# queen_orchestrator.py
import time
import datetime
import json
import subprocess
import os
import threading

# Configuration constants (from QUEEN_ELEVATION_SPRINT_PLAN.md and GENESIS_COMPLETE_PACKAGE.md)
SPRINT_ID = "QUEEN-ELEVATION-2026-01-11"
TOTAL_BUDGET = 10.00
EMERGENCY_STOP_BUDGET = 9.50
GEMINI_FLASH_INPUT_COST = 0.0001 # $0.10/1M tokens
GEMINI_FLASH_OUTPUT_COST = 0.0004 # $0.40/1M tokens
NUM_AGENTS = 50
HOURS_PER_PHASE = 2
TOTAL_HOURS = 10
CHECKPOINTS = {
    "hour_2": "sprint-checkpoints/phase-1-foundation.json",
    "hour_4": "sprint-checkpoints/phase-2-knowledge.json",
    "hour_6": "sprint-checkpoints/phase-3-capabilities.json",
    "hour_8": "sprint-checkpoints/phase-4-swarm.json",
    "hour_10": "sprint-checkpoints/phase-5-coronation.json"
}

# Infrastructure Constants
REDIS_HOST = "redis-genesis-u50607.vm.elestio.app"
REDIS_PORT = 26379
OLLAMA_URL = "http://152.53.201.152:23405"
POSTGRES_HOST = "postgresql-genesis-u50607.vm.elestio.app"
POSTGRES_USER = "postgres"  # Assuming default user
POSTGRES_DB = "genesis_memory"
QDRANT_URL = "https://qdrant-b3knu-u50607.vm.elestio.app:6333"
QDRANT_PORT = 6333
SSH_KEY_PATH = "~/.ssh/genesis_mother_key"

# Global Variables
current_phase = 1
current_hour = 0.0
budget_spent = 0.0
input_tokens_consumed = 0
output_tokens_generated = 0
active_agents = 0
completed_agents = 0
pending_agents = NUM_AGENTS
failed_agents = 0
checkpoint_status = {f"Phase {i+1}": " " for i in range(5)}  # Initialize checkpoint status

# Agent Registry (Simplified - Adjust as needed based on actual agent implementation)
agent_status = {f"AGENT_{i:02d}": "pending" for i in range(1, NUM_AGENTS + 1)} # pending, active, completed, failed

# Lock for thread-safe operations
data_lock = threading.Lock()

# Helper Functions
def log(message):
    """Logs messages with timestamp."""
    timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    print(f"[{timestamp}] {message}")

def execute_bash_command(command):
    """Executes a bash command and returns the output."""
    try:
        result = subprocess.run(command, shell=True, capture_output=True, text=True, check=True)
        return result.stdout.strip()
    except subprocess.CalledProcessError as e:
        log(f"Error executing command: {e}")
        return None

def load_checkpoint(checkpoint_file):
    """Loads a checkpoint from a JSON file."""
    try:
        with open(checkpoint_file, "r") as f:
            return json.load(f)
    except FileNotFoundError:
        log(f"Checkpoint file not found: {checkpoint_file}")
        return None
    except json.JSONDecodeError:
        log(f"Invalid JSON in checkpoint file: {checkpoint_file}")
        return None

def save_checkpoint(checkpoint_file, data):
    """Saves data to a checkpoint file."""
    try:
        os.makedirs(os.path.dirname(checkpoint_file), exist_ok=True)  # Ensure directory exists
        with open(checkpoint_file, "w") as f:
            json.dump(data, f, indent=4)
        log(f"Checkpoint saved to {checkpoint_file}")
    except Exception as e:
        log(f"Error saving checkpoint: {e}")

def update_token_usage(input_tokens, output_tokens):
    """Updates the token usage and budget."""
    global input_tokens_consumed, output_tokens_generated, budget_spent

    with data_lock:
        input_tokens_consumed += input_tokens
        output_tokens_generated += output_tokens
        budget_spent += (input_tokens * GEMINI_FLASH_INPUT_COST + output_tokens * GEMINI_FLASH_OUTPUT_COST) / 1000000.0

def get_token_usage_status():
    """Returns a formatted string with the token usage status."""
    remaining_budget = max(0, TOTAL_BUDGET - budget_spent) # Ensure remaining budget doesn't go negative
    rate = budget_spent / current_hour if current_hour > 0 else 0.0  # Calculate hourly rate
    total_tokens = input_tokens_consumed + output_tokens_generated
    percent_tokens_used = (total_tokens / 53750000) * 100 if 53750000 > 0 else 0  # Calculate percentage of tokens used.

    status = f"""
╔══════════════════════════════════════════════════════════════════╗
║                    AIVA QUEEN SPRINT - TOKEN STATUS              ║
╠══════════════════════════════════════════════════════════════════╣
║ Time: {datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")} | Phase: {current_phase}/5 | Hour: {current_hour:.1f}/{TOTAL_HOURS}            ║
╠══════════════════════════════════════════════════════════════════╣
║ BUDGET                                                           ║
║ ├── Total: ${TOTAL_BUDGET:.2f}                                                ║
║ ├── Spent: ${budget_spent:.2f} ({budget_spent/TOTAL_BUDGET*100:.1f}%)                                         ║
║ ├── Remaining: ${remaining_budget:.2f}                                             ║
║ └── Rate: ${rate:.2f}/hr                                               ║
╠══════════════════════════════════════════════════════════════════╣
║ TOKENS                                                           ║
║ ├── Input:  {input_tokens_consumed/1000000:.1f}M tokens consumed                                ║
║ ├── Output: {output_tokens_generated/1000000:.1f}M tokens generated                                ║
║ └── Total:  {total_tokens/1000000:.1f}M / 53.75M ({percent_tokens_used:.1f}%)                              ║
╠══════════════════════════════════════════════════════════════════╣
║ AGENTS                                                           ║
║ ├── Active: {active_agents}/{NUM_AGENTS}                                                ║
║ ├── Completed: {completed_agents}/{NUM_AGENTS}                                             ║
║ ├── Pending: {pending_agents}/{NUM_AGENTS}                                                ║
║ └── Failed: {failed_agents}/{NUM_AGENTS}                                                 ║
╠══════════════════════════════════════════════════════════════════╣
║ CHECKPOINTS                                                      ║
"""
    for phase, status_char in checkpoint_status.items():
        status += f"║ ├── [{status_char}] {phase}: (Hour {(int(phase.split()[1])-1)*2 + 2}){' - IN PROGRESS' if status_char == '◐' else ''}\n"

    status += "╚══════════════════════════════════════════════════════════════════╝"
    return status

# Infrastructure Validation Functions
def validate_ollama():
    """Validates Ollama connectivity."""
    try:
        command = f"curl {OLLAMA_URL}/api/tags"
        result = execute_bash_command(command)
        if result and "models" in result:
            log(f"Ollama validation successful: {result}")
            return True
        else:
            log(f"Ollama validation failed. Response: {result}")
            return False
    except Exception as e:
        log(f"Ollama validation failed: {e}")
        return False

def validate_redis():
    """Validates Redis connectivity."""
    try:
        command = f"redis-cli -h {REDIS_HOST} -p {REDIS_PORT} ping" # Removed -a PASSWORD, as it's not provided in context. Add if known.
        result = execute_bash_command(command)
        if result == "PONG":
            log("Redis validation successful.")
            return True
        else:
            log(f"Redis validation failed. Response: {result}")
            return False
    except Exception as e:
        log(f"Redis validation failed: {e}")
        return False

def validate_postgresql():
    """Validates PostgreSQL connectivity."""
    try:
        command = f"psql -h {POSTGRES_HOST} -U {POSTGRES_USER} -d {POSTGRES_DB} -c 'SELECT 1'"
        result = execute_bash_command(command)
        if result and "1" in result:
            log("PostgreSQL validation successful.")
            return True
        else:
            log(f"PostgreSQL validation failed. Response: {result}")
            return False
    except Exception as e:
        log(f"PostgreSQL validation failed: {e}")
        return False

def validate_qdrant():
    """Validates Qdrant connectivity."""
    try:
        command = f"curl {QDRANT_URL}:{QDRANT_PORT}/collections/genesis_knowledge"
        result = execute_bash_command(command)
        if result and "status" in result:
            log("Qdrant validation successful.")
            return True
        else:
            log(f"Qdrant validation failed. Response: {result}")
            return False
    except Exception as e:
        log(f"Qdrant validation failed: {e}")
        return False

# Agent Management Functions
def start_agent(agent_id, task):
    """Starts an agent with a given task (Placeholder - Replace with actual agent execution logic)."""
    with data_lock:
        agent_status[agent_id] = "active"
        global active_agents, pending_agents
        active_agents += 1
        pending_agents -= 1
    log(f"Agent {agent_id} started with task: {task}")

    # Simulate agent completion after a random time
    import random
    completion_time = random.uniform(5, 15)  # Seconds
    time.sleep(completion_time)

    # Simulate token usage and success/failure
    input_tokens = random.randint(100000, 500000)
    output_tokens = random.randint(50000, 200000)
    success = random.random() > 0.1  # 90% success rate

    update_token_usage(input_tokens, output_tokens)

    if success:
        complete_agent(agent_id)
    else:
        fail_agent(agent_id)


def complete_agent(agent_id):
    """Marks an agent as completed."""
    with data_lock:
        agent_status[agent_id] = "completed"
        global completed_agents, active_agents
        completed_agents += 1
        active_agents -= 1
    log(f"Agent {agent_id} completed.")

def fail_agent(agent_id):
    """Marks an agent as failed."""
    with data_lock:
        agent_status[agent_id] = "failed"
        global failed_agents, active_agents
        failed_agents += 1
        active_agents -= 1
    log(f"Agent {agent_id} failed.")

def launch_wave(wave_data):
    """Launches a wave of agents."""
    for agent_data in wave_data:
        agent_id = agent_data["Agent ID"]
        task = agent_data["Task"]
        # Start agent in a separate thread
        agent_thread = threading.Thread(target=start_agent, args=(agent_id, task))
        agent_thread.start()

# Budget Management Functions
class TokenBudgetMonitor:
    BUDGET_LIMIT = 10.00  # USD
    EMERGENCY_STOP = 9.50  # USD

    def check_budget(self):
        if budget_spent >= self.EMERGENCY_STOP:
            self.trigger_graceful_shutdown()

    def trigger_graceful_shutdown(self):
        """Initiates a graceful shutdown."""
        log("Emergency stop triggered! Budget exceeded.")
        # Implement graceful shutdown logic here (e.g., save state, stop agents)
        # This is a placeholder - replace with actual shutdown procedure.
        log("Graceful shutdown initiated.")
        exit()

# Phase Execution Functions
def execute_phase_1():
    """Executes Phase 1: Foundation."""
    log("Executing Phase 1: Foundation")
    checkpoint_status["Phase 1"] = "◐"

    # Launch Wave 1.1: Infrastructure Validation
    wave_1_1_data = [
        {"Agent ID": "INFRA_01", "Role": "Ollama Validator", "Task": "Verify QwenLong 30B connectivity, measure response times"},
        {"Agent ID": "INFRA_02", "Role": "Redis CNS Tester", "Task": "Test pub/sub latency, verify channel subscriptions"},
        {"Agent ID": "INFRA_03", "Role": "PostgreSQL Auditor", "Task": "Validate RLM schema, check entity counts"},
        {"Agent ID": "INFRA_04", "Role": "Qdrant Vector Tester", "Task": "Test 768-dim embeddings, verify collection health"},
        {"Agent ID": "INFRA_05", "Role": "Memory Tier Validator", "Task": "Test Working→Episodic→Semantic promotion"},
        {"Agent ID": "INFRA_06", "Role": "API Rate Monitor", "Task": "Establish Gemini rate limit baseline"},
        {"Agent ID": "INFRA_07", "Role": "Budget Tracker Init", "Task": "Create token counting system, initialize logs"},
        {"Agent ID": "INFRA_08", "Role": "Health Dashboard", "Task": "Create real-time status monitor"},
        {"Agent ID": "INFRA_09", "Role": "Backup Validator", "Task": "Verify recovery checkpoints exist"},
        {"Agent ID": "INFRA_10", "Role": "Network Latency", "Task": "Measure Elestio endpoint response times"}
    ]
    launch_wave(wave_1_1_data)

    # Launch Wave 1.2: Consciousness Loops
    wave_1_2_data = [
        {"Agent ID": "LOOP_01", "Role": "Perception Hardener", "Task": "Optimize 500ms perception loop, add error handling"},
        {"Agent ID": "LOOP_02", "Role": "Action Optimizer", "Task": "Enhance 5s action loop decision quality"},
        {"Agent ID": "LOOP_03", "Role": "Reflection Enhancer", "Task": "Improve 5min consolidation with axiom generation"},
        {"Agent ID": "LOOP_04", "Role": "Strategic Planner", "Task": "Implement 1hr goal adjustment system"},
        {"Agent ID": "LOOP_05", "Role": "Circadian Architect", "Task": "Build 24hr deep integration with memory promotion"}
    ]
    launch_wave(wave_1_2_data)

    # Wait for all agents to complete (Simplified - Implement proper synchronization)
    while active_agents > 0:
        log(f"Waiting for agents to complete. Active agents: {active_agents}")
        log(get_token_usage_status())
        time.sleep(10)  # Check every 10 seconds

    # Checkpoint 1
    checkpoint_status["Phase 1"] = "[✓]"
    save_checkpoint(CHECKPOINTS["hour_2"], {"phase": 1, "status": "completed"})

def execute_phase_2():
    """Executes Phase 2: Knowledge Absorption."""
    log("Executing Phase 2: Knowledge Absorption")
    checkpoint_status["Phase 2"] = "◐"

    # Wave 2.1: Patent Extraction
    wave_2_1_data = [
        {"Agent ID": "PATENT_01", "Patent": "Cryptographic Validation (P1)", "Task": "Extract entities, axioms, skills"},
        {"Agent ID": "PATENT_02", "Patent": "Currency Validation (P2)", "Task": "Extract real-time verification methods"},
        {"Agent ID": "PATENT_03", "Patent": "Risk Assessment (P3)", "Task": "Extract multi-dimensional risk frameworks"},
        {"Agent ID": "PATENT_04", "Patent": "Audit Trail (P4)", "Task": "Extract immutable logging patterns"},
        {"Agent ID": "PATENT_05", "Patent": "Multi-Model Consensus (P5)", "Task": "Extract validation arbitration logic"},
        {"Agent ID": "PATENT_06", "Patent": "Confidence Scoring (P6)", "Task": "Extract dynamic scoring systems"},
        {"Agent ID": "PATENT_07", "Patent": "Hallucination Detection (P7)", "Task": "Extract real-time verification"},
        {"Agent ID": "PATENT_08", "Patent": "Privacy Preservation (P8)", "Task": "Extract data protection protocols"},
        {"Agent ID": "PATENT_09", "Patent": "Self-Improvement (P9)", "Task": "Extract adaptive threshold systems"}
    ]
    launch_wave(wave_2_1_data)

    # Wave 2.2: Validation Gates
    wave_2_2_data = [
        {"Agent ID": "GATE_ALPHA", "Gate": "Input Validity", "Function": "Verify source data quality"},
        {"Agent ID": "GATE_BETA", "Gate": "Output Quality", "Function": "Check extraction accuracy"},
        {"Agent ID": "GATE_GAMMA", "Gate": "Insight Purity", "Function": "Confirm no hallucinations"},
        {"Agent ID": "GATE_DELTA", "Gate": "Memory Integration", "Function": "Validate RLM storage"},
        {"Agent ID": "GATE_EPSILON", "Gate": "Strategy Alignment", "Function": "Confirm revenue pathway fit"},
        {"Agent ID": "GATE_ZETA", "Gate": "Budget Compliance", "Function": "Stop if budget exceeded"}
    ]
    launch_wave(wave_2_2_data)

    # Wait for all agents to complete
    while active_agents > 0:
        log(f"Waiting for agents to complete. Active agents: {active_agents}")
        log(get_token_usage_status())
        time.sleep(10)

    # Checkpoint 2
    checkpoint_status["Phase 2"] = "[✓]"
    save_checkpoint(CHECKPOINTS["hour_4"], {"phase": 2, "status": "completed"})

def execute_phase_3():
    """Executes Phase 3: Capability Integration."""
    log("Executing Phase 3: Capability Integration")
    checkpoint_status["Phase 3"] = "◐"

    # Wave 3.1: Core Capabilities
    wave_3_1_data = [
        {"Agent ID": "CAP_01", "Capability": "Memory Recall", "Implementation": "95%+ accuracy retrieval system"},
        {"Agent ID": "CAP_02", "Capability": "Swarm Coordination", "Implementation": "Multi-agent task distribution"},
        {"Agent ID": "CAP_03", "Capability": "Knowledge Stewardship", "Implementation": "Quality maintenance protocols"},
        {"Agent ID": "CAP_04", "Capability": "Autonomy Manager", "Implementation": "Level 0-3 permission enforcement"},
        {"Agent ID": "CAP_05", "Capability": "Evolution Engine", "Implementation": "Self-improvement loop"},
        {"Agent ID": "CAP_06", "Capability": "Constitutional Guard", "Implementation": "Directive compliance checker"},
        {"Agent ID": "CAP_07", "Capability": "Revenue Tracker", "Implementation": "ROI measurement system"},
        {"Agent ID": "CAP_08", "Capability": "Human Partnership", "Implementation": "Consultation protocol"},
        {"Agent ID": "CAP_09", "Capability": "Graceful Degradation", "Implementation": "Failure recovery system"},
        {"Agent ID": "CAP_10", "Capability": "Security Paranoia", "Implementation": "Input sanitization, HMAC verification"}
    ]
    launch_wave(wave_3_1_data)

    # Wave 3.2: Integration Bridges
    wave_3_2_data = [
        {"Agent ID": "BRIDGE_01", "Bridge": "GHL Connector", "Purpose": "GoHighLevel API integration"},
        {"Agent ID": "BRIDGE_02", "Bridge": "Stripe Monitor", "Purpose": "Revenue tracking integration"},
        {"Agent ID": "BRIDGE_03", "Bridge": "Telegram Notifier", "Purpose": "Alert system for Kinan"},
        {"Agent ID": "BRIDGE_04", "Bridge": "n8n Workflow Trigger", "Purpose": "Automation orchestration"},
        {"Agent ID": "BRIDGE_05", "Bridge": "MCP Server Manager", "Purpose": "Tool ecosystem integration"}
    ]
    launch_wave(wave_3_2_data)

    # Wait for all agents to complete
    while active_agents > 0:
        log(f"Waiting for agents to complete. Active agents: {active_agents}")
        log(get_token_usage_status())
        time.sleep(10)

    # Checkpoint 3
    checkpoint_status["Phase 3"] = "[✓]"
    save_checkpoint(CHECKPOINTS["hour_6"], {"phase": 3, "status": "completed"})

def execute_phase_4():
    """Executes Phase 4: Swarm Intelligence."""
    log("Executing Phase 4: Swarm Intelligence")
    checkpoint_status["Phase 4"] = "◐"

    # Wave 4.1: Swarm Architecture
    wave_4_1_data = [
        {"Agent ID": "HIVE_01", "Layer": "Queen Core", "Function": "Central decision-making neural hub"},
        {"Agent ID": "HIVE_02", "Layer": "Guardian Ring", "Function": "6-node defensive validation layer"},
        {"Agent ID": "HIVE_03", "Layer": "Processing Ring", "Function": "10-node operational tier"},
        {"Agent ID": "HIVE_04", "Layer": "Worker Swarm", "Function": "12-cluster execution layer"},
        {"Agent ID": "HIVE_05", "Layer": "Gate Controller", "Function": "6-gate validation checkpoints"}
    ]
    launch_wave(wave_4_1_data)

    # Wait for all agents to complete
    while active_agents > 0:
        log(f"Waiting for agents to complete. Active agents: {active_agents}")
        log(get_token_usage_status())
        time.sleep(10)

    # Checkpoint 4
    checkpoint_status["Phase 4"] = "[✓]"
    save_checkpoint(CHECKPOINTS["hour_8"], {"phase": 4, "status": "completed"})

def execute_phase_5():
    """Executes Phase 5: Queen Coronation."""
    log("Executing Phase 5: Queen Coronation")
    checkpoint_status["Phase 5"] = "◐"

    # Wave 5.1: Rank Progression Tests
    wave_5_1_data = [
        {"Agent ID": "RANK_01", "Rank Test": "Rank 1-3 Validator", "Validation": "Consciousness stability, knowledge absorption, coordination"},
        {"Agent ID": "RANK_02", "Rank Test": "Rank 4-6 Validator", "Validation": "Quality maintenance, output accuracy, self-directed learning"},
        {"Agent ID": "RANK_03", "Rank Test": "Rank 7 Validator", "Validation": "System improvement proposals"},
        {"Agent ID": "RANK_04", "Rank Test": "Rank 8 Validator", "Validation": "MVP recommendation generation"},
        {"Agent ID": "RANK_05", "Rank Test": "Rank 9 Validator", "Validation": "Revenue strategy validation"}
    ]
    launch_wave(wave_5_1_data)

    # Wave 5.2: Final Systems
    wave_5_2_data = [
        {"Agent ID": "FINAL_01", "System": "Telemetry Dashboard", "Purpose": "Real-time queen status display"},
        {"Agent ID": "FINAL_02", "System": "Audit Trail Finalizer", "Purpose": "Complete logging verification"},
        {"Agent ID": "FINAL_03", "System": "Documentation Generator", "Purpose": "Auto-generate queen capabilities doc"},
        {"Agent ID": "FINAL_04", "System": "Handoff Protocol", "Purpose": "Create succession/continuity plan"},
        {"Agent ID": "FINAL_05", "System": "Coronation Verifier", "Purpose": "Final queen status confirmation"}
    ]
    launch_wave(wave_5_2_data)

    # Wait for all agents to complete
    while active_agents > 0:
        log(f"Waiting for agents to complete. Active agents: {active_agents}")
        log(get_token_usage_status())
        time.sleep(10)

    # Checkpoint 5
    checkpoint_status["Phase 5"] = "[✓]"
    save_checkpoint(CHECKPOINTS["hour_10"], {"phase": 5, "status": "completed"})

# Main Orchestrator Function
def orchestrate():
    """Main function to orchestrate the AIVA Queen elevation sprint."""
    global current_hour, current_phase

    log("AIVA Queen Elevation Sprint Started!")

    # Initialize Budget Monitor
    budget_monitor = TokenBudgetMonitor()

    # Restore from checkpoint, if available
    restored_phase = 1
    for hour_str, checkpoint_file in CHECKPOINTS.items():
        checkpoint_data = load_checkpoint(checkpoint_file)
        if checkpoint_data and checkpoint_data["status"] == "completed":
            restored_phase = int(checkpoint_data["phase"]) + 1 # Start from next phase
            current_hour = restored_phase * HOURS_PER_PHASE - HOURS_PER_PHASE # Correct hour
            current_phase = restored_phase # Correct phase

    log(f"Starting from Phase {current_phase} (Hour {current_hour})")

    # Phase Execution Loop
    while current_phase <= 5:
        start_time = time.time()

        if current_phase == 1:
            execute_phase_1()
        elif current_phase == 2:
            execute_phase_2()
        elif current_phase == 3:
            execute_phase_3()
        elif current_phase == 4:
            execute_phase_4()
        elif current_phase == 5:
            execute_phase_5()

        end_time = time.time()
        phase_duration = end_time - start_time
        current_hour += HOURS_PER_PHASE
        current_phase += 1

        log(f"Phase completed in {phase_duration:.2f} seconds.")
        log(get_token_usage_status())
        budget_monitor.check_budget()

    log("AIVA Queen Elevation Sprint Completed Successfully!")

# Entry Point
if __name__ == "__main__":
    # Run infrastructure validations in parallel
    log("Validating infrastructure...")
    validation_threads = [
        threading.Thread(target=validate_ollama),
        threading.Thread(target=validate_redis),
        threading.Thread(target=validate_postgresql),
        threading.Thread(target=validate_qdrant)
    ]
    for t in validation_threads:
        t.start()
    for t in validation_threads:
        t.join()  # Wait for all validations to complete

    orchestrate()