diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index f8f2d3bf..4c188183 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -191,7 +191,9 @@ call WHERE uvicorn > .tmp
 
 
 if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
+if not exist "..\models\vae" mkdir "..\models\vae"
 echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
+echo. > "..\models\vae\Put your VAE files here.txt"
 
 @if exist "sd-v1-4.ckpt" (
     for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
@@ -321,22 +323,22 @@ echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
 
 
 
-@if exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" (
-    for %%I in ("..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt") do if "%%~zI" EQU "334695179" (
+@if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
+    for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" EQU "334695179" (
         echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
     ) else (
-        echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
-        del "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt"
+        echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\vae\vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
+        del "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt"
     )
 )
 
-@if not exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" (
+@if not exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
     @echo. & echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." & echo.
 
-    @call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt
+    @call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt
 
-    @if exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" (
-        for %%I in ("..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt") do if "%%~zI" NEQ "334695179" (
+    @if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
+        for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" NEQ "334695179" (
             echo. & echo "Error: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: %%~zI" & echo.
             echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
             pause
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index eedc798b..6facac16 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -170,7 +170,9 @@ fi
 
 
 mkdir -p "../models/stable-diffusion"
+mkdir -p "../models/vae"
 echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt"
+echo "" > "../models/vae/Put your VAE files here.txt"
 
 if [ -f "sd-v1-4.ckpt" ]; then
     model_size=`find "sd-v1-4.ckpt" -printf "%s"`
@@ -300,24 +302,24 @@ if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
 fi
 
 
-if [ -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then
-    model_size=`find ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt -printf "%s"`
+if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
+    model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
 
     if [ "$model_size" -eq "334695179" ]; then
         echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
     else
-        printf "\n\nThe model file present at models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt is invalid. It is only $model_size bytes in size. Re-downloading.."
-        rm ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt
+        printf "\n\nThe model file present at models/vae/vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
+        rm ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
     fi
 fi
 
-if [ ! -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then
+if [ ! -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
     echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).."
 
-    curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt
+    curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
 
-    if [ -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then
-        model_size=`find ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt -printf "%s"`
+    if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
+        model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
         if [ ! "$model_size" -eq "334695179" ]; then
             printf "\n\nError: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: $model_size\n\n"
             printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n  1. Run this installer again.\n  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"
diff --git a/ui/index.html b/ui/index.html
index 67c0cc65..866d4649 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -7,7 +7,7 @@
     <link rel="icon" type="image/png" href="/media/images/favicon-32x32.png" sizes="32x32">
     <link rel="stylesheet" href="/media/css/fonts.css?v=1">
     <link rel="stylesheet" href="/media/css/themes.css?v=1">
-    <link rel="stylesheet" href="/media/css/main.css?v=4">
+    <link rel="stylesheet" href="/media/css/main.css?v=6">
     <link rel="stylesheet" href="/media/css/auto-save.css?v=3">
     <link rel="stylesheet" href="/media/css/modifier-thumbnails.css?v=3">
     <link rel="stylesheet" href="/media/css/fontawesome-all.min.css?v=1">
@@ -19,7 +19,7 @@
 <div id="container">
     <div id="top-nav">
         <div id="logo">
-            <h1>Stable Diffusion UI <small>v2.3.9 <span id="updateBranchLabel"></span></small></h1>
+            <h1>Stable Diffusion UI <small>v2.3.10 <span id="updateBranchLabel"></span></small></h1>
         </div>
         <div id="server-status">
             <div id="server-status-color">●</div>
@@ -47,7 +47,11 @@
                     <textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea>
                     <input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden -->
 
-                    <label for="negative_prompt" class="collapsible" id="negative_prompt_handle">Negative Prompt <small>(optional)</small></label>
+                    <label for="negative_prompt" class="collapsible" id="negative_prompt_handle">
+                        Negative Prompt
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about Negative Prompts</span></i></a>
+                        <small>(optional)</small>
+                    </label>
                     <div class="collapsible-content">
                         <input id="negative_prompt" name="negative_prompt" placeholder="list the things to remove from the image (e.g. fog, green)">
                     </div>
@@ -64,7 +68,12 @@
                         </div>
 
                         <br/>
-                        <input id="enable_mask" name="enable_mask" type="checkbox"> <label for="enable_mask">In-Painting (beta) <small>(select the area which the AI will paint into)</small></label>
+                        <input id="enable_mask" name="enable_mask" type="checkbox">
+                        <label for="enable_mask">
+                            In-Painting (beta)
+                            <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Inpainting" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about InPainting</span></i></a>
+                            <small>(select the area which the AI will paint into)</small>
+                        </label>
                         <div id="inpaintingEditor"></div>
                     </div>
                 </div>
@@ -92,12 +101,19 @@
                 <div id="editor-settings-entries" class="collapsible-content">
                     <div><table>
                     <tr><b class="settings-subheader">Image Settings</b></tr>
-                    <tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="30000"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
-                    <tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
+                    <tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="30000" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
+                    <tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
                     <tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td>
                         <select id="stable_diffusion_model" name="stable_diffusion_model">
                             <!-- <option value="sd-v1-4" selected>sd-v1-4</option> -->
                         </select>
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about custom models</span></i></a>
+                    </td></tr>
+                    <tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
+                        <select id="vae_model" name="vae_model">
+                            <!-- <option value="" selected>None</option> -->
+                        </select>
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about VAEs</span></i></a>
                     </td></tr>
                     <tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td>
                         <select id="sampler" name="sampler">
@@ -110,6 +126,7 @@
                             <option value="dpm2_a">dpm2_a</option>
                             <option value="lms">lms</option>
                         </select>
+                        <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about samplers</span></i></a>
                     </td></tr>
                     <tr class="pl-5"><td><label>Image Size: </label></td><td>
                         <select id="width" name="width" value="512">
@@ -157,9 +174,9 @@
                         </select>
                         <label for="height"><small>(height)</small></label>
                     </td></tr>
-                    <tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25"></td></tr>
-                    <tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4"></td></tr>
-                    <tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4"><br/></td></tr></span>
+                    <tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25" onkeypress="preventNonNumericalInput(event)"></td></tr>
+                    <tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
+                    <tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td></tr></span>
                     <tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td>
                         <select id="output_format" name="output_format">
                             <option value="jpeg" selected>jpeg</option>
@@ -170,7 +187,7 @@
 
                     <div><ul>
                     <li><b class="settings-subheader">Render Settings</b></li>
-                    <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slightly slower image creation)</small></label></li>
+                    <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, and slower image creation)</small></label></li>
                     <li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox" checked> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
                     <li class="pl-5">
                         <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
@@ -274,14 +291,15 @@
 </div>
 </body>
 
-<script src="media/js/parameters.js?v=1"></script>
+<script src="media/js/parameters.js?v=2"></script>
 <script src="media/js/plugins.js?v=1"></script>
-<script src="media/js/utils.js?v=4"></script>
+<script src="media/js/utils.js?v=5"></script>
 <script src="media/js/inpainting-editor.js?v=1"></script>
 <script src="media/js/image-modifiers.js?v=4"></script>
-<script src="media/js/auto-save.js?v=3"></script>
-<script src="media/js/main.js?v=7"></script>
+<script src="media/js/auto-save.js?v=4"></script>
+<script src="media/js/main.js?v=8"></script>
 <script src="media/js/themes.js?v=3"></script>
+<script src="media/js/dnd.js?v=6"></script>
 <script>
 async function init() {
     await initSettings()
diff --git a/ui/media/css/main.css b/ui/media/css/main.css
index bab54268..27043067 100644
--- a/ui/media/css/main.css
+++ b/ui/media/css/main.css
@@ -593,13 +593,38 @@ input::file-selector-button {
     #server-status {
         top: 66%;
     }
+    .popup > div {
+        padding-left: 5px !important;
+        padding-right: 5px !important;
+    }
+    .popup > div input, .popup > div select {
+        max-width: 40vw;
+    }
+    .popup .close-button {
+        padding: 0px !important;
+        margin: 24px !important;
+    }
+    .simple-tooltip.right {
+        right: initial;
+        left: 0px;
+        top: 50%;
+        transform: translate(calc(-100% + 15%), -50%);
+    }
+    :hover > .simple-tooltip.right {
+        transform: translate(100%, -50%);
+    }
 }
+
 @media (min-width: 700px) {
     #editor {
         max-width: 500px;
     }
 }
 
+.help-btn {
+    position: relative;
+}
+
 #promptsFromFileBtn {
     font-size: 9pt;
 }
@@ -608,6 +633,20 @@ input::file-selector-button {
     position: relative;
     transform: translateY(-13%);
 }
+#copy-image-settings {
+    position: relative;
+    cursor: pointer;
+    padding: 8px;
+    opacity: 1;
+    transition: opacity 0.2;
+}
+.collapsible:not(.active) #copy-image-settings {
+    display: none;
+}
+#copy-image-settings.hidden {
+    opacity: 0;
+    pointer-events: none;
+}
 
 .section-button {
     cursor: pointer;
@@ -633,7 +672,7 @@ input::file-selector-button {
 .simple-tooltip {
 	border-radius: 3px;
 	font-weight: bold;
-	font-size: 16px;
+	font-size: 12px;
     background-color: var(--background-color3);
 
 	visibility: hidden;
@@ -744,6 +783,12 @@ input::file-selector-button {
     transition: 0s visibility, 0.3s opacity;
 }
 
+@media only screen and (min-height: 1050px) {
+    .popup {
+        position: fixed;
+    }
+}
+
 .popup > div {
     position: relative;
     background: var(--background-color2);
@@ -806,33 +851,3 @@ input::file-selector-button {
 }
 
 
-/* FLOATING FIXED STUFF */
-/*
-@media (min-width: 700px) {
-    #editor {
-        max-width: 500px;
-    }
-
-    #tab-content {
-        flex-direction: column;
-    }
-
-    #editor {
-        flex-direction: row;
-        max-width: none;
-        max-height: 500px;
-    }
-
-    #editor .line-separator {
-        height: inherit;
-        flex-basis: 8px;
-        flex-grow: 0;
-        flex-shrink: 0;
-        margin: 0px 16px;
-    }
-
-    #editor-settings-entries {
-        flex-direction: row;
-    } 
-}
-*/
diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index 327d9d4a..5fec8433 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -13,6 +13,7 @@ const SETTINGS_IDS_LIST = [
     "num_outputs_total",
     "num_outputs_parallel",
     "stable_diffusion_model",
+    "vae_model",
     "sampler",
     "width",
     "height",
diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
new file mode 100644
index 00000000..14c98a99
--- /dev/null
+++ b/ui/media/js/dnd.js
@@ -0,0 +1,417 @@
+"use strict" // Opt in to a restricted variant of JavaScript
+
+function parseBoolean(stringValue) {
+    if (typeof stringValue === 'boolean') {
+        return stringValue
+    }
+    if (typeof stringValue === 'number') {
+        return stringValue !== 0
+    }
+    if (typeof stringValue !== 'string') {
+        return false
+    }
+    switch(stringValue?.toLowerCase()?.trim()) {
+        case "true":
+        case "yes":
+        case "on":
+        case "1":
+          return true;
+
+        case "false":
+        case "no":
+        case "off":
+        case "0":
+        case null:
+        case undefined:
+          return false;
+    }
+    try {
+        return Boolean(JSON.parse(stringValue));
+    } catch {
+        return Boolean(stringValue)
+    }
+}
+
+const TASK_MAPPING = {
+    prompt: { name: 'Prompt',
+        setUI: (prompt) => {
+            promptField.value = prompt
+        },
+        readUI: () => promptField.value,
+        parse: (val) => val
+    },
+    negative_prompt: { name: 'Negative Prompt',
+        setUI: (negative_prompt) => {
+            negativePromptField.value = negative_prompt
+        },
+        readUI: () => negativePromptField.value,
+        parse: (val) => val
+    },
+    width: { name: 'Width',
+        setUI: (width) => {
+            const oldVal = widthField.value
+            widthField.value = width
+            if (!widthField.value) {
+                widthField.value = oldVal
+            }
+        },
+        readUI: () => parseInt(widthField.value),
+        parse: (val) => parseInt(val)
+    },
+    height: { name: 'Height',
+        setUI: (height) => {
+            const oldVal = heightField.value
+            heightField.value = height
+            if (!heightField.value) {
+                heightField.value = oldVal
+            }
+        },
+        readUI: () => parseInt(heightField.value),
+        parse: (val) => parseInt(val)
+    },
+    seed: { name: 'Seed',
+        setUI: (seed) => {
+            if (!seed) {
+                randomSeedField.checked = true
+                seedField.disabled = true
+                return
+            }
+            randomSeedField.checked = false
+            seedField.disabled = false
+            seedField.value = seed
+        },
+        readUI: () => (randomSeedField.checked ? Math.floor(Math.random() * 10000000) : parseInt(seedField.value)),
+        parse: (val) => parseInt(val)
+    },
+    num_inference_steps: { name: 'Steps',
+        setUI: (num_inference_steps) => {
+            numInferenceStepsField.value = num_inference_steps
+        },
+        readUI: () => parseInt(numInferenceStepsField.value),
+        parse: (val) => parseInt(val)
+    },
+    guidance_scale: { name: 'Guidance Scale',
+        setUI: (guidance_scale) => {
+            guidanceScaleField.value = guidance_scale
+            updateGuidanceScaleSlider()
+        },
+        readUI: () => parseFloat(guidanceScaleField.value),
+        parse: (val) => parseFloat(val)
+    },
+    prompt_strength: { name: 'Prompt Strength',
+        setUI: (prompt_strength) => {
+            promptStrengthField.value = prompt_strength
+            updatePromptStrengthSlider()
+        },
+        readUI: () => parseFloat(promptStrengthField.value),
+        parse: (val) => parseFloat(val)
+    },
+
+    init_image:  { name: 'Initial Image',
+        setUI: (init_image) => {
+            initImagePreview.src = init_image
+        },
+        readUI: () => initImagePreview.src,
+        parse: (val) => val
+    },
+    mask:  { name: 'Mask',
+        setUI: (mask) => {
+            inpaintingEditor.setImg(mask)
+            maskSetting.checked = Boolean(mask)
+        },
+        readUI: () => (maskSetting.checked ? inpaintingEditor.getImg() : undefined),
+        parse: (val) => val
+    },
+
+    use_face_correction: { name: 'Use Face Correction',
+        setUI: (use_face_correction) => {
+            useFaceCorrectionField.checked = parseBoolean(use_face_correction)
+        },
+        readUI: () => useFaceCorrectionField.checked,
+        parse: (val) => parseBoolean(val)
+    },
+    use_upscale: { name: 'Use Upscaling',
+        setUI: (use_upscale) => {
+            const oldVal = upscaleModelField.value
+            upscaleModelField.value = use_upscale
+            if (upscaleModelField.value) { // Is a valid value for the field.
+                useUpscalingField.checked = true
+                upscaleModelField.disabled = false
+            } else { // Not a valid value, restore the old value and disable the filter.
+                upscaleModelField.disabled = true
+                upscaleModelField.value = oldVal
+                useUpscalingField.checked = false
+            }
+        },
+        readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
+        parse: (val) => val
+    },
+    sampler: { name: 'Sampler',
+        setUI: (sampler) => {
+            samplerField.value = sampler
+        },
+        readUI: () => samplerField.value,
+        parse: (val) => val
+    },
+    use_stable_diffusion_model: { name: 'Stable Diffusion model',
+        setUI: (use_stable_diffusion_model) => {
+            const oldVal = stableDiffusionModelField.value
+
+            let pathIdx = use_stable_diffusion_model.lastIndexOf('/') // Linux, Mac paths
+            if (pathIdx < 0) {
+                pathIdx = use_stable_diffusion_model.lastIndexOf('\\') // Windows paths.
+            }
+            if (pathIdx >= 0) {
+                use_stable_diffusion_model = use_stable_diffusion_model.slice(pathIdx + 1)
+            }
+            const modelExt = '.ckpt'
+            if (use_stable_diffusion_model.endsWith(modelExt)) {
+                use_stable_diffusion_model = use_stable_diffusion_model.slice(0, use_stable_diffusion_model.length - modelExt.length)
+            }
+
+            stableDiffusionModelField.value = use_stable_diffusion_model
+
+            if (!stableDiffusionModelField.value) {
+                stableDiffusionModelField.value = oldVal
+            }
+        },
+        readUI: () => stableDiffusionModelField.value,
+        parse: (val) => val
+    },
+
+    numOutputsParallel: { name: 'Parallel Images',
+        setUI: (numOutputsParallel) => {
+            numOutputsParallelField.value = numOutputsParallel
+        },
+        readUI: () => parseInt(numOutputsParallelField.value),
+        parse: (val) => val
+    },
+
+    use_cpu: { name: 'Use CPU',
+        setUI: (use_cpu) => {
+            useCPUField.checked = use_cpu
+        },
+        readUI: () => useCPUField.checked,
+        parse: (val) => val
+    },
+    turbo: { name: 'Turbo',
+        setUI: (turbo) => {
+            turboField.checked = turbo
+        },
+        readUI: () => turboField.checked,
+        parse: (val) => Boolean(val)
+    },
+    use_full_precision: { name: 'Use Full Precision',
+        setUI: (use_full_precision) => {
+            useFullPrecisionField.checked = use_full_precision
+        },
+        readUI: () => useFullPrecisionField.checked,
+        parse: (val) => Boolean(val)
+    },
+
+    stream_image_progress: { name: 'Stream Image Progress',
+        setUI: (stream_image_progress) => {
+            streamImageProgressField.checked = (parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress)
+        },
+        readUI: () => streamImageProgressField.checked,
+        parse: (val) => Boolean(val)
+    },
+    show_only_filtered_image: { name: 'Show only the corrected/upscaled image',
+        setUI: (show_only_filtered_image) => {
+            showOnlyFilteredImageField.checked = show_only_filtered_image
+        },
+        readUI: () => showOnlyFilteredImageField.checked,
+        parse: (val) => Boolean(val)
+    },
+    output_format: { name: 'Output Format',
+        setUI: (output_format) => {
+            outputFormatField.value = output_format
+        },
+        readUI: () => outputFormatField.value,
+        parse: (val) => val
+    },
+    save_to_disk_path: { name: 'Save to disk path',
+        setUI: (save_to_disk_path) => {
+            saveToDiskField.checked = Boolean(save_to_disk_path)
+            diskPathField.value = save_to_disk_path
+        },
+        readUI: () => diskPathField.value,
+        parse: (val) => val
+    }
+}
+function restoreTaskToUI(task) {
+    if ('numOutputsTotal' in task) {
+        numOutputsTotalField.value = task.numOutputsTotal
+    }
+    if ('seed' in task) {
+        randomSeedField.checked = false
+        seedField.value = task.seed
+    }
+    if (!('reqBody' in task)) {
+        return
+    }
+    for (const key in TASK_MAPPING) {
+        if (key in task.reqBody) {
+            TASK_MAPPING[key].setUI(task.reqBody[key])
+        }
+    }
+}
+function readUI() {
+    const reqBody = {}
+    for (const key in TASK_MAPPING) {
+        reqBody[key] = TASK_MAPPING[key].readUI()
+    }
+    return {
+        'numOutputsTotal': parseInt(numOutputsTotalField.value),
+        'seed': TASK_MAPPING['seed'].readUI(),
+        'reqBody': reqBody
+    }
+}
+
+const TASK_TEXT_MAPPING = {
+    width: 'Width',
+    height: 'Height',
+    seed: 'Seed',
+    num_inference_steps: 'Steps',
+    guidance_scale: 'Guidance Scale',
+    prompt_strength: 'Prompt Strength',
+    use_face_correction: 'Use Face Correction',
+    use_upscale: 'Use Upscaling',
+    sampler: 'Sampler',
+    negative_prompt: 'Negative Prompt',
+    use_stable_diffusion_model: 'Stable Diffusion model'
+}
+const afterPromptRe = /^\s*Width\s*:\s*\d+\s*(?:\r\n|\r|\n)+\s*Height\s*:\s*\d+\s*(\r\n|\r|\n)+Seed\s*:\s*\d+\s*$/igm
+function parseTaskFromText(str) {
+    const taskReqBody = {}
+
+    // Prompt
+    afterPromptRe.lastIndex = 0
+    const match = afterPromptRe.exec(str)
+    if (match) {
+        let prompt = str.slice(0, match.index)
+        str = str.slice(prompt.length)
+        taskReqBody.prompt = prompt.trim()
+        console.log('Prompt:', taskReqBody.prompt)
+    }
+    for (const key in TASK_TEXT_MAPPING) {
+        const name = TASK_TEXT_MAPPING[key];
+        let val = undefined
+
+        const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, 'igm')
+        const match = reName.exec(str);
+        if (match) {
+            console.log(match)
+            str = str.slice(0, match.index) + str.slice(match.index + match[0].length)
+            val = match[1]
+        }
+        if (val !== undefined) {
+            taskReqBody[key] = TASK_MAPPING[key].parse(val.trim())
+            console.log(TASK_MAPPING[key].name + ':', taskReqBody[key])
+            if (!str) {
+                break
+            }
+        }
+    }
+    if (Object.keys(taskReqBody).length <= 0) {
+        return undefined
+    }
+    const task = { reqBody: taskReqBody }
+    if ('seed' in taskReqBody) {
+        task.seed = taskReqBody.seed
+    }
+    return task
+}
+
+async function readFile(file, i) {
+    const fileContent = (await file.text()).trim()
+
+    // JSON File.
+    if (fileContent.startsWith('{') && fileContent.endsWith('}')) {
+        try {
+            const task = JSON.parse(fileContent)
+            restoreTaskToUI(task)
+        } catch (e) {
+            console.warn(`file[${i}]:${file.name} - File couldn't be parsed.`, e)
+        }
+        return
+    }
+
+    // Normal txt file.
+    const task = parseTaskFromText(fileContent)
+    if (task) {
+        restoreTaskToUI(task)
+    } else {
+        console.warn(`file[${i}]:${file.name} - File couldn't be parsed.`)
+    }
+}
+
+function dropHandler(ev) {
+    console.log('Content dropped...')
+    let items = []
+
+    if (ev?.dataTransfer?.items) { // Use DataTransferItemList interface
+        items = Array.from(ev.dataTransfer.items)
+        items = items.filter(item => item.kind === 'file')
+        items = items.map(item => item.getAsFile())
+    } else if (ev?.dataTransfer?.files) { // Use DataTransfer interface
+        items = Array.from(ev.dataTransfer.files)
+    }
+
+    items = items.filter(item => item.name.toLowerCase().endsWith('.txt') || item.name.toLowerCase().endsWith('.json'))
+
+    if (items.length > 0) {
+        ev.preventDefault() // Prevent default behavior (Prevent file/content from being opened)
+        items.forEach(readFile)
+    }
+}
+function dragOverHandler(ev) {
+    console.log('Content in drop zone')
+
+    // Prevent default behavior (Prevent file/content from being opened)
+    ev.preventDefault()
+
+    ev.dataTransfer.dropEffect = "copy"
+
+    let img = new Image()
+    img.src = location.host + '/media/images/favicon-32x32.png'
+    ev.dataTransfer.setDragImage(img, 16, 16)
+}
+
+document.addEventListener("drop", dropHandler)
+document.addEventListener("dragover", dragOverHandler)
+
+const TASK_REQ_NO_EXPORT = [
+    "use_cpu",
+    "turbo",
+    "use_full_precision",
+    "save_to_disk_path"
+]
+
+// Adds a copy icon if the browser grants permission to write to clipboard.
+function checkWriteToClipboardPermission (result) {
+    if (result.state == "granted" || result.state == "prompt") {
+        const resetSettings = document.getElementById('reset-image-settings')
+        const copyIcon = document.createElement('i')
+        copyIcon.id = 'copy-image-settings'
+        copyIcon.className = 'fa-solid fa-clipboard'
+        copyIcon.innerHTML = `<span class="simple-tooltip right">Copy Image Settings</span>`
+        copyIcon.addEventListener('click', (event) => {
+            event.stopPropagation()
+            const uiState = readUI()
+            TASK_REQ_NO_EXPORT.forEach((key) => delete uiState.reqBody[key])
+            if (uiState.reqBody.init_image && !IMAGE_REGEX.test(uiState.reqBody.init_image)) {
+                delete uiState.reqBody.init_image
+                delete uiState.reqBody.prompt_strength
+            }
+            navigator.clipboard.writeText(JSON.stringify(uiState, undefined, 4))
+        })
+        resetSettings.parentNode.insertBefore(copyIcon, resetSettings)
+    }
+}
+navigator.permissions.query({ name: "clipboard-write" }).then(checkWriteToClipboardPermission, (e) => {
+    if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === 'function') {
+        // Fix for firefox https://bugzilla.mozilla.org/show_bug.cgi?id=1560373
+        checkWriteToClipboardPermission({state:"granted"})
+    }
+})
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 581d7164..fac0be99 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -39,7 +39,7 @@ let useFaceCorrectionField = document.querySelector("#use_face_correction")
 let useUpscalingField = document.querySelector("#use_upscale")
 let upscaleModelField = document.querySelector("#upscale_model")
 let stableDiffusionModelField = document.querySelector('#stable_diffusion_model')
-let vaeModelField = document.querySelector('#default_vae_model')
+let vaeModelField = document.querySelector('#vae_model')
 let outputFormatField = document.querySelector('#output_format')
 let showOnlyFilteredImageField = document.querySelector("#show_only_filtered_image")
 let updateBranchLabel = document.querySelector("#updateBranchLabel")
@@ -340,10 +340,10 @@ function onDownloadImageClick(req, img) {
     imgDownload.click()
 }
 
-function modifyCurrentRequest(req, ...reqDiff) {
+function modifyCurrentRequest(...reqDiff) {
     const newTaskRequest = getCurrentUserRequest()
 
-    newTaskRequest.reqBody = Object.assign({}, req, ...reqDiff, {
+    newTaskRequest.reqBody = Object.assign(newTaskRequest.reqBody, ...reqDiff, {
         use_cpu: useCPUField.checked
     })
     newTaskRequest.seed = newTaskRequest.reqBody.seed
@@ -774,6 +774,7 @@ function getCurrentUserRequest() {
             use_cpu: useCPUField.checked,
             use_full_precision: useFullPrecisionField.checked,
             use_stable_diffusion_model: stableDiffusionModelField.value,
+            use_vae_model: vaeModelField.value,
             stream_progress_updates: true,
             stream_image_progress: (numOutputsTotal > 50 ? false : streamImageProgressField.checked),
             show_only_filtered_image: showOnlyFilteredImageField.checked,
@@ -823,7 +824,10 @@ function makeImage() {
 
 function createTask(task) {
     let taskConfig = `Seed: ${task.seed}, Sampler: ${task.reqBody.sampler}, Inference Steps: ${task.reqBody.num_inference_steps}, Guidance Scale: ${task.reqBody.guidance_scale}, Model: ${task.reqBody.use_stable_diffusion_model}`
-    if (negativePromptField.value.trim() !== '') {
+    if (task.reqBody.use_vae_model.trim() !== '') {
+        taskConfig += `, VAE: ${task.reqBody.use_vae_model}`
+    }
+    if (task.reqBody.negative_prompt.trim() !== '') {
         taskConfig += `, Negative Prompt: ${task.reqBody.negative_prompt}`
     }
     if (task.reqBody.init_image !== undefined) {
@@ -1141,12 +1145,6 @@ useBetaChannelField.addEventListener('click', async function(e) {
     })
 })
 
-vaeModelField.addEventListener('change', async function() {
-    await changeAppConfig({
-        'model_vae': this.value
-    })
-})
-
 async function getAppConfig() {
     try {
         let res = await fetch('/get/app_config')
@@ -1165,22 +1163,25 @@ async function getAppConfig() {
 
 async function getModels() {
     try {
-        var model_setting_key = "stable_diffusion_model"
-        var selectedModel = SETTINGS[model_setting_key].value
+        var sd_model_setting_key = "stable_diffusion_model"
+        var vae_model_setting_key = "vae_model"
+        var selectedSDModel = SETTINGS[sd_model_setting_key].value
+        var selectedVaeModel = SETTINGS[vae_model_setting_key].value
         let res = await fetch('/get/models')
         const models = await res.json()
 
-        let activeModels = models['active']
+        console.log('get models response', models)
+
         let modelOptions = models['options']
         let stableDiffusionOptions = modelOptions['stable-diffusion']
         let vaeOptions = modelOptions['vae']
-        let activeVae = activeModels['vae']
+        vaeOptions.unshift('') // add a None option
 
         function createModelOptions(modelField, selectedModel) {
             return function(modelName) {
                 let modelOption = document.createElement('option')
                 modelOption.value = modelName
-                modelOption.innerText = modelName
+                modelOption.innerText = modelName !== '' ? modelName : 'None'
 
                 if (modelName === selectedModel) {
                     modelOption.selected = true
@@ -1190,16 +1191,14 @@ async function getModels() {
             }
         }
 
-        stableDiffusionOptions.forEach(createModelOptions(stableDiffusionModelField, selectedModel))
-        vaeOptions.forEach(createModelOptions(vaeModelField, activeVae))
+        stableDiffusionOptions.forEach(createModelOptions(stableDiffusionModelField, selectedSDModel))
+        vaeOptions.forEach(createModelOptions(vaeModelField, selectedVaeModel))
 
         // TODO: set default for model here too
-        SETTINGS[model_setting_key].default = stableDiffusionOptions[0]
-        if (getSetting(model_setting_key) == '' || SETTINGS[model_setting_key].value == '') {
-            setSetting(model_setting_key, stableDiffusionOptions[0])
+        SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
+        if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
+            setSetting(sd_model_setting_key, stableDiffusionOptions[0])
         }
-
-        console.log('get models response', models)
     } catch (e) {
         console.log('get models error', e)
     }
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index ec35f718..0e541cd7 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -51,11 +51,6 @@ var PARAMETERS = [
 			return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
 		}
 	},
-	{
-		id: "default_vae_model",
-		type: ParameterType.select, // Note: options generated dynamically
-		label: "Default VAE",
-	},
 	{
 		id: "sound_toggle",
 		type: ParameterType.checkbox,
diff --git a/ui/media/js/utils.js b/ui/media/js/utils.js
index 6dd0b903..3172579f 100644
--- a/ui/media/js/utils.js
+++ b/ui/media/js/utils.js
@@ -30,9 +30,15 @@ function toggleCollapsible(element) {
     collapsibleHeader.classList.toggle("active")
     let content = getNextSibling(collapsibleHeader, '.collapsible-content')
     if (!collapsibleHeader.classList.contains("active")) {
-        handle.innerHTML = '&#x2795;' // plus
+        content.style.display = "none"
+        if (handle != null) {  // render results don't have a handle
+            handle.innerHTML = '&#x2795;' // plus
+        }
     } else {
-        handle.innerHTML = '&#x2796;' // minus
+        content.style.display = "block"
+        if (handle != null) {  // render results don't have a handle
+            handle.innerHTML = '&#x2796;' // minus
+        }
     }
     
     if (COLLAPSIBLES_INITIALIZED && COLLAPSIBLE_PANELS.includes(element)) {
@@ -340,3 +346,15 @@ function asyncDelay(timeout) {
         setTimeout(resolve, timeout, true)
     })
 }
+
+function preventNonNumericalInput(e) {
+    e = e || window.event;
+    let charCode = (typeof e.which == "undefined") ? e.keyCode : e.which;
+    let charStr = String.fromCharCode(charCode);
+    let re = e.target.getAttribute('pattern') || '^[0-9]+$'
+    re = new RegExp(re)
+
+    if (!charStr.match(re)) {
+        e.preventDefault();
+    }
+}
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 0b159ae7..da5f6b59 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -18,7 +18,6 @@ class Request:
     precision: str = "autocast" # or "full"
     save_to_disk_path: str = None
     turbo: bool = True
-    use_cpu: bool = False
     use_full_precision: bool = False
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
@@ -50,7 +49,7 @@ class Request:
             "output_format": self.output_format,
         }
 
-    def to_string(self):
+    def __str__(self):
         return f'''
     session_id: {self.session_id}
     prompt: {self.prompt}
@@ -64,7 +63,6 @@ class Request:
     precision: {self.precision}
     save_to_disk_path: {self.save_to_disk_path}
     turbo: {self.turbo}
-    use_cpu: {self.use_cpu}
     use_full_precision: {self.use_full_precision}
     use_face_correction: {self.use_face_correction}
     use_upscale: {self.use_upscale}
diff --git a/ui/sd_internal/runtime.py b/ui/sd_internal/runtime.py
index 9e8d2818..20fb51c7 100644
--- a/ui/sd_internal/runtime.py
+++ b/ui/sd_internal/runtime.py
@@ -45,6 +45,25 @@ from io import BytesIO
 from threading import local as LocalThreadVars
 thread_data = LocalThreadVars()
 
+def get_processor_name():
+    try:
+        import platform, subprocess
+        if platform.system() == "Windows":
+            return platform.processor()
+        elif platform.system() == "Darwin":
+            os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
+            command ="sysctl -n machdep.cpu.brand_string"
+            return subprocess.check_output(command).strip()
+        elif platform.system() == "Linux":
+            command = "cat /proc/cpuinfo"
+            all_info = subprocess.check_output(command, shell=True).decode().strip()
+            for line in all_info.split("\n"):
+                if "model name" in line:
+                    return re.sub( ".*model name.*:", "", line,1).strip()
+    except:
+        print(traceback.format_exc())
+        return "cpu"
+
 def device_would_fail(device):
     if device == 'cpu': return None
     # Returns None when no issues found, otherwise returns the detected error str.
@@ -68,17 +87,17 @@ def device_select(device):
         print(failure_msg)
         return False
 
-    device_name = torch.cuda.get_device_name(device)
+    thread_data.device_name = torch.cuda.get_device_name(device)
+    thread_data.device = device
 
-    # otherwise these NVIDIA cards create green images
-    thread_data.force_full_precision = ('nvidia' in device_name.lower() or 'geforce' in device_name.lower()) and (' 1660' in device_name or ' 1650' in device_name)
+    # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
+    device_name = thread_data.device_name.lower()
+    thread_data.force_full_precision = ('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)
     if thread_data.force_full_precision:
-        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', device_name)
+        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', thread_data.device_name)
         # Apply force_full_precision now before models are loaded.
         thread_data.precision = 'full'
 
-    thread_data.device = device
-    thread_data.has_valid_gpu = True
     return True
 
 def device_init(device_selection=None):
@@ -100,27 +119,31 @@ def device_init(device_selection=None):
     thread_data.model_is_half = False
     thread_data.model_fs_is_half = False
     thread_data.device = None
+    thread_data.device_name = None
     thread_data.unet_bs = 1
     thread_data.precision = 'autocast'
     thread_data.sampler_plms = None
     thread_data.sampler_ddim = None
 
     thread_data.turbo = False
-    thread_data.has_valid_gpu = False
     thread_data.force_full_precision = False
     thread_data.reduced_memory = True
 
-    if device_selection.lower() == 'cpu':
-        print('CPU requested, skipping gpu init.')
+    device_selection = device_selection.lower()
+
+    if device_selection == 'cpu':
         thread_data.device = 'cpu'
+        thread_data.device_name = get_processor_name()
+        print('Render device CPU available as', thread_data.device_name)
         return
     if not torch.cuda.is_available():
         if device_selection == 'auto' or device_selection == 'current':
-            print('WARNING: torch.cuda is not available. Using the CPU, but this will be very slow!')
+            print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
             thread_data.device = 'cpu'
+            thread_data.device_name = get_processor_name()
             return
         else:
-            raise EnvironmentError('torch.cuda is not available.')
+            raise EnvironmentError(f'Could not find a compatible GPU for the requested device_selection: {device_selection}!')
     device_count = torch.cuda.device_count()
     if device_count <= 1 and device_selection == 'auto':
         device_selection = 'current' # Use 'auto' only when there is more than one compatible device found.
@@ -141,10 +164,10 @@ def device_init(device_selection=None):
             print(f'Setting GPU:{device} as active')
             torch.cuda.device(device)
             return
-    if isinstance(device_selection, str):
-        device_selection = device_selection.lower()
-        if device_selection.startswith('gpu:'):
-            device_selection = int(device_selection[4:])
+
+    if device_selection.startswith('gpu:'):
+        device_selection = int(device_selection[4:])
+
     if device_selection != 'cuda' and device_selection != 'current' and device_selection != 'gpu':
         if device_select(device_selection):
             if isinstance(device_selection, int):
@@ -162,6 +185,7 @@ def device_init(device_selection=None):
         return
     print('WARNING: No compatible GPU found. Using the CPU, but this will be very slow!')
     thread_data.device = 'cpu'
+    thread_data.device_name = get_processor_name()
 
 def is_first_cuda_device(device):
     if device is None: return False
@@ -234,13 +258,15 @@ def load_model_ckpt():
     _, _ = modelFS.load_state_dict(sd, strict=False)
 
     if thread_data.vae_file is not None:
-        if os.path.exists(thread_data.vae_file + '.vae.pt'):
-            print(f"Loading VAE weights from: {thread_data.vae_file}.vae.pt")
-            vae_ckpt = torch.load(thread_data.vae_file + '.vae.pt', map_location="cpu")
-            vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
-            modelFS.first_stage_model.load_state_dict(vae_dict, strict=False)
-        else:
-            print(f'Cannot find VAE file: {thread_data.vae_file}.vae.pt')
+        for model_extension in ['.ckpt', '.vae.pt']:
+            if os.path.exists(thread_data.vae_file + model_extension):
+                print(f"Loading VAE weights from: {thread_data.vae_file}{model_extension}")
+                vae_ckpt = torch.load(thread_data.vae_file + model_extension, map_location="cpu")
+                vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
+                modelFS.first_stage_model.load_state_dict(vae_dict, strict=False)
+                break
+            else:
+                print(f'Cannot find VAE file: {thread_data.vae_file}{model_extension}')
 
     modelFS.eval()
     if thread_data.device != 'cpu':
@@ -261,7 +287,12 @@ def load_model_ckpt():
         thread_data.model_is_half = False
         thread_data.model_fs_is_half = False
 
-    print('loaded', thread_data.ckpt_file, 'as', model.device, '->', modelCS.cond_stage_model.device, '->', thread_data.modelFS.device, 'using precision', thread_data.precision)
+    print(f'''loaded model
+ model file: {thread_data.ckpt_file}.ckpt
+ model.device: {model.device}
+ modelCS.device: {modelCS.cond_stage_model.device}
+ modelFS.device: {thread_data.modelFS.device}
+ using precision: {thread_data.precision}''')
 
 def unload_filters():
     if thread_data.model_gfpgan is not None:
@@ -341,13 +372,21 @@ def load_model_real_esrgan():
     thread_data.model_real_esrgan.model.name = thread_data.real_esrgan_file
     print('loaded ', thread_data.real_esrgan_file, 'to', thread_data.model_real_esrgan.device, 'precision', thread_data.precision)
 
+
+def get_session_out_path(disk_path, session_id):
+    if disk_path is None: return None
+    if session_id is None: return None
+
+    session_out_path = os.path.join(disk_path, filename_regex.sub('_',session_id))
+    os.makedirs(session_out_path, exist_ok=True)
+    return session_out_path
+
 def get_base_path(disk_path, session_id, prompt, img_id, ext, suffix=None):
     if disk_path is None: return None
     if session_id is None: return None
     if ext is None: raise Exception('Missing ext')
 
-    session_out_path = os.path.join(disk_path, session_id)
-    os.makedirs(session_out_path, exist_ok=True)
+    session_out_path = get_session_out_path(disk_path, session_id)
 
     prompt_flattened = filename_regex.sub('_', prompt)[:50]
 
@@ -475,7 +514,7 @@ def do_mk_img(req: Request):
         thread_data.vae_file = req.use_vae_model
         needs_model_reload = True
 
-    if thread_data.has_valid_gpu:
+    if thread_data.device != 'cpu':
         if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
             (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
             thread_data.precision = 'full' if req.use_full_precision else 'autocast'
@@ -500,7 +539,7 @@ def do_mk_img(req: Request):
     opt_f = 8
     opt_ddim_eta = 0.0
 
-    print(req.to_string(), '\n    device', thread_data.device)
+    print(req, '\n    device', torch.device(thread_data.device), "as", thread_data.device_name)
     print('\n\n    Using precision:', thread_data.precision)
 
     seed_everything(opt_seed)
@@ -552,8 +591,7 @@ def do_mk_img(req: Request):
         print(f"target t_enc is {t_enc} steps")
 
     if req.save_to_disk_path is not None:
-        session_out_path = os.path.join(req.save_to_disk_path, req.session_id)
-        os.makedirs(session_out_path, exist_ok=True)
+        session_out_path = get_session_out_path(req.save_to_disk_path, req.session_id)
     else:
         session_out_path = None
 
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index eae17891..7fd7aba2 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -21,6 +21,7 @@ LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
 # It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
 
 DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
+CPU_UNLOAD_TIMEOUT = 4 * 60 # seconds - Idle time before CPU unload resource when GPUs are present.
 
 class SymbolClass(type): # Print nicely formatted Symbol names.
     def __repr__(self): return self.__qualname__
@@ -38,6 +39,7 @@ class RenderTask(): # Task with output queue and completion lock.
     def __init__(self, req: Request):
         self.request: Request = req # Initial Request
         self.response: Any = None # Copy of the last reponse
+        self.render_device = None
         self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2)
         self.error: Exception = None
         self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
@@ -68,7 +70,8 @@ class ImageRequest(BaseModel):
     # allow_nsfw: bool = False
     save_to_disk_path: str = None
     turbo: bool = True
-    use_cpu: bool = False
+    use_cpu: bool = False ##TODO Remove after UI and plugins transition.
+    render_device: str = None
     use_full_precision: bool = False
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
@@ -89,7 +92,7 @@ class FilterRequest(BaseModel):
     height: int = 512
     save_to_disk_path: str = None
     turbo: bool = True
-    use_cpu: bool = False
+    render_device: str = None
     use_full_precision: bool = False
     output_format: str = "jpeg" # or "png"
 
@@ -219,26 +222,24 @@ def thread_get_next_task():
                     queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.')
                     task = queued_task
                     break
-                if queued_task.request.use_cpu:
+                if queued_task.render_device == 'cpu':
                     queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.')
                     task = queued_task
                     break
                 if not runtime.is_first_cuda_device(runtime.thread_data.device):
                     continue  # Wait for cuda:0
-            if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu':
-                if is_alive('cpu') > 0:
-                    continue  # CPU Tasks, Skip GPU device
+            if queued_task.render_device and runtime.thread_data.device != queued_task.render_device:
+                # Is asking for a specific render device.
+                if is_alive(queued_task.render_device) > 0:
+                    continue  # requested device alive, skip current one.
                 else:
-                    queued_task.error = Exception('Cpu is not enabled in render_devices.')
-                    task = queued_task
-                    break
-            if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu':
-                if is_alive() > 1:  # cpu is alive, so need more than one.
-                    continue  # GPU Tasks, don't run on CPU unless there is nothing else.
-                else:
-                    queued_task.error = Exception('No active gpu found. Please check the error message in the command-line window at startup.')
+                    # Requested device is not active, return error to UI.
+                    queued_task.error = Exception(str(queued_task.render_device) + ' is not currently active.')
                     task = queued_task
                     break
+            if not queued_task.render_device and runtime.thread_data.device == 'cpu' and is_alive() > 1:
+                # not asking for any specific devices, cpu want to grab task but other render devices are alive.
+                continue  # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
             task = queued_task
             break
         if task is not None:
@@ -252,11 +253,15 @@ def thread_render(device):
     from . import runtime
     try:
         runtime.device_init(device)
-    except:
+    except Exception as e:
         print(traceback.format_exc())
+        weak_thread_data[threading.current_thread()] = {
+            'error': e
+        }
         return
     weak_thread_data[threading.current_thread()] = {
-        'device': runtime.thread_data.device
+        'device': runtime.thread_data.device,
+        'device_name': runtime.thread_data.device_name
     }
     if runtime.thread_data.device != 'cpu' or is_alive() == 1:
         preload_model()
@@ -268,6 +273,12 @@ def thread_render(device):
             return
         task = thread_get_next_task()
         if task is None:
+            if runtime.thread_data.device == 'cpu' and is_alive() > 1 and hasattr(runtime.thread_data, 'lastActive') and time.time() - runtime.thread_data.lastActive > CPU_UNLOAD_TIMEOUT:
+                # GPUs present and CPU is idle. Unload resources.
+                runtime.unload_models()
+                runtime.unload_filters()
+                del runtime.thread_data.lastActive
+                print('unloaded models from CPU because it was idle for too long')
             time.sleep(1)
             continue
         if task.error is not None:
@@ -280,9 +291,12 @@ def thread_render(device):
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        print(f'Session {task.request.session_id} starting task {id(task)}')
+        print(f'Session {task.request.session_id} starting task {id(task)} on {runtime.thread_data.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
+            if runtime.thread_data.device == 'cpu' and is_alive() > 1:
+                # CPU is not the only device. Keep track of active time to unload resources later.
+                runtime.thread_data.lastActive = time.time()
             # Open data generator.
             res = runtime.mk_img(task.request)
             if current_model_path == task.request.use_stable_diffusion_model:
@@ -331,7 +345,7 @@ def thread_render(device):
         elif task.error is not None:
             print(f'Session {task.request.session_id} task {id(task)} failed!')
         else:
-            print(f'Session {task.request.session_id} task {id(task)} completed.')
+            print(f'Session {task.request.session_id} task {id(task)} completed by {runtime.thread_data.device_name}.')
         current_state = ServerStates.Online
 
 def get_cached_task(session_id:str, update_ttl:bool=False):
@@ -341,6 +355,21 @@ def get_cached_task(session_id:str, update_ttl:bool=False):
         return None
     return task_cache.tryGet(session_id)
 
+def get_devices():
+    if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('get_devices' + ERR_LOCK_FAILED)
+    try:
+        device_dict = {}
+        for rthread in render_threads:
+            if not rthread.is_alive():
+                continue
+            weak_data = weak_thread_data.get(rthread)
+            if not weak_data or not 'device' in weak_data or not 'device_name' in weak_data:
+                continue
+            device_dict.update({weak_data['device']:weak_data['device_name']})
+        return device_dict
+    finally:
+        manager_lock.release()
+
 def is_first_cuda_device(device):
     from . import runtime # When calling runtime from outside thread_render DO NOT USE thread specific attributes or functions.
     return runtime.is_first_cuda_device(device)
@@ -352,8 +381,7 @@ def is_alive(name=None):
         for rthread in render_threads:
             if name is not None:
                 weak_data = weak_thread_data.get(rthread)
-                if weak_data is None or weak_data['device'] is None:
-                    print('The thread', rthread.name, 'is registered but has no data store in the task manager.')
+                if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
                     continue
                 thread_name = str(weak_data['device']).lower()
                 if is_first_cuda_device(name):
@@ -380,6 +408,8 @@ def start_render_thread(device='auto'):
         manager_lock.release()
     timeout = DEVICE_START_TIMEOUT
     while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
+        if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
+            return False
         if timeout <= 0:
             return False
         timeout -= 1
@@ -416,7 +446,6 @@ def render(req : ImageRequest):
     r.sampler = req.sampler
     # r.allow_nsfw = req.allow_nsfw
     r.turbo = req.turbo
-    r.use_cpu = req.use_cpu
     r.use_full_precision = req.use_full_precision
     r.save_to_disk_path = req.save_to_disk_path
     r.use_upscale: str = req.use_upscale
@@ -433,6 +462,8 @@ def render(req : ImageRequest):
         r.stream_image_progress = False
 
     new_task = RenderTask(r)
+    new_task.render_device = req.render_device
+
     if task_cache.put(r.session_id, new_task, TASK_TTL):
         # Use twice the normal timeout for adding user requests.
         # Tries to force task_cache.put to fail before tasks_queue.put would. 
diff --git a/ui/server.py b/ui/server.py
index c722894f..bdfbec6c 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -30,9 +30,6 @@ APP_CONFIG_DEFAULT_MODELS = [
     'custom-model', # Check if user has a custom model, use it first.
     'sd-v1-4', # Default fallback.
 ]
-APP_CONFIG_DEFAULT_VAE = [
-    'vae-ft-mse-840000-ema-pruned', # Default fallback.
-]
 
 from fastapi import FastAPI, HTTPException
 from fastapi.staticfiles import StaticFiles
@@ -107,11 +104,24 @@ def setConfig(config):
         config_bat = [
             f"@set update_branch={config['update_branch']}"
         ]
-        if len(gpu_devices) > 0 and not has_first_cuda_device:
-            config_bat.append('::Set the devices visible inside SD-UI here')
-            config_bat.append(f"::@set CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
-            print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
+
+        if os.getenv('CUDA_VISIBLE_DEVICES') is None:
+            if len(gpu_devices) > 0 and not has_first_cuda_device:
+                config_bat.append('::Set the devices visible inside SD-UI here')
+                config_bat.append(f"::@set CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
+                print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
+        else:
+            config_bat.append(f"@set CUDA_VISIBLE_DEVICES={os.getenv('CUDA_VISIBLE_DEVICES')}")
+            if len(gpu_devices) > 0 and not has_first_cuda_device:
+                print('GPU:0 seems to be missing! Validate that CUDA_VISIBLE_DEVICES is set properly.')
         config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
+
+        if os.getenv('SD_UI_BIND_PORT') is not None:
+            config_bat.append(f"@set SD_UI_BIND_PORT={os.getenv('SD_UI_BIND_PORT')}")
+        if os.getenv('SD_UI_BIND_IP') is not None:
+            config_bat.append(f"@set SD_UI_BIND_IP={os.getenv('SD_UI_BIND_IP')}")
+
+
         with open(config_bat_path, 'w', encoding='utf-8') as f:
             f.write('\r\n'.join(config_bat))
     except Exception as e:
@@ -122,17 +132,28 @@ def setConfig(config):
             '#!/bin/bash',
             f"export update_branch={config['update_branch']}"
         ]
-        if len(gpu_devices) > 0 and not has_first_cuda_device:
-            config_sh.append('#Set the devices visible inside SD-UI here')
-            config_sh.append(f"#CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
-            print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
+        if os.getenv('CUDA_VISIBLE_DEVICES') is None:
+            if len(gpu_devices) > 0 and not has_first_cuda_device:
+                config_sh.append('#Set the devices visible inside SD-UI here')
+                config_sh.append(f"#CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
+                print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
+        else:
+            config_sh.append(f"export CUDA_VISIBLE_DEVICES=\"{os.getenv('CUDA_VISIBLE_DEVICES')}\"")
+            if len(gpu_devices) > 0 and not has_first_cuda_device:
+                print('GPU:0 seems to be missing! Validate that CUDA_VISIBLE_DEVICES is set properly.')
+
+        if os.getenv('SD_UI_BIND_PORT') is not None:
+            config_sh.append(f"export SD_UI_BIND_PORT={os.getenv('SD_UI_BIND_PORT')}")
+        if os.getenv('SD_UI_BIND_IP') is not None:
+            config_sh.append(f"export SD_UI_BIND_IP={os.getenv('SD_UI_BIND_IP')}")
+
         config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
         with open(config_sh_path, 'w', encoding='utf-8') as f:
             f.write('\n'.join(config_sh))
     except Exception as e:
         print(traceback.format_exc())
 
-def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extension:str, default_models=[]):
+def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extensions:list, default_models=[]):
     model_dirs = [os.path.join(MODELS_DIR, model_dir), SD_DIR]
     if not model_name: # When None try user configured model.
         config = getConfig()
@@ -141,43 +162,38 @@ def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_ex
     if model_name:
         # Check models directory
         models_dir_path = os.path.join(MODELS_DIR, model_dir, model_name)
-        if os.path.exists(models_dir_path + model_extension):
-            return models_dir_path
-        if os.path.exists(model_name + model_extension):
-            # Direct Path to file
-            model_name = os.path.abspath(model_name)
-            return model_name
+        for model_extension in model_extensions:
+            if os.path.exists(models_dir_path + model_extension):
+                return models_dir_path
+            if os.path.exists(model_name + model_extension):
+                # Direct Path to file
+                model_name = os.path.abspath(model_name)
+                return model_name
     # Default locations
     if model_name in default_models:
         default_model_path = os.path.join(SD_DIR, model_name)
-        if os.path.exists(default_model_path + model_extension):
-            return default_model_path
+        for model_extension in model_extensions:
+            if os.path.exists(default_model_path + model_extension):
+                return default_model_path
     # Can't find requested model, check the default paths.
     for default_model in default_models:
         for model_dir in model_dirs:
             default_model_path = os.path.join(model_dir, default_model)
-            if os.path.exists(default_model_path + model_extension):
-                if model_name is not None:
-                    print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
-                return default_model_path
+            for model_extension in model_extensions:
+                if os.path.exists(default_model_path + model_extension):
+                    if model_name is not None:
+                        print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
+                    return default_model_path
     raise Exception('No valid models found.')
 
 def resolve_ckpt_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extension='.ckpt', default_models=APP_CONFIG_DEFAULT_MODELS)
+    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=['.ckpt'], default_models=APP_CONFIG_DEFAULT_MODELS)
 
-def resolve_vae_to_use(ckpt_model_path:str=None):
-    if ckpt_model_path is not None:
-        if os.path.exists(ckpt_model_path + '.vae.pt'):
-            return ckpt_model_path
-
-        ckpt_model_name = os.path.basename(ckpt_model_path)
-        model_dirs = [os.path.join(MODELS_DIR, 'stable-diffusion'), SD_DIR]
-        for model_dir in model_dirs:
-            default_model_path = os.path.join(model_dir, ckpt_model_name)
-            if os.path.exists(default_model_path + '.vae.pt'):
-                return default_model_path
-
-    return resolve_model_to_use(model_name=None, model_type='vae', model_dir='stable-diffusion', model_extension='.vae.pt', default_models=APP_CONFIG_DEFAULT_VAE)
+def resolve_vae_to_use(model_name:str=None):
+    try:
+        return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=['.vae.pt', '.ckpt'], default_models=[])
+    except:
+        return None
 
 class SetAppConfigRequest(BaseModel):
     update_branch: str = None
@@ -203,10 +219,6 @@ async def setAppConfig(req : SetAppConfigRequest):
             render_devices.append('GPU:' + req.render_devices)
         if len(render_devices) > 0:
             config['render_devices'] = render_devices
-    if req.model_vae:
-        if 'model' not in config:
-            config['model'] = {}
-        config['model']['vae'] = req.model_vae
     try:
         setConfig(config)
         return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
@@ -226,21 +238,25 @@ def getModels():
         },
     }
 
+    def listModels(models_dirname, model_type, model_extensions):
+        models_dir = os.path.join(MODELS_DIR, models_dirname)
+        for file in os.listdir(models_dir):
+            for model_extension in model_extensions:
+                if file.endswith(model_extension):
+                    model_name = file[:-len(model_extension)]
+                    models['options'][model_type].append(model_name)
+
+        models['options'][model_type] = [*set(models['options'][model_type])] # remove duplicates
+
     # custom models
-    sd_models_dir = os.path.join(MODELS_DIR, 'stable-diffusion')
-    for model_type, model_extension in [('stable-diffusion', '.ckpt'), ('vae', '.vae.pt')]:
-        for file in os.listdir(sd_models_dir):
-            if file.endswith(model_extension):
-                model_name = file[:-len(model_extension)]
-                models['options'][model_type].append(model_name)
+    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=['.ckpt'])
+    listModels(models_dirname='vae', model_type='vae', model_extensions=['.vae.pt', '.ckpt'])
 
     # legacy
     custom_weight_path = os.path.join(SD_DIR, 'custom-model.ckpt')
     if os.path.exists(custom_weight_path):
         models['options']['stable-diffusion'].append('custom-model')
 
-    models['active']['vae'] = os.path.basename(task_manager.default_vae_to_load)
-
     return models
 
 def getUIPlugins():
@@ -261,6 +277,8 @@ def read_web_data(key:str=None):
         if config is None:
             raise HTTPException(status_code=500, detail="Config file is missing or unreadable")
         return JSONResponse(config, headers=NOCACHE_HEADERS)
+    elif key == 'devices':
+        return JSONResponse(task_manager.get_devices(), headers=NOCACHE_HEADERS)
     elif key == 'models':
         return JSONResponse(getModels(), headers=NOCACHE_HEADERS)
     elif key == 'modifiers': return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
@@ -295,23 +313,32 @@ def ping(session_id:str=None):
                 response['session'] = 'pending'
     return JSONResponse(response, headers=NOCACHE_HEADERS)
 
-def save_model_to_config(model_name):
+def save_model_to_config(ckpt_model_name, vae_model_name):
     config = getConfig()
     if 'model' not in config:
         config['model'] = {}
 
-    config['model']['stable-diffusion'] = model_name
+    config['model']['stable-diffusion'] = ckpt_model_name
+    config['model']['vae'] = vae_model_name
+
+    if vae_model_name is None or vae_model_name == "":
+        del config['model']['vae']
+
     setConfig(config)
 
 @app.post('/render')
 def render(req : task_manager.ImageRequest):
-    if req.use_cpu and task_manager.is_alive('cpu') <= 0: raise HTTPException(status_code=403, detail=f'CPU rendering is not enabled in config.json or the thread has died...') # HTTP403 Forbidden
+    if req.use_cpu:  # TODO Remove after transition.
+        print('WARNING Replace {use_cpu: true} by {render_device: "cpu"}')
+        req.render_device = 'cpu'
+        del req.use_cpu
+    if req.render_device and task_manager.is_alive(req.render_device) <= 0: raise HTTPException(status_code=403, detail=f'{req.render_device} rendering is not enabled in config.json or the thread has died...') # HTTP403 Forbidden
     if req.use_face_correction and task_manager.is_alive(0) <= 0: #TODO Remove when GFPGANer is fixed upstream.
         raise HTTPException(status_code=412, detail=f'GFPGANer only works GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') # HTTP412 Precondition Failed
     try:
-        save_model_to_config(req.use_stable_diffusion_model)
+        save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model)
         req.use_stable_diffusion_model = resolve_ckpt_to_use(req.use_stable_diffusion_model)
-        req.use_vae_model = resolve_vae_to_use(ckpt_model_path=req.use_stable_diffusion_model)
+        req.use_vae_model = resolve_vae_to_use(req.use_vae_model)
         new_task = task_manager.render(req)
         response = {
             'status': str(task_manager.current_state), 
@@ -390,44 +417,41 @@ config = getConfig()
 
 # Start the task_manager
 task_manager.default_model_to_load = resolve_ckpt_to_use()
-task_manager.default_vae_to_load = resolve_vae_to_use(ckpt_model_path=task_manager.default_model_to_load)
+task_manager.default_vae_to_load = resolve_vae_to_use()
 if 'render_devices' in config:  # Start a new thread for each device.
     if isinstance(config['render_devices'], str):
         config['render_devices'] = config['render_devices'].split(',')
     if not isinstance(config['render_devices'], list):
         raise Exception('Invalid render_devices value in config.')
     for device in config['render_devices']:
+        if task_manager.is_alive(device) >= 1:
+            print(device, 'already registered.')
+            continue
         if not task_manager.start_render_thread(device):
             print(device, 'failed to start.')
     if task_manager.is_alive() <= 0: # No running devices, probably invalid user config.
         print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json')
         print('Loading default render devices to replace invalid render_devices field from config', config['render_devices'])
 
-display_warning = False
 if task_manager.is_alive() <= 0: # Either no defauls or no devices after loading config.
     # Select best GPU device using free memory, if more than one device.
     if task_manager.start_render_thread('auto'): # Detect best device for renders
-        if task_manager.is_alive(0) <= 0:  # has no cuda:0
-            if task_manager.is_alive('cpu') >= 1:  # auto used CPU.
-                pass # Maybe add warning here about CPU mode...
-            elif task_manager.start_render_thread('cuda'): # An other cuda device is better and cuda:0 is missing, try to start it...
-                display_warning = True # And warn user to update settings...
-            else:
-                print('Failed to start GPU:0...')
+        # if cuda:0 is missing, another cuda device is better. try to start it...
+        if task_manager.is_alive(0) <= 0 and task_manager.is_alive('cpu') <= 0 and not task_manager.start_render_thread('cuda'):
+            print('Failed to start GPU:0...')
     else:
         print('Failed to start gpu device.')
-    if task_manager.is_alive('cpu') <= 0:
-        # Allow CPU to be used for renders
-        if not task_manager.start_render_thread('cpu'):
-            print('Failed to start CPU render device...')
+    if task_manager.is_alive('cpu') <= 0 and not task_manager.start_render_thread('cpu'): # Allow CPU to be used for renders
+        print('Failed to start CPU render device...')
 
-if display_warning or task_manager.is_alive(0) <= 0:
+is_using_a_gpu = (task_manager.is_alive() > task_manager.is_alive('cpu'))
+if is_using_a_gpu and task_manager.is_alive(0) <= 0:
     print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.')
     print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer')
     print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
     print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
 
-del display_warning
+print('active devices', task_manager.get_devices())
 
 # start the browser ui
-import webbrowser; webbrowser.open('http://localhost:9000')
\ No newline at end of file
+import webbrowser; webbrowser.open('http://localhost:9000')