diff --git a/tab_batch.py b/tab_batch.py
index 5eb2f0e..86221b1 100644
--- a/tab_batch.py
+++ b/tab_batch.py
@@ -1,6 +1,6 @@
 import streamlit as st
 import random
-from utils import DEFAULTS, save_json, load_json, render_smart_input
+from utils import DEFAULTS, save_json, load_json
 from history_tree import HistoryTree 
 
 def create_batch_callback(original_filename, current_data, current_dir):
@@ -187,38 +187,18 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
                     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")
 
-            # --- LoRA Settings (SMART INPUTS + SAFE FLOAT FIX) ---
+            # --- LoRA Settings (Reverted to plain text) ---
             with st.expander("💊 LoRA Settings"):
-                meta = st.session_state.get("comfy_meta", {})
-                lora_list = meta.get("loras", [])
-                
-                lc1, lc2 = st.columns(2)
-                
-                # HELPER: Safe conversion
-                def get_safe_float(val, default=1.0):
-                    try:
-                        return float(val)
-                    except (ValueError, TypeError):
-                        # If it's a string like "<lora:name>", return default 1.0
-                        return default
-
+                lc1, lc2, lc3 = st.columns(3)
                 with lc1:
-                    st.caption("LoRA 1")
-                    seq["lora 1 high"] = render_smart_input("Model", f"{prefix}_l1h", seq.get("lora 1 high", ""), lora_list)
-                    val = get_safe_float(seq.get("lora 1 low", 1.0))
-                    seq["lora 1 low"] = str(st.slider("Strength", 0.0, 2.0, val, 0.05, key=f"{prefix}_l1l"))
-
+                    seq["lora 1 high"] = st.text_input("LoRA 1 Name", value=seq.get("lora 1 high", ""), key=f"{prefix}_l1h")
+                    seq["lora 1 low"] = st.text_input("LoRA 1 Strength", value=str(seq.get("lora 1 low", "")), key=f"{prefix}_l1l")
                 with lc2:
-                    st.caption("LoRA 2")
-                    seq["lora 2 high"] = render_smart_input("Model", f"{prefix}_l2h", seq.get("lora 2 high", ""), lora_list)
-                    val = get_safe_float(seq.get("lora 2 low", 1.0))
-                    seq["lora 2 low"] = str(st.slider("Strength", 0.0, 2.0, val, 0.05, key=f"{prefix}_l2l"))
-                
-                with lc1:
-                    st.caption("LoRA 3")
-                    seq["lora 3 high"] = render_smart_input("Model", f"{prefix}_l3h", seq.get("lora 3 high", ""), lora_list)
-                    val = get_safe_float(seq.get("lora 3 low", 1.0))
-                    seq["lora 3 low"] = str(st.slider("Strength", 0.0, 2.0, val, 0.05, key=f"{prefix}_l3l"))
+                    seq["lora 2 high"] = st.text_input("LoRA 2 Name", value=seq.get("lora 2 high", ""), key=f"{prefix}_l2h")
+                    seq["lora 2 low"] = st.text_input("LoRA 2 Strength", value=str(seq.get("lora 2 low", "")), key=f"{prefix}_l2l")
+                with lc3:
+                    seq["lora 3 high"] = st.text_input("LoRA 3 Name", value=seq.get("lora 3 high", ""), key=f"{prefix}_l3h")
+                    seq["lora 3 low"] = st.text_input("LoRA 3 Strength", value=str(seq.get("lora 3 low", "")), key=f"{prefix}_l3l")
 
             # --- CUSTOM PARAMETERS ---
             st.markdown("---")
@@ -283,3 +263,4 @@ def render_batch_processor(data, file_path, json_files, current_dir, selected_fi
                 del st.session_state.restored_indicator
             
             st.toast("Batch Saved & Snapshot Created!", icon="🚀")
+            st.rerun()