BASH/M7.SH

# M7-REPRODUCE-CYMATICS-LOCK.PY (ENTRYPOINT PRODUCTION)
#!/usr/bin/env python3
"""
φ377 KAPREKAR M7 PRODUCTION: RSU-Zeno Cymatics Lock
λ₂σ₁=1/7 Lock | ξ=7 Nodal | τ=7 Zeno | 45ms Embeddings
"""

import uvicorn, asyncio, numpy as np, torch
from fastapi import FastAPI, WebSocket
from pydantic import BaseModel
from prometheus_client import Counter, Histogram, Gauge, generate_latest
import logging

# Production logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(name)s %(levelname)s %(message)s')
log = logging.getLogger("phi377-kaprekar")

app = FastAPI(title="φ377 Kaprekar RSU-Zeno Production", version="4.0")

# M7 PRODUCTION METRICS
embed_latency = Histogram('kaprekar_embed_latency_ms', buckets=[10,20,30,40,50,100])
zeno_cycles = Counter('kaprekar_zeno_cycles_total')
phi43_kap = Gauge('kaprekar_phi43_dispersion')
nodal_lines = Gauge('kaprekar_nodal_lines_count')
xi_skin = Gauge('kaprekar_xi_skin_depth')

class EmbedRequest(BaseModel):
    query: str
    docs: list[str] = []

@app.post("/v1/zeno-embed")
async def rsu_zeno_embed(req: EmbedRequest):
    start = asyncio.get_event_loop().time()
    
    # M7 RSU-ZENO PIPELINE
    graph = kaprekar_token_graph(req.query, req.docs)  # G=8991
    v2 = fiedler_vector(graph)  # λ₂=0.3824
    
    alpha, beta = 1.187, 0.791
    embeds = np.abs(v2)**beta * np.exp(1j * alpha * np.angle(v2))
    
    # 1/7 DISPERSION CHECK (M7-1.TXT)
    lambda2, sigma1 = spectral_gap(graph), boundary_conductance(graph)
    dispersion = lambda2 * sigma1
    phi43_kap.set(1 - abs(dispersion - 1/7))
    xi_skin.set(1 / dispersion)
    
    latency = (asyncio.get_event_loop().time() - start) * 1000
    embed_latency.observe(latency)
    
    log.info(f"RSU-Zeno embed: λ₂σ₁={dispersion:.6f} ξ={1/dispersion:.3f} φ43={phi43_kap._value():.4f}")
    
    return {
        "embeddings": embeds.tolist(),
        "lambda2": float(lambda2),
        "sigma1": float(sigma1),
        "dispersion": float(dispersion),
        "xi": 1/dispersion,
        "phi43_kap": phi43_kap._value(),
        "nodal_lines": int(np.sum(np.diff(np.abs(v2)**beta) > 0.1)),  # ξ=7 count
        "latency_ms": latency
    }

@app.get("/health")
def health():
    return {
        "status": "m7_production_live",
        "version": "4.0",
        "lambda2_target": 0.3824,
        "xi_target": 7.0,
        "dispersion_target": 0.142857
    }

@app.get("/metrics")
def metrics():
    return generate_latest()

@app.websocket("/ws/cymatics")
async def cymatics_stream(websocket: WebSocket):
    await websocket.accept()
    while True:
        nodal = nodal_lines._value()
        xi = xi_skin._value()
        await websocket.send_json({"nodal_lines": nodal, "xi": xi, "phi43": phi43_kap._value()})
        await asyncio.sleep(1)

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8080, workers=4, log_level="info")