Update tab_batch.py
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29
tab_batch.py
29
tab_batch.py
@@ -1,6 +1,6 @@
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import streamlit as st
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import random
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from utils import DEFAULTS, save_json, load_json
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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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@@ -39,7 +39,6 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
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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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# -----------------------------------
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batch_list = data.get("batch_data", [])
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@@ -189,11 +188,27 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
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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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with st.expander("LoRA Settings"):
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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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for li, lk in enumerate(lora_keys):
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with (lc1 if li % 2 == 0 else lc2):
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seq[lk] = st.text_input(lk.title(), value=seq.get(lk, ""), key=f"{prefix}_{lk}")
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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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@@ -243,7 +258,6 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
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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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# Commit to Tree
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tree_data = data.get("history_tree", {})
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htree = HistoryTree(tree_data)
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@@ -255,7 +269,6 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
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data["history_tree"] = htree.to_dict()
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save_json(file_path, data)
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# CLEAR THE INDICATOR SINCE WE MOVED FORWARD
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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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