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manas/core/semantic.py

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+"""Semantic memory — an editable, verifiable knowledge graph (DOC 4 §5.3, GraphRAG).
+
+The model can READ and WRITE facts. Only verifier-confirmed facts are written
+as 'verified'. Supports lookup for grounding and contradiction checks.
+"""
+import re
+import time
+
+
+def _norm(s):
+    return re.sub(r"\s+", " ", s.strip().lower())
+
+
+class SemanticMemory:
+    def __init__(self):
+        # subject -> list of fact dicts
+        self.facts = {}
+
+    @staticmethod
+    def _subject(text):
+        # crude subject extraction: first content chunk before 'is/are/was'
+        m = re.split(r"\b(is|are|was|were|has|have)\b", text, maxsplit=1)
+        return _norm(m[0]) if m else _norm(text)[:48]
+
+    def write(self, fact: str, verified: bool = False, source: str = "model"):
+        subj = self._subject(fact)
+        entry = {"fact": fact.strip(), "verified": bool(verified),
+                 "source": source, "ts": time.time()}
+        self.facts.setdefault(subj, [])
+        # avoid exact dupes
+        if not any(_norm(e["fact"]) == _norm(fact) for e in self.facts[subj]):
+            self.facts[subj].append(entry)
+        return subj
+
+    def read(self, query: str, k: int = 4):
+        q = set(re.findall(r"[a-z]{3,}", query.lower()))
+        scored = []
+        for subj, entries in self.facts.items():
+            for e in entries:
+                fw = set(re.findall(r"[a-z]{3,}", e["fact"].lower()))
+                ov = len(q & fw)
+                if ov:
+                    scored.append((ov, e))
+        scored.sort(key=lambda x: (-x[0], not x[1]["verified"]))
+        return [e for _, e in scored[:k]]
+
+    def verify_fact(self, fact: str):
+        """Mark a stored fact verified (called by the symbolic verifier)."""
+        subj = self._subject(fact)
+        for e in self.facts.get(subj, []):
+            if _norm(e["fact"]) == _norm(fact):
+                e["verified"] = True
+                return True
+        return False
+
+    def contradicts(self, fact: str) -> bool:
+        """True if a stored verified fact on the same subject says something different."""
+        subj = self._subject(fact)
+        for e in self.facts.get(subj, []):
+            if e["verified"] and _norm(e["fact"]) != _norm(fact):
+                return True
+        return False
+
+    def __len__(self):
+        return sum(len(v) for v in self.facts.values())