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>
This commit is contained in:
213
tab_timeline.py
213
tab_timeline.py
@@ -1,11 +1,10 @@
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import streamlit as st
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import copy
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import json
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import graphviz
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import time
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from history_tree import HistoryTree
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from utils import save_json, KEY_BATCH_DATA, KEY_HISTORY_TREE
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def render_timeline_tab(data, file_path):
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tree_data = data.get(KEY_HISTORY_TREE, {})
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if not tree_data:
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@@ -20,14 +19,18 @@ def render_timeline_tab(data, file_path):
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# --- VIEW SWITCHER ---
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c_title, c_view = st.columns([2, 1])
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c_title.subheader("🕰️ Version History")
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view_mode = c_view.radio(
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"View Mode",
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["🌳 Horizontal", "🌲 Vertical", "📜 Linear Log"],
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"View Mode",
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["🌳 Horizontal", "🌲 Vertical", "📜 Linear Log"],
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horizontal=True,
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label_visibility="collapsed"
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)
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# --- Build sorted node list (shared by all views) ---
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all_nodes = list(htree.nodes.values())
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all_nodes.sort(key=lambda x: x["timestamp"], reverse=True)
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# --- RENDER GRAPH VIEWS ---
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if view_mode in ["🌳 Horizontal", "🌲 Vertical"]:
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direction = "LR" if view_mode == "🌳 Horizontal" else "TB"
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@@ -36,13 +39,11 @@ def render_timeline_tab(data, file_path):
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st.graphviz_chart(graph_dot, use_container_width=True)
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except Exception as e:
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st.error(f"Graph Error: {e}")
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# --- RENDER LINEAR LOG VIEW ---
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elif view_mode == "📜 Linear Log":
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st.caption("A simple chronological list of all snapshots.")
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all_nodes = list(htree.nodes.values())
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all_nodes.sort(key=lambda x: x["timestamp"], reverse=True)
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for n in all_nodes:
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is_head = (n["id"] == htree.head_id)
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with st.container():
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@@ -51,41 +52,26 @@ def render_timeline_tab(data, file_path):
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st.markdown("### 📍" if is_head else "### ⚫")
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with c2:
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note_txt = n.get('note', 'Step')
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ts = time.strftime('%H:%M:%S', time.localtime(n['timestamp']))
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ts = time.strftime('%b %d %H:%M', time.localtime(n['timestamp']))
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if is_head:
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st.markdown(f"**{note_txt}** (Current)")
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else:
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st.write(f"**{note_txt}**")
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st.caption(f"ID: {n['id'][:6]} • Time: {ts}")
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st.caption(f"ID: {n['id'][:6]} • {ts}")
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with c3:
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if not is_head:
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if st.button("⏪", key=f"log_rst_{n['id']}", help="Restore this version"):
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# --- FIX: Cleanup 'batch_data' if restoring a Single File ---
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if KEY_BATCH_DATA not in n["data"] and KEY_BATCH_DATA in data:
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del data[KEY_BATCH_DATA]
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# -------------------------------------------------------------
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data.update(n["data"])
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htree.head_id = n['id']
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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label = f"{n.get('note')} ({n['id'][:4]})"
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st.session_state.restored_indicator = label
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st.toast(f"Restored!", icon="🔄")
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st.rerun()
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_restore_node(data, n, htree, file_path)
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st.divider()
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st.markdown("---")
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# --- ACTIONS & SELECTION ---
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# --- NODE SELECTOR ---
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col_sel, col_act = st.columns([3, 1])
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all_nodes = list(htree.nodes.values())
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all_nodes.sort(key=lambda x: x["timestamp"], reverse=True)
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def fmt_node(n):
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return f"{n.get('note', 'Step')} ({n['id']})"
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ts = time.strftime('%b %d %H:%M', time.localtime(n['timestamp']))
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return f"{n.get('note', 'Step')} • {ts} ({n['id'][:6]})"
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with col_sel:
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current_idx = 0
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@@ -93,66 +79,127 @@ def render_timeline_tab(data, file_path):
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if n["id"] == htree.head_id:
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current_idx = i
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break
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selected_node = st.selectbox(
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"Select Version to Manage:",
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all_nodes,
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"Select Version to Manage:",
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all_nodes,
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format_func=fmt_node,
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index=current_idx
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)
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if selected_node:
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node_data = selected_node["data"]
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# --- ACTIONS ---
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with col_act:
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st.write(""); st.write("")
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if st.button("⏪ Restore Version", type="primary", use_container_width=True):
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# --- FIX: Cleanup 'batch_data' if restoring a Single File ---
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if KEY_BATCH_DATA not in node_data and KEY_BATCH_DATA in data:
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del data[KEY_BATCH_DATA]
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# -------------------------------------------------------------
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if not selected_node:
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return
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data.update(node_data)
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htree.head_id = selected_node['id']
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node_data = selected_node["data"]
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# --- RESTORE ---
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with col_act:
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st.write(""); st.write("")
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if st.button("⏪ Restore Version", type="primary", use_container_width=True):
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_restore_node(data, selected_node, htree, file_path)
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# --- RENAME ---
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rn_col1, rn_col2 = st.columns([3, 1])
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new_label = rn_col1.text_input("Rename Label", value=selected_node.get("note", ""))
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if rn_col2.button("Update Label"):
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selected_node["note"] = new_label
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.rerun()
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# --- DANGER ZONE ---
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st.markdown("---")
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with st.expander("⚠️ Danger Zone (Delete)"):
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st.warning("Deleting a node cannot be undone.")
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if st.button("🗑️ Delete This Node", type="primary"):
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if selected_node['id'] in htree.nodes:
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if "history_tree_backup" not in data:
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data["history_tree_backup"] = []
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data["history_tree_backup"].append(copy.deepcopy(htree.to_dict()))
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del htree.nodes[selected_node['id']]
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for b, tip in list(htree.branches.items()):
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if tip == selected_node['id']:
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del htree.branches[b]
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if htree.head_id == selected_node['id']:
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if htree.nodes:
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fallback = sorted(htree.nodes.values(), key=lambda x: x["timestamp"])[-1]
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htree.head_id = fallback["id"]
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else:
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htree.head_id = None
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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label = f"{selected_node.get('note')} ({selected_node['id'][:4]})"
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st.session_state.restored_indicator = label
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st.toast(f"Restored!", icon="🔄")
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st.toast("Node Deleted", icon="🗑️")
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st.rerun()
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# --- RENAME ---
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rn_col1, rn_col2 = st.columns([3, 1])
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new_label = rn_col1.text_input("Rename Label", value=selected_node.get("note", ""))
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if rn_col2.button("Update Label"):
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selected_node["note"] = new_label
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.rerun()
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# --- DATA PREVIEW ---
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st.markdown("---")
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with st.expander("🔍 Data Preview", expanded=False):
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batch_list = node_data.get(KEY_BATCH_DATA, [])
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# --- DANGER ZONE ---
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st.markdown("---")
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with st.expander("⚠️ Danger Zone (Delete)"):
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st.warning("Deleting a node cannot be undone.")
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if st.button("🗑️ Delete This Node", type="primary"):
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if selected_node['id'] in htree.nodes:
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# Backup current tree state before destructive operation
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if "history_tree_backup" not in data:
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data["history_tree_backup"] = []
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data["history_tree_backup"].append(copy.deepcopy(htree.to_dict()))
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del htree.nodes[selected_node['id']]
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for b, tip in list(htree.branches.items()):
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if tip == selected_node['id']:
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del htree.branches[b]
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if htree.head_id == selected_node['id']:
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if htree.nodes:
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fallback = sorted(htree.nodes.values(), key=lambda x: x["timestamp"])[-1]
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htree.head_id = fallback["id"]
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else:
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htree.head_id = None
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.toast("Node Deleted", icon="🗑️")
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st.rerun()
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if batch_list and isinstance(batch_list, list) and len(batch_list) > 0:
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st.info(f"📚 This snapshot contains {len(batch_list)} sequences.")
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for i, seq_data in enumerate(batch_list):
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seq_num = seq_data.get("sequence_number", i + 1)
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with st.expander(f"🎬 Sequence #{seq_num}", expanded=(i == 0)):
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prefix = f"p_{selected_node['id']}_s{i}"
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_render_preview_fields(seq_data, prefix)
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else:
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prefix = f"p_{selected_node['id']}_single"
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_render_preview_fields(node_data, prefix)
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def _restore_node(data, node, htree, file_path):
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"""Restore a history node as the current version."""
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node_data = node["data"]
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if KEY_BATCH_DATA not in node_data and KEY_BATCH_DATA in data:
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del data[KEY_BATCH_DATA]
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data.update(node_data)
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htree.head_id = node['id']
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data[KEY_HISTORY_TREE] = htree.to_dict()
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save_json(file_path, data)
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st.session_state.ui_reset_token += 1
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label = f"{node.get('note')} ({node['id'][:4]})"
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st.session_state.restored_indicator = label
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st.toast("Restored!", icon="🔄")
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st.rerun()
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def _render_preview_fields(item_data, prefix):
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"""Render a read-only preview of prompts, settings, and LoRAs."""
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# Prompts
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p_col1, p_col2 = st.columns(2)
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with p_col1:
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st.text_area("General Positive", value=item_data.get("general_prompt", ""), height=80, disabled=True, key=f"{prefix}_gp")
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val_sp = item_data.get("current_prompt", "") or item_data.get("prompt", "")
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st.text_area("Specific Positive", value=val_sp, height=80, disabled=True, key=f"{prefix}_sp")
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with p_col2:
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st.text_area("General Negative", value=item_data.get("general_negative", ""), height=80, disabled=True, key=f"{prefix}_gn")
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st.text_area("Specific Negative", value=item_data.get("negative", ""), height=80, disabled=True, key=f"{prefix}_sn")
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# Settings
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s_col1, s_col2, s_col3 = st.columns(3)
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s_col1.text_input("Camera", value=str(item_data.get("camera", "static")), disabled=True, key=f"{prefix}_cam")
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s_col2.text_input("FLF", value=str(item_data.get("flf", "0.0")), disabled=True, key=f"{prefix}_flf")
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s_col3.text_input("Seed", value=str(item_data.get("seed", "-1")), disabled=True, key=f"{prefix}_seed")
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# LoRAs
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with st.expander("💊 LoRA Configuration", expanded=False):
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l1, l2, l3 = st.columns(3)
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with l1:
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st.text_input("L1 Name", value=item_data.get("lora 1 high", ""), disabled=True, key=f"{prefix}_l1h")
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st.text_input("L1 Str", value=str(item_data.get("lora 1 low", "")), disabled=True, key=f"{prefix}_l1l")
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with l2:
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st.text_input("L2 Name", value=item_data.get("lora 2 high", ""), disabled=True, key=f"{prefix}_l2h")
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st.text_input("L2 Str", value=str(item_data.get("lora 2 low", "")), disabled=True, key=f"{prefix}_l2l")
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with l3:
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st.text_input("L3 Name", value=item_data.get("lora 3 high", ""), disabled=True, key=f"{prefix}_l3h")
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st.text_input("L3 Str", value=str(item_data.get("lora 3 low", "")), disabled=True, key=f"{prefix}_l3l")
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# VACE
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vace_keys = ["frame_to_skip", "vace schedule", "video file path"]
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if any(k in item_data for k in vace_keys):
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with st.expander("🎞️ VACE / I2V Settings", expanded=False):
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v1, v2, v3 = st.columns(3)
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v1.text_input("Skip Frames", value=str(item_data.get("frame_to_skip", "")), disabled=True, key=f"{prefix}_fts")
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v2.text_input("Schedule", value=str(item_data.get("vace schedule", "")), disabled=True, key=f"{prefix}_vsc")
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v3.text_input("Video Path", value=str(item_data.get("video file path", "")), disabled=True, key=f"{prefix}_vid")
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