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llama.cpp/examples/server/public_legacy/index.html
Georgi Gerganov 644fd71b44
sampling : refactor + optimize penalties sampler (#10803) 
* sampling : refactor + optimize penalties sampler

ggml-ci

* common : apply ignore_eos as logit bias

ggml-ci

* batched : remove penalties sampler

* params : allow penalty_last_n == -1 to be equal to context size

ggml-ci

* common : by default, move the penalties at the end of the sampling chain

ggml-ci

* common : ignore all EOG tokens

Co-authored-by: Diego Devesa <slarengh@gmail.com>

* common : move back the penalties at the front of the sampling chain

ggml-ci

* readme : restore hint about --ignore-eos flag [no ci]

* llama : minor

ggml-ci

* webui : update

---------

Co-authored-by: Diego Devesa <slarengh@gmail.com>
2024-12-16 12:31:14 +02:00

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<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%;
}
.grid-container {
display: grid;
grid-template-columns: auto auto auto;
padding: 10px;
}
.grid-item {
padding: 5px;
/* font-size: 30px; */
text-align: center;
}
#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;
}
h1 {
text-align: center;
}
.customlink:link {
color: white;
background-color: #007aff;
font-weight: 600;
text-decoration: none;
float: right;
margin-top: 30px;
display: flex;
flex-direction: row;
gap: 0.5em;
justify-content: flex-end;
border-radius: 4px;
padding: 8px;
}
.customlink:visited {
color: white;
background-color: #007aff;
font-weight: 600;
text-decoration: none;
float: right;
margin-top: 30px;
display: flex;
flex-direction: row;
gap: 0.5em;
justify-content: flex-end;
padding: 8px;
}
.customlink:hover {
color: white;
background-color: #0070ee;
font-weight: 600;
text-decoration: none;
float: right;
margin-top: 30px;
display: flex;
flex-direction: row;
gap: 0.5em;
justify-content: flex-end;
padding: 8px;
}
.customlink:active {
color: #0070ee;
background-color: #80b3ef;
font-weight: 600;
text-decoration: none;
float: right;
margin-top: 30px;
display: flex;
flex-direction: row;
gap: 0.5em;
justify-content: flex-end;
padding: 8px;
}
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;
}
.message-controls {
display: flex;
justify-content: flex-end;
}
.message-controls > div:nth-child(2) {
display: flex;
flex-direction: column;
gap: 0.5em;
}
.message-controls > div:nth-child(2) > div {
display: flex;
margin-left: auto;
gap: 0.5em;
}
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
dry_multiplier: 0.0, // 0.0 = disabled, 0.8 works well
dry_base: 1.75, // 0.0 = disabled
dry_allowed_length: 2, // tokens extending repetitions beyond this receive penalty, 2 works well
dry_penalty_last_n: -1, // how many tokens to scan for repetitions (0 = disable penalty, -1 = context size)
top_k: 40, // <= 0 to use vocab size
top_p: 0.95, // 1.0 = disabled
min_p: 0.05, // 0 = disabled
xtc_probability: 0.0, // 0 = disabled;
xtc_threshold: 0.1, // > 0.5 disables XTC;
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 tts = window.speechSynthesis;
const ttsVoice = signal(null)
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: new URL('.', document.baseURI).href })) {
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);
}
});
}
const SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
const talkRecognition = SpeechRecognition ? new SpeechRecognition() : null;
function MessageInput() {
const message = useSignal("");
const talkActive = useSignal(false);
const sendOnTalk = useSignal(false);
const talkStop = (e) => {
if (e) e.preventDefault();
talkActive.value = false;
talkRecognition?.stop();
}
const talk = (e) => {
e.preventDefault();
if (talkRecognition)
talkRecognition.start();
else
alert("Speech recognition is not supported by this browser.");
}
if(talkRecognition) {
talkRecognition.onstart = () => {
talkActive.value = true;
}
talkRecognition.onresult = (e) => {
if (event.results.length > 0) {
message.value = event.results[0][0].transcript;
if (sendOnTalk.value) {
submit(e);
}
}
}
talkRecognition.onspeechend = () => {
talkStop();
}
}
const ttsVoices = useSignal(tts?.getVoices() || []);
const ttsVoiceDefault = computed(() => ttsVoices.value.find(v => v.default));
if (tts) {
tts.onvoiceschanged = () => {
ttsVoices.value = tts.getVoices();
}
}
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="${message}"
/>
</div>
<div class="message-controls">
<div> </div>
<div>
<div>
<button type="submit" disabled=${generating.value || talkActive.value}>Send</button>
<button disabled=${generating.value || talkActive.value} onclick=${uploadImage}>Upload Image</button>
<button onclick=${stop} disabled=${!generating.value}>Stop</button>
<button onclick=${reset}>Reset</button>
</div>
<div>
<a href="#" style="cursor: help;" title="Help" onclick=${e => {
e.preventDefault();
alert(`STT supported by your browser: ${SpeechRecognition ? 'Yes' : 'No'}\n` +
`(TTS and speech recognition are not provided by llama.cpp)\n` +
`Note: STT requires HTTPS to work.`);
}}>[?]</a>
<button disabled=${generating.value} onclick=${talkActive.value ? talkStop : talk}>${talkActive.value ? "Stop Talking" : "Talk"}</button>
<div>
<input type="checkbox" id="send-on-talk" name="send-on-talk" checked="${sendOnTalk}" onchange=${(e) => sendOnTalk.value = e.target.checked} />
<label for="send-on-talk" style="line-height: initial;">Send after talking</label>
</div>
</div>
<div>
<a href="#" style="cursor: help;" title="Help" onclick=${e => {
e.preventDefault();
alert(`TTS supported by your browser: ${tts ? 'Yes' : 'No'}\n(TTS and speech recognition are not provided by llama.cpp)`);
}}>[?]</a>
<label for="tts-voices" style="line-height: initial;">Bot Voice:</label>
<select id="tts-voices" name="tts-voices" onchange=${(e) => ttsVoice.value = e.target.value} style="max-width: 100px;">
<option value="" selected="${!ttsVoice.value}">None</option>
${[
...(ttsVoiceDefault.value ? [ttsVoiceDefault.value] : []),
...ttsVoices.value.filter(v => !v.default),
].map(
v => html`<option value="${v.name}" selected="${ttsVoice.value === v.name}">${v.name} (${v.lang}) ${v.default ? '(default)' : ''}</option>`
)}
</select>
</div>
</div>
</div>
</form>
`
}
function CompletionControls() {
const submit = (e) => {
stop(e);
runCompletion();
}
return html`
<div>
<button onclick=${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 ttsChatLineActiveIx = useSignal(undefined);
const ttsChatLine = (e, ix, msg) => {
if (e) e.preventDefault();
if (!tts || !ttsVoice.value || !('SpeechSynthesisUtterance' in window)) return;
const ttsVoices = tts.getVoices();
const voice = ttsVoices.find(v => v.name === ttsVoice.value);
if (!voice) return;
if (ttsChatLineActiveIx.value !== undefined) {
tts.cancel();
if (ttsChatLineActiveIx.value === ix) {
ttsChatLineActiveIx.value = undefined;
return;
}
}
ttsChatLineActiveIx.value = ix;
let ttsUtter = new SpeechSynthesisUtterance(msg);
ttsUtter.voice = voice;
ttsUtter.onend = e => {
ttsChatLineActiveIx.value = undefined;
};
tts.speak(ttsUtter);
}
const isCompletionMode = session.value.type === 'completion'
// Try play the last bot message
const lastCharChatLinesIxs = useSignal([]);
const lastCharChatLinesIxsOld = useSignal([]);
useEffect(() => {
if (
!isCompletionMode
&& lastCharChatLinesIxs.value.length !== lastCharChatLinesIxsOld.value.length
&& !generating.value
) {
const ix = lastCharChatLinesIxs.value[lastCharChatLinesIxs.value.length - 1];
if (ix !== undefined) {
const msg = messages[ix];
ttsChatLine(null, ix, Array.isArray(msg) ? msg[1].map(m => m.content).join('') : msg);
}
lastCharChatLinesIxsOld.value = structuredClone(lastCharChatLinesIxs.value);
}
}, [generating.value]);
const chatLine = ([user, data], index) => {
let message
const isArrayMessage = Array.isArray(data);
const text = isArrayMessage ?
data.map(msg => msg.content).join('') :
data;
if (params.value.n_probs > 0 && isArrayMessage) {
message = html`<${Probabilities} data=${data} />`
} else {
message = isCompletionMode ?
text :
html`<${Markdownish} text=${template(text)} />`
}
const fromBot = user && user === '{{char}}';
if (fromBot && !lastCharChatLinesIxs.value.includes(index))
lastCharChatLinesIxs.value.push(index);
if (user) {
return html`
<div>
<p key=${index}><strong>${template(user)}:</strong> ${message}</p>
${
fromBot && ttsVoice.value
&& html`<button disabled=${generating.value} onclick=${e => ttsChatLine(e, index, text)} aria-label=${ttsChatLineActiveIx.value === index ? 'Pause' : 'Play'}>${ ttsChatLineActiveIx.value === index ? '⏸️' : '▶️' }</div>`
}
</div>
`;
} else {
return isCompletionMode ?
html`<span key=${index}>${message}</span>` :
html`<div><p key=${index}>${message}</p></div>`
}
};
const handleCompletionEdit = (e) => {
session.value.prompt = e.target.innerText;
session.value.transcript = [];
}
return html`
<div id="chat" ref=${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 })}
${FloatField({ label: "DRY Penalty Multiplier", max: 5.0, min: 0.0, name: "dry_multiplier", step: 0.01, value: params.value.dry_multiplier })}
${FloatField({ label: "DRY Base", max: 3.0, min: 1.0, name: "dry_base", step: 0.01, value: params.value.dry_base })}
${IntField({ label: "DRY Allowed Length", max: 10, min: 2, step: 1, name: "dry_allowed_length", value: params.value.dry_allowed_length })}
${IntField({ label: "DRY Penalty Last N", max: 2048, min: -1, step: 16, name: "dry_penalty_last_n", value: params.value.dry_penalty_last_n })}
${FloatField({ label: "XTC probability", max: 1.0, min: 0.0, name: "xtc_probability", step: 0.01, value: params.value.xtc_probability })}
${FloatField({ label: "XTC threshold", max: 0.5, min: 0.0, name: "xtc_threshold", step: 0.01, value: params.value.xtc_threshold })}
</fieldset>
<hr />
<fieldset class="three">
<div>
<label><input type="radio" name="mirostat" value="0" checked=${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}>
${msg.content.match(/\n/gim) ? html`<br />` : msg.content}
</>
`
});
}
// poor mans markdown replacement
const Markdownish = (params) => {
const chunks = params.text.split('```');
for (let i = 0; i < chunks.length; i++) {
if (i % 2 === 0) { // outside code block
chunks[i] = chunks[i]
.replace(/&/g, '&amp;')
.replace(/</g, '&lt;')
.replace(/>/g, '&gt;')
.replace(/(^|\n)#{1,6} ([^\n]*)(?=([^`]*`[^`]*`)*[^`]*$)/g, '$1<h3>$2</h3>')
.replace(/\*\*(.*?)\*\*(?=([^`]*`[^`]*`)*[^`]*$)/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>$1</code>')
.replace(/\n/gim, '<br />');
} else { // inside code block
chunks[i] = `<pre><code>${chunks[i]}</code></pre>`;
}
}
const restoredText = chunks.join('');
return html`<span dangerouslySetInnerHTML=${{ __html: restoredText }} />`;
};
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-${session.value.type}">
<header>
<div class="grid-container">
<div class="grid-item"></div>
<div class="grid-item"><h1>llama.cpp</h1></div>
<div class="grid-item"><a class="customlink" href="index-new.html">New UI</a></div>
</div>
</header>
<main id="content">
<${chatStarted.value ? ChatLog : ConfigForm} />
</main>
<section id="write">
<${session.value.type === 'chat' ? MessageInput : CompletionControls} />
</section>
<footer>
<p><${ModelGenerationInfo} /></p>
<p>Powered by <a href="https://github.com/ggerganov/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>
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