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authorAUTOMATIC1111 <16777216c@gmail.com>2023-07-08 13:50:23 +0000
committerGitHub <noreply@github.com>2023-07-08 13:50:23 +0000
commit993dd9a8927407de8d19142cacb07e6f76686a67 (patch)
tree89df31c33ecf054c9cb70aaf38fc3382f306f450 /modules/api/api.py
parentff6acd35d0807a4e0c3ee86cdb1520a4a3a11cdd (diff)
parentd7d6e8cfc8b85a99a48f82975ee213d487783c28 (diff)
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Merge branch 'dev' into patch-1
Diffstat (limited to 'modules/api/api.py')
-rw-r--r--modules/api/api.py298
1 files changed, 173 insertions, 125 deletions
diff --git a/modules/api/api.py b/modules/api/api.py
index 9bb95dfd..224bbfc6 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -14,32 +14,31 @@ 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
-from modules.api.models import *
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart
+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 modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights
+from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights, checkpoint_alisases
+from modules.sd_vae import vae_dict
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 List
+from typing import Dict, List, Any
import piexif
import piexif.helper
+from contextlib import closing
-def upscaler_to_index(name: str):
- try:
- return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
- except:
- raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in sd_upscalers])}")
def script_name_to_index(name, scripts):
try:
return [script.title().lower() for script in scripts].index(name.lower())
- except:
- raise HTTPException(status_code=422, detail=f"Script '{name}' not found")
+ except Exception as e:
+ raise HTTPException(status_code=422, detail=f"Script '{name}' not found") from e
+
def validate_sampler_name(name):
config = sd_samplers.all_samplers_map.get(name, None)
@@ -48,20 +47,23 @@ def validate_sampler_name(name):
return name
+
def setUpscalers(req: dict):
reqDict = vars(req)
reqDict['extras_upscaler_1'] = reqDict.pop('upscaler_1', None)
reqDict['extras_upscaler_2'] = reqDict.pop('upscaler_2', None)
return reqDict
+
def decode_base64_to_image(encoding):
if encoding.startswith("data:image/"):
encoding = encoding.split(";")[1].split(",")[1]
try:
image = Image.open(BytesIO(base64.b64decode(encoding)))
return image
- except Exception as err:
- raise HTTPException(status_code=500, detail="Invalid encoded image")
+ except Exception as e:
+ raise HTTPException(status_code=500, detail="Invalid encoded image") from e
+
def encode_pil_to_base64(image):
with io.BytesIO() as output_bytes:
@@ -76,6 +78,8 @@ def encode_pil_to_base64(image):
image.save(output_bytes, format="PNG", pnginfo=(metadata if use_metadata else None), quality=opts.jpeg_quality)
elif opts.samples_format.lower() in ("jpg", "jpeg", "webp"):
+ if image.mode == "RGBA":
+ image = image.convert("RGB")
parameters = image.info.get('parameters', None)
exif_bytes = piexif.dump({
"Exif": { piexif.ExifIFD.UserComment: piexif.helper.UserComment.dump(parameters or "", encoding="unicode") }
@@ -92,6 +96,7 @@ def encode_pil_to_base64(image):
return base64.b64encode(bytes_data)
+
def api_middleware(app: FastAPI):
rich_available = True
try:
@@ -99,8 +104,7 @@ def api_middleware(app: FastAPI):
import starlette # importing just so it can be placed on silent list
from rich.console import Console
console = Console()
- except:
- import traceback
+ except Exception:
rich_available = False
@app.middleware("http")
@@ -131,11 +135,12 @@ def api_middleware(app: FastAPI):
"errors": str(e),
}
if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions
- print(f"API error: {request.method}: {request.url} {err}")
+ message = f"API error: {request.method}: {request.url} {err}"
if rich_available:
+ print(message)
console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200]))
else:
- traceback.print_exc()
+ errors.report(message, exc_info=True)
return JSONResponse(status_code=vars(e).get('status_code', 500), content=jsonable_encoder(err))
@app.middleware("http")
@@ -157,7 +162,7 @@ def api_middleware(app: FastAPI):
class Api:
def __init__(self, app: FastAPI, queue_lock: Lock):
if shared.cmd_opts.api_auth:
- self.credentials = dict()
+ self.credentials = {}
for auth in shared.cmd_opts.api_auth.split(","):
user, password = auth.split(":")
self.credentials[user] = password
@@ -166,36 +171,44 @@ class Api:
self.app = app
self.queue_lock = queue_lock
api_middleware(self.app)
- self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
- self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
- self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
- self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
- self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
- self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
+ self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse)
+ self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse)
+ self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse)
+ self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse)
+ self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse)
+ self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse)
self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"])
- self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel)
+ 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=FlagsModel)
- self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem])
- self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem])
- self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem])
- self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem])
- self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem])
- self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem])
- self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
- self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse)
+ 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/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/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/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/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/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/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=PreprocessResponse)
- self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
+ 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=ScriptsList)
+ 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])
+
+ if shared.cmd_opts.api_server_stop:
+ self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
+ self.add_api_route("/sdapi/v1/server-restart", self.restart_webui, methods=["POST"])
+ self.add_api_route("/sdapi/v1/server-stop", self.stop_webui, methods=["POST"])
self.default_script_arg_txt2img = []
self.default_script_arg_img2img = []
@@ -219,17 +232,25 @@ class Api:
script_idx = script_name_to_index(script_name, script_runner.selectable_scripts)
script = script_runner.selectable_scripts[script_idx]
return script, script_idx
-
+
def get_scripts_list(self):
- t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles]
- i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles]
+ t2ilist = [script.name for script in scripts.scripts_txt2img.scripts if script.name is not None]
+ i2ilist = [script.name for script in scripts.scripts_img2img.scripts if script.name is not None]
+
+ return models.ScriptsList(txt2img=t2ilist, img2img=i2ilist)
+
+ def get_script_info(self):
+ res = []
- return ScriptsList(txt2img = t2ilist, img2img = i2ilist)
+ for script_list in [scripts.scripts_txt2img.scripts, scripts.scripts_img2img.scripts]:
+ res += [script.api_info for script in script_list if script.api_info is not None]
+
+ return res
def get_script(self, script_name, script_runner):
if script_name is None or script_name == "":
return None, None
-
+
script_idx = script_name_to_index(script_name, script_runner.scripts)
return script_runner.scripts[script_idx]
@@ -261,14 +282,14 @@ class Api:
script_args[0] = selectable_idx + 1
# Now check for always on scripts
- if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
+ if request.alwayson_scripts:
for alwayson_script_name in request.alwayson_scripts.keys():
alwayson_script = self.get_script(alwayson_script_name, script_runner)
- if alwayson_script == None:
+ if alwayson_script is None:
raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found")
# Selectable script in always on script param check
- if alwayson_script.alwayson == False:
- raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params")
+ if alwayson_script.alwayson is False:
+ raise HTTPException(status_code=422, detail="Cannot have a selectable script in the always on scripts params")
# always on script with no arg should always run so you don't really need to add them to the requests
if "args" in request.alwayson_scripts[alwayson_script_name]:
# min between arg length in scriptrunner and arg length in the request
@@ -276,7 +297,7 @@ class Api:
script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx]
return script_args
- def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
+ def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
@@ -304,25 +325,25 @@ class Api:
args.pop('save_images', None)
with self.queue_lock:
- p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
- p.scripts = script_runner
- p.outpath_grids = opts.outdir_txt2img_grids
- p.outpath_samples = opts.outdir_txt2img_samples
-
- shared.state.begin()
- if selectable_scripts != None:
- p.script_args = script_args
- processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
- else:
- p.script_args = tuple(script_args) # Need to pass args as tuple here
- processed = process_images(p)
- shared.state.end()
+ with closing(StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)) as p:
+ p.scripts = script_runner
+ p.outpath_grids = opts.outdir_txt2img_grids
+ p.outpath_samples = opts.outdir_txt2img_samples
+
+ shared.state.begin(job="scripts_txt2img")
+ if selectable_scripts is not None:
+ p.script_args = script_args
+ processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
+ else:
+ p.script_args = tuple(script_args) # Need to pass args as tuple here
+ processed = process_images(p)
+ shared.state.end()
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
- return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
+ return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
- def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
+ def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI):
init_images = img2imgreq.init_images
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
@@ -360,20 +381,20 @@ class Api:
args.pop('save_images', None)
with self.queue_lock:
- p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
- p.init_images = [decode_base64_to_image(x) for x in init_images]
- p.scripts = script_runner
- p.outpath_grids = opts.outdir_img2img_grids
- p.outpath_samples = opts.outdir_img2img_samples
-
- shared.state.begin()
- if selectable_scripts != None:
- p.script_args = script_args
- processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
- else:
- p.script_args = tuple(script_args) # Need to pass args as tuple here
- processed = process_images(p)
- shared.state.end()
+ with closing(StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)) as p:
+ p.init_images = [decode_base64_to_image(x) for x in init_images]
+ p.scripts = script_runner
+ p.outpath_grids = opts.outdir_img2img_grids
+ p.outpath_samples = opts.outdir_img2img_samples
+
+ shared.state.begin(job="scripts_img2img")
+ if selectable_scripts is not None:
+ p.script_args = script_args
+ processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
+ else:
+ p.script_args = tuple(script_args) # Need to pass args as tuple here
+ processed = process_images(p)
+ shared.state.end()
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
@@ -381,9 +402,9 @@ class Api:
img2imgreq.init_images = None
img2imgreq.mask = None
- return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
+ return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
- def extras_single_image_api(self, req: ExtrasSingleImageRequest):
+ def extras_single_image_api(self, req: models.ExtrasSingleImageRequest):
reqDict = setUpscalers(req)
reqDict['image'] = decode_base64_to_image(reqDict['image'])
@@ -391,9 +412,9 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
+ return models.ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
- def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
+ def extras_batch_images_api(self, req: models.ExtrasBatchImagesRequest):
reqDict = setUpscalers(req)
image_list = reqDict.pop('imageList', [])
@@ -402,15 +423,15 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
+ return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
- def pnginfoapi(self, req: PNGInfoRequest):
+ def pnginfoapi(self, req: models.PNGInfoRequest):
if(not req.image.strip()):
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
image = decode_base64_to_image(req.image.strip())
if image is None:
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
geninfo, items = images.read_info_from_image(image)
if geninfo is None:
@@ -418,13 +439,13 @@ class Api:
items = {**{'parameters': geninfo}, **items}
- return PNGInfoResponse(info=geninfo, items=items)
+ return models.PNGInfoResponse(info=geninfo, items=items)
- def progressapi(self, req: ProgressRequest = Depends()):
+ def progressapi(self, req: models.ProgressRequest = Depends()):
# copy from check_progress_call of ui.py
if shared.state.job_count == 0:
- return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
# avoid dividing zero
progress = 0.01
@@ -446,9 +467,9 @@ class Api:
if shared.state.current_image and not req.skip_current_image:
current_image = encode_pil_to_base64(shared.state.current_image)
- return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
- def interrogateapi(self, interrogatereq: InterrogateRequest):
+ def interrogateapi(self, interrogatereq: models.InterrogateRequest):
image_b64 = interrogatereq.image
if image_b64 is None:
raise HTTPException(status_code=404, detail="Image not found")
@@ -465,7 +486,7 @@ class Api:
else:
raise HTTPException(status_code=404, detail="Model not found")
- return InterrogateResponse(caption=processed)
+ return models.InterrogateResponse(caption=processed)
def interruptapi(self):
shared.state.interrupt()
@@ -497,6 +518,10 @@ class Api:
return options
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_alisases:
+ raise RuntimeError(f"model {checkpoint_name!r} not found")
+
for k, v in req.items():
shared.opts.set(k, v)
@@ -521,9 +546,20 @@ class Api:
for upscaler in shared.sd_upscalers
]
+ def get_latent_upscale_modes(self):
+ return [
+ {
+ "name": upscale_mode,
+ }
+ for upscale_mode in [*(shared.latent_upscale_modes or {})]
+ ]
+
def get_sd_models(self):
return [{"title": x.title, "model_name": x.model_name, "hash": x.shorthash, "sha256": x.sha256, "filename": x.filename, "config": find_checkpoint_config_near_filename(x)} for x in checkpoints_list.values()]
+ def get_sd_vaes(self):
+ return [{"model_name": x, "filename": vae_dict[x]} for x in vae_dict.keys()]
+
def get_hypernetworks(self):
return [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks]
@@ -566,44 +602,42 @@ class Api:
def create_embedding(self, args: dict):
try:
- shared.state.begin()
+ shared.state.begin(job="create_embedding")
filename = create_embedding(**args) # create empty embedding
sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used
- shared.state.end()
- return CreateResponse(info=f"create embedding filename: {filename}")
+ return models.CreateResponse(info=f"create embedding filename: {filename}")
except AssertionError as e:
+ return models.TrainResponse(info=f"create embedding error: {e}")
+ finally:
shared.state.end()
- return TrainResponse(info=f"create embedding error: {e}")
+
def create_hypernetwork(self, args: dict):
try:
- shared.state.begin()
+ shared.state.begin(job="create_hypernetwork")
filename = create_hypernetwork(**args) # create empty embedding
- shared.state.end()
- return CreateResponse(info=f"create hypernetwork filename: {filename}")
+ return models.CreateResponse(info=f"create hypernetwork filename: {filename}")
except AssertionError as e:
+ return models.TrainResponse(info=f"create hypernetwork error: {e}")
+ finally:
shared.state.end()
- return TrainResponse(info=f"create hypernetwork error: {e}")
def preprocess(self, args: dict):
try:
- shared.state.begin()
+ shared.state.begin(job="preprocess")
preprocess(**args) # quick operation unless blip/booru interrogation is enabled
shared.state.end()
- return PreprocessResponse(info = 'preprocess complete')
+ 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()
- return PreprocessResponse(info=f"preprocess error: invalid token: {e}")
- except AssertionError as e:
- shared.state.end()
- return PreprocessResponse(info=f"preprocess error: {e}")
- except FileNotFoundError as e:
- shared.state.end()
- return PreprocessResponse(info=f'preprocess error: {e}')
def train_embedding(self, args: dict):
try:
- shared.state.begin()
+ shared.state.begin(job="train_embedding")
apply_optimizations = shared.opts.training_xattention_optimizations
error = None
filename = ''
@@ -616,15 +650,15 @@ class Api:
finally:
if not apply_optimizations:
sd_hijack.apply_optimizations()
- shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
- except AssertionError as msg:
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ except Exception as msg:
+ return models.TrainResponse(info=f"train embedding error: {msg}")
+ finally:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {msg}")
def train_hypernetwork(self, args: dict):
try:
- shared.state.begin()
+ shared.state.begin(job="train_hypernetwork")
shared.loaded_hypernetworks = []
apply_optimizations = shared.opts.training_xattention_optimizations
error = None
@@ -641,14 +675,16 @@ class Api:
if not apply_optimizations:
sd_hijack.apply_optimizations()
shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
- except AssertionError as msg:
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ except Exception as exc:
+ return models.TrainResponse(info=f"train embedding error: {exc}")
+ finally:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {error}")
def get_memory(self):
try:
- import os, psutil
+ import os
+ import psutil
process = psutil.Process(os.getpid())
res = process.memory_info() # only rss is cross-platform guaranteed so we dont rely on other values
ram_total = 100 * res.rss / process.memory_percent() # and total memory is calculated as actual value is not cross-platform safe
@@ -675,11 +711,23 @@ class Api:
'events': warnings,
}
else:
- cuda = { 'error': 'unavailable' }
+ cuda = {'error': 'unavailable'}
except Exception as err:
- cuda = { 'error': f'{err}' }
- return MemoryResponse(ram = ram, cuda = cuda)
+ cuda = {'error': f'{err}'}
+ return models.MemoryResponse(ram=ram, cuda=cuda)
def launch(self, server_name, port):
self.app.include_router(self.router)
- uvicorn.run(self.app, host=server_name, port=port)
+ uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=0)
+
+ def kill_webui(self):
+ restart.stop_program()
+
+ def restart_webui(self):
+ if restart.is_restartable():
+ restart.restart_program()
+ return Response(status_code=501)
+
+ def stop_webui(request):
+ shared.state.server_command = "stop"
+ return Response("Stopping.")