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fso_conversational_memory.py

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+import hashlib
+import time
+
+class ConversationalMemory:
+    """
+    Law XII Component: Topological Memory
+    Stores conversational history as a sequence of coordinates in Fiber 2.
+    Allows for temporal context retrieval.
+    """
+    def __init__(self, m=256, k=4):
+        self.m = m
+        self.k = k
+        self.history = [] # List of entries
+
+    def _get_coord(self, text, fiber=2):
+        h = hashlib.sha256(text.encode()).digest()
+        coords = [h[i % len(h)] % self.m for i in range(self.k - 1)]
+        w = (fiber - sum(coords)) % self.m
+        return tuple(coords + [w])
+
+    def record_turn(self, speaker, text):
+        coord = self._get_coord(text)
+        entry = {
+            "timestamp": time.time(),
+            "speaker": speaker,
+            "text": text,
+            "coord": coord
+        }
+        self.history.append(entry)
+        print(f"      [MEMORY]: Recorded {speaker} turn @ {coord}")
+        return coord
+
+    def get_recent_context(self, depth=5):
+        return "\n".join([f"{h['speaker']}: {h['text']}" for h in self.history[-depth:]])
+
+if __name__ == "__main__":
+    mem = ConversationalMemory()
+    mem.record_turn("User", "Hello TGI.")
+    mem.record_turn("TGI", "Greetings. I am operational.")
+    print(f"\nContext Retrieval:\n{mem.get_recent_context()}")