import numpy as np

class SemanticRecord:
    def __init__(self, text, embedding):
        self.text = text
        self.embedding = embedding

class SlimeTreeRLM:
    def __init__(self, hot_capacity=3):
        self.hot_slots = []
        self.cold_slots = []
        self.regret = 0.0
        self.global_stability = 0.0
        self.priorities = {}

    def unresolved_pressure(self, slot):
        # U(q) = value * novelty * conflict / (1 + cost)
        value, novelty, conflict, cost = 1.0, np.random.rand(), np.random.rand(), np.random.rand()
        return (value * novelty * conflict) / (1 + cost)

    def route_mode(self, query_emb):
        # Continuous mode selection via argmax (no if-statements)
        u_q = np.mean([self.unresolved_pressure(s) for s in self.hot_slots + self.cold_slots])
        scores = {'Delta': 1 - u_q, 'Mu': 0.5, 'RLM': u_q}
        return max(scores, key=scores.get)

    def insert(self, record):
        priority = np.linalg.norm(record.embedding)
        hash_key = hash(record.text) % 1000
        if hash_key in self.priorities:
            self.regret += 0.1  # Failure signal
            return "Duplicate/Failure"
        self.priorities[hash_key] = priority
        if len(self.hot_slots) < self.hot_capacity:
            self.hot_slots.append(record)
        else:
            self.cold_slots.append(record)
        # Update stability (basis for adaptive eta)
        self.global_stability = len(self.hot_slots) / (len(self.hot_slots) + len(self.cold_slots) + 1)
        return "Inserted"

    def query(self, query_emb, num_results=3):
        results = []
        all_slots = self.hot_slots + self.cold_slots
        for slot in all_slots:
            sim = np.dot(query_emb, slot.embedding) / (np.linalg.norm(query_emb) * np.linalg.norm(slot.embedding))
            results.append((sim, slot.text))
        return sorted(results, reverse=True)[:num_results]

# === Test Execution ===
tree = SlimeTreeRLM()
records = [SemanticRecord(f"Sample text {i}", np.random.rand(5)) for i in range(10)]

for rec in records:
    print(tree.insert(rec))

query_emb = np.random.rand(5)
print(f"Selected Mode: {tree.route_mode(query_emb)}")
print(f"Global Stability: {tree.global_stability}")
print(f"Query Top 3: {tree.query(query_emb)}")
print(f"Regret: {tree.regret}")