Support custom text encoders and Flux VAEs in the UI

scripts/check_modules.py

@@ -124,10 +124,10 @@ def update_modules():
     #  if sdkit is 2.0.15.x (or lower), then diffusers should be restricted to 0.21.4 (see below for the reason)
     #  otherwise use the current sdkit version (with the corresponding diffusers version)
 
-    expected_sdkit_version_str = "2.0.22.8"
+    expected_sdkit_version_str = "2.0.22.9"
     expected_diffusers_version_str = "0.28.2"
 
-    legacy_sdkit_version_str = "2.0.15.17"
+    legacy_sdkit_version_str = "2.0.15.18"
     legacy_diffusers_version_str = "0.21.4"
 
     sdkit_version_str = version("sdkit")

ui/easydiffusion/backends/webui/__init__.py

@@ -18,6 +18,7 @@ from .impl import (
     ping,
     load_model,
     unload_model,
+    flush_model_changes,
     set_options,
     generate_images,
     filter_images,
@@ -53,6 +54,7 @@ MODELS_TO_OVERRIDE = {
     "codeformer": "--codeformer-models-path",
     "embeddings": "--embeddings-dir",
     "controlnet": "--controlnet-dir",
+    "text-encoder": "--text-encoder-dir",
 }
 
 WEBUI_PATCHES = [

ui/easydiffusion/backends/webui/impl.py

@@ -27,6 +27,7 @@ webui_opts: dict = None
 curr_models = {
     "stable-diffusion": None,
     "vae": None,
+    "text-encoder": None,
 }
 
 
@@ -96,50 +97,51 @@ def ping(timeout=1):
 
 
 def load_model(context, model_type, **kwargs):
+    from easydiffusion.app import ROOT_DIR, getConfig
+
+    config = getConfig()
+    models_dir = config.get("models_dir", os.path.join(ROOT_DIR, "models"))
+
     model_path = context.model_paths[model_type]
 
+    if model_type == "stable-diffusion":
+        base_dir = os.path.join(models_dir, model_type)
+        model_path = os.path.relpath(model_path, base_dir)
+
+    # print(f"load model: {model_type=} {model_path=} {curr_models=}")
+    curr_models[model_type] = model_path
+
+
+def unload_model(context, model_type, **kwargs):
+    # print(f"unload model: {model_type=} {curr_models=}")
+    curr_models[model_type] = None
+
+
+def flush_model_changes(context):
     if webui_opts is None:
         print("Server not ready, can't set the model")
         return
 
-    if model_type == "stable-diffusion":
+    modules = []
-        model_name = os.path.basename(model_path)
+    for model_type in ("vae", "text-encoder"):
-        model_name = os.path.splitext(model_name)[0]
+        if curr_models[model_type]:
-        print(f"setting sd model: {model_name}")
+            model_paths = curr_models[model_type]
-        if curr_models[model_type] != model_name:
+            model_paths = [model_paths] if not isinstance(model_paths, list) else model_paths
-            try:
+            modules += model_paths
-                res = webui_post("/sdapi/v1/options", json={"sd_model_checkpoint": model_name})
-                if res.status_code != 200:
-                    raise Exception(res.text)
-            except Exception as e:
-                raise RuntimeError(
-                    f"The engine failed to set the required options. Please check the logs in the command line window for more details."
-                )
 
-            curr_models[model_type] = model_name
+    opts = {"sd_model_checkpoint": curr_models["stable-diffusion"], "forge_additional_modules": modules}
-    elif model_type == "vae":
-        if curr_models[model_type] != model_path:
-            vae_model = [model_path] if model_path else []
 
-            opts = {"sd_model_checkpoint": curr_models["stable-diffusion"], "forge_additional_modules": vae_model}
+    print("Setting backend models", opts)
-            print("setting opts 2", opts)
 
-            try:
+    try:
-                res = webui_post("/sdapi/v1/options", json=opts)
+        res = webui_post("/sdapi/v1/options", json=opts)
-                if res.status_code != 200:
+        print("got res", res.status_code)
-                    raise Exception(res.text)
+        if res.status_code != 200:
-            except Exception as e:
+            raise Exception(res.text)
-                raise RuntimeError(
+    except Exception as e:
-                    f"The engine failed to set the required options. Please check the logs in the command line window for more details."
+        raise RuntimeError(
-                )
+            f"The engine failed to set the required options. Please check the logs in the command line window for more details."
-
+        )
-            curr_models[model_type] = model_path
-
-
-def unload_model(context, model_type, **kwargs):
-    if model_type == "vae":
-        context.model_paths[model_type] = None
-        load_model(context, model_type)
 
 
 def generate_images(
@@ -346,7 +348,7 @@ def refresh_models():
             pass
 
     try:
-        for type in ("checkpoints", "vae"):
+        for type in ("checkpoints", "vae-and-text-encoders"):
             t = Thread(target=make_refresh_call, args=(type,))
             t.start()
     except Exception as e:

ui/easydiffusion/model_manager.py

@@ -3,6 +3,7 @@ import shutil
 from glob import glob
 import traceback
 from typing import Union
+from os import path
 
 from easydiffusion import app
 from easydiffusion.types import ModelsData
@@ -22,6 +23,7 @@ KNOWN_MODEL_TYPES = [
     "codeformer",
     "embeddings",
     "controlnet",
+    "text-encoder",
 ]
 MODEL_EXTENSIONS = {
     "stable-diffusion": [".ckpt", ".safetensors", ".sft", ".gguf"],
@@ -33,6 +35,7 @@ MODEL_EXTENSIONS = {
     "codeformer": [".pth"],
     "embeddings": [".pt", ".bin", ".safetensors", ".sft"],
     "controlnet": [".pth", ".safetensors", ".sft"],
+    "text-encoder": [".safetensors", ".sft"],
 }
 DEFAULT_MODELS = {
     "stable-diffusion": [
@@ -59,6 +62,7 @@ ALTERNATE_FOLDER_NAMES = {  # for WebUI compatibility
     "realesrgan": "RealESRGAN",
     "lora": "Lora",
     "controlnet": "ControlNet",
+    "text-encoder": "text_encoder",
 }
 
 known_models = {}
@@ -204,6 +208,9 @@ def reload_models_if_necessary(context: Context, models_data: ModelsData, models
                     context.model_load_errors = {}
                 context.model_load_errors[model_type] = str(e)  # storing the entire Exception can lead to memory leaks
 
+    if hasattr(backend, "flush_model_changes"):
+        backend.flush_model_changes(context)
+
 
 def resolve_model_paths(models_data: ModelsData):
     from easydiffusion.backend_manager import backend
@@ -224,14 +231,25 @@ def resolve_model_paths(models_data: ModelsData):
     for model_type in model_paths:
         if model_type in skip_models:  # doesn't use model paths
             continue
-        if model_type == "codeformer" and model_paths[model_type]:
+
-            download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
+        if model_type in ("vae", "codeformer", "controlnet", "text-encoder") and model_paths[model_type]:
-        elif model_type == "controlnet" and model_paths[model_type]:
+            model_ids = model_paths[model_type]
-            model_id = model_paths[model_type]
+            model_ids = model_ids if isinstance(model_ids, list) else [model_ids]
-            model_info = get_model_info_from_db(model_type=model_type, model_id=model_id)
+
-            if model_info:
+            new_model_paths = []
-                filename = model_info.get("url", "").split("/")[-1]
+
-                download_if_necessary("controlnet", filename, model_id, skip_if_others_exist=False)
+            for model_id in model_ids:
+                log.info(f"Checking for {model_id=}")
+                model_info = get_model_info_from_db(model_type=model_type, model_id=model_id)
+                if model_info:
+                    filename = model_info.get("url", "").split("/")[-1]
+                    download_if_necessary(model_type, filename, model_id, skip_if_others_exist=False)
+
+                    new_model_paths.append(path.splitext(filename)[0])
+                else:  # not in the model db, probably a regular file
+                    new_model_paths.append(model_id)
+
+            model_paths[model_type] = new_model_paths
 
         model_paths[model_type] = resolve_model_to_use(model_paths[model_type], model_type=model_type)
 
@@ -256,17 +274,31 @@ def download_default_models_if_necessary():
 
 
 def download_if_necessary(model_type: str, file_name: str, model_id: str, skip_if_others_exist=True):
-    model_dir = get_model_dirs(model_type)[0]
+    from easydiffusion.backend_manager import backend
-    model_path = os.path.join(model_dir, file_name)
+
     expected_hash = get_model_info_from_db(model_type=model_type, model_id=model_id)["quick_hash"]
-
     other_models_exist = any_model_exists(model_type) and skip_if_others_exist
-    known_model_exists = os.path.exists(model_path)
-    known_model_is_corrupt = known_model_exists and hash_file_quick(model_path) != expected_hash
 
-    if known_model_is_corrupt or (not other_models_exist and not known_model_exists):
+    for model_dir in get_model_dirs(model_type):
-        print("> download", model_type, model_id)
+        model_path = os.path.join(model_dir, file_name)
-        download_model(model_type, model_id, download_base_dir=app.MODELS_DIR, download_config_if_available=False)
+
+        known_model_exists = os.path.exists(model_path)
+        known_model_is_corrupt = known_model_exists and hash_file_quick(model_path) != expected_hash
+
+        needs_download = known_model_is_corrupt or (not other_models_exist and not known_model_exists)
+
+        log.info(f"{model_path=} {needs_download=}")
+        if known_model_exists:
+            log.info(f"{expected_hash=} {hash_file_quick(model_path)=}")
+        log.info(f"{known_model_is_corrupt=} {other_models_exist=} {known_model_exists=}")
+
+        if not needs_download:
+            return
+
+    print("> download", model_type, model_id)
+    download_model(model_type, model_id, download_base_dir=app.MODELS_DIR, download_config_if_available=False)
+
+    backend.refresh_models()
 
 
 def migrate_legacy_model_location():
@@ -363,7 +395,7 @@ def getModels(scan_for_malicious: bool = True):
     models = {
         "options": {
             "stable-diffusion": [],
-            "vae": [],
+            "vae": [{"ae": "ae (Flux VAE fp16)"}],
             "hypernetwork": [],
             "lora": [],
             "codeformer": [{"codeformer": "CodeFormer"}],
@@ -383,6 +415,11 @@ def getModels(scan_for_malicious: bool = True):
                 # {"control_v11e_sd15_shuffle": "Shuffle"},
                 # {"control_v11f1e_sd15_tile": "Tile"},
             ],
+            "text-encoder": [
+                {"t5xxl_fp16": "T5 XXL fp16"},
+                {"clip_l": "CLIP L"},
+                {"clip_g": "CLIP G"},
+            ],
         },
     }
 
@@ -466,6 +503,7 @@ def getModels(scan_for_malicious: bool = True):
     listModels(model_type="lora")
     listModels(model_type="embeddings", nameFilter=get_embedding_token)
     listModels(model_type="controlnet")
+    listModels(model_type="text-encoder")
 
     if scan_for_malicious and models_scanned > 0:
         log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")

ui/easydiffusion/types.py

@@ -80,6 +80,7 @@ class RenderTaskData(TaskData):
     latent_upscaler_steps: int = 10
     use_stable_diffusion_model: Union[str, List[str]] = "sd-v1-4"
     use_vae_model: Union[str, List[str]] = None
+    use_text_encoder_model: Union[str, List[str]] = None
     use_hypernetwork_model: Union[str, List[str]] = None
     use_lora_model: Union[str, List[str]] = None
     use_controlnet_model: Union[str, List[str]] = None
@@ -211,6 +212,7 @@ def convert_legacy_render_req_to_new(old_req: dict):
     # move the model info
     model_paths["stable-diffusion"] = old_req.get("use_stable_diffusion_model")
     model_paths["vae"] = old_req.get("use_vae_model")
+    model_paths["text-encoder"] = old_req.get("use_text_encoder_model")
     model_paths["hypernetwork"] = old_req.get("use_hypernetwork_model")
     model_paths["lora"] = old_req.get("use_lora_model")
     model_paths["controlnet"] = old_req.get("use_controlnet_model")

ui/index.html

@@ -302,6 +302,14 @@
                         <input id="vae_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
                         <a href="https://github.com/easydiffusion/easydiffusion/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about VAEs</span></i></a>
                     </td></tr>
+                    <tr id="text_encoder_model_container" class="pl-5 gated-feature" data-feature-keys="backend_webui">
+                        <td>
+                            <label for="text_encoder_model">Text Encoder:</label>
+                        </td>
+                        <td>
+                            <div id="text_encoder_model" data-path=""></div>
+                        </td>
+                    </tr>
                     <tr id="samplerSelection" class="pl-5"><td><label for="sampler_name">Sampler:</label></td><td>
                         <select id="sampler_name" name="sampler_name">
                             <option value="plms">PLMS</option>
@@ -442,7 +450,7 @@
                     <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="11" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" inputmode="decimal"></td></tr>
                     <tr class="pl-5 displayNone warning-label" id="guidanceWarning"><td></td><td id="guidanceWarningText"></td></tr>
                     <tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" inputmode="decimal"><br/></td></tr>
-                    <tr id="distilled_guidance_scale_container" class="pl-5 displayNone"><td><label for="distilled_guidance_scale_slider">Distilled Guidance:</label></td><td> <input id="distilled_guidance_scale_slider" name="distilled_guidance_scale_slider" class="editor-slider" value="35" type="range" min="11" max="500"> <input id="distilled_guidance_scale" name="distilled_guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" inputmode="decimal"></td></tr>
+                    <tr id="distilled_guidance_scale_container" class="pl-5 gated-feature" data-feature-keys="backend_webui"><td><label for="distilled_guidance_scale_slider">Distilled Guidance:</label></td><td> <input id="distilled_guidance_scale_slider" name="distilled_guidance_scale_slider" class="editor-slider" value="35" type="range" min="11" max="500"> <input id="distilled_guidance_scale" name="distilled_guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" inputmode="decimal"></td></tr>
                     <tr id="lora_model_container" class="pl-5 gated-feature" data-feature-keys="backend_ed_diffusers backend_webui">
                         <td>
                             <label for="lora_model">LoRA:</label>

ui/media/js/auto-save.js

@@ -60,6 +60,7 @@ const SETTINGS_IDS_LIST = [
     "extract_lora_from_prompt",
     "embedding-card-size-selector",
     "lora_model",
+    "text_encoder_model",
     "enable_vae_tiling",
     "controlnet_alpha",
 ]

ui/media/js/dnd.js

@@ -394,6 +394,45 @@ const TASK_MAPPING = {
             return val
         },
     },
+    use_text_encoder_model: {
+        name: "Text Encoder model",
+        setUI: (use_text_encoder_model) => {
+            let modelPaths = []
+            use_text_encoder_model = use_text_encoder_model === null ? "" : use_text_encoder_model
+            use_text_encoder_model = Array.isArray(use_text_encoder_model) ? use_text_encoder_model : [use_text_encoder_model]
+            use_text_encoder_model.forEach((m) => {
+                if (m.includes("models\\text-encoder\\")) {
+                    m = m.split("models\\text-encoder\\")[1]
+                } else if (m.includes("models\\\\text-encoder\\\\")) {
+                    m = m.split("models\\\\text-encoder\\\\")[1]
+                } else if (m.includes("models/text-encoder/")) {
+                    m = m.split("models/text-encoder/")[1]
+                }
+                m = m.replaceAll("\\\\", "/")
+                m = getModelPath(m, [".safetensors", ".sft"])
+                modelPaths.push(m)
+            })
+            text_encoderModelField.modelNames = modelPaths
+        },
+        readUI: () => {
+            return text_encoderModelField.modelNames
+        },
+        parse: (val) => {
+            val = !val || val === "None" ? "" : val
+            if (typeof val === "string" && val.includes(",")) {
+                val = val.split(",")
+                val = val.map((v) => v.trim())
+                val = val.map((v) => v.replaceAll("\\", "\\\\"))
+                val = val.map((v) => v.replaceAll('"', ""))
+                val = val.map((v) => v.replaceAll("'", ""))
+                val = val.map((v) => '"' + v + '"')
+                val = "[" + val + "]"
+                val = JSON.parse(val)
+            }
+            val = Array.isArray(val) ? val : [val]
+            return val
+        },
+    },
     use_hypernetwork_model: {
         name: "Hypernetwork model",
         setUI: (use_hypernetwork_model) => {
@@ -620,6 +659,7 @@ const TASK_TEXT_MAPPING = {
     hypernetwork_strength: "Hypernetwork Strength",
     use_lora_model: "LoRA model",
     lora_alpha: "LoRA Strength",
+    use_text_encoder_model: "Text Encoder model",
     use_controlnet_model: "ControlNet model",
     control_filter_to_apply: "ControlNet Filter",
     control_alpha: "ControlNet Strength",

ui/media/js/main.js

@@ -54,6 +54,7 @@ const taskConfigSetup = {
             label: "Hypernetwork Strength",
             visible: ({ reqBody }) => !!reqBody?.use_hypernetwork_model,
         },
+        use_text_encoder_model: { label: "Text Encoder", visible: ({ reqBody }) => !!reqBody?.use_text_encoder_model },
         use_lora_model: { label: "Lora Model", visible: ({ reqBody }) => !!reqBody?.use_lora_model },
         lora_alpha: { label: "Lora Strength", visible: ({ reqBody }) => !!reqBody?.use_lora_model },
         preserve_init_image_color_profile: "Preserve Color Profile",
@@ -141,6 +142,7 @@ let tilingField = document.querySelector("#tiling")
 let controlnetModelField = new ModelDropdown(document.querySelector("#controlnet_model"), "controlnet", "None", false)
 let vaeModelField = new ModelDropdown(document.querySelector("#vae_model"), "vae", "None")
 let loraModelField = new MultiModelSelector(document.querySelector("#lora_model"), "lora", "LoRA", 0.5, 0.02)
+let textEncoderModelField = new MultiModelSelector(document.querySelector("#text_encoder_model"), "text-encoder", "Text Encoder", 0.5, 0.02, false)
 let hypernetworkModelField = new ModelDropdown(document.querySelector("#hypernetwork_model"), "hypernetwork", "None")
 let hypernetworkStrengthSlider = document.querySelector("#hypernetwork_strength_slider")
 let hypernetworkStrengthField = document.querySelector("#hypernetwork_strength")
@@ -1396,6 +1398,7 @@ function getCurrentUserRequest() {
         newTask.reqBody.hypernetwork_strength = parseFloat(hypernetworkStrengthField.value)
     }
     if (testDiffusers.checked) {
+        // lora
         let loraModelData = loraModelField.value
         let modelNames = loraModelData["modelNames"]
         let modelStrengths = loraModelData["modelWeights"]
@@ -1408,6 +1411,16 @@ function getCurrentUserRequest() {
             newTask.reqBody.lora_alpha = modelStrengths
         }
 
+        // text encoder
+        let textEncoderModelNames = textEncoderModelField.modelNames
+
+        if (textEncoderModelNames.length > 0) {
+            textEncoderModelNames = textEncoderModelNames.length == 1 ? textEncoderModelNames[0] : textEncoderModelNames
+
+            newTask.reqBody.use_text_encoder_model = textEncoderModelNames
+        }
+
+        // vae tiling
         if (tilingField.value !== "none") {
             newTask.reqBody.tiling = tilingField.value
         }
@@ -1891,8 +1904,31 @@ document.addEventListener("refreshModels", function() {
     onControlnetModelChange()
 })
 
-// tip for Flux
+// utilities for Flux and Chroma
 let sdModelField = document.querySelector("#stable_diffusion_model")
+
+// function checkAndSetDependentModels() {
+//     let sdModel = sdModelField.value.toLowerCase()
+//     let isFlux = sdModel.includes("flux")
+//     let isChroma = sdModel.includes("chroma")
+
+//     if (isFlux || isChroma) {
+//         vaeModelField.value = "ae"
+
+//         if (isFlux) {
+//             textEncoderModelField.modelNames = ["t5xxl_fp16", "clip_l"]
+//         } else {
+//             textEncoderModelField.modelNames = ["t5xxl_fp16"]
+//         }
+//     } else {
+//         if (vaeModelField.value == "ae") {
+//             vaeModelField.value = ""
+//         }
+//         textEncoderModelField.modelNames = []
+//     }
+// }
+// sdModelField.addEventListener("change", checkAndSetDependentModels)
+
 function checkGuidanceValue() {
     let guidance = parseFloat(guidanceScaleField.value)
     let guidanceWarning = document.querySelector("#guidanceWarning")
@@ -1917,15 +1953,16 @@ sdModelField.addEventListener("change", checkGuidanceValue)
 guidanceScaleField.addEventListener("change", checkGuidanceValue)
 guidanceScaleSlider.addEventListener("change", checkGuidanceValue)
 
-function checkGuidanceScaleVisibility() {
+// disabling until we can detect flux models more reliably
-    let guidanceScaleContainer = document.querySelector("#distilled_guidance_scale_container")
+// function checkGuidanceScaleVisibility() {
-    if (sdModelField.value.toLowerCase().includes("flux")) {
+//     let guidanceScaleContainer = document.querySelector("#distilled_guidance_scale_container")
-        guidanceScaleContainer.classList.remove("displayNone")
+//     if (sdModelField.value.toLowerCase().includes("flux")) {
-    } else {
+//         guidanceScaleContainer.classList.remove("displayNone")
-        guidanceScaleContainer.classList.add("displayNone")
+//     } else {
-    }
+//         guidanceScaleContainer.classList.add("displayNone")
-}
+//     }
-sdModelField.addEventListener("change", checkGuidanceScaleVisibility)
+// }
+// sdModelField.addEventListener("change", checkGuidanceScaleVisibility)
 
 function checkFluxSampler() {
     let samplerWarning = document.querySelector("#fluxSamplerWarning")
@@ -1980,8 +2017,9 @@ schedulerField.addEventListener("change", checkFluxSchedulerSteps)
 numInferenceStepsField.addEventListener("change", checkFluxSchedulerSteps)
 
 document.addEventListener("refreshModels", function() {
+    // checkAndSetDependentModels()
     checkGuidanceValue()
-    checkGuidanceScaleVisibility()
+    // checkGuidanceScaleVisibility()
     checkFluxSampler()
     checkFluxScheduler()
     checkFluxSchedulerSteps()

ui/media/js/multi-model-selector.js

@@ -10,6 +10,7 @@ class MultiModelSelector {
     root
     modelType
     modelNameFriendly
+    showWeights
     defaultWeight
     weightStep
 
@@ -35,13 +36,13 @@ class MultiModelSelector {
         if (typeof modelData !== "object") {
             throw new Error("Multi-model selector expects an object containing modelNames and modelWeights as keys!")
         }
-        if (!("modelNames" in modelData) || !("modelWeights" in modelData)) {
+        if (!("modelNames" in modelData) || (this.showWeights && !("modelWeights" in modelData))) {
             throw new Error("modelNames or modelWeights not present in the data passed to the multi-model selector")
         }
 
         let newModelNames = modelData["modelNames"]
         let newModelWeights = modelData["modelWeights"]
-        if (newModelNames.length !== newModelWeights.length) {
+        if (newModelWeights && newModelNames.length !== newModelWeights.length) {
             throw new Error("Need to pass an equal number of modelNames and modelWeights!")
         }
 
@@ -50,7 +51,7 @@ class MultiModelSelector {
         // the root of all this unholiness is because searchable-models automatically dispatches an update event
         // as soon as the value is updated via JS, which is against the DOM pattern of not dispatching an event automatically
         // unless the caller explicitly dispatches the event.
-        this.modelWeights = newModelWeights
+        this.modelWeights = newModelWeights || []
         this.modelNames = newModelNames
     }
     get disabled() {
@@ -91,10 +92,11 @@ class MultiModelSelector {
         }
     }
 
-    constructor(root, modelType, modelNameFriendly = undefined, defaultWeight = 0.5, weightStep = 0.02) {
+    constructor(root, modelType, modelNameFriendly = undefined, defaultWeight = 0.5, weightStep = 0.02, showWeights = true) {
         this.root = root
         this.modelType = modelType
         this.modelNameFriendly = modelNameFriendly || modelType
+        this.showWeights = showWeights
         this.defaultWeight = defaultWeight
         this.weightStep = weightStep
 
@@ -135,10 +137,13 @@ class MultiModelSelector {
 
         const modelElement = document.createElement("div")
         modelElement.className = "model_entry"
-        modelElement.innerHTML = `
+        let html = `<input id="${this.modelType}_${idx}" class="model_name model-filter" type="text" spellcheck="false" autocomplete="off" data-path="" />`
-            <input id="${this.modelType}_${idx}" class="model_name model-filter" type="text" spellcheck="false" autocomplete="off" data-path="" />
+
-            <input class="model_weight" type="number" step="${this.weightStep}" value="${this.defaultWeight}" pattern="^-?[0-9]*\.?[0-9]*$" onkeypress="preventNonNumericalInput(event)">
+        if (this.showWeights) {
-        `
+            html += `<input class="model_weight" type="number" step="${this.weightStep}" value="${this.defaultWeight}" pattern="^-?[0-9]*\.?[0-9]*$" onkeypress="preventNonNumericalInput(event)">`
+        }
+        modelElement.innerHTML = html
+
         this.modelContainer.appendChild(modelElement)
 
         let modelNameEl = modelElement.querySelector(".model_name")
@@ -160,8 +165,8 @@ class MultiModelSelector {
 
         modelNameEl.addEventListener("change", makeUpdateEvent("change"))
         modelNameEl.addEventListener("input", makeUpdateEvent("input"))
-        modelWeightEl.addEventListener("change", makeUpdateEvent("change"))
+        modelWeightEl?.addEventListener("change", makeUpdateEvent("change"))
-        modelWeightEl.addEventListener("input", makeUpdateEvent("input"))
+        modelWeightEl?.addEventListener("input", makeUpdateEvent("input"))
 
         let removeBtn = document.createElement("button")
         removeBtn.className = "remove_model_btn"
@@ -218,10 +223,14 @@ class MultiModelSelector {
     }
 
     get modelWeights() {
-        return this.getModelElements(true).map((e) => e.weight.value)
+        return this.getModelElements(true).map((e) => e.weight?.value)
     }
 
     set modelWeights(newModelWeights) {
+        if (!this.showWeights) {
+            return
+        }
+
         this.resizeEntryList(newModelWeights.length)
 
         if (newModelWeights.length === 0) {