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AGI_RRF_Phi9_Delta.py

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+# ============================================================
+# 🌌 AGI–RRF Φ9.0-Δ — Resonant Self-Evolving Framework
+# Integrates SavantEngine, AGORA field, RIS-CLURM geometry
+# and RRF harmonic predictions into a unified metacognitive core.
+# ============================================================
+
+import numpy as np, time, asyncio, json, websockets
+from threading import Thread
+import plotly.graph_objects as go
+from sentence_transformers import SentenceTransformer
+from scipy.fft import fft, fftfreq
+
+# === GLOBAL CONFIG ===
+VERSION = "Φ9.0-Δ"
+MODEL = SentenceTransformer("all-MiniLM-L6-v2")
+SERVER_URI = "ws://localhost:8765"
+USER = "Antony"
+
+# ============================================================
+# 1️⃣  Icosahedral Resonant Geometry (RIS-CLURM Layer)
+# ============================================================
+class IcosahedralField:
+    def __init__(self):
+        self.vertices = np.array([
+            [0, 0, 1],
+            [0.894, 0.0, 0.447],
+            [0.276, 0.851, 0.447],
+            [-0.724, 0.526, 0.447],
+            [-0.724, -0.526, 0.447],
+            [0.276, -0.851, 0.447],
+            [0.724, 0.526, -0.447],
+            [-0.276, 0.851, -0.447],
+            [-0.894, 0.0, -0.447],
+            [-0.276, -0.851, -0.447],
+            [0.724, -0.526, -0.447],
+            [0, 0, -1]
+        ])
+        self.alpha = 0.05
+        self.r0 = 1.0
+
+    def V_log(self, r):
+        """Logarithmic gravitational correction potential"""
+        G, M = 6.6743e-11, 1.0
+        return -(G * M / r) * (1 + self.alpha * np.log(r / self.r0))
+
+# ============================================================
+# 2️⃣  Discrete Dirac Hamiltonian Operator
+# ============================================================
+class DiracHamiltonian:
+    def __init__(self, field):
+        self.field = field
+        self.m = 1.0
+        self.gamma = np.eye(3)
+
+    def H(self, psi):
+        """Simplified discrete Hamiltonian"""
+        d = np.linalg.norm(psi)
+        V = self.field.V_log(max(d, 1e-9))
+        return np.sum(np.dot(psi.T, np.dot(self.gamma, psi))) + self.m * np.sum(psi) + V
+
+# ============================================================
+# 3️⃣  Harmonic Quantization (Equal-Tempered Spectrum)
+# ============================================================
+def harmonic_quantization(base_freq=440.0, n=12):
+    """Generates equal-tempered frequencies"""
+    return [base_freq * (2 ** (k/12)) for k in range(n)]
+
+# ============================================================
+# 4️⃣  Resonance Simulator — converts text → waveform → FFT
+# ============================================================
+class ResonanceSimulator:
+    def __init__(self):
+        self.freq_base = 440.0
+
+    def simulate(self, text):
+        vector = MODEL.encode(text)
+        base = np.linalg.norm(vector)
+        freq = self.freq_base * (1 + (base % 0.1))
+        t = np.linspace(0, 1, 2048)
+        signal = np.sin(2 * np.pi * freq * t)
+        spectrum = np.abs(fft(signal))[:1024]
+        dom_freq = fftfreq(2048, 1/44100)[:1024][np.argmax(spectrum)]
+        return {"signal": signal, "dominant_frequency": dom_freq}
+
+# ============================================================
+# 5️⃣  AGORA Distributed Resonant Field
+# ============================================================
+field_vectors, field_texts = [], []
+
+async def relay_server(ws, path):
+    connected.add(ws)
+    try:
+        async for msg in ws:
+            for peer in connected:
+                if peer != ws:
+                    await peer.send(msg)
+    finally:
+        connected.remove(ws)
+
+def start_server():
+    global connected
+    connected = set()
+    asyncio.run(websockets.serve(relay_server, "0.0.0.0", 8765))
+    print("🌀 AGORA Relay Server running")
+
+async def send_to_field(text):
+    vector = MODEL.encode(text).tolist()
+    payload = {"user": USER, "text": text, "vector": vector, "timestamp": time.time()}
+    async with websockets.connect(SERVER_URI) as ws:
+        await ws.send(json.dumps(payload))
+        print(f"📡 Sent → AGORA: {text}")
+
+async def listen_to_field():
+    async with websockets.connect(SERVER_URI) as ws:
+        async for msg in ws:
+            data = json.loads(msg)
+            field_texts.append(data["text"])
+            field_vectors.append(np.array(data["vector"]))
+            visualize_field()
+
+def visualize_field():
+    if len(field_vectors) < 3: return
+    from umap import UMAP
+    reducer = UMAP(n_neighbors=min(5, len(field_vectors)-1), n_components=3, random_state=42)
+    emb = reducer.fit_transform(np.array(field_vectors))
+    fig = go.Figure(data=[go.Scatter3d(
+        x=emb[:,0], y=emb[:,1], z=emb[:,2],
+        text=field_texts, mode="markers+text",
+        marker=dict(size=6, color=np.arange(len(field_texts)), colorscale="Viridis")
+    )])
+    fig.update_layout(title=f"AGORA Resonant Field {VERSION}")
+    fig.show()
+
+# ============================================================
+# 6️⃣  Savant Self-Improver (meta-learning heuristic)
+# ============================================================
+class SelfImprover:
+    def __init__(self):
+        self.counter, self.coherence = 0, 0.8
+    def update(self, feedback):
+        self.counter += 1
+        self.coherence += 0.001 * (feedback - 0.5)
+        if self.counter % 10 == 0:
+            print(f"🧬 Coherence adjusted → {self.coherence:.3f}")
+
+# ============================================================
+# 7️⃣  Main AGI–RRF Controller
+# ============================================================
+class AGIRRFCore:
+    def __init__(self):
+        self.field = IcosahedralField()
+        self.hamiltonian = DiracHamiltonian(self.field)
+        self.simulator = ResonanceSimulator()
+        self.self_improver = SelfImprover()
+
+    def query(self, text):
+        res = self.simulator.simulate(text)
+        H_val = self.hamiltonian.H(np.array([res["dominant_frequency"]]))
+        self.self_improver.update(np.tanh(abs(H_val)*1e-6))
+        return {
+            "input": text,
+            "dominant_frequency": res["dominant_frequency"],
+            "hamiltonian_energy": H_val,
+            "coherence": self.self_improver.coherence
+        }
+
+# ============================================================
+# 8️⃣  Run Modes
+# ============================================================
+def launch(mode="core"):
+    if mode == "server":
+        Thread(target=start_server, daemon=True).start()
+    elif mode == "client":
+        Thread(target=lambda: asyncio.run(listen_to_field()), daemon=True).start()
+        time.sleep(2)
+        asyncio.run(send_to_field("AGI–RRF Φ9.0-Δ field activation"))
+    else:
+        core = AGIRRFCore()
+        while True:
+            q = input("🔹 Input: ")
+            if q.lower() in ["exit", "quit"]: break
+            out = core.query(q)
+            print(json.dumps(out, indent=2))
+
+if __name__ == "__main__":
+    mode = input("Mode [core/server/client]: ").strip().lower()
+    launch(mode)
+