Ethanfel
a8c9a0376d
NiceGUI's ui.number returns float values, so seeds, steps, dimensions etc. were being stored as floats (e.g. 42.0) instead of integers. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
709 lines
29 KiB
Python
709 lines
29 KiB
Python
import copy
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import random
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from pathlib import Path
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from nicegui import ui
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from state import AppState
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from utils import (
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DEFAULTS, save_json, load_json,
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KEY_BATCH_DATA, KEY_HISTORY_TREE, KEY_PROMPT_HISTORY, KEY_SEQUENCE_NUMBER,
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)
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from history_tree import HistoryTree
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IMAGE_EXTENSIONS = {'.png', '.jpg', '.jpeg', '.webp', '.bmp', '.gif'}
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SUB_SEGMENT_MULTIPLIER = 1000
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VACE_MODES = [
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'End Extend', 'Pre Extend', 'Middle Extend', 'Edge Extend',
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'Join Extend', 'Bidirectional Extend', 'Frame Interpolation',
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'Replace/Inpaint', 'Video Inpaint', 'Keyframe',
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]
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VACE_FORMULAS = [
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'base + A', 'base + B', 'base + A + B', 'base + A + B',
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'base + A + B', 'base + A + B', '(B-1) * step',
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'snap(source)', 'snap(source)', 'base + A + B',
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]
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# --- Sub-segment helpers (same as original) ---
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def is_subsegment(seq_num):
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return int(seq_num) >= SUB_SEGMENT_MULTIPLIER
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def parent_of(seq_num):
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seq_num = int(seq_num)
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return seq_num // SUB_SEGMENT_MULTIPLIER if is_subsegment(seq_num) else seq_num
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def sub_index_of(seq_num):
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seq_num = int(seq_num)
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return seq_num % SUB_SEGMENT_MULTIPLIER if is_subsegment(seq_num) else 0
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def format_seq_label(seq_num):
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seq_num = int(seq_num)
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if is_subsegment(seq_num):
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return f'Sub #{parent_of(seq_num)}.{sub_index_of(seq_num)}'
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return f'Sequence #{seq_num}'
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def next_sub_segment_number(batch_list, parent_seq_num):
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parent_seq_num = int(parent_seq_num)
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max_sub = 0
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for s in batch_list:
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sn = int(s.get(KEY_SEQUENCE_NUMBER, 0))
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if is_subsegment(sn) and parent_of(sn) == parent_seq_num:
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max_sub = max(max_sub, sub_index_of(sn))
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return parent_seq_num * SUB_SEGMENT_MULTIPLIER + max_sub + 1
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def find_insert_position(batch_list, parent_index, parent_seq_num):
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parent_seq_num = int(parent_seq_num)
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pos = parent_index + 1
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while pos < len(batch_list):
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sn = int(batch_list[pos].get(KEY_SEQUENCE_NUMBER, 0))
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if is_subsegment(sn) and parent_of(sn) == parent_seq_num:
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pos += 1
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else:
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break
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return pos
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# --- Helper for repetitive dict-bound inputs ---
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def dict_input(element_fn, label, seq, key, **kwargs):
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"""Create an input element bound to seq[key] via blur event."""
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val = seq.get(key, '')
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if isinstance(val, (int, float)):
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val = str(val) if element_fn != ui.number else val
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el = element_fn(label, value=val, **kwargs)
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el.on('blur', lambda e, k=key: seq.__setitem__(k, e.sender.value))
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return el
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def dict_number(label, seq, key, **kwargs):
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"""Number input bound to seq[key] via blur."""
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val = seq.get(key, 0)
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try:
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# Try float first to handle "1.5" strings, then check if it's a clean int
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fval = float(val)
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val = int(fval) if fval == int(fval) else fval
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except (ValueError, TypeError):
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val = 0
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el = ui.number(label, value=val, **kwargs)
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def _on_blur(e, k=key):
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v = e.sender.value
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if v is None:
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v = 0
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elif isinstance(v, float) and v == int(v):
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v = int(v)
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seq[k] = v
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el.on('blur', _on_blur)
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return el
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def dict_textarea(label, seq, key, **kwargs):
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"""Textarea bound to seq[key] via blur."""
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el = ui.textarea(label, value=seq.get(key, ''), **kwargs)
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el.on('blur', lambda e, k=key: seq.__setitem__(k, e.sender.value))
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return el
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# ======================================================================
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# Main render function
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# ======================================================================
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def render_batch_processor(state: AppState):
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data = state.data_cache
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file_path = state.file_path
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is_batch_file = KEY_BATCH_DATA in data or isinstance(data, list)
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if not is_batch_file:
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ui.label('This is a Single file. To use Batch mode, create a copy.').classes(
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'text-warning')
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def create_batch():
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new_name = f'batch_{file_path.name}'
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new_path = file_path.parent / new_name
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if new_path.exists():
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ui.notify(f'File {new_name} already exists!', type='warning')
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return
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first_item = copy.deepcopy(data)
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first_item.pop(KEY_PROMPT_HISTORY, None)
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first_item.pop(KEY_HISTORY_TREE, None)
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first_item[KEY_SEQUENCE_NUMBER] = 1
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new_data = {KEY_BATCH_DATA: [first_item], KEY_HISTORY_TREE: {},
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KEY_PROMPT_HISTORY: []}
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save_json(new_path, new_data)
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ui.notify(f'Created {new_name}', type='positive')
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ui.button('Create Batch Copy', icon='content_copy', on_click=create_batch)
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return
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if state.restored_indicator:
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ui.label(f'Editing Restored Version: {state.restored_indicator}').classes(
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'text-info q-pa-sm')
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batch_list = data.get(KEY_BATCH_DATA, [])
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# Source file data for importing
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json_files = sorted(state.current_dir.glob('*.json'))
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json_files = [f for f in json_files if f.name not in (
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'.editor_config.json', '.editor_snippets.json')]
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file_options = {f.name: f.name for f in json_files}
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src_file_select = ui.select(
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file_options,
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value=file_path.name,
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label='Source File:',
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).classes('w-64')
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src_seq_select = ui.select([], label='Source Sequence:').classes('w-64')
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# Track loaded source data
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_src_cache = {'data': None, 'batch': [], 'name': None}
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def _update_src():
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name = src_file_select.value
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if name and name != _src_cache['name']:
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src_data, _ = load_json(state.current_dir / name)
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_src_cache['data'] = src_data
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_src_cache['batch'] = src_data.get(KEY_BATCH_DATA, [])
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_src_cache['name'] = name
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if _src_cache['batch']:
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opts = {i: format_seq_label(s.get(KEY_SEQUENCE_NUMBER, i+1))
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for i, s in enumerate(_src_cache['batch'])}
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src_seq_select.set_options(opts, value=0)
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else:
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src_seq_select.set_options({})
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src_file_select.on_value_change(lambda _: _update_src())
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_update_src()
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# --- Add New Sequence ---
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ui.label('Add New Sequence').classes('text-subtitle1 q-mt-md')
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def _add_sequence(new_item):
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max_seq = 0
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for s in batch_list:
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sn = int(s.get(KEY_SEQUENCE_NUMBER, 0))
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if not is_subsegment(sn):
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max_seq = max(max_seq, sn)
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new_item[KEY_SEQUENCE_NUMBER] = max_seq + 1
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for k in [KEY_PROMPT_HISTORY, KEY_HISTORY_TREE, 'note', 'loras']:
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new_item.pop(k, None)
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batch_list.append(new_item)
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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render_sequence_list.refresh()
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with ui.row():
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def add_empty():
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_add_sequence(DEFAULTS.copy())
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def add_from_source():
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item = copy.deepcopy(DEFAULTS)
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src_batch = _src_cache['batch']
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sel_idx = src_seq_select.value
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if src_batch and sel_idx is not None:
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item.update(copy.deepcopy(src_batch[int(sel_idx)]))
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elif _src_cache['data']:
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item.update(copy.deepcopy(_src_cache['data']))
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_add_sequence(item)
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ui.button('Add Empty', icon='add', on_click=add_empty)
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ui.button('From Source', icon='file_download', on_click=add_from_source)
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ui.separator()
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# --- Standard / LoRA / VACE key sets ---
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lora_keys = ['lora 1 high', 'lora 1 low', 'lora 2 high', 'lora 2 low',
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'lora 3 high', 'lora 3 low']
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standard_keys = {
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'general_prompt', 'general_negative', 'current_prompt', 'negative', 'prompt',
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'seed', 'cfg', 'camera', 'flf', KEY_SEQUENCE_NUMBER,
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'frame_to_skip', 'end_frame', 'transition', 'vace_length',
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'input_a_frames', 'input_b_frames', 'reference switch', 'vace schedule',
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'reference path', 'video file path', 'reference image path', 'flf image path',
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}
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standard_keys.update(lora_keys)
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def sort_by_number():
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batch_list.sort(key=lambda s: int(s.get(KEY_SEQUENCE_NUMBER, 0)))
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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ui.notify('Sorted by sequence number!', type='positive')
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render_sequence_list.refresh()
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# --- Sequence list + mass update (inside refreshable so they stay in sync) ---
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@ui.refreshable
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def render_sequence_list():
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# Mass update (rebuilt on refresh so checkboxes match current sequences)
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_render_mass_update(batch_list, data, file_path, state, render_sequence_list)
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with ui.row().classes('w-full items-center'):
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ui.label(f'Batch contains {len(batch_list)} sequences.')
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ui.button('Sort by Number', icon='sort', on_click=sort_by_number).props('flat')
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for i, seq in enumerate(batch_list):
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_render_sequence_card(
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i, seq, batch_list, data, file_path, state,
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_src_cache, src_seq_select,
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standard_keys, render_sequence_list,
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)
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render_sequence_list()
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ui.separator()
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# --- Save & Snap ---
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with ui.row().classes('w-full items-end q-gutter-md'):
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commit_input = ui.input('Change Note (Optional)',
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placeholder='e.g. Added sequence 3').classes('col')
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def save_and_snap():
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data[KEY_BATCH_DATA] = batch_list
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tree_data = data.get(KEY_HISTORY_TREE, {})
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htree = HistoryTree(tree_data)
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snapshot_payload = copy.deepcopy(data)
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snapshot_payload.pop(KEY_HISTORY_TREE, None)
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note = commit_input.value if commit_input.value else 'Batch Update'
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htree.commit(snapshot_payload, note=note)
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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state.restored_indicator = None
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commit_input.set_value('')
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ui.notify('Batch Saved & Snapshot Created!', type='positive')
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ui.button('Save & Snap', icon='save', on_click=save_and_snap).props('color=primary')
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# ======================================================================
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# Single sequence card
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# ======================================================================
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def _render_sequence_card(i, seq, batch_list, data, file_path, state,
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src_cache, src_seq_select, standard_keys,
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refresh_list):
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seq_num = seq.get(KEY_SEQUENCE_NUMBER, i + 1)
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if is_subsegment(seq_num):
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label = f'Sub #{parent_of(seq_num)}.{sub_index_of(seq_num)} ({int(seq_num)})'
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else:
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label = f'Sequence #{seq_num}'
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with ui.expansion(label, icon='movie').classes('w-full'):
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# --- Action row ---
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with ui.row().classes('w-full q-gutter-sm action-row'):
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# Copy from source
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def copy_source(idx=i, sn=seq_num):
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item = copy.deepcopy(DEFAULTS)
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src_batch = src_cache['batch']
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sel_idx = src_seq_select.value
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if src_batch and sel_idx is not None:
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item.update(copy.deepcopy(src_batch[int(sel_idx)]))
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elif src_cache['data']:
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item.update(copy.deepcopy(src_cache['data']))
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item[KEY_SEQUENCE_NUMBER] = sn
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item.pop(KEY_PROMPT_HISTORY, None)
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item.pop(KEY_HISTORY_TREE, None)
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batch_list[idx] = item
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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ui.notify('Copied!', type='positive')
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refresh_list.refresh()
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ui.button('Copy Src', icon='file_download', on_click=copy_source).props('dense')
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# Clone Next
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def clone_next(idx=i, sn=seq_num, s=seq):
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new_seq = copy.deepcopy(s)
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max_sn = max(
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(int(x.get(KEY_SEQUENCE_NUMBER, 0))
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for x in batch_list if not is_subsegment(x.get(KEY_SEQUENCE_NUMBER, 0))),
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default=0)
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new_seq[KEY_SEQUENCE_NUMBER] = max_sn + 1
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if not is_subsegment(sn):
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pos = find_insert_position(batch_list, idx, int(sn))
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else:
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pos = idx + 1
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batch_list.insert(pos, new_seq)
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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ui.notify('Cloned to Next!', type='positive')
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refresh_list.refresh()
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ui.button('Clone Next', icon='content_copy', on_click=clone_next).props('dense')
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# Clone End
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def clone_end(s=seq):
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new_seq = copy.deepcopy(s)
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max_sn = max(
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(int(x.get(KEY_SEQUENCE_NUMBER, 0))
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for x in batch_list if not is_subsegment(x.get(KEY_SEQUENCE_NUMBER, 0))),
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default=0)
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new_seq[KEY_SEQUENCE_NUMBER] = max_sn + 1
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batch_list.append(new_seq)
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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ui.notify('Cloned to End!', type='positive')
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refresh_list.refresh()
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ui.button('Clone End', icon='vertical_align_bottom', on_click=clone_end).props('dense')
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# Clone Sub
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def clone_sub(idx=i, sn=seq_num, s=seq):
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new_seq = copy.deepcopy(s)
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p_seq = parent_of(sn)
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p_idx = idx
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if is_subsegment(sn):
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for pi, ps in enumerate(batch_list):
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if int(ps.get(KEY_SEQUENCE_NUMBER, 0)) == p_seq:
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p_idx = pi
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break
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new_seq[KEY_SEQUENCE_NUMBER] = next_sub_segment_number(batch_list, p_seq)
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pos = find_insert_position(batch_list, p_idx, p_seq)
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batch_list.insert(pos, new_seq)
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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ui.notify(f'Created {format_seq_label(new_seq[KEY_SEQUENCE_NUMBER])}!',
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type='positive')
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refresh_list.refresh()
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ui.button('Clone Sub', icon='link', on_click=clone_sub).props('dense')
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# Promote
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def promote(idx=i, s=seq):
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single_data = copy.deepcopy(s)
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single_data[KEY_PROMPT_HISTORY] = copy.deepcopy(data.get(KEY_PROMPT_HISTORY, []))
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single_data[KEY_HISTORY_TREE] = copy.deepcopy(data.get(KEY_HISTORY_TREE, {}))
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single_data.pop(KEY_SEQUENCE_NUMBER, None)
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save_json(file_path, single_data)
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state.data_cache = single_data
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ui.notify('Converted to Single!', type='positive')
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# Full refresh so batch tab re-enters render_batch_processor
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# and sees the file is now single (no KEY_BATCH_DATA)
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state._render_main.refresh()
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ui.button('Promote', icon='north_west', on_click=promote).props('dense')
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# Delete
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def delete(idx=i):
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batch_list.pop(idx)
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data[KEY_BATCH_DATA] = batch_list
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save_json(file_path, data)
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refresh_list.refresh()
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ui.button(icon='delete', on_click=delete).props('dense color=negative')
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ui.separator()
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# --- Prompts + Settings (2-column like Streamlit) ---
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with ui.splitter(value=66).classes('w-full') as splitter:
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with splitter.before:
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dict_textarea('General Prompt', seq, 'general_prompt').classes(
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'w-full').props('outlined rows=2')
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dict_textarea('General Negative', seq, 'general_negative').classes(
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'w-full').props('outlined rows=2')
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dict_textarea('Specific Prompt', seq, 'current_prompt').classes(
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'w-full').props('outlined rows=10')
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dict_textarea('Specific Negative', seq, 'negative').classes(
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'w-full').props('outlined rows=2')
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with splitter.after:
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# Sequence number
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sn_label = (
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f'Seq Number (Sub #{parent_of(seq_num)}.{sub_index_of(seq_num)})'
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if is_subsegment(seq_num) else 'Sequence Number'
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)
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sn_input = dict_number(sn_label, seq, KEY_SEQUENCE_NUMBER)
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sn_input.props('outlined').classes('w-full')
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# Seed + randomize
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with ui.row().classes('w-full items-end'):
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seed_input = dict_number('Seed', seq, 'seed').classes('col').props('outlined')
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def randomize_seed(si=seed_input, s=seq):
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new_seed = random.randint(0, 999999999999)
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si.set_value(new_seed)
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s['seed'] = new_seed
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ui.button(icon='casino', on_click=randomize_seed).props('flat')
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# CFG
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cfg_val = float(seq.get('cfg', DEFAULTS['cfg']))
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cfg_input = ui.number('CFG', value=cfg_val, step=0.5,
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format='%.1f').props('outlined').classes('w-full')
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cfg_input.on('blur', lambda e: seq.__setitem__(
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'cfg', e.sender.value if e.sender.value is not None else DEFAULTS['cfg']))
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dict_input(ui.input, 'Camera', seq, 'camera').props('outlined').classes('w-full')
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dict_input(ui.input, 'FLF', seq, 'flf').props('outlined').classes('w-full')
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dict_number('End Frame', seq, 'end_frame').props('outlined').classes('w-full')
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dict_input(ui.input, 'Video File Path', seq, 'video file path').props(
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'outlined').classes('w-full')
|
|
|
|
# Image paths with preview
|
|
for img_label, img_key in [
|
|
('Reference Image Path', 'reference image path'),
|
|
('Reference Path', 'reference path'),
|
|
('FLF Image Path', 'flf image path'),
|
|
]:
|
|
with ui.row().classes('w-full items-center'):
|
|
inp = dict_input(ui.input, img_label, seq, img_key).classes(
|
|
'col').props('outlined')
|
|
img_path = Path(seq.get(img_key, '')) if seq.get(img_key) else None
|
|
if (img_path and img_path.exists() and
|
|
img_path.suffix.lower() in IMAGE_EXTENSIONS):
|
|
with ui.dialog() as dlg, ui.card():
|
|
ui.image(str(img_path)).classes('w-full')
|
|
ui.button(icon='visibility', on_click=dlg.open).props('flat dense')
|
|
|
|
# VACE Settings
|
|
with ui.expansion('VACE Settings', icon='settings').classes('w-full'):
|
|
_render_vace_settings(i, seq, batch_list, data, file_path, refresh_list)
|
|
|
|
# --- LoRA Settings ---
|
|
with ui.expansion('LoRA Settings', icon='style').classes('w-full'):
|
|
with ui.row().classes('w-full q-gutter-md'):
|
|
for lora_idx in range(1, 4):
|
|
with ui.column().classes('col'):
|
|
ui.label(f'LoRA {lora_idx}').classes('text-subtitle2')
|
|
for tier, tier_label in [('high', 'High'), ('low', 'Low')]:
|
|
k = f'lora {lora_idx} {tier}'
|
|
raw = str(seq.get(k, ''))
|
|
disp = raw.replace('<lora:', '').replace('>', '')
|
|
|
|
with ui.row().classes('w-full items-center'):
|
|
ui.label('<lora:').classes('text-caption font-mono')
|
|
lora_input = ui.input(
|
|
f'L{lora_idx} {tier_label}',
|
|
value=disp,
|
|
).classes('col').props('outlined dense')
|
|
ui.label('>').classes('text-caption font-mono')
|
|
|
|
def on_lora_blur(e, key=k):
|
|
v = e.sender.value
|
|
seq[key] = f'<lora:{v}>' if v else ''
|
|
|
|
lora_input.on('blur', on_lora_blur)
|
|
|
|
# --- Custom Parameters ---
|
|
ui.separator()
|
|
ui.label('Custom Parameters').classes('text-caption')
|
|
|
|
custom_keys = [k for k in seq.keys() if k not in standard_keys]
|
|
if custom_keys:
|
|
for k in custom_keys:
|
|
with ui.row().classes('w-full items-center'):
|
|
ui.input('Key', value=k).props('readonly outlined dense').classes('w-32')
|
|
val_input = ui.input('Value', value=str(seq[k])).props(
|
|
'outlined dense').classes('col')
|
|
val_input.on('blur', lambda e, key=k: seq.__setitem__(key, e.sender.value))
|
|
|
|
def del_custom(key=k):
|
|
del seq[key]
|
|
save_json(file_path, data)
|
|
refresh_list.refresh()
|
|
|
|
ui.button(icon='delete', on_click=del_custom).props('flat dense color=negative')
|
|
|
|
with ui.expansion('Add Parameter', icon='add').classes('w-full'):
|
|
new_k_input = ui.input('Key').props('outlined dense')
|
|
new_v_input = ui.input('Value').props('outlined dense')
|
|
|
|
def add_param():
|
|
k = new_k_input.value
|
|
v = new_v_input.value
|
|
if k and k not in seq:
|
|
seq[k] = v
|
|
save_json(file_path, data)
|
|
new_k_input.set_value('')
|
|
new_v_input.set_value('')
|
|
refresh_list.refresh()
|
|
|
|
ui.button('Add', on_click=add_param).props('flat')
|
|
|
|
|
|
# ======================================================================
|
|
# VACE Settings sub-section
|
|
# ======================================================================
|
|
|
|
def _render_vace_settings(i, seq, batch_list, data, file_path, refresh_list):
|
|
# Frame to Skip + shift
|
|
with ui.row().classes('w-full items-end'):
|
|
fts_input = dict_number('Frame to Skip', seq, 'frame_to_skip').classes('col').props(
|
|
'outlined')
|
|
|
|
# Capture original at render time; blur updates seq before click fires
|
|
_original_fts = int(seq.get('frame_to_skip', 81))
|
|
|
|
def shift_fts(idx=i, orig=_original_fts):
|
|
new_fts = int(fts_input.value) if fts_input.value is not None else orig
|
|
delta = new_fts - orig
|
|
if delta == 0:
|
|
ui.notify('No change to shift', type='info')
|
|
return
|
|
shifted = 0
|
|
for j in range(idx + 1, len(batch_list)):
|
|
batch_list[j]['frame_to_skip'] = int(
|
|
batch_list[j].get('frame_to_skip', 81)) + delta
|
|
shifted += 1
|
|
data[KEY_BATCH_DATA] = batch_list
|
|
save_json(file_path, data)
|
|
ui.notify(f'Shifted {shifted} sequences by {delta:+d}', type='positive')
|
|
refresh_list.refresh()
|
|
|
|
ui.button('Shift', icon='arrow_downward', on_click=shift_fts).props('dense')
|
|
|
|
dict_input(ui.input, 'Transition', seq, 'transition').props('outlined')
|
|
|
|
# VACE Schedule
|
|
sched_val = max(0, min(int(seq.get('vace schedule', 1)), len(VACE_MODES) - 1))
|
|
with ui.row().classes('w-full items-center'):
|
|
vs_input = ui.number('VACE Schedule', value=sched_val, min=0,
|
|
max=len(VACE_MODES) - 1).classes('col').props('outlined')
|
|
vs_input.on('blur', lambda e: seq.__setitem__(
|
|
'vace schedule', int(e.sender.value) if e.sender.value is not None else 0))
|
|
mode_label = ui.label(VACE_MODES[sched_val]).classes('text-caption')
|
|
|
|
def update_mode_label(e):
|
|
idx = int(e.sender.value) if e.sender.value is not None else 0
|
|
idx = max(0, min(idx, len(VACE_MODES) - 1))
|
|
mode_label.set_text(VACE_MODES[idx])
|
|
|
|
vs_input.on('update:model-value', update_mode_label)
|
|
|
|
# Mode reference
|
|
with ui.dialog() as ref_dlg, ui.card():
|
|
table_md = (
|
|
'| # | Mode | Formula |\n|:--|:-----|:--------|\n'
|
|
+ '\n'.join(
|
|
f'| **{j}** | {VACE_MODES[j]} | `{VACE_FORMULAS[j]}` |'
|
|
for j in range(len(VACE_MODES)))
|
|
+ '\n\n*All totals snapped to 4n+1 (1,5,9,...,49,...,81,...)*'
|
|
)
|
|
ui.markdown(table_md)
|
|
ui.button('Mode Reference', icon='help', on_click=ref_dlg.open).props('flat dense')
|
|
|
|
# Input A / B frames
|
|
ia_input = dict_number('Input A Frames', seq, 'input_a_frames').props('outlined')
|
|
ib_input = dict_number('Input B Frames', seq, 'input_b_frames').props('outlined')
|
|
|
|
# VACE Length + output calculation
|
|
input_a = int(seq.get('input_a_frames', 16))
|
|
input_b = int(seq.get('input_b_frames', 16))
|
|
stored_total = int(seq.get('vace_length', 49))
|
|
mode_idx = int(seq.get('vace schedule', 1))
|
|
|
|
if mode_idx == 0:
|
|
base_length = max(stored_total - input_a, 1)
|
|
elif mode_idx == 1:
|
|
base_length = max(stored_total - input_b, 1)
|
|
else:
|
|
base_length = max(stored_total - input_a - input_b, 1)
|
|
|
|
with ui.row().classes('w-full items-center'):
|
|
vl_input = ui.number('VACE Length', value=base_length, min=1).classes('col').props(
|
|
'outlined')
|
|
output_label = ui.label(f'Output: {stored_total}').classes('text-bold')
|
|
|
|
def recalc_vace(*_args):
|
|
mi = int(vs_input.value) if vs_input.value is not None else 0
|
|
ia = int(ia_input.value) if ia_input.value is not None else 16
|
|
ib = int(ib_input.value) if ib_input.value is not None else 16
|
|
nb = int(vl_input.value) if vl_input.value is not None else 1
|
|
|
|
if mi == 0:
|
|
raw = nb + ia
|
|
elif mi == 1:
|
|
raw = nb + ib
|
|
else:
|
|
raw = nb + ia + ib
|
|
|
|
snapped = ((raw + 2) // 4) * 4 + 1
|
|
seq['vace_length'] = snapped
|
|
output_label.set_text(f'Output: {snapped}')
|
|
|
|
for inp in (vs_input, ia_input, ib_input, vl_input):
|
|
inp.on('update:model-value', recalc_vace)
|
|
|
|
dict_number('Reference Switch', seq, 'reference switch').props('outlined')
|
|
|
|
|
|
# ======================================================================
|
|
# Mass Update
|
|
# ======================================================================
|
|
|
|
def _render_mass_update(batch_list, data, file_path, state: AppState, refresh_list=None):
|
|
with ui.expansion('Mass Update', icon='sync').classes('w-full'):
|
|
if len(batch_list) < 2:
|
|
ui.label('Need at least 2 sequences for mass update.').classes('text-caption')
|
|
return
|
|
|
|
source_options = {i: format_seq_label(s.get(KEY_SEQUENCE_NUMBER, i+1))
|
|
for i, s in enumerate(batch_list)}
|
|
source_select = ui.select(source_options, value=0,
|
|
label='Copy from sequence:').classes('w-full')
|
|
|
|
field_select = ui.select([], multiple=True,
|
|
label='Fields to copy:').classes('w-full')
|
|
|
|
def update_fields(_=None):
|
|
idx = source_select.value
|
|
if idx is not None and 0 <= idx < len(batch_list):
|
|
src = batch_list[idx]
|
|
keys = [k for k in src.keys() if k != 'sequence_number']
|
|
field_select.set_options(keys)
|
|
|
|
source_select.on_value_change(update_fields)
|
|
update_fields()
|
|
|
|
ui.label('Apply to:').classes('text-subtitle2 q-mt-md')
|
|
select_all_cb = ui.checkbox('Select All')
|
|
target_checks = {}
|
|
for idx, s in enumerate(batch_list):
|
|
sn = s.get(KEY_SEQUENCE_NUMBER, idx + 1)
|
|
cb = ui.checkbox(format_seq_label(sn))
|
|
target_checks[idx] = cb
|
|
|
|
def on_select_all(e):
|
|
for cb in target_checks.values():
|
|
cb.set_value(e.value)
|
|
|
|
select_all_cb.on_value_change(on_select_all)
|
|
|
|
def apply_mass_update():
|
|
src_idx = source_select.value
|
|
if src_idx is None or src_idx >= len(batch_list):
|
|
ui.notify('Source sequence no longer exists', type='warning')
|
|
return
|
|
selected_keys = field_select.value or []
|
|
if not selected_keys:
|
|
ui.notify('No fields selected', type='warning')
|
|
return
|
|
|
|
source_seq = batch_list[src_idx]
|
|
targets = [idx for idx, cb in target_checks.items()
|
|
if cb.value and idx != src_idx and idx < len(batch_list)]
|
|
if not targets:
|
|
ui.notify('No target sequences selected', type='warning')
|
|
return
|
|
|
|
for idx in targets:
|
|
for key in selected_keys:
|
|
batch_list[idx][key] = copy.deepcopy(source_seq.get(key))
|
|
|
|
data[KEY_BATCH_DATA] = batch_list
|
|
htree = HistoryTree(data.get(KEY_HISTORY_TREE, {}))
|
|
snapshot = copy.deepcopy(data)
|
|
snapshot.pop(KEY_HISTORY_TREE, None)
|
|
htree.commit(snapshot, f"Mass update: {', '.join(selected_keys)}")
|
|
data[KEY_HISTORY_TREE] = htree.to_dict()
|
|
save_json(file_path, data)
|
|
ui.notify(f'Updated {len(targets)} sequences', type='positive')
|
|
if refresh_list:
|
|
refresh_list.refresh()
|
|
|
|
ui.button('Apply Changes', icon='check', on_click=apply_mass_update).props(
|
|
'color=primary')
|