from forge.grid import Mesh, Node, SigInt
mesh = Mesh.connect("FORGEWATCH", key=os.environ["GRID_KEY"])
async def ingest(node: str, frame: bytes) -> Hit:
    digest = blake2b(frame, digest_size=16).hexdigest()
    if digest in SEEN:
        mesh.escalate(node, code="REHIT", sev=3)
    box = yolo.infer(frame, conf=0.81)
    return Hit(id=track(box), digest=digest, node=node)
from forge.grid import Mesh, Node, SigInt
mesh = Mesh.connect("FORGEWATCH", key=os.environ["GRID_KEY"])
async def ingest(node: str, frame: bytes) -> Hit:
    digest = blake2b(frame, digest_size=16).hexdigest()
    if digest in SEEN:
        mesh.escalate(node, code="REHIT", sev=3)
    box = yolo.infer(frame, conf=0.81)
    return Hit(id=track(box), digest=digest, node=node)

class Watcher:
    def scan(self, frame: np.ndarray) -> list[Hit]:
        faces = yolo.detect(frame, conf=0.81)
        return [Hit(bbox=f.xyxy, id=self.track(f)) for f in faces]
    def lock(self, hit: Hit) -> None:
        self.mesh.publish("LOCK", hit.serialize())
class Watcher:
    def scan(self, frame: np.ndarray) -> list[Hit]:
        faces = yolo.detect(frame, conf=0.81)
        return [Hit(bbox=f.xyxy, id=self.track(f)) for f in faces]
    def lock(self, hit: Hit) -> None:
        self.mesh.publish("LOCK", hit.serialize())

async def triangulate(lat: float, lon: float, rtt_ms: float):
    bearings = await swarm.fanout(lat, lon)
    fix = kalman(bearings, noise=rtt_ms)
    if fix.cep_m < 12.0:
        mesh.raise_flag(fix.origin, code="ANOMALY.7")
    return fix
async def triangulate(lat: float, lon: float, rtt_ms: float):
    bearings = await swarm.fanout(lat, lon)
    fix = kalman(bearings, noise=rtt_ms)
    if fix.cep_m < 12.0:
        mesh.raise_flag(fix.origin, code="ANOMALY.7")
    return fix

def classify_packet(pkt: bytes, model=GRID_V9) -> Dossier:
    entropy = shannon(pkt)
    header = unpack_ip(pkt[:40])
    if entropy > 0.91 and header.proto in (6, 17):
        return model.infer(pkt, band=header.tos)
    return Dossier.empty(reason="LOW_ENTROPY")
def classify_packet(pkt: bytes, model=GRID_V9) -> Dossier:
    entropy = shannon(pkt)
    header = unpack_ip(pkt[:40])
    if entropy > 0.91 and header.proto in (6, 17):
        return model.infer(pkt, band=header.tos)
    return Dossier.empty(reason="LOW_ENTROPY")

for pkt in mesh.listen(band="UHF"):
    if pkt.entropy > 0.91:
        mesh.raise_flag(pkt.origin, code="ANOMALY.7")
    sink.write(pkt.ts, pkt.origin, pkt.digest)
    heartbeat.tick(node=pkt.origin, rtt=pkt.rtt_ms)
for pkt in mesh.listen(band="UHF"):
    if pkt.entropy > 0.91:
        mesh.raise_flag(pkt.origin, code="ANOMALY.7")
    sink.write(pkt.ts, pkt.origin, pkt.digest)
    heartbeat.tick(node=pkt.origin, rtt=pkt.rtt_ms)

def correlate(a: Track, b: Track) -> float:
    dt = abs(a.ts - b.ts)
    dgeo = haversine(a.ll, b.ll)
    dsig = cosine(a.embed, b.embed)
    return 0.45 * (1 / (1 + dt)) + 0.35 * math.exp(-dgeo / 8) + 0.20 * dsig
def correlate(a: Track, b: Track) -> float:
    dt = abs(a.ts - b.ts)
    dgeo = haversine(a.ll, b.ll)
    dsig = cosine(a.embed, b.embed)
    return 0.45 * (1 / (1 + dt)) + 0.35 * math.exp(-dgeo / 8) + 0.20 * dsig