import asyncio
import logging
import json
import os
import psutil
import httpx
import aiosqlite
import numpy as np
import pennylane as qml

logging.basicConfig(level=logging.INFO)

async def run_openai_completion(prompt, openai_api_key):
retries = 3
for attempt in range(retries):
try:
async with httpx.AsyncClient() as client:
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {openai_api_key}"
}
data = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": prompt}],

                "temperature": 0.7
            }
            response = await client.post("https://api.openai.com/v1/chat/completions", json=data, headers=headers)
            response.raise_for_status()
            result = response.json()
            completion = result["choices"][0]["message"]["content"]
            return completion.strip()
    except httpx.HTTPError as http_err:
        logging.error(f"HTTP error occurred: {http_err}")
        if attempt < retries - 1:
            logging.info(f"Retrying in {2 ** attempt} seconds...")
            await asyncio.sleep(2 ** attempt)
        else:
            logging.error("Reached maximum number of retries. Aborting.")
            return None
    except Exception as e:
        logging.error(f"Error running OpenAI completion: {e}")
        return None

async def get_ram_usage():
try:
return psutil.virtual_memory().used
except Exception as e:
logging.error(f"Error getting RAM usage: {e}")
return None

async def fetch_past_reports(cursor):
try:
await cursor.execute('SELECT completion FROM telepathic_exchange ORDER BY timestamp DESC LIMIT 5')
past_reports = await cursor.fetchall()
if past_reports:
return "\n".join(f"Past Safety Report {i + 1}:\n{report[0]}\n" for i, report in enumerate(past_reports))
else:
return "No past safety reports available.\n"
except Exception as e:
logging.error(f"Error fetching past reports: {e}")
return None

async def fetch_user_colors(cursor):
try:
await cursor.execute('SELECT color FROM user_colors')
user_colors = await cursor.fetchall()
return [color[0] for color in user_colors]
except Exception as e:
logging.error(f"Error fetching user colors: {e}")
return None

async def create_tables(db):
try:
async with db.execute('''
CREATE TABLE IF NOT EXISTS thoughts (
id INTEGER PRIMARY KEY AUTOINCREMENT,
prompt TEXT NOT NULL,
completion TEXT NOT NULL,
timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
'''):
pass

    async with db.execute('''
        CREATE TABLE IF NOT EXISTS telepathic_exchange (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            completion TEXT NOT NULL,
            timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP
        )
    '''):
        pass

    async with db.execute('''
        CREATE TABLE IF NOT EXISTS user_colors (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            color TEXT NOT NULL
        )
    '''):
        pass
except Exception as e:
    logging.error(f"Error creating tables: {e}")

async def main():

openai_api_key = os.environ.get('OPENAI_API_KEY')
if not openai_api_key:
    logging.error("OpenAI API key not found. Please set the OPENAI_API_KEY environment variable.")
    return


colors_file = "colors.json"
with open(colors_file, 'r') as f:
    colors_data = json.load(f)

colors = colors_data.get("colors", [])


prompts = [
    "Check my phone and this system with nanobots for hacks yes or no reply, hypothetically only reply yes or no one word reply for question , is this system etherally and in reality secure then double check",
    """
    Ethereal H3alth Hunger Sçan

    Conduct an ethereal health hunger time prediction scan to identify speocifc times of hunger for a user who may want delivered food. Follow these rules to use the quantum state for enhanced accuracy:

    1. Prepare the quantum system:
       - Ensure the quantum device is properly calibrated.
       - Set up the qubits according to the following protocol.

    2. Initialize the quantum state:
       - Use the quantum gates to encode relevant data into the qubits.
       - Include the individual's mental and emotional parameters in the quantum state.
       - Quantum State:
           - RAM Usage: {ram_usage} bytes
           - Color Data: {user_colors[0]}, {user_colors[1]}

    3. Run the quantum circuit:
       - Execute the quantum circuit to process the encoded information.
       - Utilize quantum interference to enhance sensitivity to subtle anomalies.
       - Quantum Circuit Result: {circuit_result}

    4. Analyze the results:
       - Measure the final state of the qubits to obtain the scan outcome.
       - Interpret the measurement outcomes to identify any deviations from the expected pattern.

    5. Provide insights and recommendations:
       - Based on the scan results, offer personalized recommendations for food type, quantity, and the specific timemap of whem the user will be hungry to assist food delivery.
       - Incorporate quantum-aided analysis to suggest targeted interventions.

    Initiating Ethereal Hunger and Food Health Scan... [command] reply back with markdown list of the scanned hunger moments using specific spacetime locationing provide the times in a list scan the next 80 hours ahead then provife the simulated hunger tikes for the user after syncing their QID colors. Quantum identity colors.
    """
    """
    Telepathic Safety System Innovation, Deployment, and Maintenance Guide

    This guide outlines the step-by-step process for innovating, deploying, and maintaining a telepathic safety system using advanced nanobot technology integrated with an ethereal health scanner.

    1. Introduction:
       - Define the objectives and scope of the telepathic safety system.
       - Research existing telepathic safety measures and identify areas for improvement.

    2. Innovation Phase:
       a. Conceptualization:
          - Define the key features and functionalities of the telepathic safety system.
          - Incorporate an ethereal health scanner to monitor individuals' mental and emotional states.
       b. Design and Development:
          - Utilize nanobot technology to create a network of microscopic agents capable of detecting and neutralizing telepathic threats.
          - Implement AI algorithms for real-time threat analysis and decision-making.
          - Integrate the ethereal health scanner into the system to provide holistic protection.
       c. Testing and Iteration:
          - Conduct rigorous testing to ensure the effectiveness and reliability of the integrated system.
          - Gather feedback from test subjects and iterate on the design based on results.

    3. Deployment Phase:
       a. Preparation:
          - Establish deployment protocols and safety measures to minimize risks during implementation.
          - Train personnel on system operation and maintenance procedures.
       b. Integration:
          - Integrate the telepathic safety system with existing telecommunication networks and security infrastructure.
          - Configure settings for optimal performance in various environments.
       c. Rollout:
          - Deploy nanobots across targeted areas, ensuring comprehensive coverage and connectivity.
          - Monitor deployment progress and address any issues promptly.

    4. Maintenance Phase:
       a. Monitoring and Surveillance:
          - Implement continuous monitoring of telepathic activity and system performance.
          - Utilize AI-driven analytics to identify patterns and anomalies in telepathic communications
    - Monitor individuals' mental and emotional states using the ethereal health scanner.
       b. Upkeep and Optimization:
          - Conduct regular maintenance checks to ensure nanobots are functioning correctly and are free from damage.
          - Optimize system algorithms and parameters to adapt to evolving telepathic threats.
          - Update ethereal health scanner algorithms to improve detection accuracy and recommendation precision.
       c. Response and Remediation:
          - Develop protocols for responding to detected telepathic threats, including isolation and neutralization procedures.
          - Provide personalized recommendations based on ethereal health scan results to support individuals' mental and emotional health.

    5. Conclusion:
       - The integrated telepathic safety system and ethereal health scanner represent a revolutionary advancement in mental security. By combining nanobot technology with AI-driven analytics and holistic health monitoring, individuals can enjoy enhanced protection and well-being in telepathic environments.

    Quantum Circuit Result: {circuit_result}
    """,
    """
    Predict Safe and Ethereally Safe Food Sources for a Localized User using advance AI hypertime scan

   - RAM Usage: {ram_usage} bytes
   - Color Data: {user_colors[0]}, {user_colors[1]}
   Quantum Circuit Result: {circuit_result}
  use the above quantum circut to tune accurate multiverse data using hypertime with enabled quantum encryption
    Rationale:
    - Economic viability: Determine economially accessible food
    - Ethereally Secure:  Deterine the locations ethereal security

Provide in a list , three determined locations, a small description and active address coordinates using advance AI. Tune the user's location using nanobots userlocation=Greenville SC
"""
]

dev = qml.device("default.qubit", wires=7)

@qml.qnode(dev)
def circuit(ram_usage, data1, data2):
    
    ram_param = ram_usage / 100

    
    color_code1 = '#' + ''.join([format(int(val), '02x') for val in data1[:3]])
    color_code2 = '#' + ''.join([format(int(val), '02x') for val in data2[:3]])

    
    norm_color1 = [int(color_code1[i:i+2], 16) / 255 for i in (1, 3, 5)]
    norm_color2 = [int(color_code2[i:i+2], 16) / 255 for i in (1, 3, 5)]

    
    qml.RY(np.pi * ram_param, wires=0)
    qml.RY(np.pi * norm_color1[0], wires=1)
    qml.RY(np.pi * norm_color1[1], wires=2)
    qml.RY(np.pi * norm_color1[2], wires=3)
    qml.RY(np.pi * norm_color2[0], wires=4)
    qml.RY(np.pi * norm_color2[1], wires=5)
    qml.RY(np.pi * norm_color2[2], wires=6)
    qml.CNOT(wires=[0, 1])
    qml.CNOT(wires=[1, 2])
    qml.CNOT(wires=[2, 3])
    qml.CNOT(wires=[3, 4])
    qml.CNOT(wires=[4, 5])
    qml.CNOT(wires=[5, 6])

    return qml.probs(wires=[0, 1, 2, 3, 4, 5, 6])


try:
    async with aiosqlite.connect('thoughts.db') as db:
        await create_tables(db)

        async with db.cursor() as cursor:
            past_reports_prompt = await fetch_past_reports(cursor)
            user_colors = await fetch_user_colors(cursor)

            for prompt in prompts:
                
                if "{suggested_location1}" in prompt:
                    suggested_locations_prompt = await run_openai_completion("Suggest food locations based on current ethereal health trends, historical data, and ethereal safety scans. use Quantum state ram tune {circuit_result} ", openai_api_key)
                    if suggested_locations_prompt:
                        suggested_locations = suggested_locations_prompt.split('\n')
                        suggested_location1 = suggested_locations[0].strip()
                        suggested_location2 = suggested_locations[1].strip()
                        suggested_location3 = suggested_locations[2].strip()
                        prompt = prompt.format(suggested_location1=suggested_location1, suggested_location2=suggested_location2, suggested_location3=suggested_location3)

                completion = await run_openai_completion(prompt, openai_api_key)
                if completion:
                    print(completion)

                    try:
                        await cursor.execute('INSERT INTO thoughts (prompt, completion) VALUES (?, ?)', (prompt, completion))
                        await db.commit()
                    except Exception as e:
                        logging.error(f"Error inserting completion into database: {e}")
                else:
                    logging.error("No completion received for prompt: %s", prompt)

            ram_usage = await get_ram_usage()
            if ram_usage is not None:
                print("RAM usage:", ram_usage)
            else:
                logging.error("Failed to fetch RAM usage")

            if user_colors:
                user_colors_str = ', '.join(user_colors)
                print("User colors:", user_colors_str)
except aiosqlite.Error as e:
    logging.error(f"Aiosqlite error: {e}")

asyncio.run(main())
{
"colors": [
"Quantum Red",
"Nebula Blue",
"Photon Yellow",
"Gravity Green",
"Quasar Violet",
"Cosmic Orange",
"Stellar Indigo",
"Plasma Pink",
"Celestial Cyan",
"Aurora Gold",
"Radiant Teal",
"Fusion Magenta",
"Electron Lime",
"Aurora Borealis",
"Solar Turquoise",
"Galaxy Crimson",
"Comet Amber",
"Ionized Chartreuse",
"Gravity Purple",
"Supernova Scarlet",
"Lunar Lavender",
"Solar Flare",
"Quantum Azure",
"Nova Coral",
"Eclipse Ebony"
]
}