Add ETA calculation to web dashboard and CLI monitor

Parses batch timestamps from setup.log, averages last 20 batches,
calculates remaining time. Shows ETA, docs remaining, and avg
seconds per batch in both web summary cards and CLI header.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

monitor.py

@@ -171,19 +171,63 @@ def collect_status():
 
     # Read last N lines from setup.log
     log_lines = []
+    batch_times = []
     if LOG_PATH.exists():
         try:
             with open(LOG_PATH, "r", encoding="utf-8") as f:
                 all_lines = f.readlines()
                 log_lines = [l.rstrip() for l in all_lines[-15:]]
+
+            # Parse batch timestamps to calculate ETA
+            # Format: "01:32:34 [INFO]   ✓ arbiter batch 1/80: 5 embedded (5/396)"
+            import re
+            for line in all_lines:
+                m = re.match(r'^(\d{2}:\d{2}:\d{2}) \[INFO\]\s+✓\s+\w+ batch \d+/\d+:', line)
+                if m:
+                    batch_times.append(m.group(1))
         except Exception:
             pass
 
+    # Calculate ETA from batch speed
+    total_expected = sum(p["expected"] for p in personas)
+    total_assigned = sum(len(v) for v in ws_docs.values())
+    remaining = max(0, total_expected - total_assigned)
+
+    eta_seconds = None
+    avg_batch_seconds = None
+    if len(batch_times) >= 2:
+        try:
+            from datetime import datetime
+            times = []
+            for t in batch_times[-20:]:  # last 20 batches for avg
+                dt = datetime.strptime(t, "%H:%M:%S")
+                times.append(dt.hour * 3600 + dt.minute * 60 + dt.second)
+            if len(times) >= 2:
+                deltas = [times[i+1] - times[i] for i in range(len(times)-1)]
+                # Handle midnight wrap
+                deltas = [d if d > 0 else d + 86400 for d in deltas]
+                avg_batch_seconds = sum(deltas) / len(deltas)
+                remaining_batches = remaining / 5  # batch size = 5
+                eta_seconds = int(remaining_batches * avg_batch_seconds)
+        except Exception:
+            pass
+
+    # Format ETA
+    eta_str = None
+    if eta_seconds is not None:
+        hours = eta_seconds // 3600
+        minutes = (eta_seconds % 3600) // 60
+        if hours > 0:
+            eta_str = f"{hours}h {minutes}m"
+        else:
+            eta_str = f"{minutes}m"
+
     return {
         "personas": personas,
         "clusters": clusters,
         "total_uploaded": len(uploaded),
-        "total_assigned": sum(len(v) for v in ws_docs.values()),
+        "total_assigned": total_assigned,
+        "total_expected": total_expected,
         "total_personas": len(workspaces),
         "personas_with_vectors": sum(1 for p in personas if p["has_vectors"]),
         "lancedb_size_mb": dir_size_mb(LANCEDB_PATH),
@@ -193,6 +237,9 @@ def collect_status():
         "script_running": script_running,
         "timestamp": time.strftime("%H:%M:%S"),
         "log_tail": log_lines,
+        "eta": eta_str,
+        "avg_batch_seconds": round(avg_batch_seconds, 1) if avg_batch_seconds else None,
+        "remaining_docs": remaining,
     }
 
 
@@ -232,9 +279,14 @@ def cli_output(status):
     lines.append(f"  API: {api}  Script: {script}  "
                  f"LanceDB: {status['lancedb_size_mb']:.0f}MB  "
                  f"Docs: {status['docs_size_mb']:.0f}MB")
+    eta_str = ""
+    if status.get("eta"):
+        eta_str = f"  ETA: {GREEN}{status['eta']}{RESET} ({status['remaining_docs']} left, {status['avg_batch_seconds']}s/batch)"
     lines.append(f"  Uploaded: {status['total_uploaded']}  "
-                 f"Assigned: {status['total_assigned']}  "
+                 f"Assigned: {status['total_assigned']}/{status.get('total_expected', '?')}  "
                  f"Vectors: {status['personas_with_vectors']}/{status['total_personas']}")
+    if eta_str:
+        lines.append(eta_str)
     lines.append("")
 
     # Per-cluster persona table
@@ -373,6 +425,7 @@ function render(data) {
     <div class="summary-card"><div class="label">Vectors</div><div class="value">${data.personas_with_vectors}<span class="unit">/${data.total_personas}</span></div><div class="unit">${pctVec}%</div></div>
     <div class="summary-card"><div class="label">LanceDB</div><div class="value">${data.lancedb_size_mb < 1 ? Math.round(data.lancedb_size_mb * 1024) + '<span class="unit">KB</span>' : Math.round(data.lancedb_size_mb) + '<span class="unit">MB</span>'}</div></div>
     <div class="summary-card"><div class="label">Documents</div><div class="value">${Math.round(data.docs_size_mb)}<span class="unit">MB</span></div></div>
+    ${data.eta ? `<div class="summary-card"><div class="label">ETA</div><div class="value">${data.eta}</div><div class="unit">${data.remaining_docs} docs left · ${data.avg_batch_seconds}s/batch</div></div>` : ''}
   `;
 
   // Status bar