Merge timeline tabs into single polished tab with adaptive scaling

Combine stable and WIP timeline tabs into one with all features:
view switcher, restore/rename/delete, and data preview panel.
Add adaptive graph spacing based on node count, show full dates
and branch names on node labels, increase label truncation to 25
chars, and drop streamlit-agraph dependency.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

app.py

@@ -11,7 +11,6 @@ from utils import (
 from tab_single import render_single_editor
 from tab_batch import render_batch_processor
 from tab_timeline import render_timeline_tab
-from tab_timeline_wip import render_timeline_wip
 from tab_comfy import render_comfy_monitor
 from tab_raw import render_raw_editor
 
@@ -200,7 +199,6 @@ if selected_file_name:
         "📝 Single Editor",
         "🚀 Batch Processor",
         "🕒 Timeline",
-        "🧪 Interactive Timeline",
         "💻 Raw Editor"
     ]
     
@@ -227,9 +225,6 @@ if selected_file_name:
     elif current_tab == "🕒 Timeline":
         render_timeline_tab(data, file_path)
 
-    elif current_tab == "🧪 Interactive Timeline":
-        render_timeline_wip(data, file_path)
-        
     elif current_tab == "💻 Raw Editor":
         render_raw_editor(data, file_path)
 

history_tree.py

@@ -75,17 +75,27 @@ class HistoryTree:
         Generates Graphviz source.
         direction: "LR" (Horizontal) or "TB" (Vertical)
         """
+        node_count = len(self.nodes)
+        if node_count <= 5:
+            nodesep, ranksep = 0.5, 0.6
+        elif node_count <= 15:
+            nodesep, ranksep = 0.3, 0.4
+        else:
+            nodesep, ranksep = 0.15, 0.25
+
+        # Build reverse lookup: branch tip -> branch name(s)
+        tip_to_branches: dict[str, list[str]] = {}
+        for b_name, tip_id in self.branches.items():
+            if tip_id:
+                tip_to_branches.setdefault(tip_id, []).append(b_name)
+
         dot = [
             'digraph History {',
-            f'  rankdir={direction};',  # Dynamic Direction
+            f'  rankdir={direction};',
             '  bgcolor="white";',
             '  splines=ortho;',
-            
+            f'  nodesep={nodesep};',
-            # TIGHT SPACING
+            f'  ranksep={ranksep};',
-            '  nodesep=0.2;',
-            '  ranksep=0.3;',
-            
-            # GLOBAL STYLES
             '  node [shape=plain, fontname="Arial"];',
             '  edge [color="#888888", arrowsize=0.6, penwidth=1.0];'
         ]
@@ -96,7 +106,14 @@ class HistoryTree:
             nid = n["id"]
             full_note = n.get('note', 'Step')
 
-            display_note = (full_note[:15] + '..') if len(full_note) > 15 else full_note
+            display_note = (full_note[:25] + '..') if len(full_note) > 25 else full_note
+
+            ts = time.strftime('%b %d %H:%M', time.localtime(n['timestamp']))
+
+            # Branch label for tip nodes
+            branch_label = ""
+            if nid in tip_to_branches:
+                branch_label = ", ".join(tip_to_branches[nid])
 
             # COLORS
             bg_color = "#f9f9f9"
@@ -104,19 +121,25 @@ class HistoryTree:
             border_width = "1"
 
             if nid == self.head_id:
-                bg_color = "#fff6cd" # Yellow for Current
+                bg_color = "#fff6cd"
                 border_color = "#eebb00"
                 border_width = "2"
             elif nid in self.branches.values():
-                bg_color = "#e6ffe6" # Green for Tips
+                bg_color = "#e6ffe6"
                 border_color = "#66aa66"
 
             # HTML LABEL
+            rows = [
+                f'<TR><TD><B><FONT POINT-SIZE="10">{display_note}</FONT></B></TD></TR>',
+                f'<TR><TD><FONT POINT-SIZE="8" COLOR="#555555">{ts} • {nid[:4]}</FONT></TD></TR>',
+            ]
+            if branch_label:
+                rows.append(f'<TR><TD><FONT POINT-SIZE="8" COLOR="#4488cc"><I>{branch_label}</I></FONT></TD></TR>')
+
             label = (
                 f'<<TABLE BORDER="{border_width}" CELLBORDER="0" CELLSPACING="0" CELLPADDING="4" BGCOLOR="{bg_color}" COLOR="{border_color}">'
-                f'<TR><TD><B><FONT POINT-SIZE="10">{display_note}</FONT></B></TD></TR>'
+                + "".join(rows)
-                f'<TR><TD><FONT POINT-SIZE="8" COLOR="#555555">{nid[:4]}</FONT></TD></TR>'
+                + '</TABLE>>'
-                f'</TABLE>>'
             )
 
             safe_tooltip = full_note.replace('"', "'")

tab_timeline.py

@@ -1,11 +1,10 @@
 import streamlit as st
 import copy
-import json
-import graphviz
 import time
 from history_tree import HistoryTree
 from utils import save_json, KEY_BATCH_DATA, KEY_HISTORY_TREE
 
+
 def render_timeline_tab(data, file_path):
     tree_data = data.get(KEY_HISTORY_TREE, {})
     if not tree_data:
@@ -28,6 +27,10 @@ def render_timeline_tab(data, file_path):
         label_visibility="collapsed"
     )
 
+    # --- Build sorted node list (shared by all views) ---
+    all_nodes = list(htree.nodes.values())
+    all_nodes.sort(key=lambda x: x["timestamp"], reverse=True)
+
     # --- RENDER GRAPH VIEWS ---
     if view_mode in ["🌳 Horizontal", "🌲 Vertical"]:
         direction = "LR" if view_mode == "🌳 Horizontal" else "TB"
@@ -40,8 +43,6 @@ def render_timeline_tab(data, file_path):
     # --- RENDER LINEAR LOG VIEW ---
     elif view_mode == "📜 Linear Log":
         st.caption("A simple chronological list of all snapshots.")
-        all_nodes = list(htree.nodes.values())
-        all_nodes.sort(key=lambda x: x["timestamp"], reverse=True)
 
         for n in all_nodes:
             is_head = (n["id"] == htree.head_id)
@@ -51,41 +52,26 @@ def render_timeline_tab(data, file_path):
                     st.markdown("### 📍" if is_head else "### ⚫")
                 with c2:
                     note_txt = n.get('note', 'Step')
-                    ts = time.strftime('%H:%M:%S', time.localtime(n['timestamp']))
+                    ts = time.strftime('%b %d %H:%M', time.localtime(n['timestamp']))
                     if is_head:
                         st.markdown(f"**{note_txt}** (Current)")
                     else:
                         st.write(f"**{note_txt}**")
-                    st.caption(f"ID: {n['id'][:6]} • Time: {ts}")
+                    st.caption(f"ID: {n['id'][:6]} • {ts}")
                 with c3:
                     if not is_head:
                         if st.button("⏪", key=f"log_rst_{n['id']}", help="Restore this version"):
-                            # --- FIX: Cleanup 'batch_data' if restoring a Single File ---
+                            _restore_node(data, n, htree, file_path)
-                            if KEY_BATCH_DATA not in n["data"] and KEY_BATCH_DATA in data:
-                                del data[KEY_BATCH_DATA]
-                            # -------------------------------------------------------------
-                            
-                            data.update(n["data"])
-                            htree.head_id = n['id']
-                            data[KEY_HISTORY_TREE] = htree.to_dict()
-                            save_json(file_path, data)
-                            st.session_state.ui_reset_token += 1
-                            label = f"{n.get('note')} ({n['id'][:4]})"
-                            st.session_state.restored_indicator = label
-                            st.toast(f"Restored!", icon="🔄")
-                            st.rerun()
             st.divider()
 
     st.markdown("---")
 
-    # --- ACTIONS & SELECTION ---
+    # --- NODE SELECTOR ---
     col_sel, col_act = st.columns([3, 1])
 
-    all_nodes = list(htree.nodes.values())
-    all_nodes.sort(key=lambda x: x["timestamp"], reverse=True) 
-    
     def fmt_node(n):
-        return f"{n.get('note', 'Step')} ({n['id']})"
+        ts = time.strftime('%b %d %H:%M', time.localtime(n['timestamp']))
+        return f"{n.get('note', 'Step')} • {ts} ({n['id'][:6]})"
 
     with col_sel:
         current_idx = 0
@@ -101,58 +87,119 @@ def render_timeline_tab(data, file_path):
             index=current_idx
         )
 
-    if selected_node:
+    if not selected_node:
-        node_data = selected_node["data"]
+        return
 
-        # --- ACTIONS ---
+    node_data = selected_node["data"]
-        with col_act:
-            st.write(""); st.write("")
-            if st.button("⏪ Restore Version", type="primary", use_container_width=True):
-                # --- FIX: Cleanup 'batch_data' if restoring a Single File ---
-                if KEY_BATCH_DATA not in node_data and KEY_BATCH_DATA in data:
-                    del data[KEY_BATCH_DATA]
-                # -------------------------------------------------------------
 
-                data.update(node_data)
+    # --- RESTORE ---
-                htree.head_id = selected_node['id']
+    with col_act:
+        st.write(""); st.write("")
+        if st.button("⏪ Restore Version", type="primary", use_container_width=True):
+            _restore_node(data, selected_node, htree, file_path)
+
+    # --- RENAME ---
+    rn_col1, rn_col2 = st.columns([3, 1])
+    new_label = rn_col1.text_input("Rename Label", value=selected_node.get("note", ""))
+    if rn_col2.button("Update Label"):
+        selected_node["note"] = new_label
+        data[KEY_HISTORY_TREE] = htree.to_dict()
+        save_json(file_path, data)
+        st.rerun()
+
+    # --- DANGER ZONE ---
+    st.markdown("---")
+    with st.expander("⚠️ Danger Zone (Delete)"):
+        st.warning("Deleting a node cannot be undone.")
+        if st.button("🗑️ Delete This Node", type="primary"):
+            if selected_node['id'] in htree.nodes:
+                if "history_tree_backup" not in data:
+                    data["history_tree_backup"] = []
+                data["history_tree_backup"].append(copy.deepcopy(htree.to_dict()))
+                del htree.nodes[selected_node['id']]
+                for b, tip in list(htree.branches.items()):
+                    if tip == selected_node['id']:
+                        del htree.branches[b]
+                if htree.head_id == selected_node['id']:
+                    if htree.nodes:
+                        fallback = sorted(htree.nodes.values(), key=lambda x: x["timestamp"])[-1]
+                        htree.head_id = fallback["id"]
+                    else:
+                        htree.head_id = None
                 data[KEY_HISTORY_TREE] = htree.to_dict()
                 save_json(file_path, data)
-                st.session_state.ui_reset_token += 1
+                st.toast("Node Deleted", icon="🗑️")
-                label = f"{selected_node.get('note')} ({selected_node['id'][:4]})"
-                st.session_state.restored_indicator = label
-                st.toast(f"Restored!", icon="🔄")
                 st.rerun()
 
-        # --- RENAME ---
+    # --- DATA PREVIEW ---
-        rn_col1, rn_col2 = st.columns([3, 1])
+    st.markdown("---")
-        new_label = rn_col1.text_input("Rename Label", value=selected_node.get("note", ""))
+    with st.expander("🔍 Data Preview", expanded=False):
-        if rn_col2.button("Update Label"):
+        batch_list = node_data.get(KEY_BATCH_DATA, [])
-            selected_node["note"] = new_label
-            data[KEY_HISTORY_TREE] = htree.to_dict()
-            save_json(file_path, data)
-            st.rerun()
 
-        # --- DANGER ZONE ---
+        if batch_list and isinstance(batch_list, list) and len(batch_list) > 0:
-        st.markdown("---")
+            st.info(f"📚 This snapshot contains {len(batch_list)} sequences.")
-        with st.expander("⚠️ Danger Zone (Delete)"):
+            for i, seq_data in enumerate(batch_list):
-            st.warning("Deleting a node cannot be undone.")
+                seq_num = seq_data.get("sequence_number", i + 1)
-            if st.button("🗑️ Delete This Node", type="primary"):
+                with st.expander(f"🎬 Sequence #{seq_num}", expanded=(i == 0)):
-                if selected_node['id'] in htree.nodes:
+                    prefix = f"p_{selected_node['id']}_s{i}"
-                    # Backup current tree state before destructive operation
+                    _render_preview_fields(seq_data, prefix)
-                    if "history_tree_backup" not in data:
+        else:
-                        data["history_tree_backup"] = []
+            prefix = f"p_{selected_node['id']}_single"
-                    data["history_tree_backup"].append(copy.deepcopy(htree.to_dict()))
+            _render_preview_fields(node_data, prefix)
-                    del htree.nodes[selected_node['id']]
+
-                    for b, tip in list(htree.branches.items()):
+
-                        if tip == selected_node['id']:
+def _restore_node(data, node, htree, file_path):
-                            del htree.branches[b] 
+    """Restore a history node as the current version."""
-                    if htree.head_id == selected_node['id']:
+    node_data = node["data"]
-                        if htree.nodes:
+    if KEY_BATCH_DATA not in node_data and KEY_BATCH_DATA in data:
-                            fallback = sorted(htree.nodes.values(), key=lambda x: x["timestamp"])[-1]
+        del data[KEY_BATCH_DATA]
-                            htree.head_id = fallback["id"]
+    data.update(node_data)
-                        else:
+    htree.head_id = node['id']
-                            htree.head_id = None
+    data[KEY_HISTORY_TREE] = htree.to_dict()
-                    data[KEY_HISTORY_TREE] = htree.to_dict()
+    save_json(file_path, data)
-                    save_json(file_path, data)
+    st.session_state.ui_reset_token += 1
-                    st.toast("Node Deleted", icon="🗑️")
+    label = f"{node.get('note')} ({node['id'][:4]})"
-                    st.rerun()
+    st.session_state.restored_indicator = label
+    st.toast("Restored!", icon="🔄")
+    st.rerun()
+
+
+def _render_preview_fields(item_data, prefix):
+    """Render a read-only preview of prompts, settings, and LoRAs."""
+    # Prompts
+    p_col1, p_col2 = st.columns(2)
+    with p_col1:
+        st.text_area("General Positive", value=item_data.get("general_prompt", ""), height=80, disabled=True, key=f"{prefix}_gp")
+        val_sp = item_data.get("current_prompt", "") or item_data.get("prompt", "")
+        st.text_area("Specific Positive", value=val_sp, height=80, disabled=True, key=f"{prefix}_sp")
+    with p_col2:
+        st.text_area("General Negative", value=item_data.get("general_negative", ""), height=80, disabled=True, key=f"{prefix}_gn")
+        st.text_area("Specific Negative", value=item_data.get("negative", ""), height=80, disabled=True, key=f"{prefix}_sn")
+
+    # Settings
+    s_col1, s_col2, s_col3 = st.columns(3)
+    s_col1.text_input("Camera", value=str(item_data.get("camera", "static")), disabled=True, key=f"{prefix}_cam")
+    s_col2.text_input("FLF", value=str(item_data.get("flf", "0.0")), disabled=True, key=f"{prefix}_flf")
+    s_col3.text_input("Seed", value=str(item_data.get("seed", "-1")), disabled=True, key=f"{prefix}_seed")
+
+    # LoRAs
+    with st.expander("💊 LoRA Configuration", expanded=False):
+        l1, l2, l3 = st.columns(3)
+        with l1:
+            st.text_input("L1 Name", value=item_data.get("lora 1 high", ""), disabled=True, key=f"{prefix}_l1h")
+            st.text_input("L1 Str", value=str(item_data.get("lora 1 low", "")), disabled=True, key=f"{prefix}_l1l")
+        with l2:
+            st.text_input("L2 Name", value=item_data.get("lora 2 high", ""), disabled=True, key=f"{prefix}_l2h")
+            st.text_input("L2 Str", value=str(item_data.get("lora 2 low", "")), disabled=True, key=f"{prefix}_l2l")
+        with l3:
+            st.text_input("L3 Name", value=item_data.get("lora 3 high", ""), disabled=True, key=f"{prefix}_l3h")
+            st.text_input("L3 Str", value=str(item_data.get("lora 3 low", "")), disabled=True, key=f"{prefix}_l3l")
+
+    # VACE
+    vace_keys = ["frame_to_skip", "vace schedule", "video file path"]
+    if any(k in item_data for k in vace_keys):
+        with st.expander("🎞️ VACE / I2V Settings", expanded=False):
+            v1, v2, v3 = st.columns(3)
+            v1.text_input("Skip Frames", value=str(item_data.get("frame_to_skip", "")), disabled=True, key=f"{prefix}_fts")
+            v2.text_input("Schedule", value=str(item_data.get("vace schedule", "")), disabled=True, key=f"{prefix}_vsc")
+            v3.text_input("Video Path", value=str(item_data.get("video file path", "")), disabled=True, key=f"{prefix}_vid")

tab_timeline_wip.py

@@ -1,191 +0,0 @@
-import streamlit as st
-import json
-from history_tree import HistoryTree
-from utils import save_json, KEY_BATCH_DATA, KEY_HISTORY_TREE
-
-try:
-    from streamlit_agraph import agraph, Node, Edge, Config
-    _HAS_AGRAPH = True
-except ImportError:
-    _HAS_AGRAPH = False
-
-def render_timeline_wip(data, file_path):
-    if not _HAS_AGRAPH:
-        st.error("The `streamlit-agraph` package is required for this tab. Install it with: `pip install streamlit-agraph`")
-        return
-    tree_data = data.get(KEY_HISTORY_TREE, {})
-    if not tree_data:
-        st.info("No history timeline exists.")
-        return
-
-    htree = HistoryTree(tree_data)
-
-    # --- 1. BUILD GRAPH ---
-    nodes = []
-    edges = []
-    
-    sorted_nodes = sorted(htree.nodes.values(), key=lambda x: x["timestamp"])
-    
-    for n in sorted_nodes:
-        nid = n["id"]
-        note = n.get('note', 'Step')
-        short_note = (note[:15] + '..') if len(note) > 15 else note
-        
-        color = "#ffffff"     
-        border = "#666666"    
-        
-        if nid == htree.head_id:
-            color = "#fff6cd" 
-            border = "#eebb00"
-        
-        if nid in htree.branches.values():
-            if color == "#ffffff": 
-                color = "#e6ffe6"
-                border = "#44aa44"
-
-        nodes.append(Node(
-            id=nid,
-            label=f"{short_note}\n({nid[:4]})",
-            size=25,
-            shape="box",
-            color=color,
-            borderWidth=1,
-            borderColor=border,
-            font={'color': 'black', 'face': 'Arial', 'size': 14}
-        ))
-        
-        if n["parent"] and n["parent"] in htree.nodes:
-            edges.append(Edge(
-                source=n["parent"],
-                target=nid,
-                color="#aaaaaa",
-                type="STRAIGHT"
-            ))
-
-    # --- UPDATED CONFIGURATION ---
-    config = Config(
-        width="100%",
-        # Increased height from 400px to 600px for better visibility
-        height="600px", 
-        directed=True, 
-        physics=False, 
-        hierarchical=True, 
-        layout={
-            "hierarchical": {
-                "enabled": True,
-                # Increased separation to widen the tree structure
-                "levelSeparation": 200,  # Was 150
-                "nodeSpacing": 150,      # Was 100
-                "treeSpacing": 150,      # Was 100
-                "direction": "LR", 
-                "sortMethod": "directed"
-            }
-        }
-    )
-
-    st.subheader("✨ Interactive Timeline")
-    st.caption("Click a node to view its settings below.")
-    
-    # --- FIX: REMOVED 'key' ARGUMENT ---
-    selected_id = agraph(nodes=nodes, edges=edges, config=config)
-
-    st.markdown("---")
-
-    # --- 2. DETERMINE TARGET ---
-    target_node_id = selected_id if selected_id else htree.head_id
-
-    if target_node_id and target_node_id in htree.nodes:
-        selected_node = htree.nodes[target_node_id]
-        node_data = selected_node["data"]
-
-        # Header
-        c_h1, c_h2 = st.columns([3, 1])
-        c_h1.markdown(f"### 📄 Previewing: {selected_node.get('note', 'Step')}")
-        c_h1.caption(f"ID: {target_node_id}")
-
-        # Restore Button
-        with c_h2:
-            st.write(""); st.write("")
-            if st.button("⏪ Restore This Version", type="primary", use_container_width=True, key=f"rst_{target_node_id}"):
-                # --- FIX: Cleanup 'batch_data' if restoring a Single File ---
-                if KEY_BATCH_DATA not in node_data and KEY_BATCH_DATA in data:
-                    del data[KEY_BATCH_DATA]
-                # -------------------------------------------------------------
-
-                data.update(node_data)
-                htree.head_id = target_node_id
-                
-                data[KEY_HISTORY_TREE] = htree.to_dict()
-                save_json(file_path, data)
-                
-                st.session_state.ui_reset_token += 1
-                label = f"{selected_node.get('note')} ({target_node_id[:4]})"
-                st.session_state.restored_indicator = label
-                
-                st.toast(f"Restored {target_node_id}!", icon="🔄")
-                st.rerun()
-
-        # --- 3. PREVIEW LOGIC (BATCH VS SINGLE) ---
-        
-        # Helper to render one set of inputs
-        def render_preview_fields(item_data, prefix):
-            # A. Prompts
-            p_col1, p_col2 = st.columns(2)
-            with p_col1:
-                val_gp = item_data.get("general_prompt", "")
-                st.text_area("General Positive", value=val_gp, height=80, disabled=True, key=f"{prefix}_gp")
-                
-                val_sp = item_data.get("current_prompt", "") or item_data.get("prompt", "")
-                st.text_area("Specific Positive", value=val_sp, height=80, disabled=True, key=f"{prefix}_sp")
-            with p_col2:
-                val_gn = item_data.get("general_negative", "")
-                st.text_area("General Negative", value=val_gn, height=80, disabled=True, key=f"{prefix}_gn")
-                
-                val_sn = item_data.get("negative", "")
-                st.text_area("Specific Negative", value=val_sn, height=80, disabled=True, key=f"{prefix}_sn")
-
-            # B. Settings
-            s_col1, s_col2, s_col3 = st.columns(3)
-            s_col1.text_input("Camera", value=str(item_data.get("camera", "static")), disabled=True, key=f"{prefix}_cam")
-            s_col2.text_input("FLF", value=str(item_data.get("flf", "0.0")), disabled=True, key=f"{prefix}_flf")
-            s_col3.text_input("Seed", value=str(item_data.get("seed", "-1")), disabled=True, key=f"{prefix}_seed")
-
-            # C. LoRAs
-            with st.expander("💊 LoRA Configuration", expanded=False):
-                l1, l2, l3 = st.columns(3)
-                with l1:
-                    st.text_input("L1 Name", value=item_data.get("lora 1 high", ""), disabled=True, key=f"{prefix}_l1h")
-                    st.text_input("L1 Str", value=str(item_data.get("lora 1 low", "")), disabled=True, key=f"{prefix}_l1l")
-                with l2:
-                    st.text_input("L2 Name", value=item_data.get("lora 2 high", ""), disabled=True, key=f"{prefix}_l2h")
-                    st.text_input("L2 Str", value=str(item_data.get("lora 2 low", "")), disabled=True, key=f"{prefix}_l2l")
-                with l3:
-                    st.text_input("L3 Name", value=item_data.get("lora 3 high", ""), disabled=True, key=f"{prefix}_l3h")
-                    st.text_input("L3 Str", value=str(item_data.get("lora 3 low", "")), disabled=True, key=f"{prefix}_l3l")
-            
-            # D. VACE
-            vace_keys = ["frame_to_skip", "vace schedule", "video file path"]
-            has_vace = any(k in item_data for k in vace_keys)
-            if has_vace:
-                with st.expander("🎞️ VACE / I2V Settings", expanded=False):
-                    v1, v2, v3 = st.columns(3)
-                    v1.text_input("Skip Frames", value=str(item_data.get("frame_to_skip", "")), disabled=True, key=f"{prefix}_fts")
-                    v2.text_input("Schedule", value=str(item_data.get("vace schedule", "")), disabled=True, key=f"{prefix}_vsc")
-                    v3.text_input("Video Path", value=str(item_data.get("video file path", "")), disabled=True, key=f"{prefix}_vid")
-
-        # --- DETECT BATCH VS SINGLE ---
-        batch_list = node_data.get(KEY_BATCH_DATA, [])
-        
-        if batch_list and isinstance(batch_list, list) and len(batch_list) > 0:
-            st.info(f"📚 This snapshot contains {len(batch_list)} sequences.")
-            
-            for i, seq_data in enumerate(batch_list):
-                seq_num = seq_data.get("sequence_number", i+1)
-                with st.expander(f"🎬 Sequence #{seq_num}", expanded=(i==0)):
-                    # Unique prefix for every sequence in every node
-                    prefix = f"p_{target_node_id}_s{i}"
-                    render_preview_fields(seq_data, prefix)
-        else:
-            # Single File Preview
-            prefix = f"p_{target_node_id}_single"
-            render_preview_fields(node_data, prefix)