Files
Comfyui-JSON-Manager/tab_timeline.py
Ethanfel 87ed2f1dfb 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>
2026-02-02 13:10:23 +01:00

206 lines
8.7 KiB
Python

import streamlit as st
import copy
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:
st.info("No history timeline exists. Make some changes in the Editor first!")
return
htree = HistoryTree(tree_data)
if 'restored_indicator' in st.session_state and st.session_state.restored_indicator:
st.info(f"📍 Editing Restored Version: **{st.session_state.restored_indicator}**")
# --- VIEW SWITCHER ---
c_title, c_view = st.columns([2, 1])
c_title.subheader("🕰️ Version History")
view_mode = c_view.radio(
"View Mode",
["🌳 Horizontal", "🌲 Vertical", "📜 Linear Log"],
horizontal=True,
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"
try:
graph_dot = htree.generate_graph(direction=direction)
st.graphviz_chart(graph_dot, use_container_width=True)
except Exception as e:
st.error(f"Graph Error: {e}")
# --- RENDER LINEAR LOG VIEW ---
elif view_mode == "📜 Linear Log":
st.caption("A simple chronological list of all snapshots.")
for n in all_nodes:
is_head = (n["id"] == htree.head_id)
with st.container():
c1, c2, c3 = st.columns([0.5, 4, 1])
with c1:
st.markdown("### 📍" if is_head else "### ⚫")
with c2:
note_txt = n.get('note', 'Step')
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]}{ts}")
with c3:
if not is_head:
if st.button("", key=f"log_rst_{n['id']}", help="Restore this version"):
_restore_node(data, n, htree, file_path)
st.divider()
st.markdown("---")
# --- NODE SELECTOR ---
col_sel, col_act = st.columns([3, 1])
def fmt_node(n):
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
for i, n in enumerate(all_nodes):
if n["id"] == htree.head_id:
current_idx = i
break
selected_node = st.selectbox(
"Select Version to Manage:",
all_nodes,
format_func=fmt_node,
index=current_idx
)
if not selected_node:
return
node_data = selected_node["data"]
# --- RESTORE ---
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.toast("Node Deleted", icon="🗑️")
st.rerun()
# --- DATA PREVIEW ---
st.markdown("---")
with st.expander("🔍 Data Preview", expanded=False):
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)):
prefix = f"p_{selected_node['id']}_s{i}"
_render_preview_fields(seq_data, prefix)
else:
prefix = f"p_{selected_node['id']}_single"
_render_preview_fields(node_data, prefix)
def _restore_node(data, node, htree, file_path):
"""Restore a history node as the current version."""
node_data = node["data"]
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 = node['id']
data[KEY_HISTORY_TREE] = htree.to_dict()
save_json(file_path, data)
st.session_state.ui_reset_token += 1
label = f"{node.get('note')} ({node['id'][:4]})"
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")