 0.5em 0.5em 0;
	margin-top: 0.5em;
	}

	summary {
	font-weight: bold;
	margin: -0.5em -0.5em 0;
	padding: 0.5em;
	cursor: pointer;
	}

	details[open] {
	padding: 0.5em;
	}

	.prob-set {
	padding: 0.3em;
	border-bottom: 1px solid #ccc;
	}

	.popover-content {
	position: absolute;
	background-color: white;
	padding: 0.2em;
	box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
	}

	textarea {
	padding: 5px;
	flex-grow: 1;
	width: 100%;
	}

	pre code {
	display: block;
	background-color: #222;
	color: #ddd;
	}

	code {
	font-family: monospace;
	padding: 0.1em 0.3em;
	border-radius: 3px;
	}

	fieldset label {
	margin: 0.5em 0;
	display: block;
	}

	fieldset label.slim {
	margin: 0 0.5em;
	display: inline;
	}

	header,
	footer {
	text-align: center;
	}

	footer {
	font-size: 80%;
	color: #888;
	}

	.mode-chat textarea[name=prompt] {
	height: 4.5em;
	}

	.mode-completion textarea[name=prompt] {
	height: 10em;
	}

	[contenteditable] {
	display: inline-block;
	white-space: pre-wrap;
	outline: 0px solid transparent;
	}

	@keyframes loading-bg-wipe {
	0% {
	background-position: 0%;
	}

	100% {
	background-position: 100%;
	}
	}

	.loading {
	--loading-color-1: #eeeeee00;
	--loading-color-2: #eeeeeeff;
	background-size: 50% 100%;
	background-image: linear-gradient(90deg, var(--loading-color-1), var(--loading-color-2), var(--loading-color-1));
	animation: loading-bg-wipe 2s linear infinite;
	}

	@media (prefers-color-scheme: dark) {
	.loading {
	--loading-color-1: #22222200;
	--loading-color-2: #222222ff;
	}

	.popover-content {
	background-color: black;
	}
	}
	</style>

	<script type="module">
	import {
	html, h, signal, effect, computed, render, useSignal, useEffect, useRef, Component
	} from './index.js';

	import { llama } from './completion.js';
	import { SchemaConverter } from './json-schema-to-grammar.mjs';
	let selected_image = false;
	var slot_id = -1;

	const session = signal({
	prompt: "This is a conversation between User and Llama, a friendly chatbot. Llama is helpful, kind, honest, good at writing, and never fails to answer any requests immediately and with precision.",
	template: "{{prompt}}\n\n{{history}}\n{{char}}:",
	historyTemplate: "{{name}}: {{message}}",
	transcript: [],
	type: "chat", // "chat" \| "completion"
	char: "Llama",
	user: "User",
	image_selected: ''
	})

	const params = signal({
	n_predict: 400,
	temperature: 0.7,
	repeat_last_n: 256, // 0 = disable penalty, -1 = context size
	repeat_penalty: 1.18, // 1.0 = disabled
	top_k: 40, // <= 0 to use vocab size
	top_p: 0.95, // 1.0 = disabled
	min_p: 0.05, // 0 = disabled
	typical_p: 1.0, // 1.0 = disabled
	presence_penalty: 0.0, // 0.0 = disabled
	frequency_penalty: 0.0, // 0.0 = disabled
	mirostat: 0, // 0/1/2
	mirostat_tau: 5, // target entropy
	mirostat_eta: 0.1, // learning rate
	grammar: '',
	n_probs: 0, // no completion_probabilities,
	min_keep: 0, // min probs from each sampler,
	image_data: [],
	cache_prompt: true,
	api_key: ''
	})

	/* START: Support for storing prompt templates and parameters in browsers LocalStorage */

	const local_storage_storageKey = "llamacpp_server_local_storage";

	function local_storage_setDataFromObject(tag, content) {
	localStorage.setItem(local_storage_storageKey + '/' + tag, JSON.stringify(content));
	}

	function local_storage_setDataFromRawText(tag, content) {
	localStorage.setItem(local_storage_storageKey + '/' + tag, content);
	}

	function local_storage_getDataAsObject(tag) {
	const item = localStorage.getItem(local_storage_storageKey + '/' + tag);
	if (!item) {
	return null;
	} else {
	return JSON.parse(item);
	}
	}

	function local_storage_getDataAsRawText(tag) {
	const item = localStorage.getItem(local_storage_storageKey + '/' + tag);
	if (!item) {
	return null;
	} else {
	return item;
	}
	}

	// create a container for user templates and settings

	const savedUserTemplates = signal({})
	const selectedUserTemplate = signal({ name: '', template: { session: {}, params: {} } })

	// let's import locally saved templates and settings if there are any
	// user templates and settings are stored in one object
	// in form of { "templatename": "templatedata" } and { "settingstemplatename":"settingsdata" }

	console.log('Importing saved templates')

	let importedTemplates = local_storage_getDataAsObject('user_templates')

	if (importedTemplates) {
	// saved templates were successfully imported.

	console.log('Processing saved templates and updating default template')
	params.value = { ...params.value, image_data: [] };

	//console.log(importedTemplates);
	savedUserTemplates.value = importedTemplates;

	//override default template
	savedUserTemplates.value.default = { session: session.value, params: params.value }
	local_storage_setDataFromObject('user_templates', savedUserTemplates.value)
	} else {
	// no saved templates detected.

	console.log('Initializing LocalStorage and saving default template')

	savedUserTemplates.value = { "default": { session: session.value, params: params.value } }
	local_storage_setDataFromObject('user_templates', savedUserTemplates.value)
	}

	function userTemplateResetToDefault() {
	console.log('Resetting template to default')
	selectedUserTemplate.value.name = 'default';
	selectedUserTemplate.value.data = savedUserTemplates.value['default'];
	}

	function userTemplateApply(t) {
	session.value = t.data.session;
	session.value = { ...session.value, image_selected: '' };
	params.value = t.data.params;
	params.value = { ...params.value, image_data: [] };
	}

	function userTemplateResetToDefaultAndApply() {
	userTemplateResetToDefault()
	userTemplateApply(selectedUserTemplate.value)
	}

	function userTemplateLoadAndApplyAutosaved() {
	// get autosaved last used template
	let lastUsedTemplate = local_storage_getDataAsObject('user_templates_last')

	if (lastUsedTemplate) {

	console.log('Autosaved template found, restoring')

	selectedUserTemplate.value = lastUsedTemplate
	}
	else {

	console.log('No autosaved template found, using default template')
	// no autosaved last used template was found, so load from default.

	userTemplateResetToDefault()
	}

	console.log('Applying template')
	// and update internal data from templates

	userTemplateApply(selectedUserTemplate.value)
	}

	//console.log(savedUserTemplates.value)
	//console.log(selectedUserTemplate.value)

	function userTemplateAutosave() {
	console.log('Template Autosave...')
	if (selectedUserTemplate.value.name == 'default') {
	// we don't want to save over default template, so let's create a new one
	let newTemplateName = 'UserTemplate-' + Date.now().toString()
	let newTemplate = { 'name': newTemplateName, 'data': { 'session': session.value, 'params': params.value } }

	console.log('Saving as ' + newTemplateName)

	// save in the autosave slot
	local_storage_setDataFromObject('user_templates_last', newTemplate)

	// and load it back and apply
	userTemplateLoadAndApplyAutosaved()
	} else {
	local_storage_setDataFromObject('user_templates_last', { 'name': selectedUserTemplate.value.name, 'data': { 'session': session.value, 'params': params.value } })
	}
	}

	console.log('Checking for autosaved last used template')
	userTemplateLoadAndApplyAutosaved()

	/* END: Support for storing prompt templates and parameters in browsers LocalStorage */

	const llamaStats = signal(null)
	const controller = signal(null)

	// currently generating a completion?
	const generating = computed(() => controller.value != null)

	// has the user started a chat?
	const chatStarted = computed(() => session.value.transcript.length > 0)

	const transcriptUpdate = (transcript) => {
	session.value = {
	...session.value,
	transcript
	}
	}

	// simple template replace
	const template = (str, extraSettings) => {
	let settings = session.value;
	if (extraSettings) {
	settings = { ...settings, ...extraSettings };
	}
	return String(str).replaceAll(/\{\{(.*?)\}\}/g, (_, key) => template(settings[key]));
	}

	async function runLlama(prompt, llamaParams, char) {
	const currentMessages = [];
	const history = session.value.transcript;
	if (controller.value) {
	throw new Error("already running");
	}
	controller.value = new AbortController();
	for await (const chunk of llama(prompt, llamaParams, { controller: controller.value, api_url: location.pathname.replace(/\/+$/, '') })) {
	const data = chunk.data;

	if (data.stop) {
	while (
	currentMessages.length > 0 &&
	currentMessages[currentMessages.length - 1].content.match(/\n$/) != null
	) {
	currentMessages.pop();
	}
	transcriptUpdate([...history, [char, currentMessages]])
	console.log("Completion finished: '", currentMessages.map(msg => msg.content).join(''), "', summary: ", data);
	} else {
	currentMessages.push(data);
	slot_id = data.slot_id;
	if (selected_image && !data.multimodal) {
	alert("The server was not compiled for multimodal or the model projector can't be loaded.");
	return;
	}
	transcriptUpdate([...history, [char, currentMessages]])
	}

	if (data.timings) {
	llamaStats.value = data;
	}
	}

	controller.value = null;
	}

	// send message to server
	const chat = async (msg) => {
	if (controller.value) {
	console.log('already running...');
	return;
	}

	transcriptUpdate([...session.value.transcript, ["{{user}}", msg]])

	let prompt = template(session.value.template, {
	message: msg,
	history: session.value.transcript.flatMap(
	([name, data]) =>
	template(
	session.value.historyTemplate,
	{
	name,
	message: Array.isArray(data) ?
	data.map(msg => msg.content).join('').replace(/^\s/, '') :
	data,
	}
	)
	).join("\n"),
	});
	if (selected_image) {
	prompt = `A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\nUSER:[img-10]${msg}\nASSISTANT:`;
	}
	await runLlama(prompt, {
	...params.value,
	slot_id: slot_id,
	stop: ["</s>", template("{{char}}:"), template("{{user}}:")],
	}, "{{char}}");
	}

	const runCompletion = () => {
	if (controller.value) {
	console.log('already running...');
	return;
	}
	const { prompt } = session.value;
	transcriptUpdate([...session.value.transcript, ["", prompt]]);
	runLlama(prompt, {
	...params.value,
	slot_id: slot_id,
	stop: [],
	}, "").finally(() => {
	session.value.prompt = session.value.transcript.map(([_, data]) =>
	Array.isArray(data) ? data.map(msg => msg.content).join('') : data
	).join('');
	session.value.transcript = [];
	})
	}

	const stop = (e) => {
	e.preventDefault();
	if (controller.value) {
	controller.value.abort();
	controller.value = null;
	}
	}

	const reset = (e) => {
	stop(e);
	transcriptUpdate([]);
	}

	const uploadImage = (e) => {
	e.preventDefault();
	document.getElementById("fileInput").click();
	document.getElementById("fileInput").addEventListener("change", function (event) {
	const selectedFile = event.target.files[0];
	if (selectedFile) {
	const reader = new FileReader();
	reader.onload = function () {
	const image_data = reader.result;
	session.value = { ...session.value, image_selected: image_data };
	params.value = {
	...params.value, image_data: [
	{ data: image_data.replace(/data:image\/[^;]+;base64,/, ''), id: 10 }]
	}
	};
	selected_image = true;
	reader.readAsDataURL(selectedFile);
	}
	});
	}

	function MessageInput() {
	const message = useSignal("")

	const submit = (e) => {
	stop(e);
	chat(message.value);
	message.value = "";
	}

	const enterSubmits = (event) => {
	if (event.which === 13 && !event.shiftKey) {
	submit(event);
	}
	}

	return html`
	<form onsubmit=${submit}>
	<div>
	<textarea
	className=${generating.value ? "loading" : null}
	oninput=${(e) => message.value = e.target.value}
	onkeypress=${enterSubmits}
	placeholder="Say something..."
	rows=2
	type="text"
	value="${message}"
	/>
	</div>
	<div class="right">
	<button type="submit" disabled=${generating.value}>Send</button>
	<button onclick=${uploadImage}>Upload Image</button>
	<button onclick=${stop} disabled=${!generating.value}>Stop</button>
	<button onclick=${reset}>Reset</button>
	</div>
	</form>
	`
	}

	function CompletionControls() {
	const submit = (e) => {
	stop(e);
	runCompletion();
	}
	return html`
	<div>
	<button onclick=${submit} type="button" disabled=${generating.value}>Start</button>
	<button onclick=${stop} disabled=${!generating.value}>Stop</button>
	<button onclick=${reset}>Reset</button>
	</div>`;
	}

	const ChatLog = (props) => {
	const messages = session.value.transcript;
	const container = useRef(null)

	useEffect(() => {
	// scroll to bottom (if needed)
	const parent = container.current.parentElement;
	if (parent && parent.scrollHeight <= parent.scrollTop + parent.offsetHeight + 300) {
	parent.scrollTo(0, parent.scrollHeight)
	}
	}, [messages])

	const isCompletionMode = session.value.type === 'completion'
	const chatLine = ([user, data], index) => {
	let message
	const isArrayMessage = Array.isArray(data)
	if (params.value.n_probs > 0 && isArrayMessage) {
	message = html`<${Probabilities} data=${data} />`
	} else {
	const text = isArrayMessage ?
	data.map(msg => msg.content).join('').replace(/^\s+/, '') :
	data;
	message = isCompletionMode ?
	text :
	html`<${Markdownish} text=${template(text)} />`
	}
	if (user) {
	return html`<p key=${index}><strong>${template(user)}:</strong> ${message}</p>`
	} else {
	return isCompletionMode ?
	html`<span key=${index}>${message}</span>` :
	html`<p key=${index}>${message}</p>`
	}
	};

	const handleCompletionEdit = (e) => {
	session.value.prompt = e.target.innerText;
	session.value.transcript = [];
	}

	return html`
	<div id="chat" ref=${container} key=${messages.length}>
	<img style="width: 60%;${!session.value.image_selected ? `display: none;` : ``}" src="${session.value.image_selected}"/>
	<span contenteditable=${isCompletionMode} ref=${container} oninput=${handleCompletionEdit}>
	${messages.flatMap(chatLine)}
	</span>
	</div>`;
	};

	const ConfigForm = (props) => {
	const updateSession = (el) => session.value = { ...session.value, [el.target.name]: el.target.value }
	const updateParams = (el) => params.value = { ...params.value, [el.target.name]: el.target.value }
	const updateParamsFloat = (el) => params.value = { ...params.value, [el.target.name]: parseFloat(el.target.value) }
	const updateParamsInt = (el) => params.value = { ...params.value, [el.target.name]: Math.floor(parseFloat(el.target.value)) }
	const updateParamsBool = (el) => params.value = { ...params.value, [el.target.name]: el.target.checked }

	const grammarJsonSchemaPropOrder = signal('')
	const updateGrammarJsonSchemaPropOrder = (el) => grammarJsonSchemaPropOrder.value = el.target.value
	const convertJSONSchemaGrammar = async () => {
	try {
	let schema = JSON.parse(params.value.grammar)
	const converter = new SchemaConverter({
	prop_order: grammarJsonSchemaPropOrder.value
	.split(',')
	.reduce((acc, cur, i) => ({ ...acc, [cur.trim()]: i }), {}),
	allow_fetch: true,
	})
	schema = await converter.resolveRefs(schema, 'input')
	converter.visit(schema, '')
	params.value = {
	...params.value,
	grammar: converter.formatGrammar(),
	}
	} catch (e) {
	alert(`Convert failed: ${e.message}`)
	}
	}

	const FloatField = ({ label, max, min, name, step, value }) => {
	return html`
	<div>
	<label for="${name}">${label}</label>
	<input type="range" id="${name}" min="${min}" max="${max}" step="${step}" name="${name}" value="${value}" oninput=${updateParamsFloat} />
	<span>${value}</span>
	</div>
	`
	};

	const IntField = ({ label, max, min, name, value }) => {
	return html`
	<div>
	<label for="${name}">${label}</label>
	<input type="range" id="${name}" min="${min}" max="${max}" name="${name}" value="${value}" oninput=${updateParamsInt} />
	<span>${value}</span>
	</div>
	`
	};

	const BoolField = ({ label, name, value }) => {
	return html`
	<div>
	<label for="${name}">${label}</label>
	<input type="checkbox" id="${name}" name="${name}" checked="${value}" onclick=${updateParamsBool} />
	</div>
	`
	};

	const userTemplateReset = (e) => {
	e.preventDefault();
	userTemplateResetToDefaultAndApply()
	}

	const UserTemplateResetButton = () => {
	if (selectedUserTemplate.value.name == 'default') {
	return html`
	<button disabled>Using default template</button>
	`
	}

	return html`
	<button onclick=${userTemplateReset}>Reset all to default</button>
	`
	};

	useEffect(() => {
	// autosave template on every change
	userTemplateAutosave()
	}, [session.value, params.value])

	const GrammarControl = () => (
	html`
	<div>
	<label for="template">Grammar</label>
	<textarea id="grammar" name="grammar" placeholder="Use gbnf or JSON Schema+convert" value="${params.value.grammar}" rows=4 oninput=${updateParams}/>
	<input type="text" name="prop-order" placeholder="order: prop1,prop2,prop3" oninput=${updateGrammarJsonSchemaPropOrder} />
	<button type="button" onclick=${convertJSONSchemaGrammar}>Convert JSON Schema</button>
	</div>
	`
	);

	const PromptControlFieldSet = () => (
	html`
	<fieldset>
	<div>
	<label htmlFor="prompt">Prompt</label>
	<textarea type="text" name="prompt" value="${session.value.prompt}" oninput=${updateSession}/>
	</div>
	</fieldset>
	`
	);

	const ChatConfigForm = () => (
	html`
	${PromptControlFieldSet()}

	<fieldset class="two">
	<div>
	<label for="user">User name</label>
	<input type="text" name="user" value="${session.value.user}" oninput=${updateSession} />
	</div>

	<div>
	<label for="bot">Bot name</label>
	<input type="text" name="char" value="${session.value.char}" oninput=${updateSession} />
	</div>
	</fieldset>

	<fieldset>
	<div>
	<label for="template">Prompt template</label>
	<textarea id="template" name="template" value="${session.value.template}" rows=4 oninput=${updateSession}/>
	</div>

	<div>
	<label for="template">Chat history template</label>
	<textarea id="template" name="historyTemplate" value="${session.value.historyTemplate}" rows=1 oninput=${updateSession}/>
	</div>
	${GrammarControl()}
	</fieldset>
	`
	);

	const CompletionConfigForm = () => (
	html`
	${PromptControlFieldSet()}
	<fieldset>${GrammarControl()}</fieldset>
	`
	);

	return html`
	<form>
	<fieldset class="two">
	<${UserTemplateResetButton}/>
	<div>
	<label class="slim"><input type="radio" name="type" value="chat" checked=${session.value.type === "chat"} oninput=${updateSession} /> Chat</label>
	<label class="slim"><input type="radio" name="type" value="completion" checked=${session.value.type === "completion"} oninput=${updateSession} /> Completion</label>
	</div>
	</fieldset>

	${session.value.type === 'chat' ? ChatConfigForm() : CompletionConfigForm()}

	<fieldset class="two">
	${IntField({ label: "Predictions", max: 2048, min: -1, name: "n_predict", value: params.value.n_predict })}
	${FloatField({ label: "Temperature", max: 2.0, min: 0.0, name: "temperature", step: 0.01, value: params.value.temperature })}
	${FloatField({ label: "Penalize repeat sequence", max: 2.0, min: 0.0, name: "repeat_penalty", step: 0.01, value: params.value.repeat_penalty })}
	${IntField({ label: "Consider N tokens for penalize", max: 2048, min: 0, name: "repeat_last_n", value: params.value.repeat_last_n })}
	${IntField({ label: "Top-K sampling", max: 100, min: -1, name: "top_k", value: params.value.top_k })}
	${FloatField({ label: "Top-P sampling", max: 1.0, min: 0.0, name: "top_p", step: 0.01, value: params.value.top_p })}
	${FloatField({ label: "Min-P sampling", max: 1.0, min: 0.0, name: "min_p", step: 0.01, value: params.value.min_p })}
	</fieldset>
	<details>
	<summary>More options</summary>
	<fieldset class="two">
	${FloatField({ label: "Typical P", max: 1.0, min: 0.0, name: "typical_p", step: 0.01, value: params.value.typical_p })}
	${FloatField({ label: "Presence penalty", max: 1.0, min: 0.0, name: "presence_penalty", step: 0.01, value: params.value.presence_penalty })}
	${FloatField({ label: "Frequency penalty", max: 1.0, min: 0.0, name: "frequency_penalty", step: 0.01, value: params.value.frequency_penalty })}
	</fieldset>
	<hr />
	<fieldset class="three">
	<div>
	<label><input type="radio" name="mirostat" value="0" checked=${params.value.mirostat == 0} oninput=${updateParamsInt} /> no Mirostat</label>
	<label><input type="radio" name="mirostat" value="1" checked=${params.value.mirostat == 1} oninput=${updateParamsInt} /> Mirostat v1</label>
	<label><input type="radio" name="mirostat" value="2" checked=${params.value.mirostat == 2} oninput=${updateParamsInt} /> Mirostat v2</label>
	</div>
	${FloatField({ label: "Mirostat tau", max: 10.0, min: 0.0, name: "mirostat_tau", step: 0.01, value: params.value.mirostat_tau })}
	${FloatField({ label: "Mirostat eta", max: 1.0, min: 0.0, name: "mirostat_eta", step: 0.01, value: params.value.mirostat_eta })}
	</fieldset>
	<fieldset>
	${IntField({ label: "Show Probabilities", max: 10, min: 0, name: "n_probs", value: params.value.n_probs })}
	</fieldset>
	<fieldset>
	${IntField({ label: "Min Probabilities from each Sampler", max: 10, min: 0, name: "min_keep", value: params.value.min_keep })}
	</fieldset>
	<fieldset>
	<label for="api_key">API Key</label>
	<input type="text" name="api_key" value="${params.value.api_key}" placeholder="Enter API key" oninput=${updateParams} />
	</fieldset>
	</details>
	</form>
	`
	}

	const probColor = (p) => {
	const r = Math.floor(192 * (1 - p));
	const g = Math.floor(192 * p);
	return `rgba(${r},${g},0,0.3)`;
	}

	const Probabilities = (params) => {
	return params.data.map(msg => {
	const { completion_probabilities } = msg;
	if (
	!completion_probabilities \|\|
	completion_probabilities.length === 0
	) return msg.content

	if (completion_probabilities.length > 1) {
	// Not for byte pair
	if (completion_probabilities[0].content.startsWith('byte: \\')) return msg.content

	const splitData = completion_probabilities.map(prob => ({
	content: prob.content,
	completion_probabilities: [prob]
	}))
	return html`<${Probabilities} data=${splitData} />`
	}

	const { probs, content } = completion_probabilities[0]
	const found = probs.find(p => p.tok_str === msg.content)
	const pColor = found ? probColor(found.prob) : 'transparent'

	const popoverChildren = html`
	<div class="prob-set">
	${probs.map((p, index) => {
	return html`
	<div
	key=${index}
	title=${`prob: ${p.prob}`}
	style=${{
	padding: '0.3em',
	backgroundColor: p.tok_str === content ? probColor(p.prob) : 'transparent'
	}}
	>
	<span>${p.tok_str}: </span>
	<span>${Math.floor(p.prob * 100)}%</span>
	</div>
	`
	})}
	</div>
	`

	return html`
	<${Popover} style=${{ backgroundColor: pColor }} popoverChildren=${popoverChildren}>
	${msg.content.match(/\n/gim) ? html`<br />` : msg.content}
	</>
	`
	});
	}

	// poor mans markdown replacement
	const Markdownish = (params) => {
	const md = params.text
	.replace(/&/g, '&')
	.replace(/</g, '<')
	.replace(/>/g, '>')
	.replace(/^#{1,6} (.*)$/gim, '<h3>$1</h3>')
	.replace(/\\(.?)\\*/g, '<strong>$1</strong>')
	.replace(/__(.*?)__/g, '<strong>$1</strong>')
	.replace(/\(.?)\*/g, '<em>$1</em>')
	.replace(/_(.*?)_/g, '<em>$1</em>')
	.replace(/```.?\n([\s\S]?)```/g, '<pre><code>$1</code></pre>')
	.replace(/`(.*?)`/g, '<code>$1</code>')
	.replace(/\n/gim, '<br />');
	return html`<span dangerouslySetInnerHTML=${{ __html: md }} />`;
	};

	const ModelGenerationInfo = (params) => {
	if (!llamaStats.value) {
	return html`<span/>`
	}
	return html`
	<span>
	${llamaStats.value.tokens_predicted} predicted, ${llamaStats.value.tokens_cached} cached, ${llamaStats.value.timings.predicted_per_token_ms.toFixed()}ms per token, ${llamaStats.value.timings.predicted_per_second.toFixed(2)} tokens per second
	</span>
	`
	}

	// simple popover impl
	const Popover = (props) => {
	const isOpen = useSignal(false);
	const position = useSignal({ top: '0px', left: '0px' });
	const buttonRef = useRef(null);
	const popoverRef = useRef(null);

	const togglePopover = () => {
	if (buttonRef.current) {
	const rect = buttonRef.current.getBoundingClientRect();
	position.value = {
	top: `${rect.bottom + window.scrollY}px`,
	left: `${rect.left + window.scrollX}px`,
	};
	}
	isOpen.value = !isOpen.value;
	};

	const handleClickOutside = (event) => {
	if (popoverRef.current && !popoverRef.current.contains(event.target) && !buttonRef.current.contains(event.target)) {
	isOpen.value = false;
	}
	};

	useEffect(() => {
	document.addEventListener('mousedown', handleClickOutside);
	return () => {
	document.removeEventListener('mousedown', handleClickOutside);
	};
	}, []);

	return html`
	<span style=${props.style} ref=${buttonRef} onClick=${togglePopover}>${props.children}</span>
	${isOpen.value && html`
	<${Portal} into="#portal">
	<div
	ref=${popoverRef}
	class="popover-content"
	style=${{
	top: position.value.top,
	left: position.value.left,
	}}
	>
	${props.popoverChildren}
	</div>
	</${Portal}>
	`}
	`;
	};

	// Source: preact-portal (https://github.com/developit/preact-portal/blob/master/src/preact-portal.js)
	/** Redirect rendering of descendants into the given CSS selector */
	class Portal extends Component {
	componentDidUpdate(props) {
	for (let i in props) {
	if (props[i] !== this.props[i]) {
	return setTimeout(this.renderLayer);
	}
	}
	}

	componentDidMount() {
	this.isMounted = true;
	this.renderLayer = this.renderLayer.bind(this);
	this.renderLayer();
	}

	componentWillUnmount() {
	this.renderLayer(false);
	this.isMounted = false;
	if (this.remote && this.remote.parentNode) this.remote.parentNode.removeChild(this.remote);
	}

	findNode(node) {
	return typeof node === 'string' ? document.querySelector(node) : node;
	}

	renderLayer(show = true) {
	if (!this.isMounted) return;

	// clean up old node if moving bases:
	if (this.props.into !== this.intoPointer) {
	this.intoPointer = this.props.into;
	if (this.into && this.remote) {
	this.remote = render(html`<${PortalProxy} />`, this.into, this.remote);
	}
	this.into = this.findNode(this.props.into);
	}

	this.remote = render(html`
	<${PortalProxy} context=${this.context}>
	${show && this.props.children \|\| null}
	</${PortalProxy}>
	`, this.into, this.remote);
	}

	render() {
	return null;
	}
	}
	// high-order component that renders its first child if it exists.
	// used as a conditional rendering proxy.
	class PortalProxy extends Component {
	getChildContext() {
	return this.props.context;
	}
	render({ children }) {
	return children \|\| null;
	}
	}

	function App(props) {
	useEffect(() => {
	const query = new URLSearchParams(location.search).get("q");
	if (query) chat(query);
	}, []);

	return html`
	<div class="mode-${session.value.type}">
	<header>
	<h1>llama.cpp</h1>
	</header>

	<section id="write">
	<${session.value.type === 'chat' ? MessageInput : CompletionControls} />
	</section>

	<main id="content">
	<${chatStarted.value ? ChatLog : ConfigForm} />
	</main>

	<footer>
	<p><${ModelGenerationInfo} /></p>
	<p>Powered by <a href="https://github.com/ggml-org/llama.cpp">llama.cpp</a> and <a href="https://ggml.ai">ggml.ai</a>.</p>
	</footer>
	</div>
	`;
	}

	render(h(App), document.querySelector('#container'));
	</script>
	</head>

	<body>
	<div id="container">
	<input type="file" id="fileInput" accept="image/*" style="display: none;">
	</div>
	<div id="portal"></div>
	</body>

	</html>