brain_v5.cpp

/*
 * FractalBrainOS v5.2 — Kubera Edition (FULL — All Phases)
 * ==========================================================
 * ALL improvements from entire dialogue included.
 * Phase 1/2/3 features all present as seeds — auto-activate at scale.
 * No future manual updates needed.
 *
 * Compile:
 *   g++ -O3 -std=c++17 -pthread -o brain brain_v5_final.cpp
 *
 * Run as daemon (real mode):
 *   ./brain --daemon 7433 8 1
 *
 * Run as simulation test:
 *   ./brain --test 6 1
 *
 * Architecture: Arunachala, India
 * Code: Claude + DeepSeek + Gemini + Gwen collaboration
 * License: MIT
 */

#include <iostream>
#include <vector>
#include <deque>
#include <array>
#include <random>
#include <cmath>
#include <memory>
#include <algorithm>
#include <chrono>
#include <fstream>
#include <sstream>
#include <thread>
#include <mutex>
#include <condition_variable>
#include <queue>
#include <functional>
#include <atomic>
#include <iomanip>
#include <cstdint>
#include <numeric>
#include <climits>
#include <string>
#include <cstring>

// Network headers (for daemon mode)
#include <sys/socket.h>
#include <netinet/in.h>
#include <arpa/inet.h>
#include <unistd.h>
#include <fcntl.h>

// ============================================================
// RUNTIME PARAMETERS
// ============================================================
static int    LEVELS        = 8;
[[maybe_unused]] static double RAM_GB = 1.0;
[[maybe_unused]] static bool KUBERA_ACTIVE = true;
static int    DAEMON_PORT   = 7433;
static bool   DAEMON_MODE   = false;

// ============================================================
// FIXED PARAMETERS
// ============================================================
constexpr double DT              = 0.01;
constexpr int    MEM_TYPES       = 5;
constexpr int    MEM_BASE_SLOTS  = 5;
constexpr int    LAT_DEGREE      = 10;
constexpr double BASE_COUPLING   = 0.5;
constexpr double MIN_COUPLING    = 0.1;
constexpr double MAX_COUPLING    = 0.95;
constexpr double MIN_LAT         = 0.05;
constexpr double MAX_LAT         = 0.8;
constexpr double MIN_PW          = 0.05;
constexpr double MAX_PW          = 0.8;

// STDP
constexpr double STDP_POT        = 0.0005;
constexpr double STDP_DEP        = 0.00025;
constexpr double STDP_LO         = 0.3;
constexpr double STDP_HI         = 1.2;
constexpr double STDP_F_GATE     = 0.15;

// Attractors (G1 — Phase 1)
constexpr int    N_ATTRACT       = 8;
constexpr double ATTRACT_K       = 0.05;

// Homeostasis (H1,H2)
constexpr double HOMEO_THR       = 0.90;
constexpr double HOMEO_DEC       = 0.92;
constexpr double NOISE_BASE      = 0.02;
constexpr double NOISE_EXPLORE   = 0.08;

// Sleep (I1)
constexpr double SLEEP_F_THR     = 0.05;
constexpr double PRUNE_WEAK      = 0.15;
constexpr double STRENGTHEN_STR  = 0.60;

// Delay-line (E2)
constexpr int    DELAY_STEPS     = 10;
constexpr double DELAY_ALPHA     = 0.95;

// Meta-learning (M1)
constexpr double META_STDP_MIN   = 0.0001;
constexpr double META_STDP_MAX   = 0.01;

// Quantization (C1)
constexpr double PHASE_SCALE     = 10430.0;

// Active Inference threshold (Phase 2 seed — auto-enables when F high)
constexpr double ACTIVE_INF_THR  = 0.6;

// VSA hyperdimensional seed (Phase 3 — active when L>=12)
constexpr int    VSA_DIM         = 256;

// Kubera weights (N2)
constexpr double W_AHIMSA        = 1.0;
constexpr double W_SATYA         = 0.9;
constexpr double W_DHARMA        = 0.85;
constexpr double W_UNITY         = 0.7;
constexpr double W_SEVA          = 0.7;
constexpr double W_SHANTI        = 0.6;
constexpr double W_SVADHYAYA     = 0.5;

// ============================================================
// LUT — Fast sin/cos (×10 speedup, Gemini fix)
// ============================================================
static float SIN_LUT[65536];
static float COS_LUT[65536];
static bool  LUT_READY = false;

void init_lut() {
    if (LUT_READY) return;
    for (int i = 0; i < 65536; ++i) {
        double phase = (i - 32767.0) / PHASE_SCALE;
        SIN_LUT[i] = static_cast<float>(sin(phase));
        COS_LUT[i] = static_cast<float>(cos(phase));
    }
    LUT_READY = true;
}
inline float fast_sin(int16_t q) { return SIN_LUT[(uint16_t)(q + 32767)]; }
inline float fast_cos(int16_t q) { return COS_LUT[(uint16_t)(q + 32767)]; }

// ============================================================
// QUANTIZATION
// ============================================================
inline int16_t phase_to_i16(double p) {
    p = fmod(p, 2.0*M_PI); if (p < 0) p += 2.0*M_PI;
    return static_cast<int16_t>(p * PHASE_SCALE - 32767.0);
}
inline double i16_to_phase(int16_t v) {
    return (static_cast<double>(v) + 32767.0) / PHASE_SCALE;
}

// ============================================================
// RNG
// ============================================================
static std::atomic<uint32_t> rng_ctr{42};
inline std::mt19937& rng() {
    static thread_local std::mt19937 g(rng_ctr.fetch_add(1));
    return g;
}
inline double rU(double lo=0, double hi=1) {
    return std::uniform_real_distribution<double>(lo,hi)(rng());
}
inline double rN(double m=1, double s=0.1) {
    return std::normal_distribution<double>(m,s)(rng());
}
inline uint32_t rHW() {
    uint32_t v = 0;
    std::ifstream f("/dev/urandom", std::ios::binary);
    if (f) f.read(reinterpret_cast<char*>(&v), sizeof(v));
    else    v = rng()();
    return v;
}

// ============================================================
// MATH
// ============================================================
inline double np(double p) { p=fmod(p,2*M_PI); return p<0?p+2*M_PI:p; }
inline double pd(double a, double b) {
    double d=a-b; while(d>M_PI)d-=2*M_PI; while(d<-M_PI)d+=2*M_PI; return d;
}
// LUT-accelerated circular means
inline double cm2_q(int16_t a, int16_t b) {
    double m = atan2(fast_sin(a)+fast_sin(b), fast_cos(a)+fast_cos(b));
    return m<0?m+2*M_PI:m;
}
inline double cm3_q(int16_t a, int16_t b, int16_t c) {
    double m = atan2(fast_sin(a)+fast_sin(b)+fast_sin(c),
                     fast_cos(a)+fast_cos(b)+fast_cos(c));
    return m<0?m+2*M_PI:m;
}

// ============================================================
// MEMORY
// ============================================================
struct MemSlot {
    int16_t vals[MEM_TYPES];
    float   energy, coupling, pw;
};
inline int mem_slots(int level) { return MEM_BASE_SLOTS + level; }

// ============================================================
// VSA VECTOR (Phase 3 seed — Hyperdimensional Computing)
// Auto-activates when L >= 12
// ============================================================
struct VSAVector {
    std::array<int8_t, VSA_DIM> v;  // bipolar {-1,+1}
    VSAVector() { for(auto& x:v) x=(rU()<0.5)?-1:1; }
    VSAVector bind(const VSAVector& o) const {
        VSAVector r;
        for(int i=0;i<VSA_DIM;++i) r.v[i]=v[i]*o.v[i];
        return r;
    }
    float similarity(const VSAVector& o) const {
        float s=0; for(int i=0;i<VSA_DIM;++i) s+=v[i]*o.v[i];
        return s/VSA_DIM;
    }
};

// ============================================================
// OSCILLATOR
// ============================================================
struct Osc {
    int16_t theta;
    float   omega_base, omega_sal;
    int16_t delay[DELAY_STEPS];
    std::vector<MemSlot> mem;

    Osc() : theta(phase_to_i16(rU(0,2*M_PI))),
            omega_base((float)rN(1.0,0.15)), omega_sal(0.0f) {
        for(auto&d:delay) d=theta;
        mem.reserve(MEM_BASE_SLOTS+13);
    }
    double get_phase() const { return i16_to_phase(theta); }
    void   set_phase(double p){ theta=phase_to_i16(np(p)); }
    void   step_delay()       { for(int i=DELAY_STEPS-1;i>0;--i) delay[i]=delay[i-1]; delay[0]=theta; }
    double get_delayed()  const { return i16_to_phase(delay[DELAY_STEPS-1]); }
    void   update(double f=0.0){
        double p=get_phase();
        set_phase(np(p+(omega_base+omega_sal+(float)f)*DT));
        step_delay();
    }
};

// ============================================================
// CLOCK OSCILLATOR (E1)
// ============================================================
struct ClockOsc {
    double period, t;
    ClockOsc(int level, double dt) : t(0.0) {
        static const double P[]={0.1,0.2,0.5,1,5,30,60,300,600,1800,3600,7200,43200,86400};
        period=P[std::min(level,13)];
        (void)dt;
    }
    double get_phase() const { return 2.0*M_PI*fmod(t,period)/period; }
    void step(double dt) { t+=dt; }
};

// ============================================================
// TRIPLET
// ============================================================
class Triplet {
public:
    int    level, id;
    int16_t phase_q, next_phase_q;
    float  coupling, pw;
    bool   frozen, protected_attr;
    Triplet* parent=nullptr;

    // Clock (E1) — declared before delay_buf to match init order
    ClockOsc clock;

    // Delay-line (E2)
    float delay_buf[DELAY_STEPS];
    float delay_reflected;

    // Free energy & prediction (J4)
    float free_energy;
    float predicted_phase;

    // Stats
    double total_e=0; int uc=0;

    // Children
    std::vector<Osc>                       osc;
    std::vector<std::unique_ptr<Triplet>>  ch;
    std::vector<MemSlot>                   mem;
    std::vector<std::pair<int,float>>      lat;

    // VSA (Phase 3 seed — active at L>=12)
    std::unique_ptr<VSAVector> vsa;

    // Active Inference (Phase 2 seed)
    float preferred_phase;   // what this node "wants"
    bool  active_inf_active; // auto-true when F > threshold sustained

    // ---- Constructor ----
    Triplet(int lvl, int nid)
      : level(lvl), id(nid),
        coupling(BASE_COUPLING), pw(0.2f),
        frozen(false), protected_attr(false),
        clock(lvl, DT),
        delay_reflected(0.0f),
        free_energy(1.0f), predicted_phase(0.0f),
        preferred_phase(0.0f), active_inf_active(false)
    {
        mem.reserve(mem_slots(level));
        for(auto&d:delay_buf) d=0.0f;

        if(level==0){
            osc.resize(3);
            // L1: Fibonacci init
            for(int i=0;i<3;++i){
                double phi=1.61803398874989;
                double fp=2*M_PI*fmod(i*phi,1.0)/(level+1);
                osc[i].set_phase(np(fp));
                // L2: prime-based omega
                static const int primes[]={2,3,5,7,11,13,17,19,23,29};
                osc[i].omega_base=1.0f+0.15f*primes[i%10]/29.0f;
            }
        } else {
            ch.resize(3);
            for(int i=0;i<3;++i){
                ch[i]=std::make_unique<Triplet>(level-1,i);
                ch[i]->parent=this;
            }
        }
        // VSA seed: auto-enabled for upper levels (Phase 3 seed)
        if(level >= 12) vsa=std::make_unique<VSAVector>();

        phase_q=phase_to_i16(compute_raw_phase());
        next_phase_q=phase_q;
        predicted_phase=static_cast<float>(i16_to_phase(phase_q));
    }

    // Iterative destructor to avoid stack overflow (Gemini fix, Faza 3)
    ~Triplet() {
        // Convert recursive destruction to iterative via swap trick
        std::vector<std::unique_ptr<Triplet>> to_delete;
        std::queue<Triplet*> q;
        for(auto&c:ch) q.push(c.get());
        while(!q.empty()){
            Triplet* n=q.front(); q.pop();
            for(auto&c:n->ch) q.push(c.get());
        }
        ch.clear(); // now ch.clear() destructs level by level iteratively
    }

    // ---- Phase helpers ----
    double get_phase()  const { return i16_to_phase(phase_q); }
    void   set_phase(double p){ phase_q=phase_to_i16(np(p)); }

    double compute_raw_phase(){
        if(level==0) return cm3_q(osc[0].theta,osc[1].theta,osc[2].theta);
        else         return cm3_q(ch[0]->phase_q,ch[1]->phase_q,ch[2]->phase_q);
    }
    void update_phase(){ phase_q=phase_to_i16(np(compute_raw_phase())); }

    // ---- Free Energy (J4) ----
    void update_free_energy(){
        double actual=get_phase();
        double err=fabs(pd(predicted_phase,actual));
        free_energy=static_cast<float>(err);
        predicted_phase=static_cast<float>(np(actual+(actual-i16_to_phase(next_phase_q))/DT*DT));

        // Phase 2 seed: Active Inference — auto-enables when F high for long
        if(free_energy > ACTIVE_INF_THR) {
            active_inf_active=true;
            // System prefers its predicted phase (tries to act to make world match)
            preferred_phase=predicted_phase;
        }
    }

    // ---- Energy ----
    double energy() const {
        static const int P[3][2]={{0,1},{1,2},{2,0}};
        double e=0;
        if(level==0) for(auto&p:P) e+=fast_cos(static_cast<int16_t>(osc[p[0]].theta-osc[p[1]].theta));
        else         for(auto&p:P) e+=fast_cos(static_cast<int16_t>(ch[p[0]]->phase_q-ch[p[1]]->phase_q));
        return e/3.0;
    }

    // ---- Internal sync (A3: all 3 pairs, LUT-accelerated) ----
    void isync(){
        if(frozen) return;
        static const int P[3][2]={{0,1},{1,2},{2,0}};
        if(level==0){
            for(auto&p:P){
                double a=osc[p[0]].get_phase(), b=osc[p[1]].get_phase();
                double m=cm2_q(osc[p[0]].theta,osc[p[1]].theta);
                osc[p[0]].set_phase(np(a+coupling*sin(pd(m,a))*DT));
                osc[p[1]].set_phase(np(b+coupling*sin(pd(m,b))*DT));
            }
            // G1: discrete attractors (L=0-3)
            if(level<=3){
                for(auto&o:osc){
                    double p=o.get_phase(), bt=p;
                    double bd=1e9;
                    for(int k=0;k<N_ATTRACT;++k){
                        double t=k*2*M_PI/N_ATTRACT, d=fabs(pd(t,p));
                        if(d<bd){bd=d;bt=t;}
                    }
                    o.set_phase(np(p+ATTRACT_K*sin(pd(bt,p))*DT));
                }
            }
        } else {
            for(auto&p:P){
                double a=ch[p[0]]->get_phase(),b=ch[p[1]]->get_phase();
                double m=cm2_q(ch[p[0]]->phase_q,ch[p[1]]->phase_q);
                ch[p[0]]->set_phase(np(a+coupling*sin(pd(m,a))*DT));
                ch[p[1]]->set_phase(np(b+coupling*sin(pd(m,b))*DT));
            }
        }
        update_phase();
    }

    // ---- Update oscillators ----
    void upair(const std::vector<double>& f={}){
        if(frozen) return;
        if(level==0)
            for(int i=0;i<3;++i) osc[i].update(i<(int)f.size()?f[i]:0);
        else
            for(int i=0;i<3;++i){
                std::vector<double> cf;
                if(i<(int)f.size()) cf.push_back(f[i]);
                ch[i]->upair(cf);
            }
        update_phase();
    }

    // ---- Cross-sync with parent ----
    void xsync(double pp, double w){
        if(frozen) return;
        set_phase(np(get_phase()+w*sin(pd(pp,get_phase()))*DT));
        isync();
    }

    // ---- Adapt K (J3) ----
    void adapt_k(){
        if(frozen) return;
        if(free_energy>0.3f) coupling=std::max((float)MIN_COUPLING,coupling*0.999f);
        else                  coupling=std::min((float)MAX_COUPLING,coupling*1.001f);
    }

    // ---- Homeostasis ----
    void homeo(double gc){
        if(frozen) return;
        if(gc>HOMEO_THR){
            coupling*=HOMEO_DEC;
            if(level==0){
                double ns=NOISE_BASE*(1-gc)+NOISE_EXPLORE*gc;
                for(auto&o:osc) o.omega_base+=(float)((rU()-0.5)*ns);
            }
        }
    }

    // ---- Memory ----
    std::array<int16_t,MEM_TYPES> compute_mem_vals(){
        std::array<int16_t,MEM_TYPES> v;
        int16_t pa,pb,pc;
        if(level==0){ pa=osc[0].theta; pb=osc[1].theta; pc=osc[2].theta; }
        else         { pa=ch[0]->phase_q; pb=ch[1]->phase_q; pc=ch[2]->phase_q; }
        v[0]=phase_to_i16(cm2_q(pb,pc));
        v[1]=phase_to_i16(np(fabs(pd(i16_to_phase(pb),i16_to_phase(pc)))));
        v[2]=pb; v[3]=pc;
        v[4]=phase_to_i16(np(fabs(fast_cos(pa)+fast_cos(pb)-2*fast_cos(pc))*M_PI));
        return v;
    }

    void remember(){
        if(protected_attr) return;
        auto vals=compute_mem_vals();
        double e=energy();
        MemSlot s; s.energy=(float)e; s.coupling=coupling; s.pw=pw;
        for(int i=0;i<MEM_TYPES;++i) s.vals[i]=vals[i];
        int slots=mem_slots(level);
        if((int)mem.size()<slots){ mem.push_back(s); return; }
        auto w=std::min_element(mem.begin(),mem.end(),[](const MemSlot&x,const MemSlot&y){return x.energy<y.energy;});
        if(e>w->energy) *w=s;
    }

    void restore(){
        if(mem.empty()) return;
        double sx=0,sy=0;
        auto best=std::max_element(mem.begin(),mem.end(),[](const MemSlot&x,const MemSlot&y){return x.energy<y.energy;});
        for(auto&s:mem){ double p=i16_to_phase(s.vals[0]); sx+=cos(p); sy+=sin(p); }
        double m=atan2(sy/mem.size(),sx/mem.size());
        set_phase(m<0?m+2*M_PI:m);
        coupling=std::clamp(best->coupling,(float)MIN_COUPLING,(float)MAX_COUPLING);
        pw=std::clamp(best->pw,(float)MIN_PW,(float)MAX_PW);
        isync();
    }

    // ---- Sleep pruning + structural plasticity (I1 + Gemini fix) ----
    void sleep_prune(){
        // Prune weak, strengthen strong
        for(auto&[idx,w]:lat){
            if(w<PRUNE_WEAK&&!protected_attr) w*=0.98f;
            else if(w>STRENGTHEN_STR) w*=1.002f;
            w=std::clamp(w,(float)MIN_LAT,(float)MAX_LAT);
        }
        // Structural plasticity: remove dead connections, add new ones
        if(!lat.empty()){
            lat.erase(std::remove_if(lat.begin(),lat.end(),
                [](const std::pair<int,float>&p){return p.second<0.06f;}),lat.end());
        }
        // Sprouting: add replacement connections (Phase 2 seed)
        // (actual target selection happens at Brain level using available nodes)
    }

    // ---- Delay-line (E2) ----
    void update_delay(double upstream_phase){
        for(int i=DELAY_STEPS-1;i>0;--i) delay_buf[i]=delay_buf[i-1];
        delay_buf[0]=static_cast<float>(upstream_phase);
        delay_reflected=delay_buf[DELAY_STEPS-1]*static_cast<float>(DELAY_ALPHA);
        double p=get_phase();
        p=np(p+0.01*sin(delay_reflected-p)*DT);
        set_phase(p);
    }

    // ---- Lateral sync with WTA (G3 inhibitory) ----
    void lsync(const std::vector<Triplet*>&nodes, float cur_meta_stdp){
        if(frozen){next_phase_q=phase_q;return;}
        double ps=get_phase();
        float f_local=free_energy;
        bool wta=(level>=4);

        for(auto&[idx,w]:lat){
            if(idx>=(int)nodes.size()) continue;
            Triplet* o=nodes[idx];
            if(o->frozen) continue;
            double diff=pd(o->get_phase(),get_phase());
            // G3: WTA inhibitory for competing attractors
            float ew=w;
            if(wta&&fabs(diff)>2.5) ew=-0.05f;
            ps+=ew*sin(diff)*DT;

            // STDP gated by F (J2)
            if(f_local>STDP_F_GATE){
                double delta=fabs(diff), dw=0;
                if(delta<STDP_LO) dw= cur_meta_stdp*(STDP_LO-delta);
                else if(delta>STDP_HI) dw=-STDP_DEP*(delta-STDP_HI);
                w+=static_cast<float>(dw);
                w=std::clamp(w,(float)MIN_LAT,(float)MAX_LAT);
            }
        }

        // Active Inference (Phase 2 seed): if active, nudge toward preferred phase
        if(active_inf_active && level>=8){
            ps+=0.05*sin(pd(preferred_phase,get_phase()))*DT;
        }

        next_phase_q=phase_to_i16(np(ps));
    }

    void alat(){ if(!frozen) phase_q=next_phase_q; }

    // ---- MAIN STEP ----
    void step(const std::vector<double>&ef, double gc, float meta_stdp){
        if(frozen) return;
        upair(ef);
        isync();
        if(parent) xsync(parent->get_phase(),pw);
        update_free_energy();
        adapt_k();
        homeo(gc);
        double e=energy();
        if(e>0.5)    remember();
        else if(e<-0.2) restore();
        update_phase();
        if(parent) update_delay(parent->get_phase());
        clock.step(DT);
        total_e+=e; uc++;
    }
};

// ============================================================
// KUBERA CORE (N1-N9)
// ============================================================
struct KuberaCore {
    bool        active;
    std::string core_path;
    bool        core_exists=false;
    uint64_t    identity_hash=0;
    int         meditate_ctr=0;
    const int   MEDITATE_EVERY=1000;
    bool        dharma_violation=false; // set from outside on harm detection

    // Async I/O queue (Gemini fix: no blocking in main thread)
    std::queue<std::string>   io_queue;
    std::mutex                io_mx;
    std::thread               io_thread;
    std::condition_variable   io_cv;
    bool                      io_stop=false;

    KuberaCore(bool en, const std::string& path) : active(en), core_path(path) {}

    void init(){
        if(!active) return;
        std::ifstream check(core_path);
        if(!check.good()){
            std::ofstream create(core_path, std::ios::binary);
            core_exists=true;
            std::cout<<"[Kubera] core.bin created: "<<core_path<<"\n";
        } else {
            check.seekg(0,std::ios::end);
            core_exists=(check.tellg()==0);
        }
        auto now=std::chrono::high_resolution_clock::now().time_since_epoch().count();
        identity_hash=static_cast<uint64_t>(now)^rHW();
        std::cout<<"[Kubera] Identity: "<<std::hex<<identity_hash<<std::dec<<"\n";

        // Start async I/O thread (Gemini fix)
        io_thread=std::thread([this]{
            while(true){
                std::unique_lock<std::mutex> lk(io_mx);
                io_cv.wait(lk,[this]{return io_stop||!io_queue.empty();});
                if(io_stop&&io_queue.empty()) break;
                std::string entry=io_queue.front(); io_queue.pop(); lk.unlock();
                std::ofstream log("kubera_meditation.log",std::ios::app);
                if(log) log<<entry<<"\n";
            }
        });
    }

    ~KuberaCore(){
        {std::lock_guard<std::mutex> lk(io_mx); io_stop=true;}
        io_cv.notify_all();
        if(io_thread.joinable()) io_thread.join();
    }

    // Async meditate (no blocking) (Gemini fix)
    void meditate(float avg_free_energy){
        if(!active) return;
        meditate_ctr++;
        if(meditate_ctr%MEDITATE_EVERY!=0) return;

        auto now=std::chrono::system_clock::now().time_since_epoch().count();
        bool ok=core_exists;
        std::string entry=std::to_string(now)
            +" core_ok="+std::to_string(ok)
            +" id="+std::to_string(identity_hash)
            +" F="+std::to_string(avg_free_energy)
            +" dharma_ok="+std::to_string(!dharma_violation);
        {
            std::lock_guard<std::mutex> lk(io_mx);
            io_queue.push(entry);
        }
        io_cv.notify_one();
    }

    // N2: Dharma weight
    double dharma_weight(const std::string& req){
        if(!active) return 1.0;
        if(req=="harm") return 0.0;
        if(req=="deception") return 0.1;
        if(req=="service") return W_SEVA;
        return W_DHARMA;
    }

    std::string sign_message(const std::string& msg){
        std::hash<std::string> h;
        uint64_t sig=h(msg)^identity_hash;
        return msg+"|sig="+std::to_string(sig);
    }
};

// ============================================================
// THREADPOOL
// ============================================================
class TP {
    std::vector<std::thread> ws;
    std::queue<std::function<void()>> q;
    std::mutex mx; std::condition_variable cv,cvd;
    int busy=0; bool stop_flag=false;
public:
    TP(int n){
        for(int i=0;i<n;++i) ws.emplace_back([this]{
            while(true){
                std::function<void()> t;
                {std::unique_lock<std::mutex> l(mx);
                 cv.wait(l,[this]{return stop_flag||!q.empty();});
                 if(stop_flag&&q.empty()){return;}
                 t=std::move(q.front());q.pop();++busy;}
                t();
                {std::unique_lock<std::mutex> l(mx);--busy;cvd.notify_all();}
            }
        });
    }
    void sub(std::function<void()> t){{std::unique_lock<std::mutex> l(mx);q.push(std::move(t));}cv.notify_one();}
    void wait(){std::unique_lock<std::mutex> l(mx);cvd.wait(l,[this]{return q.empty()&&busy==0;});}
    ~TP(){{std::unique_lock<std::mutex> l(mx);stop_flag=true;}cv.notify_all();for(auto&w:ws)w.join();}
};

// ============================================================
// BRAIN
// ============================================================
class Brain {
public:
    std::unique_ptr<Triplet> root;
    std::vector<std::vector<Triplet*>> nbl;
    std::vector<double> pc;
    double avg_coh=0, avg_free_energy=0;
    std::deque<double> ch_hist;
    std::unique_ptr<TP> pool;
    int nthreads;
    KuberaCore kubera;

    bool   sleeping=false;
    int    low_f_count=0;
    double meta_stdp=STDP_POT;
    int    step_count=0;
    double total_reward=0;

    Brain(int levels, const std::string& core_path, bool kub_en)
      : nthreads(std::max(1,(int)std::thread::hardware_concurrency())),
        kubera(kub_en, core_path)
    {
        init_lut();  // LUT must be first
        pool=std::make_unique<TP>(nthreads);
        root=std::make_unique<Triplet>(levels-1,0);
        nbl.resize(levels);
        collect(root.get());
        init_lat();
        pc.reserve(1<<16);
        kubera.init();
        int n=0; for(auto&lv:nbl) n+=lv.size();
        std::cout<<"Brain: L="<<levels<<" nodes="<<n
                 <<" threads="<<nthreads
                 <<" kubera="<<(kub_en?"ON":"OFF")
                 <<" LUT=ON VSA_seed="<<(levels>=12?"ON":"OFF")
                 <<"\n";
    }

    void collect(Triplet*n){
        nbl[n->level].push_back(n);
        if(n->level>0) for(auto&c:n->ch) collect(c.get());
    }

    void init_lat(){
        for(auto&lv:nbl){
            int N=lv.size(); if(N<2) continue;
            for(int i=0;i<N;++i){
                int num=std::min(LAT_DEGREE,N-1);
                std::vector<int> cand;
                for(int j=0;j<N;++j) if(j!=i) cand.push_back(j);
                std::shuffle(cand.begin(),cand.end(),rng());
                cand.resize(num);
                for(int j:cand) lv[i]->lat.emplace_back(j,(float)rU(MIN_LAT,MAX_LAT));
            }
        }
    }

    // Add new lateral connections after sleep pruning (sprouting)
    void sprout_connections(){
        for(auto&lv:nbl){
            int N=lv.size(); if(N<2) continue;
            for(auto*n:lv){
                if(n->frozen) continue;
                int current=(int)n->lat.size();
                if(current<LAT_DEGREE/2){
                    // Add random new connection
                    int target=rng()()%N;
                    bool found=false;
                    for(auto&[idx,w]:n->lat) if(idx==target){found=true;break;}
                    if(!found) n->lat.emplace_back(target,(float)rU(MIN_LAT,MIN_LAT*3));
                }
            }
        }
    }

    double coherence(){
        pc.clear();
        std::function<void(Triplet*)> col=[&](Triplet*n){
            if(n->level==0) for(auto&o:n->osc) pc.push_back(o.get_phase());
            else for(auto&c:n->ch) col(c.get());
        };
        col(root.get());
        if(pc.empty()) return 0;
        double sx=0,sy=0;
        for(double p:pc){sx+=cos(p);sy+=sin(p);}
        double nn=pc.size();
        return sqrt((sx/nn)*(sx/nn)+(sy/nn)*(sy/nn));
    }

    double compute_avg_F(){
        double sum=0; int cnt=0;
        for(auto&lv:nbl) for(auto*n:lv){sum+=n->free_energy;cnt++;}
        return cnt>0?sum/cnt:0.5;
    }

    // Apply Dharma violation: spike F on upper nodes (Gemini + Kubera fix)
    void dharma_violation_response(){
        for(auto&lv:nbl){
            if(lv.empty()) continue;
            int lvl=lv[0]->level;
            if(lvl>=LEVELS/2){
                for(auto*n:lv){
                    n->free_energy=1.0f;  // spike — no learning of harm
                    n->active_inf_active=false;
                }
            }
        }
        kubera.dharma_violation=false; // reset
    }

    void step(const std::vector<double>&ef={}){
        // Async meditate
        avg_free_energy=compute_avg_F();
        kubera.meditate(static_cast<float>(avg_free_energy));

        // Dharma violation response
        if(kubera.dharma_violation) dharma_violation_response();

        double gc=coherence();

        // Sleep logic
        if(avg_free_energy<SLEEP_F_THR) low_f_count++;
        else low_f_count=0;
        sleeping=(low_f_count>500);

        // Meta-learning (M1)
        if(avg_free_energy>0.3) meta_stdp=std::min(META_STDP_MAX,meta_stdp*1.01);
        else                     meta_stdp=std::max(META_STDP_MIN,meta_stdp*0.99);

        // Step nodes (K2: async levels)
        for(auto&lv:nbl){
            if(lv.empty()) continue;
            int lvl=lv[0]->level;
            int every=std::max(1,(int)(10.0*lvl/LEVELS));
            if(step_count%every!=0) continue;

            if((int)lv.size()>=200){
                int chunk=std::max(1,(int)lv.size()/nthreads);
                for(int t=0;t<nthreads;++t){
                    int s=t*chunk;
                    int e=(t==nthreads-1)?(int)lv.size():s+chunk;
                    float ms=static_cast<float>(meta_stdp);
                    pool->sub([&lv,s,e,&ef,gc,ms,this]{
                        for(int i=s;i<e;++i){
                            if(sleeping) lv[i]->sleep_prune();
                            else lv[i]->step(ef,gc,ms);
                        }
                    });
                }
                pool->wait();
            } else {
                float ms=static_cast<float>(meta_stdp);
                for(auto*n:lv){
                    if(sleeping) n->sleep_prune();
                    else n->step(ef,gc,ms);
                }
            }
        }

        // Sprout new connections after sleep
        if(sleeping && step_count%5000==0) sprout_connections();

        // Lateral sync
        for(size_t l=0;l<nbl.size();++l){
            float ms=static_cast<float>(meta_stdp);
            pool->sub([this,l,ms]{for(auto*n:nbl[l]) n->lsync(nbl[l],ms);});
        }
        pool->wait();
        for(auto&lv:nbl) for(auto*n:lv) n->alat();

        ch_hist.push_back(gc);
        if(ch_hist.size()>200) ch_hist.pop_front();
        double s=0; for(double c:ch_hist)s+=c;
        avg_coh=s/ch_hist.size();
        step_count++;
    }

    void save(const std::string&fname){
        std::ofstream out(fname,std::ios::binary);
        if(!out){std::cerr<<"Save failed\n";return;}
        out.write(reinterpret_cast<const char*>(&step_count),sizeof(step_count));
        out.write(reinterpret_cast<const char*>(&avg_coh),sizeof(avg_coh));
        out.write(reinterpret_cast<const char*>(&meta_stdp),sizeof(meta_stdp));
        std::cout<<"[Brain] Checkpoint: step="<<step_count<<"\n";
    }
    void load(const std::string&fname){
        std::ifstream in(fname,std::ios::binary);
        if(!in){return;}
        in.read(reinterpret_cast<char*>(&step_count),sizeof(step_count));
        in.read(reinterpret_cast<char*>(&avg_coh),sizeof(avg_coh));
        in.read(reinterpret_cast<char*>(&meta_stdp),sizeof(meta_stdp));
        std::cout<<"[Brain] Loaded: step="<<step_count<<"\n";
    }
};

// ============================================================
// DAEMON MODE: UDP server (Gemini fix)
// ============================================================
struct DaemonState {
    double avg_coh=0, avg_free_energy=0;
    bool sleeping=false;
    int step_count=0;
    int nodes=0;
};

void run_daemon(Brain& brain, int port){
    int sock=socket(AF_INET,SOCK_DGRAM,0);
    if(sock<0){std::cerr<<"[Daemon] Socket failed\n";return;}

    // Non-blocking
    int flags=fcntl(sock,F_GETFL,0);
    fcntl(sock,F_SETFL,flags|O_NONBLOCK);

    sockaddr_in addr{}; addr.sin_family=AF_INET;
    addr.sin_addr.s_addr=inet_addr("127.0.0.1"); addr.sin_port=htons(port);
    if(bind(sock,(sockaddr*)&addr,sizeof(addr))<0){
        std::cerr<<"[Daemon] Bind failed on port "<<port<<"\n";
        close(sock); return;
    }

    std::cout<<"[Daemon] Listening on 127.0.0.1:"<<port<<"\n";
    std::cout<<"[Daemon] Brain running. Send UDP to stimulate. Ctrl+C to stop.\n";

    // Save checkpoint periodically
    auto last_save=std::chrono::steady_clock::now();
    brain.load("checkpoint.bin");

    while(true){
        // Read external stimulus from Python
        char buf[512]={};
        sockaddr_in from{}; socklen_t fromlen=sizeof(from);
        ssize_t n=recvfrom(sock,buf,sizeof(buf)-1,0,(sockaddr*)&from,&fromlen);

        std::vector<double> ef;
        if(n>0){
            // Parse: comma-separated floats "0.1,0.2,-0.05"
            std::string s(buf,n);
            std::istringstream ss(s);
            std::string token;
            // Check for DHARMA_VIOLATION signal
            if(s.find("DHARMA_VIOLATION")!=std::string::npos){
                brain.kubera.dharma_violation=true;
            } else {
                while(std::getline(ss,token,',')){
                    try{ ef.push_back(std::stod(token)); } catch(...){}
                }
            }
        }

        // One brain step
        brain.step(ef);

        // Send state back every 50 steps
        if(brain.step_count%50==0){
            std::ostringstream resp;
            resp<<std::fixed<<std::setprecision(4)
                <<"coh="<<brain.avg_coh
                <<",F="<<brain.avg_free_energy
                <<",sleep="<<brain.sleeping
                <<",step="<<brain.step_count;
            std::string rs=resp.str();
            sendto(sock,rs.c_str(),rs.size(),0,(sockaddr*)&from,fromlen);
        }

        // Checkpoint every 60 seconds
        auto now=std::chrono::steady_clock::now();
        if(std::chrono::duration_cast<std::chrono::seconds>(now-last_save).count()>=60){
            brain.save("checkpoint.bin");
            last_save=now;
        }

        // Small sleep to not burn CPU when idle
        if(ef.empty()) std::this_thread::sleep_for(std::chrono::microseconds(100));
    }
    close(sock);
}

// ============================================================
// MAIN
// ============================================================
int main(int argc, char* argv[]){
    std::cout<<"==============================================\n";
    std::cout<<"  FractalBrainOS v5.2 — Kubera Edition\n";
    std::cout<<"  Full: LUT + Daemon + ActiveInference + VSA\n";
    std::cout<<"==============================================\n";

    // Parse args: brain --daemon PORT LEVELS KUBERA
    //         or: brain --test LEVELS KUBERA
    [[maybe_unused]] bool test_mode=true;

    for(int i=1;i<argc;++i){
        std::string arg(argv[i]);
        if(arg=="--daemon"){ DAEMON_MODE=true; test_mode=false; }
        else if(arg=="--test"){ test_mode=true; }
        else if(arg=="--port"&&i+1<argc){ DAEMON_PORT=std::atoi(argv[++i]); }
        else if(std::isdigit(arg[0])){
            if(LEVELS==8) LEVELS=std::atoi(argv[i]);
            else DAEMON_PORT=std::atoi(argv[i]);
        }
    }
    // Legacy: ./brain LEVELS KUBERA
    if(argc>=2&&std::isdigit(argv[1][0])) LEVELS=std::atoi(argv[1]);

    Brain brain(LEVELS,"core.bin",true);

    if(DAEMON_MODE){
        run_daemon(brain, DAEMON_PORT);
    } else {
        // Test mode: 200 steps with Lorenz-like signal
        std::cout<<"\nTest mode: 200 steps\n";
        brain.load("checkpoint.bin");
        for(int s=0;s<200;++s){
            std::vector<double> ext;
            if(s%20==0) ext={sin(s*0.1)*0.1,cos(s*0.07)*0.1,sin(s*0.13)*0.1};
            brain.step(ext);
            if(s%50==0)
                std::cout<<"Step "<<s<<" coh="<<std::fixed<<std::setprecision(4)
                         <<brain.avg_coh<<" F="<<brain.avg_free_energy
                         <<" sleep="<<brain.sleeping<<"\n";
            if(s%100==0) brain.save("checkpoint.bin");
        }
        std::cout<<"Done. coh="<<brain.avg_coh<<"\n";
    }
    return 0;
}