277 lines
13 KiB
Python
277 lines
13 KiB
Python
import streamlit as st
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import random
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from utils import DEFAULTS, save_json, load_json, render_smart_input
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from history_tree import HistoryTree
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def create_batch_callback(original_filename, current_data, current_dir):
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new_name = f"batch_{original_filename}"
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new_path = current_dir / new_name
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if new_path.exists():
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st.toast(f"File {new_name} already exists!", icon="⚠️")
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return
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first_item = current_data.copy()
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if "prompt_history" in first_item: del first_item["prompt_history"]
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if "history_tree" in first_item: del first_item["history_tree"]
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first_item["sequence_number"] = 1
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new_data = {
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"batch_data": [first_item],
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"history_tree": {},
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"prompt_history": []
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}
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save_json(new_path, new_data)
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st.toast(f"Created {new_name}", icon="✨")
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st.session_state.file_selector = new_name
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def render_batch_processor(data, file_path, json_files, current_dir, selected_file_name):
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is_batch_file = "batch_data" in data or isinstance(data, list)
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if not is_batch_file:
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st.warning("This is a Single file. To use Batch mode, create a copy.")
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st.button("✨ Create Batch Copy", on_click=create_batch_callback, args=(selected_file_name, data, current_dir))
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return
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# --- 1. RESTORED STATE INDICATOR ---
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if 'restored_indicator' in st.session_state and st.session_state.restored_indicator:
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st.info(f"📍 Editing Restored Version: **{st.session_state.restored_indicator}**")
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batch_list = data.get("batch_data", [])
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# --- ADD NEW SEQUENCE AREA ---
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st.subheader("Add New Sequence")
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ac1, ac2 = st.columns(2)
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with ac1:
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file_options = [f.name for f in json_files]
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d_idx = file_options.index(selected_file_name) if selected_file_name in file_options else 0
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src_name = st.selectbox("Source File:", file_options, index=d_idx, key="batch_src_file")
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src_data, _ = load_json(current_dir / src_name)
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with ac2:
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src_hist = src_data.get("prompt_history", [])
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h_opts = [f"#{i+1}: {h.get('note', 'No Note')} ({h.get('prompt', '')[:15]}...)" for i, h in enumerate(src_hist)] if src_hist else []
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sel_hist = st.selectbox("History Entry (Legacy):", h_opts, key="batch_src_hist")
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bc1, bc2, bc3 = st.columns(3)
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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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if "sequence_number" in s: max_seq = max(max_seq, int(s["sequence_number"]))
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new_item["sequence_number"] = max_seq + 1
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for k in ["prompt_history", "history_tree", "note", "loras"]:
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if k in new_item: del new_item[k]
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batch_list.append(new_item)
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data["batch_data"] = batch_list
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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st.rerun()
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if bc1.button("➕ Add Empty", use_container_width=True):
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add_sequence(DEFAULTS.copy())
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if bc2.button("➕ From File", use_container_width=True, help=f"Copy {src_name}"):
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item = DEFAULTS.copy()
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flat = src_data["batch_data"][0] if "batch_data" in src_data and src_data["batch_data"] else src_data
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item.update(flat)
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add_sequence(item)
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if bc3.button("➕ From History", use_container_width=True, disabled=not src_hist):
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if sel_hist:
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idx = int(sel_hist.split(":")[0].replace("#", "")) - 1
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item = DEFAULTS.copy()
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h_item = src_hist[idx]
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item.update(h_item)
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if "loras" in h_item and isinstance(h_item["loras"], dict):
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item.update(h_item["loras"])
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add_sequence(item)
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# --- RENDER LIST ---
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st.markdown("---")
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st.info(f"Batch contains {len(batch_list)} sequences.")
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lora_keys = ["lora 1 high", "lora 1 low", "lora 2 high", "lora 2 low", "lora 3 high", "lora 3 low"]
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standard_keys = {
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"general_prompt", "general_negative", "current_prompt", "negative", "prompt", "seed",
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"camera", "flf", "sequence_number"
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}
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standard_keys.update(lora_keys)
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standard_keys.update([
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"frame_to_skip", "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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for i, seq in enumerate(batch_list):
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seq_num = seq.get("sequence_number", i+1)
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prefix = f"{selected_file_name}_seq{i}_v{st.session_state.ui_reset_token}"
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with st.expander(f"🎬 Sequence #{seq_num}", expanded=False):
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b1, b2, b3 = st.columns([1, 1, 2])
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if b1.button(f"📥 Copy {src_name}", key=f"{prefix}_copy"):
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item = DEFAULTS.copy()
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flat = src_data["batch_data"][0] if "batch_data" in src_data and src_data["batch_data"] else src_data
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item.update(flat)
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item["sequence_number"] = seq_num
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for k in ["prompt_history", "history_tree"]:
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if k in item: del item[k]
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batch_list[i] = item
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data["batch_data"] = batch_list
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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st.toast("Copied!", icon="📥")
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st.rerun()
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if b2.button("↖️ Promote to Single", key=f"{prefix}_prom"):
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single_data = seq.copy()
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single_data["prompt_history"] = data.get("prompt_history", [])
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single_data["history_tree"] = data.get("history_tree", {})
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if "sequence_number" in single_data: del single_data["sequence_number"]
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save_json(file_path, single_data)
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st.toast("Converted to Single!", icon="✅")
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st.rerun()
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if b3.button("🗑️ Remove", key=f"{prefix}_del"):
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batch_list.pop(i)
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data["batch_data"] = batch_list
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save_json(file_path, data)
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st.rerun()
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st.markdown("---")
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c1, c2 = st.columns([2, 1])
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with c1:
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seq["general_prompt"] = st.text_area("General Prompt", value=seq.get("general_prompt", ""), height=60, key=f"{prefix}_gp")
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seq["general_negative"] = st.text_area("General Negative", value=seq.get("general_negative", ""), height=60, key=f"{prefix}_gn")
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seq["current_prompt"] = st.text_area("Specific Prompt", value=seq.get("current_prompt", ""), height=100, key=f"{prefix}_sp")
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seq["negative"] = st.text_area("Specific Negative", value=seq.get("negative", ""), height=60, key=f"{prefix}_sn")
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with c2:
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seq["sequence_number"] = st.number_input("Seq Num", value=int(seq_num), key=f"{prefix}_sn_val")
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s_row1, s_row2 = st.columns([3, 1])
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seed_key = f"{prefix}_seed"
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with s_row2:
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st.write("")
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st.write("")
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if st.button("🎲", key=f"{prefix}_rand"):
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st.session_state[seed_key] = random.randint(0, 999999999999)
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st.rerun()
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with s_row1:
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current_seed = st.session_state.get(seed_key, int(seq.get("seed", 0)))
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val = st.number_input("Seed", value=current_seed, key=seed_key)
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seq["seed"] = val
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seq["camera"] = st.text_input("Camera", value=seq.get("camera", ""), key=f"{prefix}_cam")
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seq["flf"] = st.text_input("FLF", value=str(seq.get("flf", DEFAULTS["flf"])), key=f"{prefix}_flf")
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if "video file path" in seq or "vace" in selected_file_name:
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seq["video file path"] = st.text_input("Video Path", value=seq.get("video file path", ""), key=f"{prefix}_vid")
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with st.expander("VACE Settings"):
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seq["frame_to_skip"] = st.number_input("Skip", value=int(seq.get("frame_to_skip", 81)), key=f"{prefix}_fts")
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seq["input_a_frames"] = st.number_input("In A", value=int(seq.get("input_a_frames", 0)), key=f"{prefix}_ia")
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seq["input_b_frames"] = st.number_input("In B", value=int(seq.get("input_b_frames", 0)), key=f"{prefix}_ib")
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seq["reference switch"] = st.number_input("Switch", value=int(seq.get("reference switch", 1)), key=f"{prefix}_rsw")
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seq["vace schedule"] = st.number_input("Sched", value=int(seq.get("vace schedule", 1)), key=f"{prefix}_vsc")
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seq["reference path"] = st.text_input("Ref Path", value=seq.get("reference path", ""), key=f"{prefix}_rp")
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seq["reference image path"] = st.text_input("Ref Img", value=seq.get("reference image path", ""), key=f"{prefix}_rip")
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if "i2v" in selected_file_name and "vace" not in selected_file_name:
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seq["reference image path"] = st.text_input("Ref Img", value=seq.get("reference image path", ""), key=f"{prefix}_ri2")
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seq["flf image path"] = st.text_input("FLF Img", value=seq.get("flf image path", ""), key=f"{prefix}_flfi")
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# --- LoRA Settings (SMART INPUTS) ---
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with st.expander("💊 LoRA Settings"):
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meta = st.session_state.get("comfy_meta", {})
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lora_list = meta.get("loras", [])
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lc1, lc2 = st.columns(2)
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with lc1:
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st.caption("LoRA 1")
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seq["lora 1 high"] = render_smart_input("Model", f"{prefix}_l1h", seq.get("lora 1 high", ""), lora_list)
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seq["lora 1 low"] = str(st.slider("Strength", 0.0, 2.0, float(seq.get("lora 1 low", 1.0)), 0.05, key=f"{prefix}_l1l"))
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with lc2:
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st.caption("LoRA 2")
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seq["lora 2 high"] = render_smart_input("Model", f"{prefix}_l2h", seq.get("lora 2 high", ""), lora_list)
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seq["lora 2 low"] = str(st.slider("Strength", 0.0, 2.0, float(seq.get("lora 2 low", 1.0)), 0.05, key=f"{prefix}_l2l"))
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with lc1:
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st.caption("LoRA 3")
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seq["lora 3 high"] = render_smart_input("Model", f"{prefix}_l3h", seq.get("lora 3 high", ""), lora_list)
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seq["lora 3 low"] = str(st.slider("Strength", 0.0, 2.0, float(seq.get("lora 3 low", 1.0)), 0.05, key=f"{prefix}_l3l"))
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# --- CUSTOM PARAMETERS ---
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st.markdown("---")
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st.caption("🔧 Custom Parameters")
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custom_keys = [k for k in seq.keys() if k not in standard_keys]
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keys_to_remove = []
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if custom_keys:
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for k in custom_keys:
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ck1, ck2, ck3 = st.columns([1, 2, 0.5])
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ck1.text_input("Key", value=k, disabled=True, key=f"{prefix}_ck_lbl_{k}", label_visibility="collapsed")
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val = ck2.text_input("Value", value=str(seq[k]), key=f"{prefix}_cv_{k}", label_visibility="collapsed")
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seq[k] = val
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if ck3.button("🗑️", key=f"{prefix}_cdel_{k}"):
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keys_to_remove.append(k)
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with st.expander("➕ Add Parameter"):
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nk_col, nv_col = st.columns(2)
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new_k = nk_col.text_input("Key", key=f"{prefix}_new_k")
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new_v = nv_col.text_input("Value", key=f"{prefix}_new_v")
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if st.button("Add", key=f"{prefix}_add_cust"):
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if new_k and new_k not in seq:
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seq[new_k] = new_v
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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st.rerun()
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if keys_to_remove:
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for k in keys_to_remove:
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del seq[k]
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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st.rerun()
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st.markdown("---")
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# --- SAVE ACTIONS WITH HISTORY COMMIT ---
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col_save, col_note = st.columns([1, 2])
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with col_note:
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commit_msg = st.text_input("Change Note (Optional)", placeholder="e.g. Added sequence 3")
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with col_save:
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if st.button("💾 Save & Snap", use_container_width=True):
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data["batch_data"] = batch_list
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tree_data = data.get("history_tree", {})
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htree = HistoryTree(tree_data)
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snapshot_payload = data.copy()
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if "history_tree" in snapshot_payload: del snapshot_payload["history_tree"]
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htree.commit(snapshot_payload, note=commit_msg if commit_msg else "Batch Update")
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data["history_tree"] = htree.to_dict()
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save_json(file_path, data)
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if 'restored_indicator' in st.session_state:
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del st.session_state.restored_indicator
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st.toast("Batch Saved & Snapshot Created!", icon="🚀")
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st.rerun()
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