Update context_parser.py

context_parser.py

@@ -1,6 +1,81 @@
 from __future__ import annotations
 
 import re
+from typing import Any, Dict, Tuple
+
+
+def split_unity_message(text: str) -> Tuple[str, str]:
+    """
+    Splits a Unity-style message into:
+    - game/context prefix
+    - user-facing message/question
+
+    If no structured prefix is found, returns ("", original_text).
+    """
+    raw = (text or "").strip()
+    if not raw:
+        return "", ""
+
+    # Common pattern: "QUESTION: ... USER: ..."
+    m = re.search(
+        r"(?is)^(.*?)(?:user|question|prompt)\s*:\s*(.+)$",
+        raw,
+    )
+    if m:
+        prefix = (m.group(1) or "").strip()
+        message = (m.group(2) or "").strip()
+        return prefix, message
+
+    return "", raw
+
+
+def extract_game_context_fields(text: str) -> Dict[str, Any]:
+    """
+    Lightweight parser for structured context coming from Unity / study messages.
+
+    Returns a dict with whatever fields can be detected.
+    Safe fallback: missing fields just remain absent.
+    """
+    raw = (text or "").strip()
+    lower = raw.lower()
+
+    fields: Dict[str, Any] = {}
+
+    # Money / balance
+    money_match = re.search(r"\b(?:money|balance|bank)\s*[:=]\s*([\-]?\d+(?:\.\d+)?)", raw, flags=re.I)
+    if money_match:
+        try:
+            fields["money"] = float(money_match.group(1))
+        except Exception:
+            pass
+
+    # Difficulty
+    difficulty_match = re.search(r"\bdifficulty\s*[:=]\s*([A-Za-z0-9_\- ]+)", raw, flags=re.I)
+    if difficulty_match:
+        fields["difficulty"] = difficulty_match.group(1).strip()
+
+    # Category / topic
+    category_match = re.search(r"\b(?:category|topic)\s*[:=]\s*([A-Za-z0-9_\- /]+)", raw, flags=re.I)
+    if category_match:
+        fields["category"] = category_match.group(1).strip()
+
+    # Question text
+    question_match = re.search(r"\bquestion\s*[:=]\s*(.+)", raw, flags=re.I)
+    if question_match:
+        q = question_match.group(1).strip()
+        if q:
+            fields["question_text"] = q
+
+    # Answer choices in a rough form
+    if re.search(r"\bA[\)\.\:]", raw) and re.search(r"\bB[\)\.\:]", raw):
+        fields["has_choices"] = True
+
+    # Cheap flags
+    fields["looks_like_quant"] = any(
+        token in lower for token in ["solve", "equation", "percent", "%", "ratio", "probability", "mean", "median"]
+    )
+
+    return fields
 
 
 def detect_intent(text: str) -> str: