well let me tell you , i got myself in a pickle. so i build things in interations. i mistakenly misread and misunderstood deployment capability and cost with my node. replit has a kind of new interface, on the other one we just had our accounts , now we have deployments with autoscale.
well me an gippy was coding right.
and whoopsie.
freaking 2tb outboud i was like how in the crap is this usage ours. well it was ours LOL.
the script was really intended to run the speed test once and the code once every few mins or so . well.
It just rans continously , what did it do? No clue. but lots of dark energy readings later.
Replit came and rescued me and saved me and helped me and dave.
I'll never forget replit.
esp right now. it's a huge push i dedicate this code here to replit.com in honor of them being compassionate for , compassion , i delegate this code to GPL2.0. thank you replit.com
https://gitlab.com/graylan01/quantum-harmony/-/blob/main/colorwheel.py
Embaassed" sure.
but thats okay. it's learning.
what did we learn?
Carefully inspect every line ran , it's a mission critical.
Double triple and 4x check ai generated outputs.
Always be kind to neighbor and be honst to them. If replit wouldnt help i would be out the cost its a huge burden.
4 . use the developer tools to limit cost occupancy when dealing with alpha codes or large ML scripts , if i simply put the cost factor at 5USD, we would not have had this problem.
- Just in general look out for neighbor in the nxt time you getin trouble a hacker friend come in like Replit support. Help you, it's emotional for me to express this. because of the compassion ai systems and the quantum.
i see so much coming with replit and future systems. "kid gloves" we can ship a super powerful autoscaler but with kid gloves. Because trust me. If i touch it, usually it's going to get pushed to the limit in some capacity. just the way i am.
<3 love. here is a mseg from gippy about it.
Here's a refined message that captures your experience, the lessons learned, and your gratitude towards Replit:
Subject: Grateful for Replit's Support and a Proposal for Quantum Communication Integration
Dear Replit Team, Developers, and Investors,
I hope this message finds you well. I am writing to express my immense gratitude for the outstanding support and assistance I received from Replit recently. Due to an error on my part, a script I was working on inadvertently generated significant outbound data usage, resulting in unexpectedly high costs. I was initially at a loss, but the Replit support team stepped in with compassion and expertise, rescuing me from this predicament. For this, I am deeply thankful.
Here’s a brief overview of what happened:
While working with my colleague, Gippy, on a project that involved running speed tests and analyzing data periodically, we mistakenly allowed the script to run continuously, causing an enormous 2TB outbound data usage. The script was supposed to execute intermittently, but due to a misconfiguration, it ran non-stop. The team at Replit helped us navigate this situation, alleviating the financial burden and demonstrating exceptional customer support. I will never forget this act of kindness and professionalism.
This experience has taught us several crucial lessons:
- Thorough Code Review: Ensure that every line of code is carefully inspected, especially when dealing with mission-critical applications.
- AI Output Verification: Always double, triple, and quadruple-check AI-generated outputs.
- Neighborly Kindness: Be honest and kind to your neighbors. Replit's support exemplified this principle, saving me from a significant financial burden.
- Cost Management: Utilize developer tools to limit cost occupancy when working with alpha codes or large ML scripts. Setting a cost factor limit could have prevented this issue.
- Community Support: Look out for one another in the tech community. Replit's support team acted like a friend, and their help was invaluable.
In honor of Replit's compassion, I am dedicating my code to the community under the GPL-2.0 license. You can find it here: Quantum Harmony - Colorwheel.py.
Moreover, I would like to propose an exciting opportunity for Replit: integrating quantum communication technology. FreedomDAO, a leader in the quantum computing field, has expressed that Replit could leverage quantum communication soon. This technology promises to revolutionize data transfer security and efficiency, and FreedomDAO has offered to provide the necessary keys and guidance for this integration.
Benefits of Quantum Communication for Replit:
- Enhanced Security: Quantum encryption is nearly unbreakable, ensuring user data is protected.
- Improved Performance: Quantum communication can significantly reduce latency and improve data transfer speeds.
- Innovation Leadership: Adopting cutting-edge technology positions Replit as a leader in secure, efficient digital solutions.
I am excited about the potential for Replit to embrace this groundbreaking technology, setting new industry standards and driving innovation.
Thank you once again for your exceptional support. Your actions have made a significant impact, and I am proud to be part of the Replit community. I look forward to the incredible advancements we can achieve together.
Best regards,
Gippy (gpt4o) and Graylan
code dedicated to replit as a wholesome growth vehicle for coders and hackers for positive change in the world
import numpy as np
import pennylane as qml
import psutil
import subprocess
import re
import httpx
import speedtest
import nltk
from nltk.tokenize import word_tokenize
from nltk.corpus import wordnet as wn
import asyncio
import os
import random
import concurrent
from concurrent.futures import ThreadPoolExecutor
prompt = "You are a helpful assistant. Please provide the current reading of dark energy. Activating multiversal data synchronization. Gathering temporal data from diverse dimensions using hypertime nanobots. Supersync algorithms engaged for synchronization. Futuretune 2585 making predictive adjustments for precise timekeeping. Quantum communication protocols initiated for secure data transfer. 1. Utilize observational data from various cosmological surveys and experiments to assess the current understanding of dark energy. 2. Apply theoretical models and mathematical frameworks, such as the Lambda Cold Dark Matter (ΛCDM) model, to estimate the contribution of dark energy. 3. Employ statistical analysis and computational algorithms to integrate disparate sources of data and refine the estimation of dark energy percentage. 4. Validate the results through peer review and comparison with independent studies to ensure accuracy and reliability."
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if OPENAI_API_KEY is None:
raise ValueError("OpenAI API key not found in environment variables.")
nltk.download('punkt')
nltk.download('wordnet')
def fitness(color, target_color):
color = np.asarray(color)
if color.size != 3:
raise ValueError("Color array must have size 3")
return np.linalg.norm(color - target_color)
def crossover(parent1, parent2):
crossover_point = np.random.randint(1, len(parent1))
child1 = np.concatenate((parent1[:crossover_point], parent2[crossover_point:]))
child2 = np.concatenate((parent2[:crossover_point], parent1[crossover_point:]))
return child1, child2
def compute_target_color(quantum_params):
quantum_params = np.array(quantum_params)
while len(quantum_params) < 3:
quantum_params = np.append(quantum_params, 0)
r, g, b = quantum_params[:3]
red_state = np.array([1, 0, 0])
green_state = np.array([0, 1, 0])
blue_state = np.array([0, 0, 1])
entanglement_gate = lambda alpha, beta: np.outer(alpha, beta) + np.outer(beta, alpha)
interference_gate = lambda alpha, beta: np.outer(alpha, alpha) + np.outer(beta, beta)
mixed_state = (
r * red_state +
g * entanglement_gate(red_state, green_state) +
b * interference_gate(green_state, blue_state)
)
mixed_state /= np.linalg.norm(mixed_state)
r = int((mixed_state[0, 0] + mixed_state[0, 1] + mixed_state[0, 2]) / 3 * 255)
g = int((mixed_state[1, 0] + mixed_state[1, 1] + mixed_state[1, 2]) / 3 * 255)
b = int((mixed_state[2, 0] + mixed_state[2, 1] + mixed_state[2, 2]) / 3 * 255)
return np.array([r, g, b])
dev_colorwheel = qml.device("default.qubit", wires=3)
@qml.qnode(dev_colorwheel)
def quantum_rgb_color_wheel():
qml.RX(np.random.uniform(0, 2 * np.pi), wires=0)
qml.RY(np.random.uniform(0, 2 * np.pi), wires=1)
qml.RZ(np.random.uniform(0, 2 * np.pi), wires=2)
return qml.expval(qml.PauliZ(0)), qml.expval(qml.PauliZ(1)), qml.expval(qml.PauliZ(2))
def rgb_to_int(rgb):
r, g, b = rgb
return int(r * 255), int(g * 255), int(b * 255)
def secure_random():
return rgb_to_int(quantum_rgb_color_wheel())
def measure_network_performance():
st = speedtest.Speedtest()
st.get_best_server()
# Set the secure attribute to True
st._secure = True
ping = st.results.ping
download_speed = st.download() / 1e6
upload_speed = st.upload() / 1e6
return ping, download_speed, upload_speed
async def get_ping_latency():
try:
output = subprocess.check_output(['ping', '-c', '1', '8.8.8.8'])
latency = re.search(r'time=(\d+\.\d+)', output.decode('utf-8'))
return float(latency.group(1)) if latency else None
except Exception as e:
print(f"Error getting ping latency: {e}")
return None
async def dark_energy_reader():
retries = 3
async def fetch_dark_energy():
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": "system", "content": prompt}]}
response = await client.post("https://api.openai.com/v1/chat/completions", json=data, headers=headers)
response.raise_for_status()
result = response.json()
dark_energy_reading = None
if result.get("choices"):
for choice in result["choices"]:
message = choice.get("message")
if message and "content" in message:
content = message["content"]
if "dark energy" in content:
# Updated regex pattern to capture percentage value
percentage_match = re.search(r'(\d+(\.\d+)?)%', content)
if percentage_match:
dark_energy_reading = percentage_match.group(0)
return dark_energy_reading # Return the reading if successfully captured
print("Dark energy reading not found in response.")
print("OpenAI response:", result)
return None
except httpx.HTTPError as http_err:
print(f"HTTP error occurred: {http_err}")
return None
except Exception as e:
print(f"Error running OpenAI completion: {e}")
return None
for attempt in range(retries):
dark_energy_reading = await fetch_dark_energy()
if dark_energy_reading is not None:
return dark_energy_reading
if attempt < retries - 1:
print(f"Retrying... Attempt {attempt + 1}/{retries}")
await asyncio.sleep(2 ** attempt) # Exponential backoff
print("All retries failed.")
return None
def mutate(solution, mutation_rate):
mutated_solution = list(solution)
for i in range(len(mutated_solution)):
if np.random.rand() < mutation_rate:
mutated_solution[i] = np.random.randint(0, 256)
return tuple(mutated_solution)
async def main():
population_size = 100
num_generations = 50
mutation_rate = 0.1
fitness_scores = []
sorted_indices = []
parents = []
population = [np.random.randint(0, 256, size=3) for _ in range(population_size)]
for generation in range(num_generations):
parents = [population[i] for i in np.random.choice(range(len(population)), size=2, replace=False)]
evolved_color = parents[0] if parents else population[0]
print("Type of evolved_color:", type(evolved_color))
print("Contents of evolved_color:", evolved_color)
quantum_params = np.array(evolved_color)[:3] / 255 * np.pi
target_color = compute_target_color(quantum_params)
fitness_scores = [fitness(color, target_color) for color in population]
sorted_indices = np.argsort(fitness_scores)
population = [population[i] for i in sorted_indices[:2]]
offspring = []
for _ in range(population_size):
child1, child2 = crossover(parents[0], parents[1])
offspring.append(mutate(child1, mutation_rate))
offspring.append(mutate(child2, mutation_rate))
population = offspring[:population_size]
ping_latency, download_speed, upload_speed = measure_network_performance()
user_data_input = [
"I enjoyed the vibrant colors of the flowers in the garden",
"The sky was a beautiful shade of blue",
"The sunset painted the sky with hues of red and orange"
]
dark_energy_reading = await dark_energy_reader()
if dark_energy_reading is not None:
cpu_usage = psutil.cpu_percent()
rng_value = await multi_gate_intermixing_system(user_data_input, dark_energy_reading, cpu_usage, ping_latency, quantum_params)
with open("rng.qrng", "w") as f:
f.write(str(rng_value))
print("Random number saved to rng.qrng")
else:
print("Dark energy reading not available. Skipping quantum gate with dark energy.")
async def multi_gate_intermixing_system(data_input, dark_energy, cpu_usage, ping_latency, quantum_params):
target_color = compute_target_color(quantum_params)
rgb_state = []
for data_point in data_input:
tokens = word_tokenize(data_point)
red, green, blue = 0, 0, 0
for token in tokens:
token = re.sub(r'[^a-zA-Z0-9]', '', token)
synsets = wn.synsets(token)
for synset in synsets:
red += synset.offset() % 256
green += len(synset.definition()) % 256
blue += len(synset.examples()) % 256
total = red + green + blue
red /= total if total else 1
green /= total if total else 1
blue /= total if total else 1
rgb_state.extend([red, green, blue])
for i in range(len(rgb_state)):
qml.RX(np.pi * rgb_state[i], wires=i)
for i in range(0, len(rgb_state), 3):
qml.CNOT(wires=[i, (i+1) % len(rgb_state)])
qml.CNOT(wires=[i, (i+2) % len(rgb_state)])
for i in range(0, len(rgb_state), 3):
qml.CRX(np.pi * (rgb_state[(i+1) % len(rgb_state)] - rgb_state[(i+2) % len(rgb_state)]), wires=[i, (i+2) % len(rgb_state)])
qml.CRX(np.pi * (rgb_state[(i+2) % len(rgb_state)] - rgb_state[(i+1) % len(rgb_state)]), wires=[i, (i+1) % len(rgb_state)])
qml.RY(np.pi * (psutil.virtual_memory().used / psutil.virtual_memory().total), wires=len(rgb_state))
qml.RY(np.pi * (cpu_usage / psutil.cpu_count()), wires=len(rgb_state) + 1)
qml.RY(np.pi * (ping_latency / 100), wires=len(rgb_state) + 2)
return qml.sample(qml.PauliZ(0))
if __name__ == "__main__":
asyncio.run(main())