import streamlit as st from utils import DEFAULTS, save_json, load_json # Callback for creating batch file def create_batch_callback(original_filename, current_data, current_dir): new_name = f"batch_{original_filename}" new_path = current_dir / new_name if new_path.exists(): st.toast(f"File {new_name} already exists!", icon="⚠️") return first_item = current_data.copy() if "prompt_history" in first_item: del first_item["prompt_history"] first_item["sequence_number"] = 1 new_data = { "batch_data": [first_item], "prompt_history": current_data.get("prompt_history", []) } save_json(new_path, new_data) st.toast(f"Created {new_name}", icon="✨") st.session_state.file_selector = new_name def render_batch_processor(data, file_path, json_files, current_dir, selected_file_name): is_batch_file = "batch_data" in data or isinstance(data, list) if not is_batch_file: st.warning("This is a Single file. To use Batch mode, create a copy.") st.button("✨ Create Batch Copy", on_click=create_batch_callback, args=(selected_file_name, data, current_dir)) return batch_list = data.get("batch_data", []) # --- ADD NEW SEQUENCE AREA --- st.subheader("Add New Sequence") ac1, ac2 = st.columns(2) with ac1: file_options = [f.name for f in json_files] d_idx = file_options.index(selected_file_name) if selected_file_name in file_options else 0 src_name = st.selectbox("Source File:", file_options, index=d_idx, key="batch_src_file") src_data, _ = load_json(current_dir / src_name) with ac2: src_hist = src_data.get("prompt_history", []) h_opts = [f"#{i+1}: {h.get('note', 'No Note')}" for i, h in enumerate(src_hist)] if src_hist else [] sel_hist = st.selectbox("History Entry:", h_opts, key="batch_src_hist") bc1, bc2, bc3 = st.columns(3) # Helper to add sequence def add_sequence(new_item): max_seq = 0 for s in batch_list: if "sequence_number" in s: max_seq = max(max_seq, int(s["sequence_number"])) new_item["sequence_number"] = max_seq + 1 # Cleanup for k in ["prompt_history", "note", "loras"]: if k in new_item: del new_item[k] batch_list.append(new_item) data["batch_data"] = batch_list save_json(file_path, data) st.rerun() if bc1.button("➕ Add Empty", use_container_width=True): add_sequence(DEFAULTS.copy()) if bc2.button("➕ From File", use_container_width=True, help=f"Copy {src_name}"): item = DEFAULTS.copy() # Flatten logic flat = src_data["batch_data"][0] if "batch_data" in src_data and src_data["batch_data"] else src_data item.update(flat) add_sequence(item) if bc3.button("➕ From History", use_container_width=True, disabled=not src_hist): if sel_hist: idx = int(sel_hist.split(":")[0].replace("#", "")) - 1 item = DEFAULTS.copy() h_item = src_hist[idx] item.update(h_item) if "loras" in h_item and isinstance(h_item["loras"], dict): item.update(h_item["loras"]) add_sequence(item) # --- RENDER LIST --- st.markdown("---") st.info(f"Batch contains {len(batch_list)} sequences.") for i, seq in enumerate(batch_list): seq_num = seq.get("sequence_number", i+1) # Unique prefix for this sequence in this file prefix = f"{selected_file_name}_seq{i}" with st.expander(f"🎬 Sequence #{seq_num}", expanded=False): # Header Buttons b1, b2, b3 = st.columns([1, 1, 2]) if b1.button(f"📥 Copy {src_name}", key=f"{prefix}_copy"): item = DEFAULTS.copy() flat = src_data["batch_data"][0] if "batch_data" in src_data and src_data["batch_data"] else src_data item.update(flat) item["sequence_number"] = seq_num if "prompt_history" in item: del item["prompt_history"] batch_list[i] = item data["batch_data"] = batch_list save_json(file_path, data) st.toast("Copied!", icon="📥") st.rerun() if b2.button("↖️ Promote to Single", key=f"{prefix}_prom"): single_data = seq.copy() single_data["prompt_history"] = data.get("prompt_history", []) if "sequence_number" in single_data: del single_data["sequence_number"] save_json(file_path, single_data) st.toast("Converted to Single!", icon="✅") st.rerun() if b3.button("🗑️ Remove", key=f"{prefix}_del"): batch_list.pop(i) data["batch_data"] = batch_list save_json(file_path, data) st.rerun() # Fields st.markdown("---") c1, c2 = st.columns([2, 1]) with c1: seq["general_prompt"] = st.text_area("General Prompt", value=seq.get("general_prompt", ""), height=60, key=f"{prefix}_gp") seq["general_negative"] = st.text_area("General Negative", value=seq.get("general_negative", ""), height=60, key=f"{prefix}_gn") seq["current_prompt"] = st.text_area("Specific Prompt", value=seq.get("current_prompt", ""), height=100, key=f"{prefix}_sp") seq["negative"] = st.text_area("Specific Negative", value=seq.get("negative", ""), height=60, key=f"{prefix}_sn") with c2: seq["sequence_number"] = st.number_input("Seq Num", value=int(seq_num), key=f"{prefix}_sn_val") seq["seed"] = st.number_input("Seed", value=int(seq.get("seed", 0)), key=f"{prefix}_seed") seq["camera"] = st.text_input("Camera", value=seq.get("camera", ""), key=f"{prefix}_cam") seq["flf"] = st.text_input("FLF", value=str(seq.get("flf", DEFAULTS["flf"])), key=f"{prefix}_flf") # Dynamic Paths if "video file path" in seq or "vace" in selected_file_name: seq["video file path"] = st.text_input("Video Path", value=seq.get("video file path", ""), key=f"{prefix}_vid") with st.expander("VACE Settings"): seq["frame_to_skip"] = st.number_input("Skip", value=int(seq.get("frame_to_skip", 81)), key=f"{prefix}_fts") seq["input_a_frames"] = st.number_input("In A", value=int(seq.get("input_a_frames", 0)), key=f"{prefix}_ia") seq["input_b_frames"] = st.number_input("In B", value=int(seq.get("input_b_frames", 0)), key=f"{prefix}_ib") seq["reference switch"] = st.number_input("Switch", value=int(seq.get("reference switch", 1)), key=f"{prefix}_rsw") seq["vace schedule"] = st.number_input("Sched", value=int(seq.get("vace schedule", 1)), key=f"{prefix}_vsc") seq["reference path"] = st.text_input("Ref Path", value=seq.get("reference path", ""), key=f"{prefix}_rp") seq["reference image path"] = st.text_input("Ref Img", value=seq.get("reference image path", ""), key=f"{prefix}_rip") if "i2v" in selected_file_name and "vace" not in selected_file_name: seq["reference image path"] = st.text_input("Ref Img", value=seq.get("reference image path", ""), key=f"{prefix}_ri2") seq["flf image path"] = st.text_input("FLF Img", value=seq.get("flf image path", ""), key=f"{prefix}_flfi") with st.expander("LoRA Settings"): lc1, lc2 = st.columns(2) lkeys = ["lora 1 high", "lora 1 low", "lora 2 high", "lora 2 low", "lora 3 high", "lora 3 low"] for li, lk in enumerate(lkeys): with (lc1 if li % 2 == 0 else lc2): seq[lk] = st.text_input(lk.title(), value=seq.get(lk, ""), key=f"{prefix}_{lk}") st.markdown("---") if st.button("💾 Save Batch Changes"): data["batch_data"] = batch_list save_json(file_path, data) st.toast("Batch saved!", icon="🚀")