atlasbot: use history for subjective follow-ups

services/comms/scripts/atlasbot/bot.py

@@ -191,6 +191,10 @@ _INSIGHT_HINT_WORDS = {
     "cool",
     "unique",
     "notable",
+    "coolest",
+    "favorite",
+    "favourite",
+    "trivia",
 }
 
 _OVERVIEW_HINT_WORDS = {
@@ -1550,6 +1554,21 @@ def _is_insight_query(query: str) -> bool:
     return False
 
 
+def _is_subjective_query(query: str) -> bool:
+    q = normalize_query(query)
+    if not q:
+        return False
+    return any(word in q for word in _INSIGHT_HINT_WORDS) or any(
+        phrase in q
+        for phrase in (
+            "what do you think",
+            "your favorite",
+            "your favourite",
+            "your opinion",
+        )
+    )
+
+
 def _is_overview_query(query: str) -> bool:
     q = normalize_query(query)
     if not q:
@@ -1602,9 +1621,9 @@ def _insight_candidates(
     if postgres_line:
         candidates.append(("postgres", postgres_line, "high"))
 
-    hardware_line = _hardware_mix_line(inventory)
-    if hardware_line:
-        candidates.append(("hardware", hardware_line, "medium"))
+    hardware_insight = _hardware_insight(inventory)
+    if hardware_insight:
+        candidates.append(("hardware", hardware_insight, "medium"))
 
     pods_line = _pods_summary_line(metrics)
     if pods_line:
@@ -1613,6 +1632,29 @@ def _insight_candidates(
     return candidates
 
 
+def _hardware_insight(inventory: list[dict[str, Any]]) -> str:
+    if not inventory:
+        return ""
+    groups = _group_nodes(inventory)
+    jetsons = groups.get("jetson") or []
+    rpi5 = groups.get("rpi5") or []
+    rpi4 = groups.get("rpi4") or []
+    amd64 = groups.get("amd64") or []
+    if jetsons:
+        jetson_names = ", ".join(jetsons[:2])
+        return (
+            f"Atlas mixes tiny Raspberry Pi nodes with Jetson accelerators ({jetson_names}) "
+            f"and AMD64 servers, which is unusual for a homelab cluster."
+        )
+    if amd64 and (rpi5 or rpi4):
+        return (
+            "Atlas mixes small ARM boards with a couple of AMD64 machines, "
+            "so workloads can land on either low-power or high-power nodes."
+        )
+    line = _hardware_mix_line(inventory)
+    return line.replace("Hardware mix includes ", "Atlas mixes ") if line else ""
+
+
 def _select_insight(
     prompt: str,
     candidates: list[tuple[str, str, str]],
@@ -1623,6 +1665,8 @@ def _select_insight(
     prefer_keys: list[str] = []
     if any(word in q for word in ("unconventional", "weird", "odd", "unique", "surprising")):
         prefer_keys.extend(["hardware", "availability"])
+    if any(word in q for word in ("coolest", "favorite", "favourite", "trivia", "fun")):
+        prefer_keys.extend(["hardware", "cpu", "ram"])
     if any(word in q for word in ("another", "else", "different", "other")) and len(candidates) > 1:
         return candidates[1]
     if prefer_keys:
@@ -2284,7 +2328,24 @@ class _AtlasbotHandler(BaseHTTPRequestHandler):
         snapshot = _snapshot_state()
         inventory = _snapshot_inventory(snapshot) or node_inventory_live()
         workloads = _snapshot_workloads(snapshot)
-        cluster_query = _is_cluster_query(cleaned, inventory=inventory, workloads=workloads)
+        history_payload = payload.get("history") or []
+        history_lines: list[str] = []
+        if isinstance(history_payload, list):
+            for item in history_payload[-10:]:
+                if isinstance(item, dict):
+                    content = item.get("content") or item.get("message") or ""
+                    if isinstance(content, str) and content.strip():
+                        history_lines.append(content.strip())
+                elif isinstance(item, str) and item.strip():
+                    history_lines.append(item.strip())
+        history_cluster = _history_mentions_cluster(
+            history_lines,
+            inventory=inventory,
+            workloads=workloads,
+        )
+        cluster_query = _is_cluster_query(cleaned, inventory=inventory, workloads=workloads) or (
+            _is_subjective_query(cleaned) and history_cluster
+        )
         context = ""
         if cluster_query:
             context = build_context(
@@ -2329,6 +2390,22 @@ history = collections.defaultdict(list)  # (room_id, sender|None) -> list[str] (
 def key_for(room_id: str, sender: str, is_dm: bool):
     return (room_id, None) if is_dm else (room_id, sender)
 
+
+def _history_mentions_cluster(
+    history_lines: list[str],
+    *,
+    inventory: list[dict[str, Any]] | None = None,
+    workloads: list[dict[str, Any]] | None = None,
+) -> bool:
+    recent = [line for line in history_lines[-8:] if isinstance(line, str)]
+    for line in recent:
+        cleaned = normalize_query(line)
+        if not cleaned:
+            continue
+        if _is_cluster_query(cleaned, inventory=inventory, workloads=workloads):
+            return True
+    return False
+
 def build_context(
     prompt: str,
     *,
@@ -2734,7 +2811,14 @@ def sync_loop(token: str, room_id: str):
                 if not inventory:
                     inventory = _snapshot_inventory(snapshot)
                 workloads = _snapshot_workloads(snapshot)
-                cluster_query = _is_cluster_query(cleaned_body, inventory=inventory, workloads=workloads)
+                history_cluster = _history_mentions_cluster(
+                    history[hist_key],
+                    inventory=inventory,
+                    workloads=workloads,
+                )
+                cluster_query = _is_cluster_query(cleaned_body, inventory=inventory, workloads=workloads) or (
+                    _is_subjective_query(cleaned_body) and history_cluster
+                )
                 context = ""
                 if cluster_query:
                     context = build_context(