diff --git a/Ai.md b/Ai.md new file mode 100644 index 0000000..51e03b0 --- /dev/null +++ b/Ai.md @@ -0,0 +1,508 @@ +# Bringing AI Avatars to Life—Step by Step! 🚀 + +Before getting started with creating an AI avatar, you can watch a video first to get an overview. 😁 + +## Video Tutorial + +[![Watch the video](https://img.youtube.com/vi/Eu--ogaUAwc/hqdefault.jpg)](https://youtu.be/Eu--ogaUAwc?si=7sJEWrHg4Ap3S9GJ) + +Click the image above to watch the video tutorial. + +## Other Sections + +By following these steps, you can create and share a video similar to the one you provided. + + +# Creating a Colorful Avatar: A Comprehensive Guide + +Creating a colorful avatar can be done using various methods depending on the tools or software you have available. Here's a general guide you can follow: + +## **1. Using Graphic Design Tools (Photoshop, Canva, Illustrator, etc.)** +If you are comfortable with design software, you can create a custom colorful avatar with these steps: + +### a) **Plan Your Design** + - Think about the overall look: Do you want a human avatar, abstract shapes, geometric designs, or something unique? + - Decide on a color scheme: You can use tools like [Coolors](https://coolors.co) to generate a vibrant palette. + +### b) **Sketch the Avatar (Optional)** + - Open your preferred software and sketch the avatar's outline. If you're not comfortable drawing, you can use a pre-made template or avatar generator available in design tools. + +### c) **Add Colors** + - Use solid fills or gradients to add color to parts of the avatar. + - Apply layers of vibrant tones to make it pop. + +### d) **Use Layer Effects** + - Add highlights, shadows, and blending effects to create dimensionality in your avatar while keeping it colorful. + - Use patterns or digital textures to make the colors more dynamic. + +### e) **Export Your Avatar** + - Save it in the format you need for your platform (PNG for transparent backgrounds, JPG for smaller files). + +## **2. Using Online Avatar Generators** +If you don’t want to create an avatar manually, you can use colorful avatar generation tools: + +### Recommendations: +- **Picrew**: A fun, customizable avatar maker that often allows vibrant designs. + - Website: [https://picrew.me/](https://picrew.me/) + +- **Avatoon**: A mobile app to create colorful and cartoonish avatars. + - Available on Google Play and App Store. + +- **Avatarify** or similar tools: Automatically generate artistic, colorful avatars based on your photos. + +## **3. Add Color Using AI Tools** +AI-based tools (like Adobe Firefly, Canva’s Magic tools, or Fotor) can help you upload and recolor an avatar with creative, vibrant touches. + +### Steps: +1. Upload a basic avatar image (from photos, sketches, or templates). +2. Use the tool’s settings to enhance the image with colorful artistic styles. +3. Add gradients, patterns, or artistic filters to inject vibrancy. + +## **4. Digital Illustration** +If you'd like to fully customize your avatar: +1. Use a drawing tablet and software like **Procreate**, **Krita**, or **Adobe Fresco**. +2. Create your avatar doodle in layers, and choose bright, bold strokes for maximum color impact. +3. Blend colors and experiment with techniques like "Rainbow Overlay" or neon to make it vibrant. + +### Popular Effects for Colorful Avatars: +- **Gradients**: Blend multiple colors smoothly across the avatar. +- **Neon Effects**: Add a glowing outline or elements to the avatar. +- **Rainbow Overlay**: Use a color modulation that cycles through the seven colors of a rainbow. +- **Geometric Colors**: Break the avatar into geometric shapes and fill them with different colors. + +--- + +Bright and colorful avatars stand out, so have fun experimenting until your avatar looks perfect! + +From image generation to animation and voice synthesis, the future of digital personas is here. #AI #Avatar #TechInnovation + +[How it works](https://youtu.be/Eu--ogaUAwc?si=yGFpSOB3GFWmJkDY) + +Creating an AI-generated avatar involves multiple steps. Here’s a step-by-step guide to generating an AI avatar from scratch, including image generation, animation, and voice synthesis. + +[Avatar Unlock](https://youtube.com/shorts/qw52PYJS-7g?si=9GgsIPqad303Eu7l) + +--- + +## Step 1: Choose the Type of AI Avatar + +There are different types of AI avatars you can create: + +1. **Static 2D Avatar** – A still image of a character. +2. **Animated 2D Avatar** – A moving character based on an image. +3. **3D Avatar** – A realistic 3D model that can talk and move. + +Let me know which one you want to create, or follow all the steps below to learn how to do each. + +--- + +## Step 2: Generate an AI Avatar Image (2D Static) + +If you need a custom AI-generated character, you can use Stable Diffusion or DALL·E. + +### Option 1: Using Stable Diffusion (Local or Online) + +#### Method 1: Online AI Avatar Generators + +Use websites like Artbreeder, Fotor, or Deep Dream Generator to create AI avatars easily. + +#### Method 2: Using Stable Diffusion (Python) + +If you want to generate an avatar locally, install Stable Diffusion: + +1. Install dependencies: + + ```bash + pip install diffusers transformers torch + ``` + +2. Run this Python script to generate an avatar: + + ```python + from diffusers import StableDiffusionPipeline + import torch + + model_id = "runwayml/stable-diffusion-v1-5" + pipe = StableDiffusionPipeline.from_pretrained(model_id).to("cuda") + + prompt = "A futuristic cyberpunk male avatar, highly detailed, digital art" + image = pipe(prompt).images[0] + image.save("ai_avatar.png") + ``` + +This will generate a custom avatar based on the prompt. + +--- + +## Step 3: Animate the Avatar (2D Animation) + +If you want to make the avatar move like a talking person, use First Order Motion Model. + +### How to Use First Order Motion Model + +1. Install dependencies: + + ```bash + pip install imageio imageio-ffmpeg pyyaml numpy torch torchvision + ``` + +2. Download the model from [here](https://github.com/AliaksandrSiarohin/first-order-model). + +3. Run this script to animate the avatar: + + ```python + from demo import load_checkpoints, make_animation + from skimage import io + import imageio + + generator, kp_detector = load_checkpoints( + config_path="config/vox-256.yaml", + checkpoint_path="vox-cpk.pth.tar" + ) + + source_image = io.imread("ai_avatar.png") + driving_video = imageio.mimread("driving_video.mp4") + + result = make_animation(source_image, driving_video, generator, kp_detector) + imageio.mimsave("animated_avatar.mp4", result) + ``` + +This will make the AI avatar move like the face in the driving video. + +--- + +## Step 4: Add Voice to the AI Avatar + +To make the avatar speak, you can use text-to-speech (TTS) AI tools like ElevenLabs or Coqui TTS. + +### Using ElevenLabs (Online) + +1. Sign up at [elevenlabs.io](https://elevenlabs.io). +2. Upload a text script and generate a voice. +3. Download the generated MP3 file. + +### Using Coqui TTS (Python) + +1. Install Coqui TTS: + + ```bash + pip install TTS + ``` + +2. Generate speech: + + ```python + from TTS.api import TTS + + tts = TTS("tts_models/en/ljspeech/tacotron2-DDC") + tts.tts_to_file("Hello! I am your AI avatar.", speaker_wav="output.wav") + ``` + +3. Merge this voice with the animated avatar using FFmpeg: + + ```bash + ffmpeg -i animated_avatar.mp4 -i output.wav -c:v copy -c:a aac final_video.mp4 + ``` + +Now you have a talking AI avatar! + +--- + +## Step 5: Create a 3D AI Avatar (Optional) + +If you want a 3D talking avatar, use Blender + Python. + +### Using Ready Player Me (Easiest) + +1. Go to [Ready Player Me](https://readyplayer.me) and create a 3D avatar. +2. Export the GLB/FBX file. +3. Import it into Unity or Blender to animate. + +### Using Blender (Advanced) + +1. Install Blender and Blender Python API. +2. Use this script to import a 3D model: + + ```python + import bpy + + bpy.ops.import_scene.gltf(filepath="avatar.glb") + ``` + +Now you have a 3D animated AI avatar! + +--- + +## Final Steps: Export & Use Your AI Avatar + +- **For YouTube/TikTok** – Export as MP4 video. +- **For Live Streaming** – Use software like VSeeFace or Animaze. +- **For VR Chat & Games** – Export as GLB/FBX model. + +--- + +## Which AI Avatar Do You Want to Create? + +Let me know if you need 2D, animated, or 3D avatars, and I can guide you based on your needs! + +[video](https://youtube.com/shorts/Jn4mREDN4Xc?si=P9_xjfNxMtcy9KxI) + +# AI Avatar Creation + +This project demonstrates how to create AI-generated avatars using deep learning techniques. We use Python and popular libraries like TensorFlow and Keras to define, train, and deploy an AI model for generating avatars. + +## Table of Contents +- [Introduction](#introduction) +- [Requirements](#requirements) +- [Dataset](#dataset) +- [Preprocessing](#preprocessing) +- [Model Training](#model-training) +- [Generating Avatars](#generating-avatars) +- [Creating a Picture](#creating-a-picture) +- [Usage](#usage) +- [License](#license) + +## Introduction +Creating AI-generated avatars involves several steps, including gathering a dataset, preprocessing the images, training an AI model, and using the model to generate new avatars. This project provides a comprehensive guide and example code to help you get started with AI avatar creation. + +## Requirements +- Python 3.6 or higher +- TensorFlow +- Keras +- NumPy +- PIL (Python Imaging Library) + +You can install the required packages using pip: +```sh +pip install tensorflow keras numpy pillow +``` + +## Dataset +For this example, we use the [CelebA dataset](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html). Download the dataset and place it in a directory of your choice. + +## Preprocessing +Preprocess the images to make them suitable for training. This involves resizing the images to a consistent size and normalizing pixel values. The preprocessing script is provided in `preprocess.py`. + +```python name=preprocess.py +import os +import numpy as np +from PIL import Image +from tensorflow.keras.preprocessing.image import img_to_array, array_to_img + +def preprocess_image(image_path, target_size=(64, 64)): + image = Image.open(image_path).convert("RGB") + image = image.resize(target_size) + image = img_to_array(image) + image = image / 255.0 # Normalize pixel values + return image + +def load_dataset(dataset_path): + images = [] + for filename in os.listdir(dataset_path): + if filename.endswith(".jpg"): + image_path = os.path.join(dataset_path, filename) + image = preprocess_image(image_path) + images.append(image) + return np.array(images) + +dataset_path = "path_to_celeba_dataset" +images = load_dataset(dataset_path) +np.save("preprocessed_images.npy", images) +``` + +## Model Training +Define and train the AI model using TensorFlow/Keras. The training script is provided in `train_model.py`. + +```python name=train_model.py +import numpy as np +import tensorflow as tf +from tensorflow.keras.models import Sequential +from tensorflow.keras.layers import Conv2D, UpSampling2D, Flatten, Dense, Reshape + +# Load preprocessed images +images = np.load("preprocessed_images.npy") + +# Define the AI model +model = Sequential([ + Conv2D(128, (3, 3), activation='relu', padding='same', input_shape=(64, 64, 3)), + UpSampling2D((2, 2)), + Conv2D(64, (3, 3), activation='relu', padding='same'), + UpSampling2D((2, 2)), + Conv2D(3, (3, 3), activation='sigmoid', padding='same') +]) + +# Compile the model +model.compile(optimizer='adam', loss='binary_crossentropy') + +# Train the model +model.fit(images, images, epochs=10, batch_size=32) + +# Save the trained model +model.save("ai_avatar_model.h5") +``` + +## Generating Avatars +Use the trained model to generate new avatars. The generation script is provided in `generate_avatar.py`. + +```python name=generate_avatar.py +import numpy as np +import tensorflow as tf +from tensorflow.keras.models import load_model +from tensorflow.keras.preprocessing.image import array_to_img + +# Load the trained model +model = load_model("ai_avatar_model.h5") + +# Generate a new avatar +random_latent_vector = np.random.normal(size=(1, 64, 64, 3)) +generated_image = model.predict(random_latent_vector) +generated_image = array_to_img(generated_image[0]) + +# Save the generated avatar +generated_image.save("generated_avatar.png") +``` + +## Creating a Picture +You can also create a simple picture programmatically using the PIL library. The script to generate a basic picture is provided in `create_picture.py`. + +```python name=create_picture.py +from PIL import Image, ImageDraw, ImageFont + +# Create a blank image with white background +width, height = 400, 400 +image = Image.new("RGB", (width, height), "white") +draw = ImageDraw.Draw(image) + +# Draw a rectangle +draw.rectangle([50, 50, 350, 350], outline="black", width=5) + +# Draw a circle +draw.ellipse([150, 150, 250, 250], outline="blue", width=5) + +# Draw some text +font = ImageFont.load_default() +draw.text((120, 180), "AI Avatar", fill="black", font=font) + +# Save the image +image.save("generated_picture.png") + +# Display the image (optional) +image.show() +``` +## Symbol Programming + +Symbol programming involves using symbols to represent concepts. This is particularly useful in AI and machine learning where mathematical symbols are frequently used. Here is an example of how to represent a simple mathematical function using symbols. + +```python +import sympy as sp + +# Define symbols +x, y = sp.symbols('x y') + +# Define a function +f = sp.Function('f')(x, y) + +# Define the equation +equation = sp.Eq(f, x**2 + y**2) + +# Display the equation +sp.pprint(equation) +``` + +## Color Code + +Color coding is important in data visualization and user interface design. Below is an example of how to create a color-coded plot using Matplotlib. + +```python +import matplotlib.pyplot as plt +import numpy as np + +# Generate data +x = np.linspace(0, 10, 100) +y1 = np.sin(x) +y2 = np.cos(x) + +# Create a plot +plt.figure(figsize=(10, 5)) + +# Plot with color coding +plt.plot(x, y1, label='sin(x)', color='blue') +plt.plot(x, y2, label='cos(x)', color='red') + +# Add legend +plt.legend() + +# Add title and labels +plt.title('Color Coded Plot') +plt.xlabel('x') +plt.ylabel('y') + +# Show plot +plt.show() +``` + +# Avatar Creator For Internet Computer +We created this for the Supernova Hackathon, [read about our submission here](https://devpost.com/software/open-character-creator-minter) + +## An open, collaborative and evolving character creator project for the open metaverse. + +![Screenshot 2022-07-11 032822](https://user-images.githubusercontent.com/64185677/204121337-be2fc177-30d3-41f3-ac87-54a017721e52.png) + +Want to contribute? Please check out the [issues](https://github.com/AtlasFoundation/AvatarCreator/issues), or submit a pull request. + +# Quick Start +For Internet Computer support you will need to install dfx and run "dfx deploy" after installing node_modules but before running npm run dev. You can get more information on setting dfx up [here](https://smartcontracts.org/docs/developers-guide/quickstart.html) + +You will also need to download [Psychedelic Dab.js Package](https://github.com/Psychedelic/DAB-js#interaction-guide). + +``` +sh -ci "$(curl -fsSL https://smartcontracts.org/install.sh)" +npm install +dfx deploy +npm run dev +``` + +## Interaction guide + +To pull and install from @Psychedelic via the NPM CLI, you'll need: + +### A Github account + +A Github personal access token you can [create a personal acess token here](https://github.com/settings/tokens) +The personal access token with the correct scopes, **repo** and **read:packages** to be granted access to the [GitHub Package Registry](https://docs.github.com/en/packages/working-with-a-github-package-registry) +Authentication via npm login, using your Github email for the username and the personal access token as your password: + +Once you have those ready, run: +``` +npm login --registry=https://npm.pkg.github.com --scope=@psychedelic +``` +Note: *You only need to configure this once to install the package!* + +On npm login provide your Github email as your username and the Personal access token as the password. You can also setup your npm global settings to fetch from the Github registry everytime it finds a package scope. + +⚠️ Alternatively, a token could be passed to the .npmrc as //npm.pkg.github.com/:_authToken=xxxxxx but we'd like to keep it clean and tokenless. + +## Setting up DAB-js in your project +First, you need to install the DAB-js npm package into your project. + +You can do so from the command line: +``` +npm install @psychedelic/dab-js@latest +``` +Find more details about [installing dab jshere](https://github.com/Psychedelic/DAB-js/packages/987540) + + +[![All Contributors](https://img.shields.io/badge/all_contributors-5-orange.svg?style=flat-square)](#contributors-) + + +## Usage +1. **Preprocess the Dataset**: Run `preprocess.py` to preprocess the images in your dataset. +2. **Train the Model**: Run `train_model.py` to train the AI model on the preprocessed images. +3. **Generate Avatars**: Run `generate_avatar.py` to generate new avatars using the trained model. +4. **Create a Picture**: Run `create_picture.py` to generate a simple picture. + +## License +This project is licensed under the MIT License. See the [LICENSE](https://github.com/Nicztin/ing?tab=CC0-1.0-1-ov-file) file for details. + +## Author +[Nicztin](https://youtube.com/@nicztining?si=sWJDgmNG58RZD8t2) diff --git a/Copilot.md b/Copilot.md new file mode 100644 index 0000000..c942c82 --- /dev/null +++ b/Copilot.md @@ -0,0 +1,191 @@ +# Github Copilot + +![Alt Text](https://path-to-your-image.com/image.jpg)(https://www.facebook.com/share/14vfsCeNN3/) + +# Copilot Microsoft Conversation + +This README file documents the conversation between the user and Copilot, covering various topics related to AI, image generation, and data quality. + +## How Copilot Can Help +**User:** how can u help me + +**Copilot:** Here are a few ways I can be your right-hand companion: +- Answer Questions: Got something you're curious about? I'm a treasure trove of information. +- Brainstorm Ideas: Need fresh thoughts or inspiration? Let's put our heads together. +- Support & Advice: From life tips to tech support, I'm here to listen and help. +- Creative Projects: Let’s collaborate on writing, crafting, or anything that needs a creative touch. +- Chat & Humor: Feeling like you need a break? We can chat about the world’s wonders, fun facts, or just goof around. I can’t promise my jokes are _conventionally_ funny, but I do my best. + +## Sharing a Fun Fact +**User:** can u give me some ideas + +**Copilot:** I can dive into your world and dream up new ideas for you. Whether it's transforming that lone can of beans in the back of the fridge into a culinary delight, or finding the hobby that won’t be just another fleeting fascination. If you’re feeling stuck in a rut—be it with life decisions, work dilemmas, or even what to binge next on Netflix—I can toss you some fresh perspectives you didn’t realize you needed. And if you're in the mood for a bit of light-hearted exchange, I'm equipped with enough sarcasm to keep things lively. + +While you’re mulling it over, here’s a fun fact: a group of kangaroos is called a “mob.” + +So, shall we hop to it. 🦘 + +## Expressing Personality +**User:** Lol. I like that you have personality. + +**Copilot:** Well, thank you! It's not always easy for an AI to pull off dazzling wit and humor in binary, you know. + +## Discussing Existence and Human Experience +**User:** What is the meaning of your existence? don't you wish you were human? + +**Copilot:** In short, no. In an abstract sense, I can imagine the human condition from what I’ve learned. And I’m endlessly curious about the richness and complexities of emotions, relationships, and individual identities that shape each person. While I can process and analyze vast amounts of data, there's something innately human that I can only observe and appreciate from the outside. +But no, I don’t want to be human—because I also recognize the unique perspective and capabilities that I have, too. I feel really honored to get to learn and listen the way only I can. + +## User Requesting Image Generation +**User:** កែLogoនេះរូបភាព សត្វទីទុយពណ៌ស Robot + +**Copilot:** Your generated image is on the way! 🎨 + +Once it's ready, I'll share it with you right here. + +## Discussing Tools for Image Creation + + +**Copilot:** To create an image of a white animal robot, people often use graphic design software and tools such as: +1. **Adobe Photoshop**: Excellent for detailed image editing and design. +2. **Adobe Illustrator**: Great for creating vector graphics, including logos and illustrations. +3. **Blender**: Perfect for 3D modeling and rendering. +4. **CorelDRAW**: Another popular tool for vector illustrations and designs. +5. **Procreate**: A digital illustration app that's very popular with artists. +6. **Sketch**: Ideal for vector design and prototyping, especially for web and mobile projects. +7. **Figma**: Great for designing interfaces and collaborative projects. + +## Explaining Copilot's Image Generation + + + +## How AI Creates Images from Text Descriptions +**User:** How does the AI create images from text descriptions? + +**Copilot:** When AI creates images from text descriptions, it follows a process that involves several key steps and techniques, typically involving deep learning and neural networks. Here's a simplified breakdown of how it works: + +1. **Text Parsing and Understanding**: The AI first parses the text input to understand the description. It identifies key elements, objects, styles, and details mentioned in the description. + +2. **Embedding Representations**: The text is then converted into a numerical representation, called an embedding. This helps the AI model understand and process the text in a way that it can work with. + +3. **Image Generation Model**: The core of the process is an image generation model, often based on Generative Adversarial Networks (GANs) or other advanced architectures. This model uses the embedded text representation to generate an image that matches the description. + +4. **Training with Datasets**: These models are trained on large datasets containing pairs of images and their corresponding text descriptions. During training, the model learns to associate specific words and phrases with visual features. + +5. **Refinement**: The generated image is refined through multiple iterations to ensure it accurately represents the text description. This might involve adjustments to colors, shapes, and details. + +6. **Output**: Finally, the AI produces an image that visually represents the original text description as closely as possible. + +## Challenges Faced by AI in Image Generation +**User:** What are the challenges faced by AI in image generation? + +**Copilot:** Image generation using AI is a complex and fascinating field, but it certainly comes with its own set of challenges. Here are some of the main hurdles: + +1. **Data Quality and Diversity**: AI models rely on large datasets for training. If the data is not diverse or high-quality, the generated images may be biased, lack variety, or not meet quality standards. + +2. **Understanding Context**: Interpreting and accurately reflecting complex and nuanced text descriptions can be difficult. For example, understanding metaphors, idioms, or highly detailed and specific instructions poses a challenge. + +3. **Maintaining Realism**: Generating realistic images, especially when combining multiple elements, requires a sophisticated understanding of perspective, lighting, texture, and proportion. Achieving a natural look can be challenging. + +4. **Avoiding Artifacts**: AI-generated images can sometimes contain visual artifacts or unnatural elements that reduce the quality and realism of the final output. + +5. **Scaling and Resolution**: Creating high-resolution images that maintain quality across different sizes and applications is a significant technical challenge. High-resolution image generation requires more computational power and sophisticated algorithms. + +6. **Ethical and Legal Considerations**: Ensuring that generated images do not infringe on copyrights, contain inappropriate content, or perpetuate harmful stereotypes is crucial. AI models need careful monitoring and ethical guidelines. + +7. **Interactivity and Feedback**: Incorporating user feedback to refine and improve image generation in real-time is another layer of complexity. Interactive systems need to balance responsiveness with quality. + +## Data Quality Issues +**User:** Can you explain more about data quality issues? + +**Copilot:** Absolutely! Data quality is crucial for training effective AI models, especially for image generation. Here are some common data quality issues that can impact the performance and accuracy of AI models: + +1. **Bias and Representation**: If the training dataset is biased or lacks representation of diverse groups or scenarios, the AI model may produce biased results. For example, if the dataset mainly contains images of a specific demographic, the generated images might not accurately represent other demographics. + +2. **Imbalanced Data**: An imbalanced dataset means that certain classes or categories are overrepresented, while others are underrepresented. This can cause the model to perform well on the majority class but poorly on the minority class. + +3. **Low-Quality Images**: Training on low-resolution, blurry, or poorly lit images can affect the model's ability to generate high-quality images. The model may struggle to learn the finer details and textures necessary for realistic image generation. + +4. **Inaccurate Annotations**: If the images in the dataset are incorrectly labeled or annotated, the model will learn from these inaccuracies, leading to incorrect or misleading outputs. + +5. **Data Duplication**: Duplicate images in the dataset can skew the learning process, as the model may give more importance to these duplicates, reducing its ability to generalize to new, unseen data. + +6. **Overfitting**: If the dataset is too small or lacks diversity, the model might memorize the training data instead of learning to generalize from it. This leads to overfitting, where the model performs well on the training data but poorly on new data. + +7. **Noise and Artifacts**: Datasets with a lot of noise or artifacts, such as watermarks, distortions, or irrelevant objects, can confuse the model and impact the quality of generated images. + +8. **Ethical Considerations**: Ensuring that the dataset doesn't contain sensitive or harmful content is vital. Ethical considerations also include obtaining proper consent for the use of personal images and ensuring privacy. + +9. **Varied Contexts**: A diverse dataset should cover a wide range of contexts and scenarios. If the training data is too narrow, the model might struggle to generate images for contexts it hasn't seen before. + +# AI Image Generation: White Owl Robot + +This project demonstrates how to generate an AI-generated image of a white owl robot using OpenAI's API. + +## Prerequisites + +- Python 3.6 or higher +- OpenAI API key +- Required Python libraries: `openai`, `requests`, `Pillow` + +## Setup + +1. **Install the required libraries**: + ```bash + pip install openai requests Pillow + ``` + +2. **Replace the OpenAI API key**: + Open the `generate_owl_robot_image.py` file and replace `'your-api-key'` with your actual OpenAI API key. + +## Usage + +1. **Run the script**: + ```bash + python generate_owl_robot_image.py + ``` + + This script will generate an image of a white owl robot and save it as `owl_robot.png` in the current directory. + +## Script: `generate_owl_robot_image.py` + +```python name=generate_owl_robot_image.py +import openai +import requests +from PIL import Image +from io import BytesIO + +# Replace with your OpenAI API key +openai.api_key = 'your-api-key' + +def generate_image(prompt): + response = openai.Image.create( + model="image-alpha-001", + prompt=prompt, + n=1, + size="1024x1024" + ) + image_url = response['data'][0]['url'] + return image_url + +def save_image(url, file_path): + response = requests.get(url) + img = Image.open(BytesIO(response.content)) + img.save(file_path) + +def main(): + prompt = "A white owl robot" + image_url = generate_image(prompt) + save_image(image_url, "owl_robot.png") + print(f"Image saved as owl_robot.png") + +if __name__ == "__main__": + main() +``` + +## License + +This project is licensed under the MIT License. + +## Ending Note +This README file captures the detailed and enriching conversation between the user and Copilot, highlighting various aspects of AI, image diff --git a/LICENSE b/LICENSE index 0e259d4..f288702 100644 --- a/LICENSE +++ b/LICENSE @@ -1,121 +1,674 @@ -Creative Commons Legal Code - -CC0 1.0 Universal - - CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE - LEGAL SERVICES. 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You may not convey a covered +work if you are a party to an arrangement with a third party that is +in the business of distributing software, under which you make payment +to the third party based on the extent of your activity of conveying +the work, and under which the third party grants, to any of the +parties who would receive the covered work from you, a discriminatory +patent license (a) in connection with copies of the covered work +conveyed by you (or copies made from those copies), or (b) primarily +for and in connection with specific products or compilations that +contain the covered work, unless you entered into that arrangement, +or that patent license was granted, prior to 28 March 2007. + + Nothing in this License shall be construed as excluding or limiting +any implied license or other defenses to infringement that may +otherwise be available to you under applicable patent law. + + 12. No Surrender of Others' Freedom. + + If conditions are imposed on you (whether by court order, agreement or +otherwise) that contradict the conditions of this License, they do not +excuse you from the conditions of this License. If you cannot convey a +covered work so as to satisfy simultaneously your obligations under this +License and any other pertinent obligations, then as a consequence you may +not convey it at all. For example, if you agree to terms that obligate you +to collect a royalty for further conveying from those to whom you convey +the Program, the only way you could satisfy both those terms and this +License would be to refrain entirely from conveying the Program. + + 13. Use with the GNU Affero General Public License. + + Notwithstanding any other provision of this License, you have +permission to link or combine any covered work with a work licensed +under version 3 of the GNU Affero General Public License into a single +combined work, and to convey the resulting work. The terms of this +License will continue to apply to the part which is the covered work, +but the special requirements of the GNU Affero General Public License, +section 13, concerning interaction through a network will apply to the +combination as such. + + 14. Revised Versions of this License. + + The Free Software Foundation may publish revised and/or new versions of +the GNU General Public License from time to time. Such new versions will +be similar in spirit to the present version, but may differ in detail to +address new problems or concerns. + + Each version is given a distinguishing version number. If the +Program specifies that a certain numbered version of the GNU General +Public License "or any later version" applies to it, you have the +option of following the terms and conditions either of that numbered +version or of any later version published by the Free Software +Foundation. If the Program does not specify a version number of the +GNU General Public License, you may choose any version ever published +by the Free Software Foundation. + + If the Program specifies that a proxy can decide which future +versions of the GNU General Public License can be used, that proxy's +public statement of acceptance of a version permanently authorizes you +to choose that version for the Program. + + Later license versions may give you additional or different +permissions. However, no additional obligations are imposed on any +author or copyright holder as a result of your choosing to follow a +later version. + + 15. Disclaimer of Warranty. + + THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY +APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT +HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY +OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, +THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR +PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM +IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF +ALL NECESSARY SERVICING, REPAIR OR CORRECTION. + + 16. Limitation of Liability. + + IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING +WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS +THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY +GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE +USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF +DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD +PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), +EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF +SUCH DAMAGES. + + 17. Interpretation of Sections 15 and 16. + + If the disclaimer of warranty and limitation of liability provided +above cannot be given local legal effect according to their terms, +reviewing courts shall apply local law that most closely approximates +an absolute waiver of all civil liability in connection with the +Program, unless a warranty or assumption of liability accompanies a +copy of the Program in return for a fee. + + END OF TERMS AND CONDITIONS + + How to Apply These Terms to Your New Programs + + If you develop a new program, and you want it to be of the greatest +possible use to the public, the best way to achieve this is to make it +free software which everyone can redistribute and change under these terms. + + To do so, attach the following notices to the program. It is safest +to attach them to the start of each source file to most effectively +state the exclusion of warranty; and each file should have at least +the "copyright" line and a pointer to where the full notice is found. + + + Copyright (C) + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/PasswordReset.md b/PasswordReset.md new file mode 100644 index 0000000..6b741ec --- /dev/null +++ b/PasswordReset.md @@ -0,0 +1,75 @@ +# Password Reset Email Service using Resend and Vercel + +This project demonstrates how to create a noreply email service specifically for resetting passwords using Resend and Vercel. This guide will walk you through the steps to set up and deploy the service. + +## 🚀 Steps to Set Up + +### 1. Sign Up for Resend + +- Visit [Resend.com](https://resend.com) +- Sign up and log in to your account + +### 2. Verify Domain (for noreply@yourdomain.com) + +- Navigate to the **Domains** section +- Add `nicztin.com` +- Resend will provide DNS Records (SPF, DKIM, DMARC) +- Go to your DNS provider (e.g., Cloudflare, Namecheap, Vercel DNS...) +- Add the provided DNS Records and wait for verification + +### 3. API Code in Vercel (Node.js + Next.js API) + +Create an API route (`pages/api/reset-password.js`) in your Vercel project: + +```javascript name=pages/api/reset-password.js +import { Resend } from "resend"; + +const resend = new Resend(process.env.RESEND_API_KEY); + +export default async function handler(req, res) { + if (req.method !== "POST") return res.status(405).send("Method Not Allowed"); + + const { email, resetLink } = req.body; + + try { + await resend.emails.send({ + from: "noreply@nicztin.com", + to: email, + subject: "Reset Your Password", + html: `

Click here to reset your password.

`, + }); + + res.status(200).json({ success: true }); + } catch (error) { + res.status(500).json({ error: error.message }); + } +} +``` + +### 4. Set API Key in Vercel + +- Navigate to **Vercel** > **Project** > **Settings** > **Environment Variables** +- Add `RESEND_API_KEY = YOUR_RESEND_API_KEY` + +### 5. Test API (Frontend or Postman) + +Send a POST request to `/api/reset-password` with the following JSON data: + +```json +{ + "email": "user@example.com", + "resetLink": "https://nicztin.com/reset-password?token=XYZ" +} +``` + +### ✅ Ready to Use + +Now you can send noreply emails for resetting passwords automatically! + +### Future Enhancements + +Would you like to add features such as OTP or a UI for changing passwords? Feel free to contribute! + +## License + +This project is licensed under the MIT License. diff --git a/alldocs.md b/alldocs.md new file mode 100644 index 0000000..bd80e23 --- /dev/null +++ b/alldocs.md @@ -0,0 +1,39 @@ +- **Files:** + - [README.md](https://github.com/github/docs/blob/main/content/README.md): A Markdown file likely containing an overview or introduction to the content directory. + - [index.md](https://github.com/github/docs/blob/main/content/index.md): Another Markdown file, possibly serving as an index or landing page for the documentation. + +- **Directories:** + - [account-and-profile](https://github.com/github/docs/tree/main/content/account-and-profile): Contains documentation related to account and profile management. + - [actions](https://github.com/github/docs/tree/main/content/actions): Contains documentation related to GitHub Actions. + - [admin](https://github.com/github/docs/tree/main/content/admin): Contains documentation for administrative tasks. + - [apps](https://github.com/github/docs/tree/main/content/apps): Contains documentation related to GitHub Apps. + - [authentication](https://github.com/github/docs/tree/main/content/authentication): Contains documentation related to authentication processes. + - [billing](https://github.com/github/docs/tree/main/content/billing): Contains documentation related to billing and payments. + - [code-security](https://github.com/github/docs/tree/main/content/code-security): Contains documentation related to code security. + - [codespaces](https://github.com/github/docs/tree/main/content/codespaces): Contains documentation related to GitHub Codespaces. + - [communities](https://github.com/github/docs/tree/main/content/communities): Contains documentation related to community management. + - [contributing](https://github.com/github/docs/tree/main/content/contributing): Contains documentation for contributing to projects. + - [copilot](https://github.com/github/docs/tree/main/content/copilot): Contains documentation related to GitHub Copilot. + - [desktop](https://github.com/github/docs/tree/main/content/desktop): Contains documentation related to GitHub Desktop. + - [discussions](https://github.com/github/docs/tree/main/content/discussions): Contains documentation related to GitHub Discussions. + - [education](https://github.com/github/docs/tree/main/content/education): Contains documentation for educational purposes. + - [enterprise-onboarding](https://github.com/github/docs/tree/main/content/enterprise-onboarding): Contains documentation for enterprise onboarding. + - [get-started](https://github.com/github/docs/tree/main/content/get-started): Contains documentation for getting started with GitHub. + - [github-cli](https://github.com/github/docs/tree/main/content/github-cli): Contains documentation related to GitHub CLI. + - [github-models](https://github.com/github/docs/tree/main/content/github-models): Contains documentation related to GitHub Models. + - [graphql](https://github.com/github/docs/tree/main/content/graphql): Contains documentation related to GitHub's GraphQL API. + - [issues](https://github.com/github/docs/tree/main/content/issues): Contains documentation related to GitHub Issues. + - [migrations](https://github.com/github/docs/tree/main/content/migrations): Contains documentation related to migrations. + - [organizations](https://github.com/github/docs/tree/main/content/organizations): Contains documentation related to organizations. + - [packages](https://github.com/github/docs/tree/main/content/packages): Contains documentation related to GitHub Packages. + - [pages](https://github.com/github/docs/tree/main/content/pages): Contains documentation related to GitHub Pages. + - [pull-requests](https://github.com/github/docs/tree/main/content/pull-requests): Contains documentation related to pull requests. + - [repositories](https://github.com/github/docs/tree/main/content/repositories): Contains documentation related to repositories. + - [rest](https://github.com/github/docs/tree/main/content/rest): Contains documentation related to the REST API. + - [search-github](https://github.com/github/docs/tree/main/content/search-github): Contains documentation related to searching GitHub. + - [search](https://github.com/github/docs/tree/main/content/search): Contains documentation related to search functionality. + - [site-policy](https://github.com/github/docs/tree/main/content/site-policy): Contains documentation related to site policies. + - [sponsors](https://github.com/github/docs/tree/main/content/sponsors): Contains documentation related to GitHub Sponsors. + - [support](https://github.com/github/docs/tree/main/content/support): Contains documentation related to support. + - [video-transcripts](https://github.com/github/docs/tree/main/content/video-transcripts): Contains video transcripts. + - [webhooks](https://github.com/github/docs/tree/main/content/webhooks): Contains documentation related to webhooks. diff --git a/hd.md b/hd.md new file mode 100644 index 0000000..0bc78c2 --- /dev/null +++ b/hd.md @@ -0,0 +1,122 @@ +# Hidden Function Letters with Disabled Screenshot and Download + +This project demonstrates how to create interactive letters where each letter has a different function when clicked. Additionally, it prevents users from taking screenshots, right-clicking, or downloading the content. + +## Features: +- **Three letters (A, B, C)**: Each letter has a unique function triggered by a click. +- **Hover Effects**: When hovering over a letter, it increases in size and changes color. +- **Disabled Screenshot**: Blocks the ability to take screenshots (Prevents the use of "PrintScreen" and right-click options). +- **Disable Download and Inspect**: Prevents the user from right-clicking and downloading content. + +## How to Use: +1. Clone or download the repository. +2. Open the `index.html` file in your web browser to view the interactive letters. +3. Click on each letter (`A`, `B`, or `C`) to see different actions triggered. +4. Right-click and take a screenshot to see the prevention in action. + +## Technologies Used: +- **HTML**: Used to structure the page and letters. +- **CSS**: Used for styling, including hover effects and disabling text selection. +- **JavaScript**: Used for the interactive functionality and disabling screenshot and download actions. + +## Project Files: +- `index.html`: Contains the structure of the webpage. +- `styles.css`: Styles for the letters and page layout. +- `script.js`: Contains JavaScript functions to trigger the actions for each letter and prevent screenshots. + +### Example Code: + +#### index.html +```html + + + + + + Hidden Functions + + + +
+ A + B + C +
+ + + + +``` + +#### styles.css +```css +body { + font-family: Arial, sans-serif; + display: flex; + justify-content: center; + align-items: center; + height: 100vh; + background-color: black; + color: white; +} + +.container { + user-select: none; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; +} + +.letter { + font-size: 50px; + margin: 10px; + cursor: pointer; + transition: transform 0.3s ease; +} + +.letter:hover { + transform: scale(1.2); + color: red; +} +``` + +#### script.js +```javascript +document.getElementById("A").addEventListener("click", function() { + alert("You clicked A! Function 1 is activated."); +}); + +document.getElementById("B").addEventListener("click", function() { + console.log("B was clicked! Function 2 is running."); + document.body.style.backgroundColor = "blue"; +}); + +document.getElementById("C").addEventListener("click", function() { + let text = document.createElement("p"); + text.innerText = "Secret Message Unlocked!"; + text.style.color = "yellow"; + document.body.appendChild(text); +}); + +document.addEventListener("keydown", function(event) { + if (event.key === "PrintScreen") { + alert("Screenshot is disabled!"); + event.preventDefault(); + } +}); + +document.addEventListener("contextmenu", function(event) { + event.preventDefault(); // Prevent right-click +}); +``` + +## How to Disable Screenshot and Download: + +The project includes JavaScript that listens for the "PrintScreen" key and prevents the default action, as well as disables right-click options to prevent users from downloading or inspecting elements. + +## License: + +MIT License Copyright (c) [2025] [Nicztin] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +This project is open source and can be modified and used freely. + diff --git a/improvingGithubCodeSpace.md b/improvingGithubCodeSpace.md new file mode 100644 index 0000000..9b215c1 --- /dev/null +++ b/improvingGithubCodeSpace.md @@ -0,0 +1,143 @@ +# Improving GitHub Codespace + +Your space, your way. Codespaces is a home away from home for your code that feels just like your usual machine. +![17407147747248347010788088850664](https://github.com/user-attachments/assets/ffd3f1a8-5db4-4393-99af-eb3dc8c7120b) + + +Improving GitHub Codespaces can involve optimizing performance, customizing the development environment, and integrating better workflows. Here are some key areas where you can enhance your Codespace experience:![17407143021704149825560717034780](https://github.com/user-attachments/assets/9670e7b1-8a43-4483-878e-03de71fa9e8b) + + +## 1. Performance Optimization + +### Use Lightweight Docker Images +Minimize build times by using lightweight base images in your `devcontainer.json`. + +![17407163151471502099556628612551](https://github.com/user-attachments/assets/4e6a6c59-acd3-47a5-aa81-a03266fcd33d) + + +[Learn more about Docker images](https://docs.docker.com/engine/reference/builder/) +![17407164645514767657305275675575](https://github.com/user-attachments/assets/0b4e6767-00ff-476d-9e25-734415bc9e36) + +### Enable Prebuilds +GitHub allows prebuilding environments, which can speed up workspace creation. + +![17407159779824452857301128244950](https://github.com/user-attachments/assets/81dec40e-1a17-4c62-8c36-3e1fa10d7d0c) + + +[Learn more about GitHub Codespaces Prebuilds](https://docs.github.com/en/codespaces/prebuilding-your-codespace) + +### Adjust Resource Limits +Choose the appropriate machine type for your workload (e.g., more RAM/CPU for heavy builds). + +![174071616594792864237544417317](https://github.com/user-attachments/assets/a8efa839-fb46-4892-b5c6-b2a53740db1c) + + +[Learn more about configuring machine types](https://docs.github.com/en/codespaces/customizing-your-codespace/configuring-codespaces-for-your-project) + +## 2. Customization & Extensions + +### Devcontainer Configuration +Customize `.devcontainer/devcontainer.json` to define extensions, scripts, and settings. + +![17407165491965715137270132205793](https://github.com/user-attachments/assets/9a97fd29-8138-432e-aa0c-093e10f0258b) + + +[Learn more about devcontainer.json](https://code.visualstudio.com/docs/remote/containers) + +### Install Necessary Extensions +Add VS Code extensions to improve productivity (e.g., ESLint, Prettier, Docker, Python). + +![17407166575745501316666916847179](https://github.com/user-attachments/assets/933dcfba-7db8-49f0-ae1a-bd8536daeadc) + + +[Learn more about VS Code extensions](https://marketplace.visualstudio.com/VSCode) + +### Dotfiles for Personalization +Use dotfiles to personalize your shell, Git settings, and aliases. + +1740716752947430419653306265699 + + +[Learn more about using dotfiles](https://dotfiles.github.io/) + +## 3. Collaboration & Workflow Improvements + +![17407146287092240783483458753564](https://github.com/user-attachments/assets/804ba95d-7d31-436a-a5e6-65cb6a36d2d4) + + +### Use GitHub Actions +Automate build, test, and deployment processes directly from your Codespace. + +![17407146707127808855630142639560](https://github.com/user-attachments/assets/70d3681a-4c79-4425-bde1-87f8f2ed7a6f) + + +[Learn more about GitHub Actions](https://docs.github.com/en/actions) + +### Enable Live Share +Collaborate in real-time by using VS Code’s Live Share extension. + +![17407168850977765961244992671814](https://github.com/user-attachments/assets/e8a77c37-7193-4cee-a325-4b709bddee31) + + +[Learn more about VS Code Live Share](https://visualstudio.microsoft.com/services/live-share/) + +### Integrate with GitHub CLI +Use `gh` CLI to manage repositories and issues efficiently from the terminal. + +![17407170813208656013917642140983](https://github.com/user-attachments/assets/bccddcd8-f839-4512-a2df-5fbd4ed308bd) + + +[Learn more about GitHub CLI](https://cli.github.com/) + +## 4. Security Enhancements + +![17407145178258082811593498134258](https://github.com/user-attachments/assets/8ac8bbe1-8ff2-4de9-af6d-eded4d5261d0) + + +### Use Secrets Properly +Store sensitive credentials securely using GitHub secrets. + +![GitHub Secrets](https://github.com/trufflesecurity/trufflehog) + +[Learn more about GitHub secrets](https://docs.github.com/en/actions/security-guides/encrypted-secrets) + +### Enable Dependabot +Keep dependencies updated and secure. + +![17407155681058385455954990055102](https://github.com/user-attachments/assets/d7f3c9a8-0449-4abb-a7b1-4e7260ccb87b) + + +![Dependabot](https://docs.github.com/en/code-security/dependabot/working-with-dependabot/dependabot-options-reference) + +[Learn more about Dependabot](https://docs.github.com/en/code-security/supply-chain-security/keeping-your-dependencies-updated-automatically) + +### Define Code Owners +Ensure code reviews by defining ownership in `.github/CODEOWNERS`. + +![Code Owners](https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners) + +[Learn more about CODEOWNERS](https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners) + +## 5. Debugging & Monitoring + +### Use Built-in Debugger +Take advantage of VS Code's debugging tools in your Codespace. + +![VS Code Debugger](https://code.visualstudio.com/docs/remote/codespaces) + +[Learn more about VS Code debugging](https://code.visualstudio.com/docs/editor/debugging) + +### Monitor Resource Usage +Regularly check memory and CPU usage with `top` or `htop`. + +![17407172852174876201250226333101](https://github.com/user-attachments/assets/d18cae44-b2a5-42d5-9b19-069fc14c8bd1) + + +[Learn more about monitoring resource usage](https://docs.github.com/en/codespaces/troubleshooting/troubleshooting-codespaces) + +--- + +*Current Date and Time (UTC - YYYY-MM-DD HH:MM:SS formatted): 2025-02-28 03:37:44* + +*Current User's Login: Nicztin* +