Lora Manager

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JeLuF 2023-09-04 01:36:32 +02:00 committed by GitHub
parent 74c0ca0902
commit 4aca3c4639
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4 changed files with 707 additions and 347 deletions

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@ -470,7 +470,6 @@ def modify_package_internal(package_name: str, req: dict):
def get_sha256_internal(obj_path): def get_sha256_internal(obj_path):
import hashlib
from easydiffusion.utils import sha256sum from easydiffusion.utils import sha256sum
path = obj_path.split("/") path = obj_path.split("/")

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@ -1,4 +1,5 @@
import logging import logging
import hashlib
log = logging.getLogger("easydiffusion") log = logging.getLogger("easydiffusion")

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@ -514,7 +514,7 @@ function showImages(reqBody, res, outputContainer, livePreview) {
{ {
text: "Use as Thumbnail", text: "Use as Thumbnail",
on_click: onUseAsThumbnailClick, on_click: onUseAsThumbnailClick,
filter: (req, img) => "use_embeddings_model" in req, filter: (req, img) => "use_embeddings_model" in req || "use_lora_model" in req
}, },
] ]
@ -748,16 +748,14 @@ function onUseAsThumbnailClick(req, img) {
onUseAsThumbnailClick.croppr.setImage(img.src) onUseAsThumbnailClick.croppr.setImage(img.src)
} }
useAsThumbSelect.innerHTML=""
if ("use_embeddings_model" in req) {
let embeddings = req.use_embeddings_model.map((e) => e.split("/").pop()) let embeddings = req.use_embeddings_model.map((e) => e.split("/").pop())
let LORA = []
if ("use_lora_model" in req) { let embOptions = document.createElement("optgroup")
LORA = req.use_lora_model embOptions.label = "Embeddings"
} embOptions.replaceChildren(
let optgroup = document.createElement("optgroup")
optgroup.label = "Embeddings"
optgroup.replaceChildren(
...embeddings.map((e) => { ...embeddings.map((e) => {
let option = document.createElement("option") let option = document.createElement("option")
option.innerText = e option.innerText = e
@ -765,8 +763,30 @@ function onUseAsThumbnailClick(req, img) {
return option return option
}) })
) )
useAsThumbSelect.appendChild(embOptions)
}
if ("use_lora_model" in req) {
let LORA = req.use_lora_model
if (typeof LORA == "string") {
LORA = [LORA]
}
LORA = LORA.map((e) => e.split("/").pop())
let loraOptions = document.createElement("optgroup")
loraOptions.label = "LORA"
loraOptions.replaceChildren(
...LORA.map((e) => {
let option = document.createElement("option")
option.innerText = e
option.dataset["type"] = "lora"
return option
})
)
useAsThumbSelect.appendChild(loraOptions)
}
useAsThumbSelect.replaceChildren(optgroup)
useAsThumbDialog.showModal() useAsThumbDialog.showModal()
onUseAsThumbnailClick.scale = scale onUseAsThumbnailClick.scale = scale
} }
@ -782,6 +802,50 @@ useAsThumbCancelBtn.addEventListener("click", () => {
useAsThumbDialog.close() useAsThumbDialog.close()
}) })
const Bucket = {
upload(path, blob) {
const formData = new FormData()
formData.append("file", blob)
return fetch(`bucket/${path}`, {
method: "POST",
body: formData,
})
},
getImageAsDataURL(path) {
return fetch(`bucket/${path}`)
.then((response) => {
if (response.status == 200) {
return response.blob()
} else {
throw new Error("Bucket error")
}
})
.then((blob) => {
return new Promise((resolve, reject) => {
const reader = new FileReader()
reader.onload = () => resolve(reader.result)
reader.onerror = reject
reader.readAsDataURL(blob)
})
})
},
getList(path) {
return fetch(`bucket/${path}`)
.then((response) => (response.status == 200 ? response.json() : []))
},
store(path, data) {
return Bucket.upload(`${path}.json`, JSON.stringify(data))
},
retrieve(path) {
return fetch(`bucket/${path}.json`)
.then((response) => (response.status == 200 ? response.json() : null))
},
}
useAsThumbSaveBtn.addEventListener("click", (e) => { useAsThumbSaveBtn.addEventListener("click", (e) => {
let scale = 1 / onUseAsThumbnailClick.scale let scale = 1 / onUseAsThumbnailClick.scale
let crop = onUseAsThumbnailClick.croppr.getValue() let crop = onUseAsThumbnailClick.croppr.getValue()
@ -793,16 +857,11 @@ useAsThumbSaveBtn.addEventListener("click", (e) => {
.then((thumb) => fetch(thumb)) .then((thumb) => fetch(thumb))
.then((response) => response.blob()) .then((response) => response.blob())
.then(async function(blob) { .then(async function(blob) {
const formData = new FormData()
formData.append("file", blob)
let options = useAsThumbSelect.selectedOptions let options = useAsThumbSelect.selectedOptions
let promises = [] let promises = []
for (let embedding of options) { for (let embedding of options) {
promises.push( promises.push(
fetch(`bucket/${profileName}/${embedding.dataset["type"]}/${embedding.value}.png`, { Bucket.upload(`${profileName}/${embedding.dataset["type"]}/${embedding.value}.png`, blob)
method: "POST",
body: formData,
})
) )
} }
return Promise.all(promises) return Promise.all(promises)
@ -2362,20 +2421,10 @@ function loadThumbnailImageFromFile() {
} }
function updateEmbeddingsList(filter = "") { function updateEmbeddingsList(filter = "") {
function html(model, iconlist = [], prefix = "", filter = "") { function html(model, iconMap = {}, prefix = "", filter = "") {
filter = filter.toLowerCase() filter = filter.toLowerCase()
let toplevel = document.createElement("div") let toplevel = document.createElement("div")
let folders = document.createElement("div") let folders = document.createElement("div")
let embIcon = Object.assign(
{},
...iconlist.map((x) => ({
[x
.toLowerCase()
.split(".")
.slice(0, -1)
.join(".")]: x,
}))
)
let profileName = profileNameField.value let profileName = profileNameField.value
model?.forEach((m) => { model?.forEach((m) => {
@ -2383,13 +2432,9 @@ function updateEmbeddingsList(filter = "") {
let token = m.toLowerCase() let token = m.toLowerCase()
if (token.search(filter) != -1) { if (token.search(filter) != -1) {
let button let button
// if (iconlist.length==0) {
// button = document.createElement("button")
// button.innerText = m
// } else {
let img = "/media/images/noimg.png" let img = "/media/images/noimg.png"
if (token in embIcon) { if (token in iconMap) {
img = `/bucket/${profileName}/embeddings/${embIcon[token]}` img = `/bucket/${profileName}/${iconMap[token]}`
} }
button = createModifierCard(m, [img, img], true) button = createModifierCard(m, [img, img], true)
// } // }
@ -2398,7 +2443,7 @@ function updateEmbeddingsList(filter = "") {
toplevel.appendChild(button) toplevel.appendChild(button)
} }
} else { } else {
let subdir = html(m[1], iconlist, prefix + m[0] + "/", filter) let subdir = html(m[1], iconMap, prefix + m[0] + "/", filter)
if (typeof subdir == "object") { if (typeof subdir == "object") {
let div1 = document.createElement("div") let div1 = document.createElement("div")
let div2 = document.createElement("div") let div2 = document.createElement("div")
@ -2457,11 +2502,44 @@ function updateEmbeddingsList(filter = "") {
</div> </div>
` `
let loraTokens = []
let profileName = profileNameField.value let profileName = profileNameField.value
fetch(`/bucket/${profileName}/embeddings/`) let iconMap = {}
.then((response) => (response.status == 200 ? response.json() : []))
.then(async function(iconlist) { Bucket.getList(`${profileName}/embeddings/`)
embeddingsList.replaceChildren(html(modelsOptions.embeddings, iconlist, "", filter)) .then((icons) => {
iconMap = Object.assign(
{},
...icons.map((x) => ({
[x
.toLowerCase()
.split(".")
.slice(0, -1)
.join(".")]: `embeddings/${x}`,
}))
)
return Bucket.getList(`${profileName}/lora/`)
})
.then(async function (icons) {
for (let lora of loraModelField.value.modelNames) {
let keywords = await getLoraKeywords(lora)
loraTokens = loraTokens.concat(keywords)
let loraname = lora.split("/").pop()
if (icons.includes(`${loraname}.png`)) {
keywords.forEach((kw) => {
iconMap[kw.toLowerCase()] = `lora/${loraname}.png`
})
}
}
let tokenList = [...modelsOptions.embeddings]
if (loraTokens.length != 0) {
tokenList.unshift(['LORA Keywords', loraTokens])
}
embeddingsList.replaceChildren(html(tokenList, iconMap, "", filter))
createCollapsibles(embeddingsList) createCollapsibles(embeddingsList)
if (filter != "") { if (filter != "") {
embeddingsExpandAll() embeddingsExpandAll()

View File

@ -1,6 +1,337 @@
;(function() { ;(function() {
"use strict" "use strict"
let mergeCSS = `
/*********** Main tab ***********/
.tab-centered {
justify-content: center;
}
#model-tool-tab-content {
background-color: var(--background-color3);
}
#model-tool-tab-content .tab-content-inner {
text-align: initial;
}
#model-tool-tab-bar .tab {
margin-bottom: 0px;
border-top-left-radius: var(--input-border-radius);
background-color: var(--background-color3);
padding: 6px 6px 0.8em 6px;
}
#tab-content-merge .tab-content-inner {
max-width: 100%;
padding: 10pt;
}
/*********** Merge UI ***********/
.merge-model-container {
margin-left: 15%;
margin-right: 15%;
text-align: left;
display: inline-grid;
grid-template-columns: 1fr 1fr;
grid-template-rows: auto auto auto;
gap: 0px 0px;
grid-auto-flow: row;
grid-template-areas:
"merge-input merge-config"
"merge-buttons merge-buttons";
}
.merge-model-container p {
margin-top: 3pt;
margin-bottom: 3pt;
}
.merge-config .tab-content {
background: var(--background-color1);
border-radius: 3pt;
}
.merge-config .tab-content-inner {
text-align: left;
}
.merge-input {
grid-area: merge-input;
padding-left:1em;
}
.merge-config {
grid-area: merge-config;
padding:1em;
}
.merge-config input {
margin-bottom: 3px;
}
.merge-config select {
margin-bottom: 3px;
}
.merge-buttons {
grid-area: merge-buttons;
padding:1em;
text-align: center;
}
#merge-button {
padding: 8px;
width:20em;
}
div#merge-log {
height:150px;
overflow-x:hidden;
overflow-y:scroll;
background:var(--background-color1);
border-radius: 3pt;
}
div#merge-log i {
color: hsl(var(--accent-hue), 100%, calc(2*var(--accent-lightness)));
font-family: monospace;
}
.disabled {
background: var(--background-color4);
color: var(--text-color);
}
#merge-type-tabs {
border-bottom: 1px solid black;
}
#merge-log-container {
display: none;
}
.merge-model-container #merge-warning {
color: var(--small-label-color);
}
/*********** LORA UI ***********/
.lora-manager-grid {
display: grid;
gap: 0px 8px;
grid-auto-flow: row;
}
@media screen and (min-width: 1501px) {
.lora-manager-grid textarea {
height:350px;
}
.lora-manager-grid {
grid-template-columns: auto 1fr 1fr;
grid-template-rows: auto 1fr;
grid-template-areas:
"selector selector selector"
"thumbnail keywords notes";
}
}
@media screen and (min-width: 1001px) and (max-width: 1500px) {
.lora-manager-grid textarea {
height:250px;
}
.lora-manager-grid {
grid-template-columns: auto auto;
grid-template-rows: auto auto auto;
grid-template-areas:
"selector selector"
"thumbnail keywords"
"thumbnail notes";
}
}
@media screen and (max-width: 1000px) {
.lora-manager-grid textarea {
height:200px;
}
.lora-manager-grid {
grid-template-columns: auto;
grid-template-rows: auto auto auto auto;
grid-template-areas:
"selector"
"keywords"
"thumbnail"
"notes";
}
}
.lora-manager-grid-selector {
grid-area: selector;
justify-self: start;
}
.lora-manager-grid-thumbnail {
grid-area: thumbnail;
justify-self: center;
}
.lora-manager-grid-keywords {
grid-area: keywords;
}
.lora-manager-grid-notes {
grid-area: notes;
}
.lora-manager-grid p {
margin-bottom: 2px;
}
`
let mergeUI = `
<div class="merge-model-container panel-box">
<div class="merge-input">
<p><label for="#mergeModelA">Select Model A:</label></p>
<input id="mergeModelA" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<p><label for="#mergeModelB">Select Model B:</label></p>
<input id="mergeModelB" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<br/><br/>
<p id="merge-warning"><small><b>Important:</b> Please merge models of similar type.<br/>For e.g. <code>SD 1.4</code> models with only <code>SD 1.4/1.5</code> models,<br/><code>SD 2.0</code> with <code>SD 2.0</code>-type, and <code>SD 2.1</code> with <code>SD 2.1</code>-type models.</small></p>
<br/>
<table>
<tr>
<td><label for="#merge-filename">Output file name:</label></td>
<td><input id="merge-filename" size=24> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Base name of the output file.<br>Mix ratio and file suffix will be appended to this.</span></i></td>
</tr>
<tr>
<td><label for="#merge-fp">Output precision:</label></td>
<td><select id="merge-fp">
<option value="fp16">fp16 (smaller file size)</option>
<option value="fp32">fp32 (larger file size)</option>
</select>
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Image generation uses fp16, so it's a good choice.<br>Use fp32 if you want to use the result models for more mixes</span></i>
</td>
</tr>
<tr>
<td><label for="#merge-format">Output file format:</label></td>
<td><select id="merge-format">
<option value="safetensors">Safetensors (recommended)</option>
<option value="ckpt">CKPT/Pickle (legacy format)</option>
</select>
</td>
</tr>
</table>
<br/>
<div id="merge-log-container">
<p><label for="#merge-log">Log messages:</label></p>
<div id="merge-log"></div>
</div>
</div>
<div class="merge-config">
<div class="tab-container">
<span id="tab-merge-opts-single" class="tab active">
<span>Make a single file</small></span>
</span>
<span id="tab-merge-opts-batch" class="tab">
<span>Make multiple variations</small></span>
</span>
</div>
<div>
<div id="tab-content-merge-opts-single" class="tab-content active">
<div class="tab-content-inner">
<small>Saves a single merged model file, at the specified merge ratio.</small><br/><br/>
<label for="#single-merge-ratio-slider">Merge ratio:</label>
<input id="single-merge-ratio-slider" name="single-merge-ratio-slider" class="editor-slider" value="50" type="range" min="1" max="1000">
<input id="single-merge-ratio" size=2 value="5">%
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Model A's contribution to the mix. The rest will be from Model B.</span></i>
</div>
</div>
<div id="tab-content-merge-opts-batch" class="tab-content">
<div class="tab-content-inner">
<small>Saves multiple variations of the model, at different merge ratios.<br/>Each variation will be saved as a separate file.</small><br/><br/>
<table>
<tr><td><label for="#merge-count">Number of variations:</label></td>
<td> <input id="merge-count" size=2 value="5"></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Number of models to create</span></i></td></tr>
<tr><td><label for="#merge-start">Starting merge ratio:</label></td>
<td> <input id="merge-start" size=2 value="5">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Smallest share of model A in the mix</span></i></td></tr>
<tr><td><label for="#merge-step">Increment each step:</label></td>
<td> <input id="merge-step" size=2 value="10">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Share of model A added into the mix per step</span></i></td></tr>
<tr><td><label for="#merge-interpolation">Interpolation model:</label></td>
<td> <select id="merge-interpolation">
<option>Exact</option>
<option>SmoothStep</option>
<option>SmootherStep</option>
<option>SmoothestStep</option>
</select></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Sigmoid function to be applied to the model share before mixing</span></i></td></tr>
</table>
<br/>
<small>Preview of variation ratios:</small><br/>
<canvas id="merge-canvas" width="400" height="400"></canvas>
</div>
</div>
</div>
</div>
<div class="merge-buttons">
<button id="merge-button" class="primaryButton">Merge models</button>
</div>
</div>`
let loraUI=`
<div class="panel-box lora-manager-grid">
<div class="lora-manager-grid-selector">
<label for="#loraModel">Select Lora:</label>
<input id="loraModel" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
</div>
<div class="lora-manager-grid-thumbnail">
<p style="height:2em;">Thumbnail:</p>
<div style="position:relative; height:256px; width:256px;background-color:#222;border-radius:1em;margin-bottom:1em;">
<i id="lora-manager-image-placeholder" class="fa-regular fa-image" style="font-size:500%;color:#555;position:absolute; top: 50%; left: 50%; transform: translate(-50%,-50%);"></i>
<img id="lora-manager-image" class="displayNone" style="border-radius:6px;max-height:256px;max-width:256px;"/>
</div>
<div style="text-align:center;">
<button class="tertiaryButton"><i class="fa-solid fa-upload"></i> Upload new thumbnail</button>
<button class="tertiaryButton"><i class="fa-solid fa-trash-can"></i> Remove</button>
</div>
</div>
<div class="lora-manager-grid-keywords">
<p style="height:2em;">Keywords:
<span style="float:right;margin-bottom:4px;"><button id="lora-keyword-from-civitai" class="tertiaryButton smallButton">Import from Civitai</button></span></p>
<textarea style="width:100%;resize:vertical;" id="lora-manager-keywords" placeholder="Put LORA specific keywords here..."></textarea>
<p style="color:var(--small-label-color);">
<b>LORA model keywords</b> can be used via the <code>+&nbsp;Embeddings</code> button. They get added to the embedding
keyword menu when the LORA has been selected in the image settings.
</p>
</div>
<div class="lora-manager-grid-notes">
<p style="height:2em;">Notes:</p>
<textarea style="width:100%;resize:vertical;" id="lora-manager-notes" placeholder="Place for things you want to remember..."></textarea>
<p id="civitai-section" class="displayNone">
<b>Civitai model page:</b>
<a id="civitai-model-page" target="_blank"></a>
</p>
</div>
</div>`
let tabHTML=`
<div id="model-tool-tab-bar" class="tab-container tab-centered">
<span id="tab-model-loraUI" class="tab active">
<span><i class="fa-solid fa-key"></i> Lora Keywords</small></span>
</span>
<span id="tab-model-mergeUI" class="tab">
<span><i class="fa-solid fa-code-merge"></i> Merge Models</small></span>
</span>
</div>
<div id="model-tool-tab-content" class="panel-box">
<div id="tab-content-model-loraUI" class="tab-content active">
<div class="tab-content-inner">
${loraUI}
</div>
</div>
<div id="tab-content-model-mergeUI" class="tab-content">
<div class="tab-content-inner">
${mergeUI}
</div>
</div>
</div>`
///////////////////// Function section ///////////////////// Function section
function smoothstep(x) { function smoothstep(x) {
return x * x * (3 - 2 * x) return x * x * (3 - 2 * x)
@ -140,189 +471,13 @@
} }
drawDiagram(fn) drawDiagram(fn)
} }
createTab({
id: "merge",
icon: "fa-code-merge",
label: "Merge models",
css: `
#tab-content-merge .tab-content-inner {
max-width: 100%;
padding: 10pt;
}
.merge-container {
margin-left: 15%;
margin-right: 15%;
text-align: left;
display: inline-grid;
grid-template-columns: 1fr 1fr;
grid-template-rows: auto auto auto;
gap: 0px 0px;
grid-auto-flow: row;
grid-template-areas:
"merge-input merge-config"
"merge-buttons merge-buttons";
}
.merge-container p {
margin-top: 3pt;
margin-bottom: 3pt;
}
.merge-config .tab-content {
background: var(--background-color1);
border-radius: 3pt;
}
.merge-config .tab-content-inner {
text-align: left;
}
.merge-input {
grid-area: merge-input;
padding-left:1em;
}
.merge-config {
grid-area: merge-config;
padding:1em;
}
.merge-config input {
margin-bottom: 3px;
}
.merge-config select {
margin-bottom: 3px;
}
.merge-buttons {
grid-area: merge-buttons;
padding:1em;
text-align: center;
}
#merge-button {
padding: 8px;
width:20em;
}
div#merge-log {
height:150px;
overflow-x:hidden;
overflow-y:scroll;
background:var(--background-color1);
border-radius: 3pt;
}
div#merge-log i {
color: hsl(var(--accent-hue), 100%, calc(2*var(--accent-lightness)));
font-family: monospace;
}
.disabled {
background: var(--background-color4);
color: var(--text-color);
}
#merge-type-tabs {
border-bottom: 1px solid black;
}
#merge-log-container {
display: none;
}
.merge-container #merge-warning {
color: rgb(153, 153, 153);
}`,
content: `
<div class="merge-container panel-box">
<div class="merge-input">
<p><label for="#mergeModelA">Select Model A:</label></p>
<input id="mergeModelA" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<p><label for="#mergeModelB">Select Model B:</label></p>
<input id="mergeModelB" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<br/><br/>
<p id="merge-warning"><small><b>Important:</b> Please merge models of similar type.<br/>For e.g. <code>SD 1.4</code> models with only <code>SD 1.4/1.5</code> models,<br/><code>SD 2.0</code> with <code>SD 2.0</code>-type, and <code>SD 2.1</code> with <code>SD 2.1</code>-type models.</small></p>
<br/>
<table>
<tr>
<td><label for="#merge-filename">Output file name:</label></td>
<td><input id="merge-filename" size=24> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Base name of the output file.<br>Mix ratio and file suffix will be appended to this.</span></i></td>
</tr>
<tr>
<td><label for="#merge-fp">Output precision:</label></td>
<td><select id="merge-fp">
<option value="fp16">fp16 (smaller file size)</option>
<option value="fp32">fp32 (larger file size)</option>
</select>
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Image generation uses fp16, so it's a good choice.<br>Use fp32 if you want to use the result models for more mixes</span></i>
</td>
</tr>
<tr>
<td><label for="#merge-format">Output file format:</label></td>
<td><select id="merge-format">
<option value="safetensors">Safetensors (recommended)</option>
<option value="ckpt">CKPT/Pickle (legacy format)</option>
</select>
</td>
</tr>
</table>
<br/>
<div id="merge-log-container">
<p><label for="#merge-log">Log messages:</label></p>
<div id="merge-log"></div>
</div>
</div>
<div class="merge-config">
<div class="tab-container">
<span id="tab-merge-opts-single" class="tab active">
<span>Make a single file</small></span>
</span>
<span id="tab-merge-opts-batch" class="tab">
<span>Make multiple variations</small></span>
</span>
</div>
<div>
<div id="tab-content-merge-opts-single" class="tab-content active">
<div class="tab-content-inner">
<small>Saves a single merged model file, at the specified merge ratio.</small><br/><br/>
<label for="#single-merge-ratio-slider">Merge ratio:</label>
<input id="single-merge-ratio-slider" name="single-merge-ratio-slider" class="editor-slider" value="50" type="range" min="1" max="1000">
<input id="single-merge-ratio" size=2 value="5">%
<i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Model A's contribution to the mix. The rest will be from Model B.</span></i>
</div>
</div>
<div id="tab-content-merge-opts-batch" class="tab-content">
<div class="tab-content-inner">
<small>Saves multiple variations of the model, at different merge ratios.<br/>Each variation will be saved as a separate file.</small><br/><br/>
<table>
<tr><td><label for="#merge-count">Number of variations:</label></td>
<td> <input id="merge-count" size=2 value="5"></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Number of models to create</span></i></td></tr>
<tr><td><label for="#merge-start">Starting merge ratio:</label></td>
<td> <input id="merge-start" size=2 value="5">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Smallest share of model A in the mix</span></i></td></tr>
<tr><td><label for="#merge-step">Increment each step:</label></td>
<td> <input id="merge-step" size=2 value="10">%</td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Share of model A added into the mix per step</span></i></td></tr>
<tr><td><label for="#merge-interpolation">Interpolation model:</label></td>
<td> <select id="merge-interpolation">
<option>Exact</option>
<option>SmoothStep</option>
<option>SmootherStep</option>
<option>SmoothestStep</option>
</select></td>
<td> <i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Sigmoid function to be applied to the model share before mixing</span></i></td></tr>
</table>
<br/>
<small>Preview of variation ratios:</small><br/>
<canvas id="merge-canvas" width="400" height="400"></canvas>
</div>
</div>
</div>
</div>
<div class="merge-buttons">
<button id="merge-button" class="primaryButton">Merge models</button>
</div>
</div>`,
onOpen: ({ firstOpen }) => {
if (!firstOpen) {
return
}
function initMergeUI() {
const tabSettingsSingle = document.querySelector("#tab-merge-opts-single") const tabSettingsSingle = document.querySelector("#tab-merge-opts-single")
const tabSettingsBatch = document.querySelector("#tab-merge-opts-batch") const tabSettingsBatch = document.querySelector("#tab-merge-opts-batch")
linkTabContents(tabSettingsSingle) linkTabContents(tabSettingsSingle)
linkTabContents(tabSettingsBatch) linkTabContents(tabSettingsBatch)
console.log("Activate")
let mergeModelAField = new ModelDropdown(document.querySelector("#mergeModelA"), "stable-diffusion") let mergeModelAField = new ModelDropdown(document.querySelector("#mergeModelA"), "stable-diffusion")
let mergeModelBField = new ModelDropdown(document.querySelector("#mergeModelB"), "stable-diffusion") let mergeModelBField = new ModelDropdown(document.querySelector("#mergeModelB"), "stable-diffusion")
updateChart() updateChart()
@ -449,6 +604,133 @@
hypernetworkModelField.innerHTML = "" hypernetworkModelField.innerHTML = ""
await getModels() await getModels()
}) })
}
const LoraUI = {
modelField: undefined,
keywordsField: undefined,
notesField: undefined,
civitaiImportBtn: undefined,
civitaiSecion: undefined,
civitaiAnchor: undefined,
image: undefined,
imagePlaceholder: undefined,
init() {
LoraUI.modelField = new ModelDropdown(document.querySelector("#loraModel"), "lora")
LoraUI.keywordsField = document.querySelector("#lora-manager-keywords")
LoraUI.notesField = document.querySelector("#lora-manager-notes")
LoraUI.civitaiImportBtn = document.querySelector("#lora-keyword-from-civitai")
LoraUI.civitaiSection = document.querySelector("#civitai-section")
LoraUI.civitaiAnchor = document.querySelector("#civitai-model-page")
LoraUI.image = document.querySelector("#lora-manager-image")
LoraUI.imagePlaceholder = document.querySelector("#lora-manager-image-placeholder")
LoraUI.modelField.addEventListener("change", LoraUI.updateFields)
LoraUI.keywordsField.addEventListener("focusout", LoraUI.saveInfos)
LoraUI.notesField.addEventListener("focusout", LoraUI.saveInfos)
LoraUI.civitaiImportBtn.addEventListener("click", LoraUI.importFromCivitai)
LoraUI.updateFields()
},
updateFields() {
document.getElementById("civitai-section").classList.add("displayNone")
Bucket.retrieve(`modelinfo/lora/${LoraUI.modelField.value}`)
.then((info) => {
if (info == null) {
LoraUI.keywordsField.value = ""
LoraUI.notesField.value = ""
LoraUI.hideCivitaiLink()
} else {
LoraUI.keywordsField.value = info.keywords.join("\n")
LoraUI.notesField.value = info.notes
if ("civitai" in info) {
LoraUI.showCivitaiLink(info.civitai)
}
}
})
Bucket.getImageAsDataURL(`${profileNameField.value}/lora/${LoraUI.modelField.value}.png`)
.then((data) => {
LoraUI.image.src=data
LoraUI.image.classList.remove("displayNone")
LoraUI.imagePlaceholder.classList.add("displayNone")
})
.catch((error) => {
console.error("Caught error:", error)
LoraUI.image.classList.add("displayNone")
LoraUI.imagePlaceholder.classList.remove("displayNone")
})
},
saveInfos() {
let info = {
keywords: LoraUI.keywordsField.value
.split("\n")
.filter((x) => (x != "")),
notes: LoraUI.notesField.value,
civitai: LoraUI.civitaiSection.checkVisibility() ? LoraUI.civitaiAnchor.href : null,
}
Bucket.store(`modelinfo/lora/${LoraUI.modelField.value}`, info)
},
importFromCivitai() {
document.body.style["cursor"] = "progress"
fetch("/sha256/lora/"+LoraUI.modelField.value)
.then((result) => result.json())
.then((json) => fetch("https://civitai.com/api/v1/model-versions/by-hash/" + json.digest))
.then((result) => result.json())
.then((json) => {
document.body.style["cursor"] = "default"
if (json == null) {
return
}
if ("trainedWords" in json) {
LoraUI.keywordsField.value = json["trainedWords"].join("\n")
} else {
showToast("No keyword info found.")
}
if ("modelId" in json) {
LoraUI.showCivitaiLink("https://civitai.com/models/" + json.modelId)
} else {
LoraUI.hideCivitaiLink()
}
LoraUI.saveInfos()
})
},
showCivitaiLink(href) {
LoraUI.civitaiSection.classList.remove("displayNone")
LoraUI.civitaiAnchor.href = href
LoraUI.civitaiAnchor.innerHTML = LoraUI.civitaiAnchor.href
},
hideCivitaiLink() {
LoraUI.civitaiSection.classList.add("displayNone")
}
}
createTab({
id: "merge",
icon: "fa-toolbox",
label: "Model tools",
css: mergeCSS,
content: tabHTML,
onOpen: ({ firstOpen }) => {
if (!firstOpen) {
return
}
initMergeUI()
LoraUI.init()
const tabMergeUI = document.querySelector("#tab-model-mergeUI")
const tabLoraUI = document.querySelector("#tab-model-loraUI")
linkTabContents(tabMergeUI)
linkTabContents(tabLoraUI)
}, },
}) })
})() })()
async function getLoraKeywords(model) {
return Bucket.retrieve(`modelinfo/lora/${model}`)
.then((info) => info.keywords)
}