diff --git a/ui/easydiffusion/model_manager.py b/ui/easydiffusion/model_manager.py
index bdecc109..1ee5ce9d 100644
--- a/ui/easydiffusion/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -5,7 +5,7 @@ import traceback
 from typing import Union
 
 from easydiffusion import app
-from easydiffusion.types import TaskData
+from easydiffusion.types import ModelsData
 from easydiffusion.utils import log
 from sdkit import Context
 from sdkit.models import load_model, scan_model, unload_model, download_model, get_model_info_from_db
@@ -57,7 +57,9 @@ def init():
 
 
 def load_default_models(context: Context):
-    set_vram_optimizations(context)
+    from easydiffusion import runtime
+
+    runtime.set_vram_optimizations(context)
 
     config = app.getConfig()
     context.embeddings_path = os.path.join(app.MODELS_DIR, "embeddings")
@@ -138,43 +140,32 @@ def resolve_model_to_use_single(model_name: str = None, model_type: str = None,
         raise Exception(f"Could not find the desired model {model_name}! Is it present in the {model_dir} folder?")
 
 
-def reload_models_if_necessary(context: Context, task_data: TaskData):
-    face_fix_lower = task_data.use_face_correction.lower() if task_data.use_face_correction else ""
-    upscale_lower = task_data.use_upscale.lower() if task_data.use_upscale else ""
-
-    model_paths_in_req = {
-        "stable-diffusion": task_data.use_stable_diffusion_model,
-        "vae": task_data.use_vae_model,
-        "hypernetwork": task_data.use_hypernetwork_model,
-        "codeformer": task_data.use_face_correction if "codeformer" in face_fix_lower else None,
-        "gfpgan": task_data.use_face_correction if "gfpgan" in face_fix_lower else None,
-        "realesrgan": task_data.use_upscale if "realesrgan" in upscale_lower else None,
-        "latent_upscaler": True if "latent_upscaler" in upscale_lower else None,
-        "nsfw_checker": True if task_data.block_nsfw else None,
-        "lora": task_data.use_lora_model,
-    }
+def reload_models_if_necessary(context: Context, models_data: ModelsData, models_to_force_reload: list = []):
     models_to_reload = {
         model_type: path
-        for model_type, path in model_paths_in_req.items()
+        for model_type, path in models_data.model_paths.items()
         if context.model_paths.get(model_type) != path
     }
 
-    if task_data.codeformer_upscale_faces:
+    if models_data.model_paths.get("codeformer"):
         if "realesrgan" not in models_to_reload and "realesrgan" not in context.models:
             default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
             models_to_reload["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
         elif "realesrgan" in models_to_reload and models_to_reload["realesrgan"] is None:
             del models_to_reload["realesrgan"]  # don't unload realesrgan
 
-    if set_vram_optimizations(context) or set_clip_skip(context, task_data):  # reload SD
-        models_to_reload["stable-diffusion"] = model_paths_in_req["stable-diffusion"]
+    for model_type in models_to_force_reload:
+        if model_type not in models_data.model_paths:
+            continue
+        models_to_reload[model_type] = models_data.model_paths[model_type]
 
     for model_type, model_path_in_req in models_to_reload.items():
         context.model_paths[model_type] = model_path_in_req
 
         action_fn = unload_model if context.model_paths[model_type] is None else load_model
+        extra_params = models_data.model_params.get(model_type, {})
         try:
-            action_fn(context, model_type, scan_model=False)  # we've scanned them already
+            action_fn(context, model_type, scan_model=False, **extra_params)  # we've scanned them already
             if model_type in context.model_load_errors:
                 del context.model_load_errors[model_type]
         except Exception as e:
@@ -183,24 +174,15 @@ def reload_models_if_necessary(context: Context, task_data: TaskData):
                 context.model_load_errors[model_type] = str(e)  # storing the entire Exception can lead to memory leaks
 
 
-def resolve_model_paths(task_data: TaskData):
-    task_data.use_stable_diffusion_model = resolve_model_to_use(
-        task_data.use_stable_diffusion_model, model_type="stable-diffusion"
-    )
-    task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type="vae")
-    task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type="hypernetwork")
-    task_data.use_lora_model = resolve_model_to_use(task_data.use_lora_model, model_type="lora")
-
-    if task_data.use_face_correction:
-        if "gfpgan" in task_data.use_face_correction.lower():
-            model_type = "gfpgan"
-        elif "codeformer" in task_data.use_face_correction.lower():
-            model_type = "codeformer"
+def resolve_model_paths(models_data: ModelsData):
+    model_paths = models_data.model_paths
+    for model_type in model_paths:
+        if model_type in ("latent_upscaler", "nsfw_checker"):  # doesn't use model paths
+            continue
+        if model_type == "codeformer":
             download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
 
-        task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, model_type)
-    if task_data.use_upscale and "realesrgan" in task_data.use_upscale.lower():
-        task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, "realesrgan")
+        model_paths[model_type] = resolve_model_to_use(model_paths[model_type], model_type=model_type)
 
 
 def fail_if_models_did_not_load(context: Context):
@@ -235,17 +217,6 @@ def download_if_necessary(model_type: str, file_name: str, model_id: str):
         download_model(model_type, model_id, download_base_dir=app.MODELS_DIR)
 
 
-def set_vram_optimizations(context: Context):
-    config = app.getConfig()
-    vram_usage_level = config.get("vram_usage_level", "balanced")
-
-    if vram_usage_level != context.vram_usage_level:
-        context.vram_usage_level = vram_usage_level
-        return True
-
-    return False
-
-
 def migrate_legacy_model_location():
     'Move the models inside the legacy "stable-diffusion" folder, to their respective folders'
 
@@ -266,16 +237,6 @@ def any_model_exists(model_type: str) -> bool:
     return False
 
 
-def set_clip_skip(context: Context, task_data: TaskData):
-    clip_skip = task_data.clip_skip
-
-    if clip_skip != context.clip_skip:
-        context.clip_skip = clip_skip
-        return True
-
-    return False
-
-
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
         model_dir_path = os.path.join(app.MODELS_DIR, model_type)
diff --git a/ui/easydiffusion/runtime.py b/ui/easydiffusion/runtime.py
new file mode 100644
index 00000000..4098ee8e
--- /dev/null
+++ b/ui/easydiffusion/runtime.py
@@ -0,0 +1,53 @@
+"""
+A runtime that runs on a specific device (in a thread).
+
+It can run various tasks like image generation, image filtering, model merge etc by using that thread-local context.
+
+This creates an `sdkit.Context` that's bound to the device specified while calling the `init()` function.
+"""
+
+from easydiffusion import device_manager
+from easydiffusion.utils import log
+from sdkit import Context
+from sdkit.utils import get_device_usage
+
+context = Context()  # thread-local
+"""
+runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
+"""
+
+
+def init(device):
+    """
+    Initializes the fields that will be bound to this runtime's context, and sets the current torch device
+    """
+    context.stop_processing = False
+    context.temp_images = {}
+    context.partial_x_samples = None
+    context.model_load_errors = {}
+    context.enable_codeformer = True
+
+    from easydiffusion import app
+
+    app_config = app.getConfig()
+    context.test_diffusers = (
+        app_config.get("test_diffusers", False) and app_config.get("update_branch", "main") != "main"
+    )
+
+    log.info("Device usage during initialization:")
+    get_device_usage(device, log_info=True, process_usage_only=False)
+
+    device_manager.device_init(context, device)
+
+
+def set_vram_optimizations(context: Context):
+    from easydiffusion import app
+
+    config = app.getConfig()
+    vram_usage_level = config.get("vram_usage_level", "balanced")
+
+    if vram_usage_level != context.vram_usage_level:
+        context.vram_usage_level = vram_usage_level
+        return True
+
+    return False
diff --git a/ui/easydiffusion/server.py b/ui/easydiffusion/server.py
index df788b0c..0f1890c3 100644
--- a/ui/easydiffusion/server.py
+++ b/ui/easydiffusion/server.py
@@ -9,7 +9,16 @@ import traceback
 from typing import List, Union
 
 from easydiffusion import app, model_manager, task_manager
-from easydiffusion.types import GenerateImageRequest, MergeRequest, TaskData
+from easydiffusion.tasks import RenderTask, FilterTask
+from easydiffusion.types import (
+    GenerateImageRequest,
+    FilterImageRequest,
+    MergeRequest,
+    TaskData,
+    ModelsData,
+    OutputFormatData,
+    convert_legacy_render_req_to_new,
+)
 from easydiffusion.utils import log
 from fastapi import FastAPI, HTTPException
 from fastapi.staticfiles import StaticFiles
@@ -97,6 +106,10 @@ def init():
     def render(req: dict):
         return render_internal(req)
 
+    @server_api.post("/filter")
+    def render(req: dict):
+        return filter_internal(req)
+
     @server_api.post("/model/merge")
     def model_merge(req: dict):
         print(req)
@@ -228,9 +241,13 @@ def ping_internal(session_id: str = None):
 
 def render_internal(req: dict):
     try:
+        req = convert_legacy_render_req_to_new(req)
+
         # separate out the request data into rendering and task-specific data
         render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
         task_data: TaskData = TaskData.parse_obj(req)
+        models_data: ModelsData = ModelsData.parse_obj(req)
+        output_format: OutputFormatData = OutputFormatData.parse_obj(req)
 
         # Overwrite user specified save path
         config = app.getConfig()
@@ -240,28 +257,53 @@ def render_internal(req: dict):
         render_req.init_image_mask = req.get("mask")  # hack: will rename this in the HTTP API in a future revision
 
         app.save_to_config(
-            task_data.use_stable_diffusion_model,
-            task_data.use_vae_model,
-            task_data.use_hypernetwork_model,
+            models_data.model_paths.get("stable-diffusion"),
+            models_data.model_paths.get("vae"),
+            models_data.model_paths.get("hypernetwork"),
             task_data.vram_usage_level,
         )
 
         # enqueue the task
-        new_task = task_manager.render(render_req, task_data)
+        task = RenderTask(render_req, task_data, models_data, output_format)
+        return enqueue_task(task)
+    except HTTPException as e:
+        raise e
+    except Exception as e:
+        log.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def filter_internal(req: dict):
+    try:
+        session_id = req.get("session_id", "session")
+        filter_req: FilterImageRequest = FilterImageRequest.parse_obj(req)
+        models_data: ModelsData = ModelsData.parse_obj(req)
+        output_format: OutputFormatData = OutputFormatData.parse_obj(req)
+
+        # enqueue the task
+        task = FilterTask(filter_req, session_id, models_data, output_format)
+        return enqueue_task(task)
+    except HTTPException as e:
+        raise e
+    except Exception as e:
+        log.error(traceback.format_exc())
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def enqueue_task(task):
+    try:
+        task_manager.enqueue_task(task)
         response = {
             "status": str(task_manager.current_state),
             "queue": len(task_manager.tasks_queue),
-            "stream": f"/image/stream/{id(new_task)}",
-            "task": id(new_task),
+            "stream": f"/image/stream/{task.id}",
+            "task": task.id,
         }
         return JSONResponse(response, headers=NOCACHE_HEADERS)
     except ChildProcessError as e:  # Render thread is dead
         raise HTTPException(status_code=500, detail=f"Rendering thread has died.")  # HTTP500 Internal Server Error
     except ConnectionRefusedError as e:  # Unstarted task pending limit reached, deny queueing too many.
         raise HTTPException(status_code=503, detail=str(e))  # HTTP503 Service Unavailable
-    except Exception as e:
-        log.error(traceback.format_exc())
-        raise HTTPException(status_code=500, detail=str(e))
 
 
 def model_merge_internal(req: dict):
diff --git a/ui/easydiffusion/task_manager.py b/ui/easydiffusion/task_manager.py
index a91cd9c6..27b53b6f 100644
--- a/ui/easydiffusion/task_manager.py
+++ b/ui/easydiffusion/task_manager.py
@@ -17,7 +17,7 @@ from typing import Any, Hashable
 
 import torch
 from easydiffusion import device_manager
-from easydiffusion.types import GenerateImageRequest, TaskData
+from easydiffusion.tasks import Task
 from easydiffusion.utils import log
 from sdkit.utils import gc
 
@@ -27,6 +27,7 @@ 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.
+MAX_OVERLOAD_ALLOWED_RATIO = 2  # i.e. 2x pending tasks compared to the number of render threads
 
 
 class SymbolClass(type):  # Print nicely formatted Symbol names.
@@ -58,46 +59,6 @@ class ServerStates:
         pass
 
 
-class RenderTask:  # Task with output queue and completion lock.
-    def __init__(self, req: GenerateImageRequest, task_data: TaskData):
-        task_data.request_id = id(self)
-        self.render_request: GenerateImageRequest = req  # Initial Request
-        self.task_data: TaskData = task_data
-        self.response: Any = None  # Copy of the last reponse
-        self.render_device = None  # Select the task affinity. (Not used to change active devices).
-        self.temp_images: list = [None] * req.num_outputs * (1 if task_data.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
-        self.buffer_queue: queue.Queue = queue.Queue()  # Queue of JSON string segments
-
-    async def read_buffer_generator(self):
-        try:
-            while not self.buffer_queue.empty():
-                res = self.buffer_queue.get(block=False)
-                self.buffer_queue.task_done()
-                yield res
-        except queue.Empty as e:
-            yield
-
-    @property
-    def status(self):
-        if self.lock.locked():
-            return "running"
-        if isinstance(self.error, StopAsyncIteration):
-            return "stopped"
-        if self.error:
-            return "error"
-        if not self.buffer_queue.empty():
-            return "buffer"
-        if self.response:
-            return "completed"
-        return "pending"
-
-    @property
-    def is_pending(self):
-        return bool(not self.response and not self.error)
-
-
 # Temporary cache to allow to query tasks results for a short time after they are completed.
 class DataCache:
     def __init__(self):
@@ -123,8 +84,8 @@ class DataCache:
             # Remove Items
             for key in to_delete:
                 (_, val) = self._base[key]
-                if isinstance(val, RenderTask):
-                    log.debug(f"RenderTask {key} expired. Data removed.")
+                if isinstance(val, Task):
+                    log.debug(f"Task {key} expired. Data removed.")
                 elif isinstance(val, SessionState):
                     log.debug(f"Session {key} expired. Data removed.")
                 else:
@@ -220,8 +181,8 @@ class SessionState:
                 tasks.append(task)
         return tasks
 
-    def put(self, task, ttl=TASK_TTL):
-        task_id = id(task)
+    def put(self, task: Task, ttl=TASK_TTL):
+        task_id = task.id
         self._tasks_ids.append(task_id)
         if not task_cache.put(task_id, task, ttl):
             return False
@@ -230,11 +191,16 @@ class SessionState:
         return True
 
 
+def keep_task_alive(task: Task):
+    task_cache.keep(task.id, TASK_TTL)
+    session_cache.keep(task.session_id, TASK_TTL)
+
+
 def thread_get_next_task():
-    from easydiffusion import renderer
+    from easydiffusion import runtime
 
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
-        log.warn(f"Render thread on device: {renderer.context.device} failed to acquire manager lock.")
+        log.warn(f"Render thread on device: {runtime.context.device} failed to acquire manager lock.")
         return None
     if len(tasks_queue) <= 0:
         manager_lock.release()
@@ -242,7 +208,7 @@ def thread_get_next_task():
     task = None
     try:  # Select a render task.
         for queued_task in tasks_queue:
-            if queued_task.render_device and renderer.context.device != queued_task.render_device:
+            if queued_task.render_device and runtime.context.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.
@@ -251,7 +217,7 @@ def thread_get_next_task():
                     queued_task.error = Exception(queued_task.render_device + " is not currently active.")
                     task = queued_task
                     break
-            if not queued_task.render_device and renderer.context.device == "cpu" and is_alive() > 1:
+            if not queued_task.render_device and runtime.context.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
@@ -266,19 +232,19 @@ def thread_get_next_task():
 def thread_render(device):
     global current_state, current_state_error
 
-    from easydiffusion import model_manager, renderer
+    from easydiffusion import model_manager, runtime
 
     try:
-        renderer.init(device)
+        runtime.init(device)
 
         weak_thread_data[threading.current_thread()] = {
-            "device": renderer.context.device,
-            "device_name": renderer.context.device_name,
+            "device": runtime.context.device,
+            "device_name": runtime.context.device_name,
             "alive": True,
         }
 
         current_state = ServerStates.LoadingModel
-        model_manager.load_default_models(renderer.context)
+        model_manager.load_default_models(runtime.context)
 
         current_state = ServerStates.Online
     except Exception as e:
@@ -290,8 +256,8 @@ def thread_render(device):
         session_cache.clean()
         task_cache.clean()
         if not weak_thread_data[threading.current_thread()]["alive"]:
-            log.info(f"Shutting down thread for device {renderer.context.device}")
-            model_manager.unload_all(renderer.context)
+            log.info(f"Shutting down thread for device {runtime.context.device}")
+            model_manager.unload_all(runtime.context)
             return
         if isinstance(current_state_error, SystemExit):
             current_state = ServerStates.Unavailable
@@ -311,62 +277,31 @@ def thread_render(device):
             task.response = {"status": "failed", "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        log.info(f"Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}")
+        log.info(f"Session {task.session_id} starting task {task.id} on {runtime.context.device_name}")
         if not task.lock.acquire(blocking=False):
             raise Exception("Got locked task from queue.")
         try:
+            task.run()
 
-            def step_callback():
-                global current_state_error
-
-                task_cache.keep(id(task), TASK_TTL)
-                session_cache.keep(task.task_data.session_id, TASK_TTL)
-
-                if (
-                    isinstance(current_state_error, SystemExit)
-                    or isinstance(current_state_error, StopAsyncIteration)
-                    or isinstance(task.error, StopAsyncIteration)
-                ):
-                    renderer.context.stop_processing = True
-                    if isinstance(current_state_error, StopAsyncIteration):
-                        task.error = current_state_error
-                        current_state_error = None
-                        log.info(f"Session {task.task_data.session_id} sent cancel signal for task {id(task)}")
-
-            current_state = ServerStates.LoadingModel
-            model_manager.resolve_model_paths(task.task_data)
-            model_manager.reload_models_if_necessary(renderer.context, task.task_data)
-            model_manager.fail_if_models_did_not_load(renderer.context)
-
-            current_state = ServerStates.Rendering
-            task.response = renderer.make_images(
-                task.render_request,
-                task.task_data,
-                task.buffer_queue,
-                task.temp_images,
-                step_callback,
-            )
             # Before looping back to the generator, mark cache as still alive.
-            task_cache.keep(id(task), TASK_TTL)
-            session_cache.keep(task.task_data.session_id, TASK_TTL)
+            keep_task_alive(task)
         except Exception as e:
             task.error = str(e)
             task.response = {"status": "failed", "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             log.error(traceback.format_exc())
         finally:
-            gc(renderer.context)
+            gc(runtime.context)
             task.lock.release()
-        task_cache.keep(id(task), TASK_TTL)
-        session_cache.keep(task.task_data.session_id, TASK_TTL)
+
+        keep_task_alive(task)
+
         if isinstance(task.error, StopAsyncIteration):
-            log.info(f"Session {task.task_data.session_id} task {id(task)} cancelled!")
+            log.info(f"Session {task.session_id} task {task.id} cancelled!")
         elif task.error is not None:
-            log.info(f"Session {task.task_data.session_id} task {id(task)} failed!")
+            log.info(f"Session {task.session_id} task {task.id} failed!")
         else:
-            log.info(
-                f"Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}."
-            )
+            log.info(f"Session {task.session_id} task {task.id} completed by {runtime.context.device_name}.")
         current_state = ServerStates.Online
 
 
@@ -548,28 +483,27 @@ def shutdown_event():  # Signal render thread to close on shutdown
     current_state_error = SystemExit("Application shutting down.")
 
 
-def render(render_req: GenerateImageRequest, task_data: TaskData):
+def enqueue_task(task: Task):
     current_thread_count = is_alive()
     if current_thread_count <= 0:  # Render thread is dead
         raise ChildProcessError("Rendering thread has died.")
 
     # Alive, check if task in cache
-    session = get_cached_session(task_data.session_id, update_ttl=True)
+    session = get_cached_session(task.session_id, update_ttl=True)
     pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
-    if current_thread_count < len(pending_tasks):
+    if len(pending_tasks) > current_thread_count * MAX_OVERLOAD_ALLOWED_RATIO:
         raise ConnectionRefusedError(
-            f"Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}."
+            f"Session {task.session_id} already has {len(pending_tasks)} pending tasks, with {current_thread_count} workers."
         )
 
-    new_task = RenderTask(render_req, task_data)
-    if session.put(new_task, TASK_TTL):
+    if session.put(task, TASK_TTL):
         # Use twice the normal timeout for adding user requests.
         # Tries to force session.put to fail before tasks_queue.put would.
         if manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT * 2):
             try:
-                tasks_queue.append(new_task)
+                tasks_queue.append(task)
                 idle_event.set()
-                return new_task
+                return task
             finally:
                 manager_lock.release()
     raise RuntimeError("Failed to add task to cache.")
diff --git a/ui/easydiffusion/tasks/__init__.py b/ui/easydiffusion/tasks/__init__.py
new file mode 100644
index 00000000..1d295da8
--- /dev/null
+++ b/ui/easydiffusion/tasks/__init__.py
@@ -0,0 +1,3 @@
+from .task import Task
+from .render_images import RenderTask
+from .filter_images import FilterTask
diff --git a/ui/easydiffusion/tasks/filter_images.py b/ui/easydiffusion/tasks/filter_images.py
new file mode 100644
index 00000000..c4e674d7
--- /dev/null
+++ b/ui/easydiffusion/tasks/filter_images.py
@@ -0,0 +1,110 @@
+import json
+import pprint
+
+from sdkit.filter import apply_filters
+from sdkit.models import load_model
+from sdkit.utils import img_to_base64_str, log
+
+from easydiffusion import model_manager, runtime
+from easydiffusion.types import FilterImageRequest, FilterImageResponse, ModelsData, OutputFormatData
+
+from .task import Task
+
+
+class FilterTask(Task):
+    "For applying filters to input images"
+
+    def __init__(
+        self, req: FilterImageRequest, session_id: str, models_data: ModelsData, output_format: OutputFormatData
+    ):
+        super().__init__(session_id)
+
+        self.request = req
+        self.models_data = models_data
+        self.output_format = output_format
+
+        # convert to multi-filter format, if necessary
+        if isinstance(req.filter, str):
+            req.filter_params = {req.filter: req.filter_params}
+            req.filter = [req.filter]
+
+        if not isinstance(req.image, list):
+            req.image = [req.image]
+
+    def run(self):
+        "Runs the image filtering task on the assigned thread"
+
+        context = runtime.context
+
+        model_manager.resolve_model_paths(self.models_data)
+        model_manager.reload_models_if_necessary(context, self.models_data)
+        model_manager.fail_if_models_did_not_load(context)
+
+        print_task_info(self.request, self.models_data, self.output_format)
+
+        images = filter_images(context, self.request.image, self.request.filter, self.request.filter_params)
+
+        output_format = self.output_format
+        images = [
+            img_to_base64_str(
+                img, output_format.output_format, output_format.output_quality, output_format.output_lossless
+            )
+            for img in images
+        ]
+
+        res = FilterImageResponse(self.request, self.models_data, images=images)
+        res = res.json()
+        self.buffer_queue.put(json.dumps(res))
+        log.info("Filter task completed")
+
+        self.response = res
+
+
+def filter_images(context, images, filters, filter_params={}):
+    filters = filters if isinstance(filters, list) else [filters]
+
+    for filter_name in filters:
+        params = filter_params.get(filter_name, {})
+
+        previous_state = before_filter(context, filter_name, params)
+
+        try:
+            images = apply_filters(context, filter_name, images, **params)
+        finally:
+            after_filter(context, filter_name, params, previous_state)
+
+    return images
+
+
+def before_filter(context, filter_name, filter_params):
+    if filter_name == "codeformer":
+        from easydiffusion.model_manager import DEFAULT_MODELS, resolve_model_to_use
+
+        default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
+        prev_realesrgan_path = None
+
+        upscale_faces = filter_params.get("upscale_faces", False)
+        if upscale_faces and default_realesrgan not in context.model_paths["realesrgan"]:
+            prev_realesrgan_path = context.model_paths.get("realesrgan")
+            context.model_paths["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
+            load_model(context, "realesrgan")
+
+        return prev_realesrgan_path
+
+
+def after_filter(context, filter_name, filter_params, previous_state):
+    if filter_name == "codeformer":
+        prev_realesrgan_path = previous_state
+        if prev_realesrgan_path:
+            context.model_paths["realesrgan"] = prev_realesrgan_path
+            load_model(context, "realesrgan")
+
+
+def print_task_info(req: FilterImageRequest, models_data: ModelsData, output_format: OutputFormatData):
+    req_str = pprint.pformat({"filter": req.filter, "filter_params": req.filter_params}).replace("[", "\[")
+    models_data = pprint.pformat(models_data.dict()).replace("[", "\[")
+    output_format = pprint.pformat(output_format.dict()).replace("[", "\[")
+
+    log.info(f"request: {req_str}")
+    log.info(f"models data: {models_data}")
+    log.info(f"output format: {output_format}")
diff --git a/ui/easydiffusion/renderer.py b/ui/easydiffusion/tasks/render_images.py
similarity index 54%
rename from ui/easydiffusion/renderer.py
rename to ui/easydiffusion/tasks/render_images.py
index a57dfc6c..42bcc76a 100644
--- a/ui/easydiffusion/renderer.py
+++ b/ui/easydiffusion/tasks/render_images.py
@@ -3,70 +3,109 @@ import pprint
 import queue
 import time
 
-from easydiffusion import device_manager
-from easydiffusion.types import GenerateImageRequest
+from easydiffusion import model_manager, runtime
+from easydiffusion.types import GenerateImageRequest, ModelsData, OutputFormatData
 from easydiffusion.types import Image as ResponseImage
-from easydiffusion.types import Response, TaskData, UserInitiatedStop
-from easydiffusion.model_manager import DEFAULT_MODELS, resolve_model_to_use
+from easydiffusion.types import GenerateImageResponse, TaskData, UserInitiatedStop
 from easydiffusion.utils import get_printable_request, log, save_images_to_disk
-from sdkit import Context
-from sdkit.filter import apply_filters
 from sdkit.generate import generate_images
-from sdkit.models import load_model
 from sdkit.utils import (
     diffusers_latent_samples_to_images,
     gc,
     img_to_base64_str,
     img_to_buffer,
     latent_samples_to_images,
-    get_device_usage,
 )
 
-context = Context()  # thread-local
-"""
-runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
-"""
+from .task import Task
+from .filter_images import filter_images
 
 
-def init(device):
-    """
-    Initializes the fields that will be bound to this runtime's context, and sets the current torch device
-    """
-    context.stop_processing = False
-    context.temp_images = {}
-    context.partial_x_samples = None
-    context.model_load_errors = {}
-    context.enable_codeformer = True
+class RenderTask(Task):
+    "For image generation"
 
-    from easydiffusion import app
+    def __init__(
+        self, req: GenerateImageRequest, task_data: TaskData, models_data: ModelsData, output_format: OutputFormatData
+    ):
+        super().__init__(task_data.session_id)
 
-    app_config = app.getConfig()
-    context.test_diffusers = (
-        app_config.get("test_diffusers", False) and app_config.get("update_branch", "main") != "main"
-    )
+        task_data.request_id = self.id
+        self.render_request: GenerateImageRequest = req  # Initial Request
+        self.task_data: TaskData = task_data
+        self.models_data = models_data
+        self.output_format = output_format
+        self.temp_images: list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
 
-    log.info("Device usage during initialization:")
-    get_device_usage(device, log_info=True, process_usage_only=False)
+    def run(self):
+        "Runs the image generation task on the assigned thread"
 
-    device_manager.device_init(context, device)
+        from easydiffusion import task_manager
+
+        context = runtime.context
+
+        def step_callback():
+            task_manager.keep_task_alive(self)
+            task_manager.current_state = task_manager.ServerStates.Rendering
+
+            if isinstance(task_manager.current_state_error, (SystemExit, StopAsyncIteration)) or isinstance(
+                self.error, StopAsyncIteration
+            ):
+                context.stop_processing = True
+                if isinstance(task_manager.current_state_error, StopAsyncIteration):
+                    self.error = task_manager.current_state_error
+                    task_manager.current_state_error = None
+                    log.info(f"Session {self.session_id} sent cancel signal for task {self.id}")
+
+        task_manager.current_state = task_manager.ServerStates.LoadingModel
+        model_manager.resolve_model_paths(self.models_data)
+
+        models_to_force_reload = []
+        if runtime.set_vram_optimizations(context) or self.has_clip_skip_changed(context):
+            models_to_force_reload.append("stable-diffusion")
+
+        model_manager.reload_models_if_necessary(context, self.models_data, models_to_force_reload)
+        model_manager.fail_if_models_did_not_load(context)
+
+        task_manager.current_state = task_manager.ServerStates.Rendering
+        self.response = make_images(
+            context,
+            self.render_request,
+            self.task_data,
+            self.models_data,
+            self.output_format,
+            self.buffer_queue,
+            self.temp_images,
+            step_callback,
+        )
+
+    def has_clip_skip_changed(self, context):
+        if not context.test_diffusers:
+            return False
+
+        model = context.models["stable-diffusion"]
+        new_clip_skip = self.models_data.model_params.get("stable-diffusion", {}).get("clip_skip", False)
+        return model["clip_skip"] != new_clip_skip
 
 
 def make_images(
+    context,
     req: GenerateImageRequest,
     task_data: TaskData,
+    models_data: ModelsData,
+    output_format: OutputFormatData,
     data_queue: queue.Queue,
     task_temp_images: list,
     step_callback,
 ):
     context.stop_processing = False
-    print_task_info(req, task_data)
+    print_task_info(req, task_data, models_data, output_format)
 
-    images, seeds = make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+    images, seeds = make_images_internal(
+        context, req, task_data, models_data, output_format, data_queue, task_temp_images, step_callback
+    )
 
-    res = Response(
-        req,
-        task_data,
-        images=construct_response(images, seeds, task_data, base_seed=req.seed),
+    res = GenerateImageResponse(
+        req, task_data, models_data, output_format, images=construct_response(images, seeds, output_format)
     )
     res = res.json()
     data_queue.put(json.dumps(res))
@@ -75,21 +114,32 @@ def make_images(
     return res
 
 
-def print_task_info(req: GenerateImageRequest, task_data: TaskData):
-    req_str = pprint.pformat(get_printable_request(req, task_data)).replace("[", "\[")
+def print_task_info(
+    req: GenerateImageRequest, task_data: TaskData, models_data: ModelsData, output_format: OutputFormatData
+):
+    req_str = pprint.pformat(get_printable_request(req, task_data, output_format)).replace("[", "\[")
     task_str = pprint.pformat(task_data.dict()).replace("[", "\[")
+    models_data = pprint.pformat(models_data.dict()).replace("[", "\[")
+    output_format = pprint.pformat(output_format.dict()).replace("[", "\[")
+
     log.info(f"request: {req_str}")
     log.info(f"task data: {task_str}")
+    # log.info(f"models data: {models_data}")
+    log.info(f"output format: {output_format}")
 
 
 def make_images_internal(
+    context,
     req: GenerateImageRequest,
     task_data: TaskData,
+    models_data: ModelsData,
+    output_format: OutputFormatData,
     data_queue: queue.Queue,
     task_temp_images: list,
     step_callback,
 ):
     images, user_stopped = generate_images_internal(
+        context,
         req,
         task_data,
         data_queue,
@@ -98,11 +148,14 @@ def make_images_internal(
         task_data.stream_image_progress,
         task_data.stream_image_progress_interval,
     )
+
     gc(context)
-    filtered_images = filter_images(req, task_data, images, user_stopped)
+
+    filters, filter_params = task_data.filters, task_data.filter_params
+    filtered_images = filter_images(context, images, filters, filter_params) if not user_stopped else images
 
     if task_data.save_to_disk_path is not None:
-        save_images_to_disk(images, filtered_images, req, task_data)
+        save_images_to_disk(images, filtered_images, req, task_data, output_format)
 
     seeds = [*range(req.seed, req.seed + len(images))]
     if task_data.show_only_filtered_image or filtered_images is images:
@@ -112,6 +165,7 @@ def make_images_internal(
 
 
 def generate_images_internal(
+    context,
     req: GenerateImageRequest,
     task_data: TaskData,
     data_queue: queue.Queue,
@@ -123,6 +177,7 @@ def generate_images_internal(
     context.temp_images.clear()
 
     callback = make_step_callback(
+        context,
         req,
         task_data,
         data_queue,
@@ -155,65 +210,14 @@ def generate_images_internal(
     return images, user_stopped
 
 
-def filter_images(req: GenerateImageRequest, task_data: TaskData, images: list, user_stopped):
-    if user_stopped:
-        return images
-
-    if task_data.block_nsfw:
-        images = apply_filters(context, "nsfw_checker", images)
-
-    if task_data.use_face_correction and "codeformer" in task_data.use_face_correction.lower():
-        default_realesrgan = DEFAULT_MODELS["realesrgan"][0]["file_name"]
-        prev_realesrgan_path = None
-        if task_data.codeformer_upscale_faces and default_realesrgan not in context.model_paths["realesrgan"]:
-            prev_realesrgan_path = context.model_paths["realesrgan"]
-            context.model_paths["realesrgan"] = resolve_model_to_use(default_realesrgan, "realesrgan")
-            load_model(context, "realesrgan")
-
-        try:
-            images = apply_filters(
-                context,
-                "codeformer",
-                images,
-                upscale_faces=task_data.codeformer_upscale_faces,
-                codeformer_fidelity=task_data.codeformer_fidelity,
-            )
-        finally:
-            if prev_realesrgan_path:
-                context.model_paths["realesrgan"] = prev_realesrgan_path
-                load_model(context, "realesrgan")
-    elif task_data.use_face_correction and "gfpgan" in task_data.use_face_correction.lower():
-        images = apply_filters(context, "gfpgan", images)
-
-    if task_data.use_upscale:
-        if "realesrgan" in task_data.use_upscale.lower():
-            images = apply_filters(context, "realesrgan", images, scale=task_data.upscale_amount)
-        elif task_data.use_upscale == "latent_upscaler":
-            images = apply_filters(
-                context,
-                "latent_upscaler",
-                images,
-                scale=task_data.upscale_amount,
-                latent_upscaler_options={
-                    "prompt": req.prompt,
-                    "negative_prompt": req.negative_prompt,
-                    "seed": req.seed,
-                    "num_inference_steps": task_data.latent_upscaler_steps,
-                    "guidance_scale": 0,
-                },
-            )
-
-    return images
-
-
-def construct_response(images: list, seeds: list, task_data: TaskData, base_seed: int):
+def construct_response(images: list, seeds: list, output_format: OutputFormatData):
     return [
         ResponseImage(
             data=img_to_base64_str(
                 img,
-                task_data.output_format,
-                task_data.output_quality,
-                task_data.output_lossless,
+                output_format.output_format,
+                output_format.output_quality,
+                output_format.output_lossless,
             ),
             seed=seed,
         )
@@ -222,6 +226,7 @@ def construct_response(images: list, seeds: list, task_data: TaskData, base_seed
 
 
 def make_step_callback(
+    context,
     req: GenerateImageRequest,
     task_data: TaskData,
     data_queue: queue.Queue,
@@ -242,7 +247,7 @@ def make_step_callback(
             images = latent_samples_to_images(context, x_samples)
 
         if task_data.block_nsfw:
-            images = apply_filters(context, "nsfw_checker", images)
+            images = filter_images(context, images, "nsfw_checker")
 
         for i, img in enumerate(images):
             buf = img_to_buffer(img, output_format="JPEG")
diff --git a/ui/easydiffusion/tasks/task.py b/ui/easydiffusion/tasks/task.py
new file mode 100644
index 00000000..4454efe6
--- /dev/null
+++ b/ui/easydiffusion/tasks/task.py
@@ -0,0 +1,47 @@
+from threading import Lock
+from queue import Queue, Empty as EmptyQueueException
+from typing import Any
+
+
+class Task:
+    "Task with output queue and completion lock"
+
+    def __init__(self, session_id):
+        self.id = id(self)
+        self.session_id = session_id
+        self.render_device = None  # Select the task affinity. (Not used to change active devices).
+        self.error: Exception = None
+        self.lock: Lock = Lock()  # Locks at task start and unlocks when task is completed
+        self.buffer_queue: Queue = Queue()  # Queue of JSON string segments
+        self.response: Any = None  # Copy of the last reponse
+
+    async def read_buffer_generator(self):
+        try:
+            while not self.buffer_queue.empty():
+                res = self.buffer_queue.get(block=False)
+                self.buffer_queue.task_done()
+                yield res
+        except EmptyQueueException as e:
+            yield
+
+    @property
+    def status(self):
+        if self.lock.locked():
+            return "running"
+        if isinstance(self.error, StopAsyncIteration):
+            return "stopped"
+        if self.error:
+            return "error"
+        if not self.buffer_queue.empty():
+            return "buffer"
+        if self.response:
+            return "completed"
+        return "pending"
+
+    @property
+    def is_pending(self):
+        return bool(not self.response and not self.error)
+
+    def run(self):
+        "Override this to implement the task's behavior"
+        pass
diff --git a/ui/easydiffusion/types.py b/ui/easydiffusion/types.py
index a9e49a24..b5f6b21a 100644
--- a/ui/easydiffusion/types.py
+++ b/ui/easydiffusion/types.py
@@ -1,4 +1,4 @@
-from typing import Any, List, Union
+from typing import Any, List, Dict, Union
 
 from pydantic import BaseModel
 
@@ -17,6 +17,8 @@ class GenerateImageRequest(BaseModel):
 
     init_image: Any = None
     init_image_mask: Any = None
+    control_image: Any = None
+    control_alpha: Union[float, List[float]] = None
     prompt_strength: float = 0.8
     preserve_init_image_color_profile = False
 
@@ -26,6 +28,35 @@ class GenerateImageRequest(BaseModel):
     tiling: str = "none"  # "none", "x", "y", "xy"
 
 
+class FilterImageRequest(BaseModel):
+    image: Any = None
+    filter: Union[str, List[str]] = None
+    filter_params: dict = {}
+
+
+class ModelsData(BaseModel):
+    """
+    Contains the information related to the models involved in a request.
+
+    - To load a model: set the relative path(s) to the model in `model_paths`. No effect if already loaded.
+    - To unload a model: set the model to `None` in `model_paths`. No effect if already unloaded.
+
+    Models that aren't present in `model_paths` will not be changed.
+    """
+
+    model_paths: Dict[str, Union[str, None, List[str]]] = None
+    "model_type to string path, or list of string paths"
+
+    model_params: Dict[str, Dict[str, Any]] = {}
+    "model_type to dict of parameters"
+
+
+class OutputFormatData(BaseModel):
+    output_format: str = "jpeg"  # or "png" or "webp"
+    output_quality: int = 75
+    output_lossless: bool = False
+
+
 class TaskData(BaseModel):
     request_id: str = None
     session_id: str = "session"
@@ -40,12 +71,12 @@ class TaskData(BaseModel):
     use_vae_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
+    filters: List[str] = []
+    filter_params: Dict[str, Dict[str, Any]] = {}
 
     show_only_filtered_image: bool = False
     block_nsfw: bool = False
-    output_format: str = "jpeg"  # or "png" or "webp"
-    output_quality: int = 75
-    output_lossless: bool = False
     metadata_output_format: str = "txt"  # or "json"
     stream_image_progress: bool = False
     stream_image_progress_interval: int = 5
@@ -80,24 +111,38 @@ class Image:
         }
 
 
-class Response:
+class GenerateImageResponse:
     render_request: GenerateImageRequest
     task_data: TaskData
+    models_data: ModelsData
     images: list
 
-    def __init__(self, render_request: GenerateImageRequest, task_data: TaskData, images: list):
+    def __init__(
+        self,
+        render_request: GenerateImageRequest,
+        task_data: TaskData,
+        models_data: ModelsData,
+        output_format: OutputFormatData,
+        images: list,
+    ):
         self.render_request = render_request
         self.task_data = task_data
+        self.models_data = models_data
+        self.output_format = output_format
         self.images = images
 
     def json(self):
         del self.render_request.init_image
         del self.render_request.init_image_mask
 
+        task_data = self.task_data.dict()
+        task_data.update(self.output_format.dict())
+
         res = {
             "status": "succeeded",
             "render_request": self.render_request.dict(),
-            "task_data": self.task_data.dict(),
+            "task_data": task_data,
+            # "models_data": self.models_data.dict(), # haven't migrated the UI to the new format (yet)
             "output": [],
         }
 
@@ -107,5 +152,102 @@ class Response:
         return res
 
 
+class FilterImageResponse:
+    request: FilterImageRequest
+    models_data: ModelsData
+    images: list
+
+    def __init__(self, request: FilterImageRequest, models_data: ModelsData, images: list):
+        self.request = request
+        self.models_data = models_data
+        self.images = images
+
+    def json(self):
+        del self.request.image
+
+        res = {
+            "status": "succeeded",
+            "request": self.request.dict(),
+            "models_data": self.models_data.dict(),
+            "output": [],
+        }
+
+        for image in self.images:
+            res["output"].append(image)
+
+        return res
+
+
 class UserInitiatedStop(Exception):
     pass
+
+
+def convert_legacy_render_req_to_new(old_req: dict):
+    new_req = dict(old_req)
+
+    # new keys
+    model_paths = new_req["model_paths"] = {}
+    model_params = new_req["model_params"] = {}
+    filters = new_req["filters"] = []
+    filter_params = new_req["filter_params"] = {}
+
+    # 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["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")
+
+    model_paths["gfpgan"] = old_req.get("use_face_correction", "")
+    model_paths["gfpgan"] = model_paths["gfpgan"] if "gfpgan" in model_paths["gfpgan"].lower() else None
+
+    model_paths["codeformer"] = old_req.get("use_face_correction", "")
+    model_paths["codeformer"] = model_paths["codeformer"] if "codeformer" in model_paths["codeformer"].lower() else None
+
+    model_paths["realesrgan"] = old_req.get("use_upscale", "")
+    model_paths["realesrgan"] = model_paths["realesrgan"] if "realesrgan" in model_paths["realesrgan"].lower() else None
+
+    model_paths["latent_upscaler"] = old_req.get("use_upscale", "")
+    model_paths["latent_upscaler"] = (
+        model_paths["latent_upscaler"] if "latent_upscaler" in model_paths["latent_upscaler"].lower() else None
+    )
+
+    if old_req.get("block_nsfw"):
+        model_paths["nsfw_checker"] = "nsfw_checker"
+
+    # move the model params
+    if model_paths["stable-diffusion"]:
+        model_params["stable-diffusion"] = {"clip_skip": bool(old_req["clip_skip"])}
+
+    # move the filter params
+    if model_paths["realesrgan"]:
+        filter_params["realesrgan"] = {"scale": int(old_req["upscale_amount"])}
+    if model_paths["latent_upscaler"]:
+        filter_params["latent_upscaler"] = {
+            "prompt": old_req["prompt"],
+            "negative_prompt": old_req.get("negative_prompt"),
+            "seed": int(old_req.get("seed", 42)),
+            "num_inference_steps": int(old_req.get("latent_upscaler_steps", 10)),
+            "guidance_scale": 0,
+        }
+    if model_paths["codeformer"]:
+        filter_params["codeformer"] = {
+            "upscale_faces": bool(old_req["codeformer_upscale_faces"]),
+            "codeformer_fidelity": float(old_req["codeformer_fidelity"]),
+        }
+
+    # set the filters
+    if old_req.get("block_nsfw"):
+        filters.append("nsfw_checker")
+
+    if model_paths["codeformer"]:
+        filters.append("codeformer")
+    elif model_paths["gfpgan"]:
+        filters.append("gfpgan")
+
+    if model_paths["realesrgan"]:
+        filters.append("realesrgan")
+    elif model_paths["latent_upscaler"]:
+        filters.append("latent_upscaler")
+
+    return new_req
diff --git a/ui/easydiffusion/utils/save_utils.py b/ui/easydiffusion/utils/save_utils.py
index f27e84de..49743554 100644
--- a/ui/easydiffusion/utils/save_utils.py
+++ b/ui/easydiffusion/utils/save_utils.py
@@ -7,7 +7,7 @@ from datetime import datetime
 from functools import reduce
 
 from easydiffusion import app
-from easydiffusion.types import GenerateImageRequest, TaskData
+from easydiffusion.types import GenerateImageRequest, TaskData, OutputFormatData
 from numpy import base_repr
 from sdkit.utils import save_dicts, save_images
 
@@ -114,12 +114,14 @@ def format_file_name(
     return filename_regex.sub("_", format)
 
 
-def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
+def save_images_to_disk(
+    images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData, output_format: OutputFormatData
+):
     now = time.time()
     app_config = app.getConfig()
     folder_format = app_config.get("folder_format", "$id")
     save_dir_path = os.path.join(task_data.save_to_disk_path, format_folder_name(folder_format, req, task_data))
-    metadata_entries = get_metadata_entries_for_request(req, task_data)
+    metadata_entries = get_metadata_entries_for_request(req, task_data, output_format)
     file_number = calculate_img_number(save_dir_path, task_data)
     make_filename = make_filename_callback(
         app_config.get("filename_format", "$p_$tsb64"),
@@ -134,9 +136,9 @@ def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageR
             filtered_images,
             save_dir_path,
             file_name=make_filename,
-            output_format=task_data.output_format,
-            output_quality=task_data.output_quality,
-            output_lossless=task_data.output_lossless,
+            output_format=output_format.output_format,
+            output_quality=output_format.output_quality,
+            output_lossless=output_format.output_lossless,
         )
         if task_data.metadata_output_format:
             for metadata_output_format in task_data.metadata_output_format.split(","):
@@ -146,7 +148,7 @@ def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageR
                         save_dir_path,
                         file_name=make_filename,
                         output_format=metadata_output_format,
-                        file_format=task_data.output_format,
+                        file_format=output_format.output_format,
                     )
     else:
         make_filter_filename = make_filename_callback(
@@ -162,17 +164,17 @@ def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageR
             images,
             save_dir_path,
             file_name=make_filename,
-            output_format=task_data.output_format,
-            output_quality=task_data.output_quality,
-            output_lossless=task_data.output_lossless,
+            output_format=output_format.output_format,
+            output_quality=output_format.output_quality,
+            output_lossless=output_format.output_lossless,
         )
         save_images(
             filtered_images,
             save_dir_path,
             file_name=make_filter_filename,
-            output_format=task_data.output_format,
-            output_quality=task_data.output_quality,
-            output_lossless=task_data.output_lossless,
+            output_format=output_format.output_format,
+            output_quality=output_format.output_quality,
+            output_lossless=output_format.output_lossless,
         )
         if task_data.metadata_output_format:
             for metadata_output_format in task_data.metadata_output_format.split(","):
@@ -181,20 +183,21 @@ def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageR
                         metadata_entries,
                         save_dir_path,
                         file_name=make_filter_filename,
-                        output_format=task_data.metadata_output_format,
-                        file_format=task_data.output_format,
+                        output_format=metadata_output_format,
+                        file_format=output_format.output_format,
                     )
 
 
-def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
-    metadata = get_printable_request(req, task_data)
+def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData, output_format: OutputFormatData):
+    metadata = get_printable_request(req, task_data, output_format)
 
     # if text, format it in the text format expected by the UI
     is_txt_format = task_data.metadata_output_format and "txt" in task_data.metadata_output_format.lower().split(",")
     if is_txt_format:
+
         def format_value(value):
             if isinstance(value, list):
-                return ", ".join([ str(it) for it in value ])
+                return ", ".join([str(it) for it in value])
             return value
 
         metadata = {
@@ -208,9 +211,10 @@ def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskD
     return entries
 
 
-def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
+def get_printable_request(req: GenerateImageRequest, task_data: TaskData, output_format: OutputFormatData):
     req_metadata = req.dict()
     task_data_metadata = task_data.dict()
+    task_data_metadata.update(output_format.dict())
 
     app_config = app.getConfig()
     using_diffusers = app_config.get("test_diffusers", False)
@@ -224,6 +228,7 @@ def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
             metadata[key] = task_data_metadata[key]
         elif key == "use_embedding_models" and using_diffusers:
             embeddings_extensions = {".pt", ".bin", ".safetensors"}
+
             def scan_directory(directory_path: str):
                 used_embeddings = []
                 for entry in os.scandir(directory_path):
@@ -232,15 +237,18 @@ def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
                         if entry_extension not in embeddings_extensions:
                             continue
 
-                        embedding_name_regex = regex.compile(r"(^|[\s,])" + regex.escape(os.path.splitext(entry.name)[0]) + r"([+-]*$|[\s,]|[+-]+[\s,])")
+                        embedding_name_regex = regex.compile(
+                            r"(^|[\s,])" + regex.escape(os.path.splitext(entry.name)[0]) + r"([+-]*$|[\s,]|[+-]+[\s,])"
+                        )
                         if embedding_name_regex.search(req.prompt) or embedding_name_regex.search(req.negative_prompt):
                             used_embeddings.append(entry.path)
                     elif entry.is_dir():
                         used_embeddings.extend(scan_directory(entry.path))
                 return used_embeddings
+
             used_embeddings = scan_directory(os.path.join(app.MODELS_DIR, "embeddings"))
             metadata["use_embedding_models"] = used_embeddings if len(used_embeddings) > 0 else None
-    
+
     # Clean up the metadata
     if req.init_image is None and "prompt_strength" in metadata:
         del metadata["prompt_strength"]
@@ -254,7 +262,9 @@ def get_printable_request(req: GenerateImageRequest, task_data: TaskData):
         del metadata["latent_upscaler_steps"]
 
     if not using_diffusers:
-        for key in (x for x in ["use_lora_model", "lora_alpha", "clip_skip", "tiling", "latent_upscaler_steps"] if x in metadata):
+        for key in (
+            x for x in ["use_lora_model", "lora_alpha", "clip_skip", "tiling", "latent_upscaler_steps"] if x in metadata
+        ):
             del metadata[key]
 
     return metadata
diff --git a/ui/media/js/engine.js b/ui/media/js/engine.js
index 39e06ed7..c584a609 100644
--- a/ui/media/js/engine.js
+++ b/ui/media/js/engine.js
@@ -1047,17 +1047,22 @@
         }
     }
     class FilterTask extends Task {
-        constructor(options = {}) {}
+        constructor(options = {}) {
+            super(options)
+        }
         /** Send current task to server.
          * @param {*} [timeout=-1] Optional timeout value in ms
          * @returns the response from the render request.
          * @memberof Task
          */
         async post(timeout = -1) {
-            let jsonResponse = await super.post("/filter", timeout)
+            let res = await super.post("/filter", timeout)
             //this._setId(jsonResponse.task)
             this._setStatus(TaskStatus.waiting)
+
+            return res
         }
+        checkReqBody() {}
         enqueue(progressCallback) {
             return Task.enqueueNew(this, FilterTask, progressCallback)
         }
@@ -1068,6 +1073,20 @@
             if (this.isStopped) {
                 return
             }
+
+            this._setStatus(TaskStatus.pending)
+            progressCallback?.call(this, { reqBody: this._reqBody })
+            Object.freeze(this._reqBody)
+
+            // Post task request to backend
+            let renderRes = undefined
+            try {
+                renderRes = yield this.post()
+                yield progressCallback?.call(this, { renderResponse: renderRes })
+            } catch (e) {
+                yield progressCallback?.call(this, { detail: e.message })
+                throw e
+            }
         }
         static start(task, progressCallback) {
             if (typeof task !== "object") {