Create solver_weighted_average.py

solver_weighted_average.py

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+from __future__ import annotations
+
+import re
+from typing import Optional
+
+from models import SolverResult
+
+
+def solve_weighted_average(text: str) -> Optional[SolverResult]:
+
+    lower = text.lower()
+
+    if "average" not in lower and "mean" not in lower:
+        return None
+
+    numbers = [float(x) for x in re.findall(r"\d+(?:\.\d+)?", lower)]
+
+    if len(numbers) < 3:
+        return None
+
+    total_items = numbers[0]
+    group_items = numbers[1]
+    group_avg = numbers[2]
+
+    if "remaining" not in lower and "rest" not in lower:
+        return None
+
+    remaining_items = total_items - group_items
+    if remaining_items <= 0:
+        return None
+
+    total_avg_match = re.search(r"overall average.*?(\d+(?:\.\d+)?)", lower)
+    if not total_avg_match:
+        return None
+
+    total_avg = float(total_avg_match.group(1))
+
+    total_sum = total_items * total_avg
+    group_sum = group_items * group_avg
+    remaining_sum = total_sum - group_sum
+
+    result = remaining_sum / remaining_items
+
+    return SolverResult(
+        domain="quant",
+        solved=True,
+        topic="weighted_average",
+        answer_value=f"{result:g}",
+        internal_answer=f"{result:g}",
+        steps=[
+            "Total sum = total items × overall average.",
+            "Subtract the known group sum.",
+            "Divide the remaining sum by the remaining number of items."
+        ]
+    )