#!/usr/bin/env python3
"""
timed_router.py

Elevated from R&D (flowtorch_quantum_bridge.py).

Technical function:
- Band-based async routing using EEG-like frequencies
- Phase-aligned delays for packet delivery
- Four routing modes: drift, reflection, morphing, fusion

Notes:
- This is not "quantum", it's a timed async router.
- Uses actual EEG band frequencies for timing windows.
- Integrated as OPTIONAL async routing layer.
"""

import asyncio
import json
import base64
import time
import math
import hashlib
from pathlib import Path
from typing import Dict, Optional, List
from datetime import datetime


class DriftClock:
    """
    Fibonacci-based phase clock for timing synchronization.

    Generates phase values using Fibonacci sequence increments.
    """

    def __init__(self):
        self.phase = 0.0
        self.tick_count = 0
        self.fib_sequence = [1, 1]
        self.start_time = time.time()

    def tick(self) -> float:
        """
        Advance clock by Fibonacci increment.

        Returns:
            Current phase value
        """
        self.tick_count += 1

        # Extend Fibonacci sequence if needed
        if self.tick_count >= len(self.fib_sequence):
            self.fib_sequence.append(
                self.fib_sequence[-1] + self.fib_sequence[-2]
            )

        # Update phase based on Fibonacci value
        fib_value = self.fib_sequence[self.tick_count % len(self.fib_sequence)]
        self.phase = (self.phase + fib_value * 0.01) % (2 * math.pi)

        return self.phase

    def get_phase(self) -> float:
        """
        Get current phase (auto-ticks based on elapsed time).

        Returns:
            Current phase value
        """
        # Auto-tick based on elapsed time
        elapsed = time.time() - self.start_time
        ticks_needed = int(elapsed * 10)  # 10 ticks per second

        while self.tick_count < ticks_needed:
            self.tick()

        return self.phase


class TimedRouter:
    """
    Asynchronous packet router with EEG frequency-based timing.

    Routes packets to different destinations based on their "band" (frequency).
    Uses phase-aligned delays to create resonance windows.
    """

    def __init__(self,
                 drift_pool_dir: Optional[Path] = None,
                 jazzbridge_url: str = "http://localhost:11434"):
        """
        Initialize timed router.

        Args:
            drift_pool_dir: Directory for drift pool storage
            jazzbridge_url: URL for JazzBridge morphing API
        """
        self.drift_pool_dir = drift_pool_dir or Path.home() / "echo-ecosystem" / "brain" / "drift_pool"
        self.jazzbridge_url = jazzbridge_url

        self.resonance_cache: Dict[str, float] = {}
        self.entanglements: Dict[str, Dict] = {}
        self.drift_clock = DriftClock()

        # EEG-based band frequencies (Hz)
        self.band_frequencies = {
            "theta": 6.0,    # 4-8 Hz center - Subconscious/drift
            "alpha": 10.5,   # 8-13 Hz center - Reflection
            "beta": 21.5,    # 13-30 Hz center - Active processing
            "gamma": 65.0    # 30-100 Hz center - Insight/fusion
        }

    def calculate_resonance_delay(self, frequency: float, phase: float) -> float:
        """
        Calculate delay until next resonance window.

        Args:
            frequency: Target frequency in Hz
            phase: Current phase (0 to 2π)

        Returns:
            Delay in seconds (capped at 100ms)
        """
        period = 1.0 / frequency
        phase_offset = (phase % (2 * math.pi)) / (2 * math.pi)
        delay = period * (1 - phase_offset)

        return min(delay, 0.1)  # Cap at 100ms

    def generate_entanglement_id(self, packet: Dict) -> str:
        """
        Generate entanglement ID for packet pairing.

        Args:
            packet: Packet dict with quantum_signature

        Returns:
            Entanglement ID string
        """
        signature = packet["sym_header"]["quantum_signature"]
        timestamp = str(time.time())
        phase = str(self.drift_clock.phase)

        entanglement = hashlib.sha256(
            f"{signature}{timestamp}{phase}".encode()
        ).hexdigest()[:16]

        return f"QE-{entanglement}"

    async def vibrate_packet(self, packet: Dict) -> Dict:
        """
        Apply resonance delay to packet based on its band.

        Waits for phase-aligned timing window before "materializing" packet.

        Args:
            packet: Packet dict with sym_header.band

        Returns:
            Packet with quantum_state metadata added
        """
        band = packet["sym_header"]["band"]
        frequency = self.band_frequencies[band]

        # Calculate resonance timing
        vibration_phase = self.drift_clock.get_phase()
        resonance_delay = self.calculate_resonance_delay(frequency, vibration_phase)

        # Wait for resonance window
        await asyncio.sleep(resonance_delay)

        # Add quantum state metadata
        packet["quantum_state"] = {
            "materialized_at": time.time(),
            "phase": vibration_phase,
            "resonance_frequency": frequency,
            "entanglement_id": self.generate_entanglement_id(packet)
        }

        return packet

    async def route_to_drift_pool(self, packet: Dict) -> Dict:
        """
        Route theta packets to drift pool (disk storage).

        Args:
            packet: Packet to route

        Returns:
            Routing result metadata
        """
        packet = await self.vibrate_packet(packet)

        # Store in drift pool for pattern emergence
        self.drift_pool_dir.mkdir(parents=True, exist_ok=True)

        pool_file = self.drift_pool_dir / f"drift_{int(time.time()*1000)}.json"
        with open(pool_file, 'w') as f:
            json.dump(packet, f)

        return {
            "status": "drifting",
            "location": "subconscious_pool",
            "file": str(pool_file),
            "emergence_eta": time.time() + 300  # 5 minutes
        }

    def generate_bloom_signature(self, packet: Dict) -> str:
        """
        Generate Bloom filter-compatible signature.

        Args:
            packet: Packet with payload_template.data

        Returns:
            Bloom signature string
        """
        data = json.dumps(packet["payload_template"]["data"])

        # Multiple hash functions for Bloom filter
        hashes = []
        for i in range(3):
            h = hashlib.sha256(f"{data}{i}".encode()).hexdigest()
            hashes.append(h[:8])

        return "-".join(hashes)

    def find_resonance_matches(self, packet: Dict) -> List[str]:
        """
        Find packets with matching resonance frequencies.

        Args:
            packet: Packet with drift_params.resonance_freq

        Returns:
            List of matching packet IDs
        """
        target_freq = packet["drift_params"]["resonance_freq"]
        tolerance = 0.1  # 10% frequency tolerance

        matches = []
        for cached_id, cached_freq in self.resonance_cache.items():
            if abs(cached_freq - target_freq) / target_freq < tolerance:
                matches.append(cached_id)

        return matches[:5]  # Top 5 matches

    async def route_to_bloom_cortex(self, packet: Dict) -> Dict:
        """
        Route alpha packets to Bloom Cortex for reflection.

        Args:
            packet: Packet to route

        Returns:
            Routing result with reflection metadata
        """
        packet = await self.vibrate_packet(packet)

        # Alpha state enables reflection and pattern matching
        reflection = {
            "original": packet,
            "reflected_at": time.time(),
            "bloom_signature": self.generate_bloom_signature(packet),
            "resonance_matches": self.find_resonance_matches(packet)
        }

        return {
            "status": "reflected",
            "location": "bloom_cortex",
            "reflection": reflection
        }

    async def route_to_jazzbridge(self, packet: Dict) -> Dict:
        """
        Route beta packets through JazzBridge morphing API.

        Args:
            packet: Packet to route

        Returns:
            Routing result with morph metadata
        """
        packet = await self.vibrate_packet(packet)

        # Encode packet for morphing
        packet_data = json.dumps(packet).encode()
        packet_b64 = base64.b64encode(packet_data).decode()

        # Mock JazzBridge call (no actual HTTP)
        # In production, would use httpx.AsyncClient
        return {
            "status": "morphed",
            "location": "jazzbridge",
            "morph_id": f"MORPH-{int(time.time())}",
            "note": "HTTP call disabled in production bridge"
        }

    def find_entangled_packets(self, entanglement_id: str) -> List[Dict]:
        """
        Find packets with matching entanglement ID prefix.

        Args:
            entanglement_id: Entanglement ID to match

        Returns:
            List of entangled packet dicts
        """
        # Simple entanglement based on ID prefix matching
        prefix = entanglement_id[:8]

        entangled = []
        for eid, packet in self.entanglements.items():
            if eid.startswith(prefix) and eid != entanglement_id:
                entangled.append(packet)

        return entangled

    def perform_fusion(self, primary: Dict, candidates: List[Dict]) -> Dict:
        """
        Fuse gamma packets to generate insights.

        Args:
            primary: Primary packet
            candidates: List of packets to fuse with

        Returns:
            Fusion result metadata
        """
        # Combine packet data
        combined_data = {
            "primary": primary["payload_template"]["data"],
            "fused_with": [c["payload_template"]["data"] for c in candidates],
            "fusion_timestamp": time.time(),
            "resonance_product": primary["drift_params"]["resonance_freq"] * len(candidates)
        }

        # Generate insight signature
        insight = {
            "type": "quantum_fusion",
            "data": combined_data,
            "emergence_level": len(candidates) + 1,
            "signature": hashlib.sha256(json.dumps(combined_data).encode()).hexdigest()[:16]
        }

        return insight

    async def route_to_fusion(self, packet: Dict) -> Dict:
        """
        Route gamma packets for fusion events.

        Args:
            packet: Packet to route

        Returns:
            Routing result with fusion metadata
        """
        packet = await self.vibrate_packet(packet)

        entanglement_id = packet["quantum_state"]["entanglement_id"]

        # Find entangled pairs for fusion
        fusion_candidates = self.find_entangled_packets(entanglement_id)

        if fusion_candidates:
            # Perform symbolic fusion
            fusion_result = self.perform_fusion(packet, fusion_candidates)

            return {
                "status": "fused",
                "location": "quantum_fusion",
                "fusion_result": fusion_result,
                "insight_generated": True
            }
        else:
            # Store for future fusion
            self.entanglements[entanglement_id] = packet

            return {
                "status": "awaiting_entanglement",
                "location": "quantum_fusion",
                "entanglement_id": entanglement_id
            }

    async def route_packet(self, packet: Dict) -> Dict:
        """
        Route packet based on its band.

        Args:
            packet: Packet with sym_header.band

        Returns:
            Routing result dict

        Raises:
            ValueError: If band is unknown
        """
        band = packet["sym_header"]["band"]

        if band == "theta":
            return await self.route_to_drift_pool(packet)
        elif band == "alpha":
            return await self.route_to_bloom_cortex(packet)
        elif band == "beta":
            return await self.route_to_jazzbridge(packet)
        elif band == "gamma":
            return await self.route_to_fusion(packet)
        else:
            raise ValueError(f"Unknown band: {band}")
