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video: support for scripts/extensions

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2026-07-28 10:43:58 +02:00
parent fcbef8f55a
commit 9dec85040e
25 changed files with 146 additions and 129 deletions
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CHANGELOG.md
+4 -3
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@@ -1,10 +1,11 @@
# Change Log for SD.Next
## Update for 2026-07-27
## Update for 2026-07-28
- **Features**
- optimized server startup
- video processing preserve audio
- startup: optimized server startup
- process: preserve audio when processing video
- video: support for scripts/extensions
- **Fixes**
- seedvr quality
extensions-builtin/sdnext-kanvas
+1 -1
Submodule extensions-builtin/sdnext-kanvas updated: dc47fa2129...b985104298
installer.py
+5
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@@ -131,6 +131,11 @@ def print_profile(profiler: cProfile.Profile, msg: str):
profile_print(msg, local_profiler=profiler)
def profile(*_args, **_kwargs):
# legacy to avoid import errors
pass
def package_version(package):
try:
return importlib.metadata.version(package)
modules/api/process.py
+36 -48
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@@ -1,7 +1,6 @@
from threading import Lock
from pydantic import BaseModel, Field # pylint: disable=no-name-in-module
from fastapi.responses import JSONResponse
from fastapi.exceptions import HTTPException
from modules.api.helpers import decode_base64_to_image, encode_pil_to_base64
from modules import errors, shared, postprocessing
from modules.api import models, helpers
@@ -20,6 +19,7 @@ class ResPreprocess(BaseModel):
model: str = Field(default='', title="Model", description="The processor model used")
image: str = Field(default='', title="Image", description="The processed image in base64 format")
class ReqMask(BaseModel):
image: str = Field(title="Image", description="The base64 encoded image")
type: str = Field(title="Mask type", description="Type of masking image to return")
@@ -27,6 +27,10 @@ class ReqMask(BaseModel):
model: str | None = Field(title="Model", description="The model to use for preprocessing")
params: dict | None = Field(default={}, title="Settings", description="Preprocessor settings")
class ResMask(BaseModel):
mask: str = Field(default='', title="Image", description="The processed image in base64 format")
class ReqFace(BaseModel):
image: str = Field(title="Image", description="The base64 encoded image")
model: str | None = Field(title="Model", description="The model to use for detection")
@@ -38,8 +42,6 @@ class ResFace(BaseModel):
images: list[str] = Field(title="Image", description="The base64 encoded images of detected faces")
scores: list[float] = Field(title="Scores", description="The scores of the detected faces")
class ResMask(BaseModel):
mask: str = Field(default='', title="Image", description="The processed image in base64 format")
class ItemPreprocess(BaseModel):
name: str = Field(title="Name", description="Preprocessor name")
@@ -215,51 +217,37 @@ class APIProcess:
seed = req.seed or -1
seed = processing_helpers.get_fixed_seed(seed)
prompt = ''
if req.type in ('text', 'image'):
from modules.scripts_manager import scripts_txt2img
default_model = 'google/gemma-3-4b-it' if req.type == 'image' else 'google/gemma-3-1b-it'
model = default_model if req.model is None or len(req.model) < 4 else req.model
instance = [s for s in scripts_txt2img.scripts if 'prompt_enhance.py' in s.filename][0]
prompt = instance.enhance(
model=model,
prompt=req.prompt,
system=req.system_prompt,
prefix=req.prefix,
suffix=req.suffix,
sample=req.do_sample,
min_tokens=req.min_tokens,
max_tokens=req.max_tokens,
temperature=req.temperature,
penalty=req.repetition_penalty,
top_k=req.top_k,
top_p=req.top_p,
thinking=req.thinking,
keep_thinking=req.keep_thinking,
use_vision=req.use_vision,
prefill=req.prefill or '',
keep_prefill=req.keep_prefill,
image=decode_base64_to_image(req.image) if req.image else None,
seed=seed,
nsfw=req.nsfw,
custom_args=req.custom_args,
process_words=req.process_words,
semantic_threshold=req.semantic_threshold,
embedding_similarity=req.embedding_similarity,
use_openai=req.use_openai
)
elif req.type == 'video':
from modules.ui_video_vlm import enhance_prompt
model = 'Google Gemma 3 4B' if req.model is None or len(req.model) < 4 else req.model
prompt = enhance_prompt(
enable=True,
image=decode_base64_to_image(req.image),
prompt=req.prompt,
model=model,
system_prompt=req.system_prompt,
nsfw=req.nsfw,
)
else:
raise HTTPException(status_code=400, detail="prompt enhancement: invalid type")
from modules.scripts_manager import scripts_txt2img
default_model = 'google/gemma-3-4b-it' if req.type == 'image' else 'google/gemma-3-1b-it'
model = default_model if req.model is None or len(req.model) < 4 else req.model
instance = [s for s in scripts_txt2img.scripts if 'prompt_enhance.py' in s.filename][0]
prompt = instance.enhance(
model=model,
prompt=req.prompt,
system=req.system_prompt,
prefix=req.prefix,
suffix=req.suffix,
sample=req.do_sample,
min_tokens=req.min_tokens,
max_tokens=req.max_tokens,
temperature=req.temperature,
penalty=req.repetition_penalty,
top_k=req.top_k,
top_p=req.top_p,
thinking=req.thinking,
keep_thinking=req.keep_thinking,
use_vision=req.use_vision,
prefill=req.prefill or '',
keep_prefill=req.keep_prefill,
image=decode_base64_to_image(req.image) if req.image else None,
seed=seed,
nsfw=req.nsfw,
custom_args=req.custom_args,
process_words=req.process_words,
semantic_threshold=req.semantic_threshold,
embedding_similarity=req.embedding_similarity,
use_openai=req.use_openai
)
res = models.ResPromptEnhance(prompt=prompt, seed=seed)
return res
modules/framepack/framepack_ui.py
+2 -2
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@@ -12,7 +12,7 @@ def change_sections(duration, mp4_fps, mp4_interpolate, latent_ws, variant):
return gr.update(value=f'Target video: {num_frames} frames in {num_sections} sections'), gr.update(lines=max(2, 2*num_sections//3))
def create_ui(prompt, negative, styles, _overrides, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
def create_ui(prompt, negative, styles, _overrides, script_inputs, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
with gr.Row():
with gr.Column(variant='compact', elem_id="framepack_settings", elem_classes=['settings-column'], scale=1):
with gr.Row():
@@ -114,7 +114,7 @@ def create_ui(prompt, negative, styles, _overrides, mp4_fps, mp4_interpolate, mp
framepack_dict = dict(
fn=run_framepack,
_js="submit_framepack",
inputs=state_inputs + framepack_inputs,
inputs=state_inputs + framepack_inputs + script_inputs,
outputs=framepack_outputs,
show_progress='hidden',
)
modules/framepack/framepack_wrappers.py
+1 -1
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@@ -114,7 +114,7 @@ def unload_model():
yield gr.update(), gr.update(), 'Model unloaded'
def run_framepack(task_id, _ui_state, init_image, end_image, start_weight, end_weight, vision_weight, prompt, system_prompt, optimized_prompt, section_prompt, negative_prompt, styles, seed, resolution, duration, latent_ws, steps, cfg_scale, cfg_distilled, cfg_rescale, shift, use_teacache, use_cfgzero, use_preview, mp4_fps, mp4_codec, mp4_sf, mp4_video, mp4_frames, mp4_thumb, mp4_opt, mp4_ext, mp4_interpolate, attention, vae_type, variant, vlm_enhance, vlm_model, vlm_system_prompt):
def run_framepack(task_id, _ui_state, init_image, end_image, start_weight, end_weight, vision_weight, prompt, system_prompt, optimized_prompt, section_prompt, negative_prompt, styles, seed, resolution, duration, latent_ws, steps, cfg_scale, cfg_distilled, cfg_rescale, shift, use_teacache, use_cfgzero, use_preview, mp4_fps, mp4_codec, mp4_sf, mp4_video, mp4_frames, mp4_thumb, mp4_opt, mp4_ext, mp4_interpolate, attention, vae_type, variant, vlm_enhance, vlm_model, vlm_system_prompt, *_args, **_kwargs):
variant = variant or 'bi-directional'
if init_image is None:
init_image = np.zeros((resolution, resolution, 3), dtype=np.uint8)
modules/ltx/ltx_process.py
+7 -3
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@@ -3,7 +3,7 @@ import time
import torch
from PIL import Image
from modules import shared, errors, timer, memstats, progress, processing, sd_models, sd_samplers, devices, extra_networks, call_queue
from modules import shared, errors, timer, memstats, progress, processing, sd_models, sd_samplers, devices, extra_networks, call_queue, scripts_manager
from modules.logger import log
from modules.ltx import ltx_capabilities
from modules.ltx.ltx_diffusers_patch import apply_patch as apply_ltx_diffusers_patch
@@ -151,6 +151,8 @@ def run_ltx(task_id,
mp4_thumb: bool,
audio_enable: bool,
_overrides,
*args,
**_kwargs,
):
def abort(e, ok: bool = False, p=None):
@@ -282,13 +284,15 @@ def run_ltx(task_id,
vae_tile_frames=16,
)
processing.fix_seed(p)
p.scripts = None
p.script_args = None
p.do_not_save_grid = True
p.do_not_save_samples = not mp4_frames
p.outpath_samples = resolve_output_path(shared.opts.outdir_samples, shared.opts.outdir_video)
p.ops.append('video')
p.scripts = scripts_manager.scripts_video
p.script_args = args
processed: processing.Processed = scripts_manager.scripts_video.run(p, *args)
p.task_args['num_inference_steps'] = p.steps
p.task_args['width'] = p.width
p.task_args['height'] = p.height
modules/ltx/ltx_ui.py
+2 -2
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@@ -55,7 +55,7 @@ def _model_change(model_name: str):
)
def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
def create_ui(prompt, negative, styles, overrides, script_inputs, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
with gr.Row():
with gr.Column(variant='compact', elem_id="ltx_settings", elem_classes=['settings-column'], scale=1):
with gr.Row():
@@ -175,7 +175,7 @@ def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4
video_dict = dict(
fn=ltx_process.run_ltx,
_js="submit_ltx",
inputs=state_inputs + video_inputs,
inputs=state_inputs + video_inputs + script_inputs,
outputs=video_outputs,
show_progress='hidden',
)
modules/scripts.py
+3 -1
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@@ -6,14 +6,16 @@ from modules.scripts_manager import * # pylint: disable=wildcard-import
scripts_txt2img = None
scripts_img2img = None
scripts_control = None
scripts_video = None
scripts_current = None
scripts_postproc = None
def register_runners():
global scripts_txt2img, scripts_img2img, scripts_control, scripts_current, scripts_postproc # pylint: disable=global-statement
global scripts_txt2img, scripts_img2img, scripts_control, scripts_video, scripts_current, scripts_postproc # pylint: disable=global-statement
scripts_txt2img = scripts_manager.scripts_txt2img
scripts_img2img = scripts_manager.scripts_img2img
scripts_control = scripts_manager.scripts_control
scripts_video = scripts_manager.scripts_video
scripts_current = scripts_manager.scripts_current
scripts_postproc = scripts_manager.scripts_postproc
modules/scripts_manager.py
+14 -5
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@@ -52,6 +52,8 @@ class Script:
alwayson = False
is_txt2img = False
is_img2img = False
is_control = False
is_video = False
api_info: ItemScript | None = None
group = None
infotext_fields: list | None = None
@@ -320,10 +322,11 @@ def load_scripts():
t.record(os.path.basename(scriptfile.basedir) if scriptfile.basedir != paths.script_path else scriptfile.filename)
sys.path = syspath
global scripts_txt2img, scripts_img2img, scripts_control, scripts_postproc # pylint: disable=global-statement
global scripts_txt2img, scripts_img2img, scripts_control, scripts_video, scripts_postproc # pylint: disable=global-statement
scripts_txt2img = ScriptRunner('txt2img')
scripts_img2img = ScriptRunner('img2img')
scripts_control = ScriptRunner('control')
scripts_video = ScriptRunner('video')
scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
return t, time.time()-t0
@@ -373,12 +376,14 @@ class ScriptRunner:
self.inputs: list = [None]
self.time = 0
def add_script(self, script_class, path, is_img2img, is_control):
def add_script(self, script_class, path, is_img2img, is_control, is_video):
try:
script = script_class()
script.filename = path
script.is_txt2img = not is_img2img
script.is_img2img = is_img2img
script.is_control = is_control
script.is_video = is_video
if path.startswith(paths.extensions_dir) and not path.startswith(paths.extensions_builtin_dir):
script.external = True
if is_control and script.external:
@@ -393,6 +398,8 @@ class ScriptRunner:
visibility = AlwaysVisible
else:
visibility = v1 or v2
elif is_video:
visibility = getattr(script, 'video_capable', False)
else:
visibility = script.show(script.is_img2img)
if visibility == AlwaysVisible:
@@ -406,7 +413,7 @@ class ScriptRunner:
log.error(f'Script initialize: {path} {e}')
errors.display(e, 'script')
def initialize_scripts(self, is_img2img=False, is_control=False):
def initialize_scripts(self, is_img2img=False, is_control=False, is_video=False):
from modules import scripts_auto_postprocessing
self.scripts.clear()
@@ -428,14 +435,14 @@ class ScriptRunner:
except Exception:
sorted_scripts = scripts_data
for script_class, path, _basedir, _script_module in sorted_scripts:
self.add_script(script_class, path, is_img2img, is_control)
self.add_script(script_class, path, is_img2img, is_control, is_video)
try:
sorted_scripts = sorted(self.auto_processing_scripts, key=lambda x: x.script_class().title().lower())
except Exception:
sorted_scripts = self.auto_processing_scripts
for script_class, path, _basedir, _script_module in sorted_scripts:
self.add_script(script_class, path, is_img2img, is_control)
self.add_script(script_class, path, is_img2img, is_control, is_video)
def prepare_ui(self):
self.inputs = [None]
@@ -817,6 +824,7 @@ class ScriptRunner:
scripts_txt2img: ScriptRunner = None
scripts_img2img: ScriptRunner = None
scripts_control: ScriptRunner = None
scripts_video: ScriptRunner = None
scripts_current: ScriptRunner = None
scripts_postproc: scripts_postprocessing.ScriptPostprocessingRunner = None
reload_scripts = load_scripts # compatibility alias
@@ -827,3 +835,4 @@ def reload_script_body_only():
scripts_txt2img.reload_sources(cache)
scripts_img2img.reload_sources(cache)
scripts_control.reload_sources(cache)
scripts_video.reload_sources(cache)
modules/ui_video.py
+14 -6
View File
@@ -1,6 +1,6 @@
import os
import gradio as gr
from modules import shared, timer, images, ui_common, ui_sections, generation_parameters_copypaste
from modules import shared, timer, images, ui_common, ui_sections, generation_parameters_copypaste, scripts_manager
from modules.logger import log
@@ -9,6 +9,10 @@ debug = log.trace if os.environ.get('SD_VIDEO_DEBUG', None) is not None else lam
def create_ui():
log.debug('UI initialize: tab=video')
scripts_manager.scripts_current = scripts_manager.scripts_video
scripts_manager.scripts_video.initialize_scripts(is_img2img=False, is_control=False, is_video=True)
with gr.Blocks(analytics_enabled=False) as _video_interface:
prompt, styles, negative, generate_btn, _reprocess, paste, networks_button, _token_counter, _token_button, _token_counter_negative, _token_button_negative = ui_sections.create_toprow(
is_img2img=False,
@@ -31,25 +35,31 @@ def create_ui():
with gr.Tab('Output', id='video-outputs-tab') as _video_outputs_tab:
from modules.video_models import video_ui
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb = video_ui.create_ui_outputs()
with gr.Tab('Extras', elem_id='video_script_container'):
video_script_inputs = scripts_manager.scripts_video.setup_ui(parent='video', accordion=True)
with gr.Tab('Generic', id='video-core-tab') as video_core_tab:
from modules.video_models import video_ui
engine, model, steps, sampler_index, width, height, frames, seed = video_ui.create_ui(
prompt, negative, styles, overrides,
prompt, negative, styles,
overrides, video_script_inputs,
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb,
)
with gr.Tab('FramePack', id='framepack-tab') as framepack_tab:
from modules.framepack import framepack_ui
framepack_ui.create_ui(
prompt, negative, styles, overrides,
prompt, negative, styles,
overrides, video_script_inputs,
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb,
)
with gr.Tab('LTX', id='ltx-tab') as ltx_tab:
from modules.ltx import ltx_ui
ltx_ui.create_ui(
prompt, negative, styles, overrides,
prompt, negative, styles,
overrides, video_script_inputs,
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb,
)
paste_fields = [
(prompt, "Prompt"), # cannot add more fields as they are not defined yet
(negative, "Negative prompt"),
@@ -75,5 +85,3 @@ def create_ui():
ltx_tab.select(fn=lambda: 'ltx', inputs=[], outputs=[current_tab])
generate_btn.click(fn=None, _js='submit_video_wrapper', inputs=[current_tab], outputs=[])
# from framepack_api import create_api # pylint: disable=wrong-import-order
modules/ui_video_vlm.py
+3
View File
@@ -1,3 +1,6 @@
# legacy module as video now uses main prompt enhancer
# except for framepack
import gradio as gr
from PIL import Image
from modules.logger import log
modules/video_models/video_prompt.py
-24
View File
@@ -1,24 +0,0 @@
from modules import shared, extra_networks, ui_video_vlm
def prepare_prompts(p, init_image, prompt:str, vlm_enhance:bool, vlm_model:str, vlm_system_prompt:str):
p.prompt = shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)
p.negative_prompt = shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)
shared.prompt_styles.apply_styles_to_extra(p)
p.prompts, p.network_data = extra_networks.parse_prompts([p.prompt])
extra_networks.activate(p)
prompt = p.prompts[0]
new_prompt = ui_video_vlm.enhance_prompt(
enable=vlm_enhance,
model=vlm_model,
image=init_image,
prompt=prompt,
system_prompt=vlm_system_prompt,
)
if new_prompt is not None and len(new_prompt) > 0:
prompt = new_prompt
p.styles = []
p.task_args['prompt'] = p.prompt
p.task_args['negative_prompt'] = p.negative_prompt
modules/video_models/video_run.py
+19 -8
View File
@@ -1,17 +1,27 @@
import os
import copy
import time
from modules import shared, errors, sd_models, processing, devices, images, ui_common
from modules import shared, errors, sd_models, processing, devices, images, ui_common, scripts_manager
from modules.logger import log
from modules.video_models import models_def, video_utils, video_load, video_vae, video_overrides, video_save, video_prompt
from modules.video_models import models_def, video_utils, video_load, video_vae, video_overrides, video_save
from modules.paths import resolve_output_path
debug = log.trace if os.environ.get('SD_VIDEO_DEBUG', None) is not None else lambda *args, **kwargs: None
def generate(*args, **kwargs):
task_id, ui_state, engine, model, prompt, negative, styles, width, height, frames, steps, sampler_index, sampler_shift, dynamic_shift, seed, guidance_scale, guidance_true, init_image, init_strength, last_image, vae_type, vae_tile_frames, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb, vlm_enhance, vlm_model, vlm_system_prompt, override_settings = args
def generate(task_id, ui_state,
engine, model,
prompt, negative, styles,
width, height, frames, steps,
sampler_index, sampler_shift, dynamic_shift,
seed, guidance_scale, guidance_true,
init_image, init_strength, last_image,
vae_type, vae_tile_frames,
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb,
override_settings,
*args, **kwargs
):
if engine is None or model is None or engine == 'None' or model == 'None':
return video_utils.queue_err('model not selected')
@@ -54,9 +64,12 @@ def generate(*args, **kwargs):
if p.vae_type == 'Remote' and not selected.vae_remote:
log.warning(f'Video: model={selected.name} remote vae not supported')
p.vae_type = 'Default'
p.scripts = None
p.script_args = None
p.state = ui_state
p.scripts = scripts_manager.scripts_video
p.script_args = args
processed: processing.Processed = scripts_manager.scripts_video.run(p, *args)
p.do_not_save_grid = True
p.do_not_save_samples = not mp4_frames
p.outpath_samples = resolve_output_path(shared.opts.outdir_samples, shared.opts.outdir_video)
@@ -101,9 +114,7 @@ def generate(*args, **kwargs):
shared.sd_model = sd_models.apply_balanced_offload(shared.sd_model)
devices.torch_gc(force=True, reason='video')
# set args
video_prompt.prepare_prompts(p, init_image, prompt, vlm_enhance, vlm_model, vlm_system_prompt)
processing.fix_seed(p)
video_vae.set_vae_params(p)
p.task_args['num_inference_steps'] = p.steps
modules/video_models/video_ui.py
+3 -6
View File
@@ -1,6 +1,6 @@
import os
import gradio as gr
from modules import sd_models, ui_common, ui_sections, ui_symbols, ui_video_vlm, call_queue
from modules import sd_models, ui_common, ui_sections, ui_symbols, call_queue
from modules.logger import log
from modules.ui_components import ToolButton
from modules.video_models import models_def, video_utils
@@ -105,7 +105,7 @@ def create_ui_outputs():
return mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb
def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
def create_ui(prompt, negative, styles, overrides, script_inputs, mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb):
with gr.Row():
with gr.Column(variant='compact', elem_id="video_settings", elem_classes=['settings-column'], scale=1):
with gr.Row():
@@ -143,8 +143,6 @@ def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4
vae_type = gr.Dropdown(label='VAE decode', choices=['Default', 'Tiny', 'Remote', 'Upscale'], value='Default', elem_id="video_vae_type")
vae_tile_frames = gr.Slider(label='Tile frames', minimum=1, maximum=64, step=1, value=16, elem_id="video_vae_tile_frames")
vlm_enhance, vlm_model, vlm_system_prompt = ui_video_vlm.create_ui(prompt_element=prompt, image_element=init_image)
# output panel with gallery and video tabs
with gr.Column(elem_id='video-output-column', scale=2) as _column_output:
with gr.Tabs(elem_classes=['video-output-tabs'], elem_id='video-output-tabs'):
@@ -174,7 +172,6 @@ def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4
init_image, init_strength, last_image,
vae_type, vae_tile_frames,
mp4_fps, mp4_interpolate, mp4_codec, mp4_ext, mp4_opt, mp4_video, mp4_frames, mp4_sf, mp4_thumb,
vlm_enhance, vlm_model, vlm_system_prompt,
overrides,
]
video_outputs = [
@@ -188,7 +185,7 @@ def create_ui(prompt, negative, styles, overrides, mp4_fps, mp4_interpolate, mp4
video_dict = dict(
fn=call_queue.wrap_gradio_gpu_call(video_run.generate, extra_outputs=[gr.update(), gr.update(), gr.update(), gr.update()], name='Video'),
_js="submit_video",
inputs=state_inputs + video_inputs,
inputs=state_inputs + video_inputs + script_inputs,
outputs=video_outputs,
show_progress='hidden',
)
scripts/autocomplete.py
+1
View File
@@ -150,6 +150,7 @@ def on_update(selected):
class AutocompleteScript(scripts_manager.Script):
video_capable = scripts_manager.AlwaysVisible
def show(self, is_img2img):
return scripts_manager.AlwaysVisible
scripts/nudenet_ext.py
+3 -2
View File
@@ -136,9 +136,10 @@ def process(
# defines script for dual-mode usage
# see below for all available options and callbacks
# <https://github.com/vladmandic/automatic/blob/master/modules/scripts.py>
class ScriptNudeNet(scripts.Script):
# see below for all available options and callbacks
# <https://github.com/vladmandic/automatic/blob/master/modules/scripts.py#L26>
video_capable = scripts.AlwaysVisible
def title(self):
return 'NudeNet'
scripts/prompt_enhance.py
+8 -1
View File
@@ -249,6 +249,12 @@ class Options:
Base the prompt on what is present in the image, its style, and its atmosphere.
Use concrete, image-generation language and avoid unrelated fluff or commentary.
''')
t2v_prompt: str = textwrap.dedent('''\
''')
i2v_prompt: str = textwrap.dedent('''\
''')
i2v_noprompt: str = textwrap.dedent('''\
''')
nsfw_ok: str = textwrap.dedent('''\
NSFW, nudity and explicit content and language are allowed.
''')
@@ -304,6 +310,7 @@ class PromptEnhanceScript(scripts_manager.Script):
busy: bool = False
server = None
options = Options()
video_capable = scripts_manager.AlwaysVisible
def title(self):
return 'Prompt enhance'
@@ -835,7 +842,7 @@ class PromptEnhanceScript(scripts_manager.Script):
log.debug(f'Prompt enhance: cls={self.llm.__class__.__name__} model="{model}" tokens={input_len} args={gen_kwargs} custom={custom}')
defaults = {k: v for k, v in helpers.get_default_args(self.llm).items() if k not in gen_kwargs}
log.debug(f'Prompt enhance: defaults={defaults}')
debug_log(f'Prompt enhance: defaults={defaults}')
outputs = self.llm.generate(**inputs, **gen_kwargs)
ui/authWrap.ts
+1 -1
View File
@@ -16,7 +16,7 @@ export async function getToken(): Promise<{ user: string | undefined; token: str
const data = (await res.json()) as TokenResponse;
user = data.user;
token = data.token;
log('getToken', user);
log('getToken', { user });
}
}
return { user, token };
ui/css/sdnext.css
+5 -1
View File
@@ -2261,8 +2261,12 @@ div:has(>#tab-gallery-folders) {
}
.video-model-link {
color: var(--button-primary-background-fill);
color: var(--button-primary-background-fill) !important;
font-weight: normal;
font-size: 0.9em;
box-sizing: content-box;
position: relative;
left: 1em;
}
.controlnet-controls .styler {
ui/dist/sdnext.mjs
Vendored
+6 -6
View File
@@ -9891,7 +9891,7 @@ async function getToken() {
const data = await res.json();
user = data.user;
token = data.token;
log("getToken", user);
log("getToken", { user });
}
}
return { user, token };
@@ -10025,7 +10025,7 @@ function executeCallbacks(queue, arg) {
const t0 = performance.now();
callback(arg);
const t1 = performance.now();
if (t1 - t0 > 250) log("callbackSlow", callback.name || callback, `time=${Math.round(t1 - t0)}`);
if (t1 - t0 > 250) log("callbackSlow", { callback: callback.name || callback, time: Math.round(t1 - t0) });
timer(callback.name || "anonymousCallback", t1 - t0);
} catch (e) {
error(`executeCallbacks: ${callback} ${e}`);
@@ -10553,12 +10553,12 @@ function sortExtraNetworks(fixed = "no") {
}
const desc = sortDesc[sortVal];
const t1 = performance.now();
log("sortNetworks", { name: pagename, val: sortVal, order: desc, fixed: fixed === "fixed", items: num, time: Math.round(t1 - t0) });
log("sortNetworks", { page: pagename, key: sortVal, order: desc, items: num, time: Math.round(t1 - t0) });
timer(`sortExtraNetworks:${desc}`, t1 - t0);
return desc;
}
async function markSelectedCards(selected, page = "") {
log("markSelectedCards", selected, page);
log("markSelectedCards", { page, selected });
selectedNetworks[page] = selected;
gradioApp().querySelectorAll(".extra-network-cards .card").forEach((el2) => {
if (page.length > 0 && el2.dataset.page !== page) return;
@@ -10578,7 +10578,7 @@ function extractLoraNames(prompt) {
}
function cardClicked(textToAdd) {
const tabName = getENActiveTab();
log("cardClicked", tabName, textToAdd);
log("cardClicked", { tab: tabName, text: textToAdd });
const textarea = activePromptTextarea[tabName];
if (textarea.value.indexOf(textToAdd) !== -1) textarea.value = textarea.value.replace(textToAdd, "");
else textarea.value += textToAdd;
@@ -12447,7 +12447,7 @@ var ConnectionMonitorState = class _ConnectionMonitorState {
if (online !== this.online) {
this.online = online;
this.ts = /* @__PURE__ */ new Date();
debug("monitorState", { online: _ConnectionMonitorState.online, ts: _ConnectionMonitorState.ts });
debug("monitorState", { online: _ConnectionMonitorState.online, ts: _ConnectionMonitorState.ts?.toLocaleTimeString() });
}
if (data?.updated) this.version = data.updated;
if (data?.commit) this.commit = data.commit;
ui/dist/sdnext.mjs.map
Vendored
+2 -2
View File
File diff suppressed because one or more lines are too long
ui/extraNetworks.ts
+4 -4
View File
@@ -309,18 +309,18 @@ function sortExtraNetworks(fixed = 'no') {
}
const desc = sortDesc[sortVal];
const t1 = performance.now();
log('sortNetworks', { name: pagename, val: sortVal, order: desc, fixed: fixed === 'fixed', items: num, time: Math.round(t1 - t0) });
log('sortNetworks', { page: pagename, key: sortVal, order: desc, items: num, time: Math.round(t1 - t0) });
timer(`sortExtraNetworks:${desc}`, t1 - t0);
return desc;
}
function refreshENInput(tabName) {
log('refreshNetworks', tabName, gradioApp().querySelector(`#${tabName}_extra_networks textarea`)?.value);
log('refreshNetworks', { tab: tabName, value: gradioApp().querySelector(`#${tabName}_extra_networks textarea`)?.value });
gradioApp().querySelector(`#${tabName}_extra_networks textarea`)?.dispatchEvent(new Event('input'));
}
export async function markSelectedCards(selected, page = '') {
log('markSelectedCards', selected, page);
log('markSelectedCards', { page, selected });
selectedNetworks[page] = selected;
gradioApp().querySelectorAll('.extra-network-cards .card').forEach((el) => {
if (page.length > 0 && el.dataset.page !== page) return; // filter by page
@@ -342,7 +342,7 @@ function extractLoraNames(prompt) {
function cardClicked(textToAdd) {
const tabName = getENActiveTab();
log('cardClicked', tabName, textToAdd);
log('cardClicked', { tab: tabName, text: textToAdd });
const textarea = activePromptTextarea[tabName];
if (textarea.value.indexOf(textToAdd) !== -1) textarea.value = textarea.value.replace(textToAdd, '');
else textarea.value += textToAdd;
ui/monitor.ts
+1 -1
View File
@@ -37,7 +37,7 @@ export class ConnectionMonitorState {
if (online !== this.online) {
this.online = online;
this.ts = new Date();
debug('monitorState', { online: ConnectionMonitorState.online, ts: ConnectionMonitorState.ts });
debug('monitorState', { online: ConnectionMonitorState.online, ts: ConnectionMonitorState.ts?.toLocaleTimeString() });
}
if (data?.updated) this.version = data.updated;
if (data?.commit) this.commit = data.commit;
ui/script.ts
+1 -1
View File
@@ -118,7 +118,7 @@ export function executeCallbacks(queue: any[], arg?: any) {
const t0 = performance.now();
callback(arg);
const t1 = performance.now();
if (t1 - t0 > 250) log('callbackSlow', callback.name || callback, `time=${Math.round(t1 - t0)}`);
if (t1 - t0 > 250) log('callbackSlow', { callback: callback.name || callback, time: Math.round(t1 - t0) });
timer(callback.name || 'anonymousCallback', t1 - t0);
} catch (e) {
error(`executeCallbacks: ${callback} ${e}`);