From 4b7b2af687eb61c6f1d7b5a4afa706715c2420ef Mon Sep 17 00:00:00 2001
From: Brad Stein <Brad.Stein@gmail.com>
Date: Wed, 4 Feb 2026 14:27:12 -0300
Subject: [PATCH] atlasbot: add metric direct fallback

---
 atlasbot/engine/answerer.py | 41 +++++++++++++++++++++++++++++++++++++
 1 file changed, 41 insertions(+)

diff --git a/atlasbot/engine/answerer.py b/atlasbot/engine/answerer.py
index 751e239..8ee3da4 100644
--- a/atlasbot/engine/answerer.py
+++ b/atlasbot/engine/answerer.py
@@ -641,6 +641,19 @@ class AnswerEngine:
                         model=plan.model,
                         tag="evidence_fix_enforce",
                     )
+            if metric_facts and not _reply_matches_metric_facts(reply, metric_facts, all_tokens):
+                direct_line = _select_metric_line(summary_lines, normalized, all_tokens)
+                if direct_line:
+                    direct_prompt = f"Question: {normalized}\nFact: {direct_line}\nAnswer using the fact."
+                    reply = await call_llm(
+                        prompts.ANSWER_SYSTEM,
+                        direct_prompt,
+                        context="",
+                        model=plan.fast_model,
+                        tag="metric_direct",
+                    )
+                    if not _reply_matches_metric_facts(reply, [direct_line], all_tokens):
+                        reply = _format_direct_metric_line(direct_line)
 
             if "raspberry" in lowered_question and "not" in lowered_question:
                 non_rpi = _non_rpi_nodes(summary)
@@ -2044,6 +2057,34 @@ def _rank_metric_lines(lines: list[str], tokens: set[str], max_lines: int) -> li
     return [item[2] for item in ranked[:max_lines]]
 
 
+def _select_metric_line(lines: list[str], question: str, tokens: list[str] | set[str]) -> str | None:
+    if not lines or not tokens:
+        return None
+    token_set = {str(tok).lower() for tok in tokens if tok}
+    ranked = _rank_metric_lines(lines, token_set, max_lines=6)
+    if not ranked:
+        return None
+    question_lower = (question or "").lower()
+    if any(term in question_lower for term in ("how many", "count", "total")):
+        for line in ranked:
+            lower = line.lower()
+            if "total" in lower or "count" in lower:
+                return line
+    return ranked[0]
+
+
+def _format_direct_metric_line(line: str) -> str:
+    if not line:
+        return ""
+    if ":" in line:
+        key, value = line.split(":", 1)
+        key = key.strip().replace("_", " ")
+        value = value.strip()
+        if value:
+            return f"{key} is {value}."
+    return line
+
+
 def _global_facts(lines: list[str]) -> list[str]:
     if not lines:
         return []