diff --git a/api/onnx_web/chain/blend_controlnet.py b/api/onnx_web/chain/blend_controlnet.py
index 37eea298..1ece0005 100644
--- a/api/onnx_web/chain/blend_controlnet.py
+++ b/api/onnx_web/chain/blend_controlnet.py
@@ -33,37 +33,23 @@ def blend_controlnet(
 
     pipe = load_pipeline(
         server,
-        OnnxStableDiffusionControlNetPipeline,
+        "controlnet",
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
     )
-    if params.lpw:
-        logger.debug("using LPW pipeline for img2img")
-        rng = torch.manual_seed(params.seed)
-        result = pipe.img2img(
-            params.prompt,
-            generator=rng,
-            guidance_scale=params.cfg,
-            image=source,
-            negative_prompt=params.negative_prompt,
-            num_inference_steps=params.steps,
-            strength=params.strength,
-            callback=callback,
-        )
-    else:
-        rng = np.random.RandomState(params.seed)
-        result = pipe(
-            params.prompt,
-            generator=rng,
-            guidance_scale=params.cfg,
-            image=source,
-            negative_prompt=params.negative_prompt,
-            num_inference_steps=params.steps,
-            strength=params.strength,
-            callback=callback,
-        )
+
+    rng = np.random.RandomState(params.seed)
+    result = pipe(
+        params.prompt,
+        generator=rng,
+        guidance_scale=params.cfg,
+        image=source,
+        negative_prompt=params.negative_prompt,
+        num_inference_steps=params.steps,
+        strength=params.strength, # TODO: ControlNet strength
+        callback=callback,
+    )
 
     output = result.images[0]
 
diff --git a/api/onnx_web/chain/blend_img2img.py b/api/onnx_web/chain/blend_img2img.py
index bf423e64..dc881f78 100644
--- a/api/onnx_web/chain/blend_img2img.py
+++ b/api/onnx_web/chain/blend_img2img.py
@@ -33,13 +33,12 @@ def blend_img2img(
 
     pipe = load_pipeline(
         server,
-        OnnxStableDiffusionImg2ImgPipeline,
+        params.pipeline,
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
     )
-    if params.lpw:
+    if params.lpw():
         logger.debug("using LPW pipeline for img2img")
         rng = torch.manual_seed(params.seed)
         result = pipe.img2img(
diff --git a/api/onnx_web/chain/blend_inpaint.py b/api/onnx_web/chain/blend_inpaint.py
index 4220364c..58b13de3 100644
--- a/api/onnx_web/chain/blend_inpaint.py
+++ b/api/onnx_web/chain/blend_inpaint.py
@@ -75,10 +75,9 @@ def blend_inpaint(
             params.model,
             params.scheduler,
             job.get_device(),
-            params.lpw,
         )
 
-        if params.lpw:
+        if params.lpw():
             logger.debug("using LPW pipeline for inpaint")
             rng = torch.manual_seed(params.seed)
             result = pipe.inpaint(
diff --git a/api/onnx_web/chain/blend_pix2pix.py b/api/onnx_web/chain/blend_pix2pix.py
index 7a1de781..194dd906 100644
--- a/api/onnx_web/chain/blend_pix2pix.py
+++ b/api/onnx_web/chain/blend_pix2pix.py
@@ -35,13 +35,12 @@ def blend_pix2pix(
 
     pipe = load_pipeline(
         server,
-        OnnxStableDiffusionInstructPix2PixPipeline,
+        "pix2pix",
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
     )
-    if params.lpw:
+    if params.lpw():
         logger.debug("using LPW pipeline for img2img")
         rng = torch.manual_seed(params.seed)
         result = pipe.img2img(
diff --git a/api/onnx_web/chain/source_txt2img.py b/api/onnx_web/chain/source_txt2img.py
index 58220e14..b20439bf 100644
--- a/api/onnx_web/chain/source_txt2img.py
+++ b/api/onnx_web/chain/source_txt2img.py
@@ -39,14 +39,13 @@ def source_txt2img(
     latents = get_latents_from_seed(params.seed, size)
     pipe = load_pipeline(
         server,
-        OnnxStableDiffusionPipeline,
+        "txt2img",
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
     )
 
-    if params.lpw:
+    if params.lpw():
         logger.debug("using LPW pipeline for txt2img")
         rng = torch.manual_seed(params.seed)
         result = pipe.text2img(
diff --git a/api/onnx_web/chain/upscale_outpaint.py b/api/onnx_web/chain/upscale_outpaint.py
index 39167bc1..0b9d29d9 100644
--- a/api/onnx_web/chain/upscale_outpaint.py
+++ b/api/onnx_web/chain/upscale_outpaint.py
@@ -75,13 +75,12 @@ def upscale_outpaint(
         latents = get_tile_latents(full_latents, dims)
         pipe = load_pipeline(
             server,
-            OnnxStableDiffusionInpaintPipeline,
+            "inpaint",
             params.model,
             params.scheduler,
             job.get_device(),
-            params.lpw,
         )
-        if params.lpw:
+        if params.lpw():
             logger.debug("using LPW pipeline for inpaint")
             rng = torch.manual_seed(params.seed)
             result = pipe.inpaint(
diff --git a/api/onnx_web/diffusers/load.py b/api/onnx_web/diffusers/load.py
index 77e9b6f3..d84cc831 100644
--- a/api/onnx_web/diffusers/load.py
+++ b/api/onnx_web/diffusers/load.py
@@ -19,15 +19,15 @@ from diffusers import (
     KDPM2DiscreteScheduler,
     LMSDiscreteScheduler,
     OnnxRuntimeModel,
+    OnnxStableDiffusionImg2ImgPipeline,
+    OnnxStableDiffusionInpaintPipeline,
+    OnnxStableDiffusionPipeline,
     PNDMScheduler,
     StableDiffusionPipeline,
 )
 from onnx import load_model
 from transformers import CLIPTokenizer
 
-from ..constants import ONNX_MODEL
-from ..diffusers.utils import expand_prompt
-
 try:
     from diffusers import DEISMultistepScheduler
 except ImportError:
@@ -38,8 +38,13 @@ try:
 except ImportError:
     from ..diffusers.stub_scheduler import StubScheduler as UniPCMultistepScheduler
 
+from ..constants import ONNX_MODEL
 from ..convert.diffusion.lora import blend_loras, buffer_external_data_tensors
 from ..convert.diffusion.textual_inversion import blend_textual_inversions
+from ..diffusers.pipelines.controlnet import OnnxStableDiffusionControlNetPipeline
+from ..diffusers.pipelines.pix2pix import OnnxStableDiffusionInstructPix2PixPipeline
+from ..diffusers.lpw_stable_diffusion_onnx import OnnxStableDiffusionLongPromptWeightingPipeline
+from ..diffusers.utils import expand_prompt
 from ..params import DeviceParams, Size
 from ..server import ServerContext
 from ..utils import run_gc
@@ -49,6 +54,15 @@ logger = getLogger(__name__)
 latent_channels = 4
 latent_factor = 8
 
+available_pipelines = {
+    "controlnet": OnnxStableDiffusionControlNetPipeline,
+    "img2img": OnnxStableDiffusionImg2ImgPipeline,
+    "inpaint": OnnxStableDiffusionInpaintPipeline,
+    "lpw": OnnxStableDiffusionLongPromptWeightingPipeline,
+    "pix2pix": OnnxStableDiffusionInstructPix2PixPipeline,
+    "txt2img": OnnxStableDiffusionPipeline,
+}
+
 pipeline_schedulers = {
     "ddim": DDIMScheduler,
     "ddpm": DDPMScheduler,
@@ -68,8 +82,12 @@ pipeline_schedulers = {
 }
 
 
-def get_pipeline_schedulers():
-    return pipeline_schedulers
+def get_available_pipelines() -> List[str]:
+    return list(available_pipelines.keys())
+
+
+def get_pipeline_schedulers() -> List[str]:
+    return list(pipeline_schedulers.keys())
 
 
 def get_scheduler_name(scheduler: Any) -> Optional[str]:
@@ -111,11 +129,10 @@ def get_tile_latents(
 
 def load_pipeline(
     server: ServerContext,
-    pipeline: DiffusionPipeline,
+    pipeline: str,
     model: str,
     scheduler_name: str,
     device: DeviceParams,
-    lpw: bool,
     control: Optional[str] = None,
     inversions: Optional[List[Tuple[str, float]]] = None,
     loras: Optional[List[Tuple[str, float]]] = None,
@@ -129,7 +146,7 @@ def load_pipeline(
     )
     logger.debug("using Torch dtype %s for pipeline", torch_dtype)
     pipe_key = (
-        pipeline.__name__,
+        pipeline,
         model,
         device.device,
         device.provider,
@@ -170,11 +187,6 @@ def load_pipeline(
             logger.debug("unloading previous diffusion pipeline")
             run_gc([device])
 
-        if lpw:
-            custom_pipeline = "./onnx_web/diffusers/lpw_stable_diffusion_onnx.py"
-        else:
-            custom_pipeline = None
-
         logger.debug("loading new diffusion pipeline from %s", model)
         components = {
             "scheduler": scheduler_type.from_pretrained(
@@ -281,6 +293,7 @@ def load_pipeline(
                 )
             )
 
+        # ControlNet component
         if control is not None:
             components["controlnet"] = OnnxRuntimeModel(
                 OnnxRuntimeModel.load_model(
@@ -290,9 +303,10 @@ def load_pipeline(
                 )
             )
 
-        pipe = pipeline.from_pretrained(
+        pipeline_class = available_pipelines.get(pipeline, OnnxStableDiffusionPipeline)
+        logger.debug("loading pretrained SD pipeline for %s", pipeline_class.__name__)
+        pipe = pipeline_class.from_pretrained(
             model,
-            custom_pipeline=custom_pipeline,
             provider=device.ort_provider(),
             sess_options=device.sess_options(),
             revision="onnx",
@@ -306,12 +320,12 @@ def load_pipeline(
 
         optimize_pipeline(server, pipe)
 
+        # TODO: CPU VAE, etc
         if device is not None and hasattr(pipe, "to"):
             pipe = pipe.to(device.torch_str())
 
         # monkey-patch pipeline
-        if not lpw:
-            patch_pipeline(server, pipe, pipeline)
+        patch_pipeline(server, pipe, pipeline)
 
         server.cache.set("diffusion", pipe_key, pipe)
         server.cache.set("scheduler", scheduler_key, components["scheduler"])
diff --git a/api/onnx_web/diffusers/run.py b/api/onnx_web/diffusers/run.py
index c71a04b7..891f4c34 100644
--- a/api/onnx_web/diffusers/run.py
+++ b/api/onnx_web/diffusers/run.py
@@ -47,17 +47,16 @@ def run_txt2img_pipeline(
 
     pipe = load_pipeline(
         server,
-        OnnxStableDiffusionPipeline,
+        "txt2img",
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
         inversions,
         loras,
     )
     progress = job.get_progress_callback()
 
-    if params.lpw:
+    if params.lpw():
         logger.debug("using LPW pipeline for txt2img")
         rng = torch.manual_seed(params.seed)
         result = pipe.text2img(
@@ -117,11 +116,10 @@ def run_txt2img_pipeline(
             # load img2img pipeline once
             highres_pipe = load_pipeline(
                 server,
-                OnnxStableDiffusionImg2ImgPipeline,
+                "img2img",
                 params.model,
                 params.scheduler,
                 job.get_device(),
-                params.lpw,
                 inversions,
                 loras,
             )
@@ -153,7 +151,7 @@ def run_txt2img_pipeline(
                         callback=highres_progress,
                     )
 
-                if params.lpw:
+                if params.lpw():
                     logger.debug("using LPW pipeline for highres")
                     rng = torch.manual_seed(params.seed)
                     result = highres_pipe.img2img(
@@ -233,18 +231,16 @@ def run_img2img_pipeline(
 
     pipe = load_pipeline(
         server,
-        # OnnxStableDiffusionImg2ImgPipeline,
-        OnnxStableDiffusionControlNetPipeline,
+        "img2img",
         params.model,
         params.scheduler,
         job.get_device(),
-        params.lpw,
         control=params.control,
         inversions=inversions,
         loras=loras,
     )
     progress = job.get_progress_callback()
-    if params.lpw:
+    if params.lpw():
         logger.debug("using LPW pipeline for img2img")
         rng = torch.manual_seed(params.seed)
         result = pipe.img2img(
diff --git a/api/onnx_web/output.py b/api/onnx_web/output.py
index 013882fc..5a9a7ed8 100644
--- a/api/onnx_web/output.py
+++ b/api/onnx_web/output.py
@@ -75,13 +75,13 @@ def make_output_name(
 
     hash_value(sha, mode)
     hash_value(sha, params.model)
+    hash_value(sha, params.pipeline)
     hash_value(sha, params.scheduler)
     hash_value(sha, params.prompt)
     hash_value(sha, params.negative_prompt)
     hash_value(sha, params.cfg)
     hash_value(sha, params.seed)
     hash_value(sha, params.steps)
-    hash_value(sha, params.lpw)
     hash_value(sha, params.eta)
     hash_value(sha, params.batch)
     hash_value(sha, size.width)
diff --git a/api/onnx_web/params.py b/api/onnx_web/params.py
index 6643d35c..5bc7d68c 100644
--- a/api/onnx_web/params.py
+++ b/api/onnx_web/params.py
@@ -161,6 +161,7 @@ class DeviceParams:
 
 class ImageParams:
     model: str
+    pipeline: str
     scheduler: str
     prompt: str
     cfg: float
@@ -175,39 +176,42 @@ class ImageParams:
     def __init__(
         self,
         model: str,
+        pipeline: str,
         scheduler: str,
         prompt: str,
         cfg: float,
         steps: int,
         seed: int,
         negative_prompt: Optional[str] = None,
-        lpw: bool = False,
         eta: float = 0.0,
         batch: int = 1,
         control: Optional[str] = None,
     ) -> None:
         self.model = model
+        self.pipeline = pipeline
         self.scheduler = scheduler
         self.prompt = prompt
         self.negative_prompt = negative_prompt
         self.cfg = cfg
         self.seed = seed
         self.steps = steps
-        self.lpw = lpw or False
         self.eta = eta
         self.batch = batch
         self.control = control
 
+    def lpw(self):
+        return self.pipeline == "lpw"
+
     def tojson(self) -> Dict[str, Optional[Param]]:
         return {
             "model": self.model,
+            "pipeline": self.pipeline,
             "scheduler": self.scheduler,
             "prompt": self.prompt,
             "negative_prompt": self.negative_prompt,
             "cfg": self.cfg,
             "seed": self.seed,
             "steps": self.steps,
-            "lpw": self.lpw,
             "eta": self.eta,
             "batch": self.batch,
             "control": self.control.name,
@@ -216,13 +220,13 @@ class ImageParams:
     def with_args(self, **kwargs):
         return ImageParams(
             kwargs.get("model", self.model),
+            kwargs.get("pipeline", self.pipeline),
             kwargs.get("scheduler", self.scheduler),
             kwargs.get("prompt", self.prompt),
+            kwargs.get("negative_prompt", self.negative_prompt),
             kwargs.get("cfg", self.cfg),
             kwargs.get("steps", self.steps),
             kwargs.get("seed", self.seed),
-            kwargs.get("negative_prompt", self.negative_prompt),
-            kwargs.get("lpw", self.lpw),
             kwargs.get("eta", self.eta),
             kwargs.get("batch", self.batch),
             kwargs.get("control", self.control),
diff --git a/api/onnx_web/server/params.py b/api/onnx_web/server/params.py
index 526dfe49..275904f1 100644
--- a/api/onnx_web/server/params.py
+++ b/api/onnx_web/server/params.py
@@ -4,7 +4,7 @@ from typing import Tuple
 import numpy as np
 from flask import request
 
-from ..diffusers.load import pipeline_schedulers
+from ..diffusers.load import get_available_pipelines, get_pipeline_schedulers, pipeline_schedulers
 from ..params import (
     Border,
     DeviceParams,
@@ -30,6 +30,7 @@ logger = getLogger(__name__)
 
 def pipeline_from_request(
     server: ServerContext,
+    default_pipeline: str,
 ) -> Tuple[DeviceParams, ImageParams, Size]:
     user = request.remote_addr
 
@@ -42,15 +43,16 @@ def pipeline_from_request(
             if platform.device == device_name:
                 device = platform
 
-    # pipeline stuff
-    lpw = get_not_empty(request.args, "lpw", "false") == "true"
+    # diffusion model
     model = get_not_empty(request.args, "model", get_config_value("model"))
     model_path = get_model_path(server, model)
-    scheduler = get_from_list(
-        request.args, "scheduler", list(pipeline_schedulers.keys())
-    )
     control = get_from_list(request.args, "control", get_network_models())
 
+    # pipeline stuff
+    pipeline = get_from_list(request.args, "pipeline", get_available_pipelines(), default_pipeline)
+    scheduler = get_from_list(
+        request.args, "scheduler", get_pipeline_schedulers())
+
     if scheduler is None:
         scheduler = get_config_value("scheduler")
 
@@ -110,11 +112,12 @@ def pipeline_from_request(
         seed = np.random.randint(np.iinfo(np.int32).max)
 
     logger.info(
-        "request from %s: %s rounds of %s using %s on %s, %sx%s, %s, %s - %s",
+        "request from %s: %s steps of %s using %s in %s on %s, %sx%s, %s, %s - %s",
         user,
         steps,
         scheduler,
         model_path,
+        pipeline,
         device or "any device",
         width,
         height,
@@ -125,6 +128,7 @@ def pipeline_from_request(
 
     params = ImageParams(
         model_path,
+        pipeline,
         scheduler,
         prompt,
         cfg,
diff --git a/api/params.json b/api/params.json
index 7eaaaacb..9212fb2a 100644
--- a/api/params.json
+++ b/api/params.json
@@ -124,6 +124,14 @@
     "max": 4,
     "step": 1
   },
+  "pipeline": {
+    "default": "",
+    "keys": [
+      "controlnet",
+      "lpw",
+      "pix2pix"
+    ]
+  },
   "platform": {
     "default": "amd",
     "keys": []
diff --git a/api/pyproject.toml b/api/pyproject.toml
index aabd4334..53c7d5bf 100644
--- a/api/pyproject.toml
+++ b/api/pyproject.toml
@@ -9,8 +9,7 @@ skip_glob = ["*/lpw_stable_diffusion_onnx.py", "*/pipeline_onnx_stable_diffusion
 [tool.mypy]
 # ignore_missing_imports = true
 exclude = [
-    "onnx_web.diffusers.lpw_stable_diffusion_onnx",
-    "onnx_web.diffusers.pipeline_onnx_stable_diffusion_upscale"
+    "onnx_web.diffusers.lpw_stable_diffusion_onnx"
 ]
 
 [[tool.mypy.overrides]]
diff --git a/gui/examples/config.json b/gui/examples/config.json
index fc907d3d..5514d239 100644
--- a/gui/examples/config.json
+++ b/gui/examples/config.json
@@ -122,6 +122,14 @@
       "max": 4,
       "step": 1
     },
+    "pipeline": {
+      "default": "",
+      "keys": [
+        "controlnet",
+        "lpw",
+        "pix2pix"
+      ]
+    },
     "platform": {
       "default": "amd",
       "keys": []
diff --git a/gui/src/client/api.ts b/gui/src/client/api.ts
index 56710758..4b1ab699 100644
--- a/gui/src/client/api.ts
+++ b/gui/src/client/api.ts
@@ -13,6 +13,11 @@ export interface ModelParams {
    */
   model: string;
 
+  /**
+   * Specialized pipeline to use.
+   */
+  pipeline: string;
+
   /**
    * The hardware acceleration platform to use.
    */
@@ -28,11 +33,6 @@ export interface ModelParams {
    */
   correction: string;
 
-  /**
-   * Use the long prompt weighting pipeline.
-   */
-  lpw: boolean;
-
   /**
    * ControlNet to be used.
    */
@@ -270,6 +270,11 @@ export interface ApiClient {
    */
   params(): Promise<ServerParams>;
 
+  /**
+   * Get the available pipelines.
+   */
+  pipelines(): Promise<Array<string>>;
+
   /**
    * Get the available hardware acceleration platforms.
    */
@@ -393,10 +398,10 @@ export function makeImageURL(root: string, type: string, params: BaseImgParams):
  */
 export function appendModelToURL(url: URL, params: ModelParams) {
   url.searchParams.append('model', params.model);
+  url.searchParams.append('pipeline', params.pipeline);
   url.searchParams.append('platform', params.platform);
   url.searchParams.append('upscaling', params.upscaling);
   url.searchParams.append('correction', params.correction);
-  url.searchParams.append('lpw', String(params.lpw));
   url.searchParams.append('control', params.control);
 }
 
@@ -453,6 +458,11 @@ export function makeClient(root: string, f = fetch): ApiClient {
       const res = await f(path);
       return await res.json() as Array<string>;
     },
+    async pipelines(): Promise<Array<string>> {
+      const path = makeApiUrl(root, 'settings', 'pipelines');
+      const res = await f(path);
+      return await res.json() as Array<string>;
+    },
     async platforms(): Promise<Array<string>> {
       const path = makeApiUrl(root, 'settings', 'platforms');
       const res = await f(path);
diff --git a/gui/src/client/local.ts b/gui/src/client/local.ts
index 8dc931af..452a457d 100644
--- a/gui/src/client/local.ts
+++ b/gui/src/client/local.ts
@@ -50,6 +50,9 @@ export const LOCAL_CLIENT = {
   async models() {
     throw new NoServerError();
   },
+  async pipelines() {
+    throw new NoServerError();
+  },
   async platforms() {
     throw new NoServerError();
   },
diff --git a/gui/src/components/control/ModelControl.tsx b/gui/src/components/control/ModelControl.tsx
index 1fa578dc..0f7e7162 100644
--- a/gui/src/components/control/ModelControl.tsx
+++ b/gui/src/components/control/ModelControl.tsx
@@ -1,9 +1,9 @@
 import { mustExist } from '@apextoaster/js-utils';
-import { Checkbox, FormControlLabel, Stack } from '@mui/material';
+import { Stack } from '@mui/material';
+import { useQuery } from '@tanstack/react-query';
 import * as React from 'react';
 import { useContext } from 'react';
 import { useTranslation } from 'react-i18next';
-import { useQuery } from '@tanstack/react-query';
 import { useHash } from 'react-use/lib/useHash';
 import { useStore } from 'zustand';
 
@@ -24,6 +24,9 @@ export function ModelControl() {
   const models = useQuery(['models'], async () => client.models(), {
     staleTime: STALE_TIME,
   });
+  const pipelines = useQuery(['pipelines'], async () => client.pipelines(), {
+    staleTime: STALE_TIME,
+  });
   const platforms = useQuery(['platforms'], async () => client.platforms(), {
     staleTime: STALE_TIME,
   });
@@ -34,7 +37,6 @@ export function ModelControl() {
     const tab = getTab(hash);
     const current = state.getState();
 
-
     switch (tab) {
       case 'txt2img': {
         const { prompt } = current.txt2img;
@@ -133,17 +135,20 @@ export function ModelControl() {
       />
     </Stack>
     <Stack direction='row' spacing={2}>
-      <FormControlLabel
-        label={t('parameter.lpw')}
-        control={<Checkbox
-          checked={params.lpw}
-          value='check'
-          onChange={(event) => {
-            setModel({
-              lpw: params.lpw === false,
-            });
-          }}
-        />}
+      <QueryList
+        id='pipeline'
+        labelKey='pipeline'
+        name={t('parameter.pipeline')}
+        query={{
+          result: pipelines,
+        }}
+        showEmpty
+        value={params.pipeline}
+        onChange={(pipeline) => {
+          setModel({
+            pipeline,
+          });
+        }}
       />
       <QueryMenu
         id='inversion'
diff --git a/gui/src/state.ts b/gui/src/state.ts
index 7ef0d663..028b3892 100644
--- a/gui/src/state.ts
+++ b/gui/src/state.ts
@@ -502,8 +502,8 @@ export function createStateSlices(server: ServerParams) {
     model: {
       control: server.control.default,
       correction: server.correction.default,
-      lpw: false,
       model: server.model.default,
+      pipeline: server.pipeline.default,
       platform: server.platform.default,
       upscaling: server.upscaling.default,
     },