Merge pull request 'hitmare-patch-1' (#2) from hitmare-patch-1 into main

Reviewed-on: #2
code was checked and changed parts were copied. SD was able to start without errors

#Original/api.py

@@ -17,19 +17,17 @@ from fastapi.encoders import jsonable_encoder
 from secrets import compare_digest
 
 import modules.shared as shared
-from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items, script_callbacks, generation_parameters_copypaste, sd_models
 from modules.api import models
 from modules.shared import opts
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
 from modules.textual_inversion.textual_inversion import create_embedding, train_embedding
-from modules.textual_inversion.preprocess import preprocess
 from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
-from PIL import PngImagePlugin,Image
+from PIL import PngImagePlugin, Image
-from modules.sd_models import unload_model_weights, reload_model_weights, checkpoint_aliases
 from modules.sd_models_config import find_checkpoint_config_near_filename
 from modules.realesrgan_model import get_realesrgan_models
 from modules import devices
-from typing import Dict, List, Any
+from typing import Any
 import piexif
 import piexif.helper
 from contextlib import closing
@@ -103,7 +101,8 @@ def decode_base64_to_image(encoding):
 
 def encode_pil_to_base64(image):
     with io.BytesIO() as output_bytes:
-
+        if isinstance(image, str):
+            return image
         if opts.samples_format.lower() == 'png':
             use_metadata = False
             metadata = PngImagePlugin.PngInfo()
@@ -221,28 +220,28 @@ class Api:
         self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)
         self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
         self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)
-        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])
+        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=list[models.SamplerItem])
-        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])
+        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=list[models.UpscalerItem])
-        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=List[models.LatentUpscalerModeItem])
+        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=list[models.LatentUpscalerModeItem])
-        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])
+        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=list[models.SDModelItem])
-        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=List[models.SDVaeItem])
+        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=list[models.SDVaeItem])
-        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])
+        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=list[models.HypernetworkItem])
-        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])
+        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=list[models.FaceRestorerItem])
-        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])
+        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=list[models.RealesrganItem])
-        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])
+        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=list[models.PromptStyleItem])
         self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)
         self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
         self.add_api_route("/sdapi/v1/refresh-vae", self.refresh_vae, methods=["POST"])
         self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse)
         self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse)
-        self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse)
         self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse)
         self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse)
         self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse)
         self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
-        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo])
+        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=list[models.ScriptInfo])
+        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])
 
         if shared.cmd_opts.api_server_stop:
             self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -473,9 +472,6 @@ class Api:
         return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 
     def pnginfoapi(self, req: models.PNGInfoRequest):
-        if(not req.image.strip()):
-            return models.PNGInfoResponse(info="")
-
         image = decode_base64_to_image(req.image.strip())
         if image is None:
             return models.PNGInfoResponse(info="")
@@ -484,9 +480,10 @@ class Api:
         if geninfo is None:
             geninfo = ""
 
-        items = {**{'parameters': geninfo}, **items}
+        params = generation_parameters_copypaste.parse_generation_parameters(geninfo)
+        script_callbacks.infotext_pasted_callback(geninfo, params)
 
-        return models.PNGInfoResponse(info=geninfo, items=items)
+        return models.PNGInfoResponse(info=geninfo, items=items, parameters=params)
 
     def progressapi(self, req: models.ProgressRequest = Depends()):
         # copy from check_progress_call of ui.py
@@ -541,12 +538,12 @@ class Api:
         return {}
 
     def unloadapi(self):
-        unload_model_weights()
+        sd_models.unload_model_weights()
 
         return {}
 
     def reloadapi(self):
-        reload_model_weights()
+        sd_models.send_model_to_device(shared.sd_model)
 
         return {}
 
@@ -564,9 +561,9 @@ class Api:
 
         return options
 
-    def set_config(self, req: Dict[str, Any]):
+    def set_config(self, req: dict[str, Any]):
         checkpoint_name = req.get("sd_model_checkpoint", None)
-        if checkpoint_name is not None and checkpoint_name not in checkpoint_aliases:
+        if checkpoint_name is not None and checkpoint_name not in sd_models.checkpoint_aliases:
             raise RuntimeError(f"model {checkpoint_name!r} not found")
 
         for k, v in req.items():
@@ -676,19 +673,6 @@ class Api:
         finally:
             shared.state.end()
 
-    def preprocess(self, args: dict):
-        try:
-            shared.state.begin(job="preprocess")
-            preprocess(**args) # quick operation unless blip/booru interrogation is enabled
-            shared.state.end()
-            return models.PreprocessResponse(info='preprocess complete')
-        except KeyError as e:
-            return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}")
-        except Exception as e:
-            return models.PreprocessResponse(info=f"preprocess error: {e}")
-        finally:
-            shared.state.end()
-
     def train_embedding(self, args: dict):
         try:
             shared.state.begin(job="train_embedding")
@@ -770,6 +754,25 @@ class Api:
             cuda = {'error': f'{err}'}
         return models.MemoryResponse(ram=ram, cuda=cuda)
 
+    def get_extensions_list(self):
+        from modules import extensions
+        extensions.list_extensions()
+        ext_list = []
+        for ext in extensions.extensions:
+            ext: extensions.Extension
+            ext.read_info_from_repo()
+            if ext.remote is not None:
+                ext_list.append({
+                    "name": ext.name,
+                    "remote": ext.remote,
+                    "branch": ext.branch,
+                    "commit_hash":ext.commit_hash,
+                    "commit_date":ext.commit_date,
+                    "version":ext.version,
+                    "enabled":ext.enabled
+                })
+        return ext_list
+
     def launch(self, server_name, port, root_path):
         self.app.include_router(self.router)
         uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive, root_path=root_path)

TRT-Patch/#Original/sd_unet.py

@@ -1,92 +1,94 @@
-import torch.nn
+import torch.nn
-import ldm.modules.diffusionmodules.openaimodel
+
-
+from modules import script_callbacks, shared, devices
-from modules import script_callbacks, shared, devices
+
-
+unet_options = []
-unet_options = []
+current_unet_option = None
-current_unet_option = None
+current_unet = None
-current_unet = None
+original_forward = None  # not used, only left temporarily for compatibility
-
+
-
+def list_unets():
-def list_unets():
+    new_unets = script_callbacks.list_unets_callback()
-    new_unets = script_callbacks.list_unets_callback()
+
-
+    unet_options.clear()
-    unet_options.clear()
+    unet_options.extend(new_unets)
-    unet_options.extend(new_unets)
+
-
+
-
+def get_unet_option(option=None):
-def get_unet_option(option=None):
+    option = option or shared.opts.sd_unet
-    option = option or shared.opts.sd_unet
+
-
+    if option == "None":
-    if option == "None":
+        return None
-        return None
+
-
+    if option == "Automatic":
-    if option == "Automatic":
+        name = shared.sd_model.sd_checkpoint_info.model_name
-        name = shared.sd_model.sd_checkpoint_info.model_name
+
-
+        options = [x for x in unet_options if x.model_name == name]
-        options = [x for x in unet_options if x.model_name == name]
+
-
+        option = options[0].label if options else "None"
-        option = options[0].label if options else "None"
+
-
+    return next(iter([x for x in unet_options if x.label == option]), None)
-    return next(iter([x for x in unet_options if x.label == option]), None)
+
-
+
-
+def apply_unet(option=None):
-def apply_unet(option=None):
+    global current_unet_option
-    global current_unet_option
+    global current_unet
-    global current_unet
+
-
+    new_option = get_unet_option(option)
-    new_option = get_unet_option(option)
+    if new_option == current_unet_option:
-    if new_option == current_unet_option:
+        return
-        return
+
-
+    if current_unet is not None:
-    if current_unet is not None:
+        print(f"Dectivating unet: {current_unet.option.label}")
-        print(f"Dectivating unet: {current_unet.option.label}")
+        current_unet.deactivate()
-        current_unet.deactivate()
+
-
+    current_unet_option = new_option
-    current_unet_option = new_option
+    if current_unet_option is None:
-    if current_unet_option is None:
+        current_unet = None
-        current_unet = None
+
-
+        if not shared.sd_model.lowvram:
-        if not shared.sd_model.lowvram:
+            shared.sd_model.model.diffusion_model.to(devices.device)
-            shared.sd_model.model.diffusion_model.to(devices.device)
+
-
+        return
-        return
+
-
+    shared.sd_model.model.diffusion_model.to(devices.cpu)
-    shared.sd_model.model.diffusion_model.to(devices.cpu)
+    devices.torch_gc()
-    devices.torch_gc()
+
-
+    current_unet = current_unet_option.create_unet()
-    current_unet = current_unet_option.create_unet()
+    current_unet.option = current_unet_option
-    current_unet.option = current_unet_option
+    print(f"Activating unet: {current_unet.option.label}")
-    print(f"Activating unet: {current_unet.option.label}")
+    current_unet.activate()
-    current_unet.activate()
+
-
+
-
+class SdUnetOption:
-class SdUnetOption:
+    model_name = None
-    model_name = None
+    """name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
-    """name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
+
-
+    label = None
-    label = None
+    """name of the unet in UI"""
-    """name of the unet in UI"""
+
-
+    def create_unet(self):
-    def create_unet(self):
+        """returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
-        """returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
+        raise NotImplementedError()
-        raise NotImplementedError()
+
-
+
-
+class SdUnet(torch.nn.Module):
-class SdUnet(torch.nn.Module):
+    def forward(self, x, timesteps, context, *args, **kwargs):
-    def forward(self, x, timesteps, context, *args, **kwargs):
+        raise NotImplementedError()
-        raise NotImplementedError()
+
-
+    def activate(self):
-    def activate(self):
+        pass
-        pass
+
-
+    def deactivate(self):
-    def deactivate(self):
+        pass
-        pass
+
-
+
-
+def create_unet_forward(original_forward):
-def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
+    def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
-    if current_unet is not None:
+        if current_unet is not None:
-        return current_unet.forward(x, timesteps, context, *args, **kwargs)
+            return current_unet.forward(x, timesteps, context, *args, **kwargs)
-
+
-    return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
+        return original_forward(self, x, timesteps, context, *args, **kwargs)
-
+
+    return UNetModel_forward
+

TRT-Patch/modules/sd_unet.py

@@ -1,101 +1,107 @@
-import torch.nn
+import torch.nn
-import ldm.modules.diffusionmodules.openaimodel
+import time
-
+from modules import script_callbacks, shared, devices
-import time
+
-from modules import script_callbacks, shared, devices
+unet_options = []
-unet_options = []
+current_unet_option = None
-current_unet_option = None
+current_unet = None
-current_unet = None
+original_forward = None  # not used, only left temporarily for compatibility
-
+
-
+def list_unets():
-def list_unets():
+    new_unets = script_callbacks.list_unets_callback()
-    new_unets = script_callbacks.list_unets_callback()
+
-
+    unet_options.clear()
-    unet_options.clear()
+    unet_options.extend(new_unets)
-    unet_options.extend(new_unets)
+
-
+
-
+def get_unet_option(option=None):
-def get_unet_option(option=None):
+    option = option or shared.opts.sd_unet
-    option = option or shared.opts.sd_unet
+
-
+    if option == "None":
-    if option == "None":
+        return None
-        return None
+
-
+    if option == "Automatic":
-    if option == "Automatic":
+        name = shared.sd_model.sd_checkpoint_info.model_name
-        name = shared.sd_model.sd_checkpoint_info.model_name
+
-
+        options = [x for x in unet_options if x.model_name == name]
-        options = [x for x in unet_options if x.model_name == name]
+
-
+        option = options[0].label if options else "None"
-        option = options[0].label if options else "None"
+
-
+    return next(iter([x for x in unet_options if x.label == option]), None)
-    return next(iter([x for x in unet_options if x.label == option]), None)
+
-
+
-
+def apply_unet(option=None):
-def apply_unet(option=None):
+    global current_unet_option
-    global current_unet_option
+    global current_unet
-    global current_unet
+
-
+    new_option = get_unet_option(option)
-    new_option = get_unet_option(option)
+    if new_option == current_unet_option:
-    if new_option == current_unet_option:
+        return
-        return
+
-
+    if current_unet is not None:
-    if current_unet is not None:
+        print(f"Dectivating unet: {current_unet.option.label}")
-        print(f"Dectivating unet: {current_unet.option.label}")
+        current_unet.deactivate()
-        current_unet.deactivate()
+
-
+    current_unet_option = new_option
-    current_unet_option = new_option
+    if current_unet_option is None:
-    if current_unet_option is None:
+        current_unet = None
-        current_unet = None
+
-
+        if not shared.sd_model.lowvram:
-        if not shared.sd_model.lowvram:
+            shared.sd_model.model.diffusion_model.to(devices.device)
-            shared.sd_model.model.diffusion_model.to(devices.device)
+
-
+        return
-        return
+
-
+    shared.sd_model.model.diffusion_model.to(devices.cpu)
-    shared.sd_model.model.diffusion_model.to(devices.cpu)
+    devices.torch_gc()
-    devices.torch_gc()
+
-
+    current_unet = current_unet_option.create_unet()
-    current_unet = current_unet_option.create_unet()
+    current_unet.option = current_unet_option
-    current_unet.option = current_unet_option
+    print(f"Activating unet: {current_unet.option.label}")
-    print(f"Activating unet: {current_unet.option.label}")
+    current_unet.activate()
-    current_unet.activate()
+
-
+
-
+class SdUnetOption:
-class SdUnetOption:
+    model_name = None
-    model_name = None
+    """name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
-    """name of related checkpoint - this option will be selected automatically for unet if the name of checkpoint matches this"""
+
-
+    label = None
-    label = None
+    """name of the unet in UI"""
-    """name of the unet in UI"""
+
-
+    def create_unet(self):
-    def create_unet(self):
+        """returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
-        """returns SdUnet object to be used as a Unet instead of built-in unet when making pictures"""
+        raise NotImplementedError()
-        raise NotImplementedError()
+
-
+
-
+class SdUnet(torch.nn.Module):
-class SdUnet(torch.nn.Module):
+    def forward(self, x, timesteps, context, *args, **kwargs):
-    def forward(self, x, timesteps, context, *args, **kwargs):
+        raise NotImplementedError()
-        raise NotImplementedError()
+
-
+    def activate(self):
-    def activate(self):
+        pass
-        pass
+
-
+    def deactivate(self):
-    def deactivate(self):
+        pass
-        pass
+
-
+
-
+def create_unet_forward(original_forward):
-def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
+    def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
-    try:
+        if current_unet is not None:
-        if current_unet is not None and shared.current_prompt != shared.skip_unet_prompt:
+            return current_unet.forward(x, timesteps, context, *args, **kwargs)
-            if '[TRT]' in shared.opts.sd_unet and '<lora:' in shared.current_prompt:
+        try:
-                raise Exception('LoRA unsupported in TRT UNet')
+            if current_unet is not None and shared.current_prompt != shared.skip_unet_prompt:
-            f = current_unet.forward(x, timesteps, context, *args, **kwargs)
+                if '[TRT]' in shared.opts.sd_unet and '<lora:' in shared.current_prompt:
-            return f
+                    raise Exception('LoRA unsupported in TRT UNet')
-    except Exception as e:
+                f = current_unet.forward(x, timesteps, context, *args, **kwargs)
-        start = time.time()
+                return f
-        print('[UNet] Skipping TRT UNet for this request:', e, '-', shared.current_prompt)
+        except Exception as e:
-        shared.sd_model.model.diffusion_model.to(devices.device)
+            start = time.time()
-        shared.skip_unet_prompt = shared.current_prompt
+            print('[UNet] Skipping TRT UNet for this request:', e, '-', shared.current_prompt)
-        print('[UNet] Used', time.time() - start, 'seconds')
+            shared.sd_model.model.diffusion_model.to(devices.device)
-
+            shared.skip_unet_prompt = shared.current_prompt
-    return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
+            print('[UNet] Used', time.time() - start, 'seconds')
+        
+
+        return original_forward(self, x, timesteps, context, *args, **kwargs)
+
+    return UNetModel_forward
+

api.py

@@ -17,19 +17,17 @@ from fastapi.encoders import jsonable_encoder
 from secrets import compare_digest
 
 import modules.shared as shared
-from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items, script_callbacks, generation_parameters_copypaste, sd_models
 from modules.api import models
 from modules.shared import opts
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
 from modules.textual_inversion.textual_inversion import create_embedding, train_embedding
-from modules.textual_inversion.preprocess import preprocess
 from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
-from PIL import PngImagePlugin,Image
+from PIL import PngImagePlugin, Image
-from modules.sd_models import unload_model_weights, reload_model_weights, checkpoint_aliases
 from modules.sd_models_config import find_checkpoint_config_near_filename
 from modules.realesrgan_model import get_realesrgan_models
 from modules import devices
-from typing import Dict, List, Any
+from typing import Any
 import piexif
 import piexif.helper
 from contextlib import closing
@@ -146,7 +144,8 @@ def decode_base64_to_image(encoding):
 
 def encode_pil_to_base64(image):
     with io.BytesIO() as output_bytes:
-
+        if isinstance(image, str):
+            return image
         if opts.samples_format.lower() == 'png':
             use_metadata = False
             metadata = PngImagePlugin.PngInfo()
@@ -264,28 +263,28 @@ class Api:
         self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)
         self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
         self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)
-        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])
+        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=list[models.SamplerItem])
-        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])
+        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=list[models.UpscalerItem])
-        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=List[models.LatentUpscalerModeItem])
+        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=list[models.LatentUpscalerModeItem])
-        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])
+        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=list[models.SDModelItem])
-        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=List[models.SDVaeItem])
+        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=list[models.SDVaeItem])
-        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])
+        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=list[models.HypernetworkItem])
-        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])
+        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=list[models.FaceRestorerItem])
-        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])
+        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=list[models.RealesrganItem])
-        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])
+        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=list[models.PromptStyleItem])
         self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)
         self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
         self.add_api_route("/sdapi/v1/refresh-vae", self.refresh_vae, methods=["POST"])
         self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse)
         self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse)
-        self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse)
         self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse)
         self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse)
         self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse)
         self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
-        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo])
+        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=list[models.ScriptInfo])
+        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])
 
         if shared.cmd_opts.api_server_stop:
             self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -462,6 +461,10 @@ class Api:
         if eris_consolelog:
             print('[t2i]', txt2imgreq.width, 'x', txt2imgreq.height, '|', txt2imgreq.prompt)
         # Eris ______
+        
+        
+        
+        
         script_runner = scripts.scripts_txt2img
         if not script_runner.scripts:
             script_runner.initialize_scripts(False)
@@ -598,7 +601,6 @@ class Api:
         if eris_consolelog:
             print('[i2i]', img2imgreq.width, 'x', img2imgreq.height, '|', img2imgreq.prompt)
         # Eris ______
-
         init_images = img2imgreq.init_images
         if init_images is None:
             raise HTTPException(status_code=404, detail="Init image not found")
@@ -618,6 +620,7 @@ class Api:
         if eris_imagelog:
             img2imgreq.save_images = True
         # Eris ______
+
         populate = img2imgreq.copy(update={  # Override __init__ params
             "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
             "do_not_save_samples": not img2imgreq.save_images,
@@ -648,7 +651,7 @@ class Api:
             apilogimg2imgtext.replace("\n", " ").replace("\r", " ")
             apilogimg2imgfile.write(f"{apilogimg2imgtext}\n")
         # Eris ______
-        
+
         with self.queue_lock:
             with closing(StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)) as p:
                 p.init_images = [decode_base64_to_image(x) for x in init_images]
@@ -699,9 +702,6 @@ class Api:
         return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 
     def pnginfoapi(self, req: models.PNGInfoRequest):
-        if(not req.image.strip()):
-            return models.PNGInfoResponse(info="")
-
         image = decode_base64_to_image(req.image.strip())
         if image is None:
             return models.PNGInfoResponse(info="")
@@ -710,9 +710,10 @@ class Api:
         if geninfo is None:
             geninfo = ""
 
-        items = {**{'parameters': geninfo}, **items}
+        params = generation_parameters_copypaste.parse_generation_parameters(geninfo)
+        script_callbacks.infotext_pasted_callback(geninfo, params)
 
-        return models.PNGInfoResponse(info=geninfo, items=items)
+        return models.PNGInfoResponse(info=geninfo, items=items, parameters=params)
 
     def progressapi(self, req: models.ProgressRequest = Depends()):
         # copy from check_progress_call of ui.py
@@ -767,12 +768,12 @@ class Api:
         return {}
 
     def unloadapi(self):
-        unload_model_weights()
+        sd_models.unload_model_weights()
 
         return {}
 
     def reloadapi(self):
-        reload_model_weights()
+        sd_models.send_model_to_device(shared.sd_model)
 
         return {}
 
@@ -790,9 +791,9 @@ class Api:
 
         return options
 
-    def set_config(self, req: Dict[str, Any]):
+    def set_config(self, req: dict[str, Any]):
         checkpoint_name = req.get("sd_model_checkpoint", None)
-        if checkpoint_name is not None and checkpoint_name not in checkpoint_aliases:
+        if checkpoint_name is not None and checkpoint_name not in sd_models.checkpoint_aliases:
             raise RuntimeError(f"model {checkpoint_name!r} not found")
 
         for k, v in req.items():
@@ -902,19 +903,6 @@ class Api:
         finally:
             shared.state.end()
 
-    def preprocess(self, args: dict):
-        try:
-            shared.state.begin(job="preprocess")
-            preprocess(**args) # quick operation unless blip/booru interrogation is enabled
-            shared.state.end()
-            return models.PreprocessResponse(info='preprocess complete')
-        except KeyError as e:
-            return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}")
-        except Exception as e:
-            return models.PreprocessResponse(info=f"preprocess error: {e}")
-        finally:
-            shared.state.end()
-
     def train_embedding(self, args: dict):
         try:
             shared.state.begin(job="train_embedding")
@@ -996,6 +984,25 @@ class Api:
             cuda = {'error': f'{err}'}
         return models.MemoryResponse(ram=ram, cuda=cuda)
 
+    def get_extensions_list(self):
+        from modules import extensions
+        extensions.list_extensions()
+        ext_list = []
+        for ext in extensions.extensions:
+            ext: extensions.Extension
+            ext.read_info_from_repo()
+            if ext.remote is not None:
+                ext_list.append({
+                    "name": ext.name,
+                    "remote": ext.remote,
+                    "branch": ext.branch,
+                    "commit_hash":ext.commit_hash,
+                    "commit_date":ext.commit_date,
+                    "version":ext.version,
+                    "enabled":ext.enabled
+                })
+        return ext_list
+
     def launch(self, server_name, port, root_path):
         self.app.include_router(self.router)
         uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive, root_path=root_path)