HTTPStatus Exception: Client error '401 Unauthorized' for url 'https://api.openai.com/v1/chat/completions'

[TravisHammonds]

When adding my API key for openAI in an attempt to generate a readme file, I receive the following error multiple times. HTTPStatus Exception: Client error '401 Unauthorized' for URL 'https://api.openai.com/v1/chat/completions'

Here is my input, replacing my API key for security: readmeai --api-key "OPEN_AI_API_KEY" --output README.md --repository https://github.com/TravisHammonds/decoder-ring.git

I then get the following output...

And the README file looks like this...

I have made sure that the API key has been input correctly and that the spelling and case sensitivity match. Any help would be appreciated.

Disclaimer: I am new to API integrations with openAI.

[Acetyld]

Same here.

[eli64s]

Hey all @Acetyld @TravisHammonds

Just pushed some updates. Let me know if you're still facing trouble. Install the following:

pip install --upgrade readmeai

Thank you, Eli

[FilipJaskovic]

I am still facing the same issues as @Acetyld @TravisHammonds.

[eli64s]

@FilipJaskovic can you share the repository if its public? Also are you using a paid account on OpenAI or the free one?

[FilipJaskovic]

The repositories I utilized are public, and you can access them through the following links:

Sieve Of Eratosthenes Repository CCC-Oct2023 Repository

Regarding your question about the OpenAI account, I am using a ‘Pay as you go’ model, which I think is the paid version.

[eli64s]

Thanks @FilipJaskovic. I was able to generate both READMEs using the latest version of readme-ai.

Lets start by running the command pip list | grep -i readmeai in your terminal to check the current version you have installed.

Make sure you're running readmeai==0.4.45 and try once more with the following steps.

pip install --upgrade readmeai

export OPENAI_API_KEY=mykey

readmeai -r https://github.com/FilipJaskovic/SieveOfEratosthenes readme-issue.md  

If that doesn't work can you share a little more info about your environment, commands you're running, and any error messages?

Thank you!

Here are your READMEs in the mean time!

Sieve Of Eratosthenes Repo

SIEVEOFERATOSTHENES

◦ Prime Power Unleashed!

◦ Developed with the software and tools below.

--- ## 📖 Table of Contents - [📖 Table of Contents](#-table-of-contents) - [📍 Overview](#-overview) - [📦 Features](#-features) - [📂 repository Structure](#-repository-structure) - [⚙️ Modules](#modules) - [🚀 Getting Started](#-getting-started) - [🔧 Installation](#-installation) - [🤖 Running SieveOfEratosthenes](#-running-SieveOfEratosthenes) - [🧪 Tests](#-tests) - [🛣 Roadmap](#-roadmap) - [🤝 Contributing](#-contributing) - [📄 License](#-license) - [👏 Acknowledgments](#-acknowledgments) --- ## 📍 Overview The repository contains multiple Python scripts implementing the Sieve of Eratosthenes algorithm to find prime numbers. The scripts include optimized versions like segmented sieves and incremental sieves. Users can input a number and get a list of prime numbers up to that number. The code offers efficient prime number generation, making it valuable for mathematical and computational applications. --- ## 📦 Features | | Feature | Description | |----|--------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | ⚙️ | **Architecture** | The codebase consists of four Python files that implement various versions of the Sieve of Eratosthenes algorithm: `SegmentedSieve.py`, `SieveOfEratosthenes.py`, `OptimisedSegmentedWheelSieve.py`, and `IncrementalSieve.py`. Each file contains a different implementation of the algorithm, demonstrating modularity and different approaches to solving the same problem. The codebase follows a modular design pattern, allowing for easy maintenance and extension. | | 📄 | **Documentation** | The repository lacks comprehensive documentation. While each file contains code comments explaining the purpose and functionality of the code, a more detailed README file or documentation explaining the usage, inputs, and expected outputs of each file would greatly enhance the comprehensiveness of the documentation. | | 🔗 | **Dependencies** | The codebase relies on the core Python language (version not specified) and the `py` library, which is typically used for testing purposes. There are no external dependencies, which simplifies the setup and usage of the codebase. | | 🧩 | **Modularity** | The codebase demonstrates good modularity by providing separate implementation files for different versions of the Sieve of Eratosthenes algorithm. Each file contains a self-contained implementation, allowing for easy interchangeability and maintainability. The code could benefit from a clear separation of concerns and organizing the codebase into folders or packages for better organization. | | 🧪 | **Testing** | The codebase includes a dependency on the `py` library, which suggests that the code may include unit tests. However, no tests or testing strategies are visible in the repository. The absence of tests introduces a risk of undetected bugs or regressions. Adding test cases, preferably using a testing framework like `pytest` or `unittest`, would improve code quality and provide confidence in the correctness of the implementations. | | ⚡️ | **Performance** | The codebase implements various versions of the Sieve of Eratosthenes algorithm, which is known for its efficiency in finding prime numbers. The specific performance characteristics of each implementation are not discussed in the code summaries, but the Sieve of Eratosthenes algorithm is generally considered to have a time complexity of O(n log log n), making it highly efficient for finding prime numbers. The choice of different algorithmic optimizations (such as wheel optimization) in some implementations also suggests an emphasis on performance. | | 🔐 | **Security** | The codebase does not address security concerns explicitly. However, as the code is focused on generating prime numbers using the Sieve of Eratosthenes algorithm, it is unlikely to introduce specific security vulnerabilities. Standard best practices for secure coding, such as input validation and protection against common attacks (e.g., injection), are not addressed in the codebase. | | 🔀 | **Version Control**| The repository uses Git for version control. It contains a single branch, indicating a lack of active development or collaboration. No specific version control strategies --- ## 📂 Repository Structure ```sh └── SieveOfEratosthenes/ ├── IncrementalSieve.py ├── OptimisedSegmentedWheelSieve.py ├── SegmentedSieve.py └── SieveOfEratosthenes.py ``` --- ## ⚙️ Modules

Root

| File | Summary | | --- | --- | | [SegmentedSieve.py](https://github.com/FilipJaskovic/SieveOfEratosthenes/blob/main/SegmentedSieve.py) | The code implements the Sieve of Eratosthenes algorithm to find all prime numbers up to a given upper limit'n'. It consists of two functions:1. simple_sieve(n): This function uses the basic sieve algorithm to find primes up to the square root of'n'.2. segmented_sieve(n): This function uses a segmented approach to find primes up to'n'. It breaks the input range into segments and applies the simple_sieve function on each segment.The code takes user input for'n' and prints the list of prime numbers using the segmented_sieve function. | | [SieveOfEratosthenes.py](https://github.com/FilipJaskovic/SieveOfEratosthenes/blob/main/SieveOfEratosthenes.py) | The code implements the Sieve of Eratosthenes algorithm to find all prime numbers less than or equal to a given number,'n'. It initializes a sieve list to mark numbers as prime or not. Then, it iterates through integers from 2 to the square root of'n', checking and marking multiples of each prime number as non-prime. Finally, it creates a list of prime numbers and returns it. The code takes user input for the value of'n' and then prints the prime numbers less than or equal to'n'. | | [OptimisedSegmentedWheelSieve.py](https://github.com/FilipJaskovic/SieveOfEratosthenes/blob/main/OptimisedSegmentedWheelSieve.py) | The code `OptimisedSegmentedWheelSieve.py` contains a function `segmented_sieve_with_wheel(n)` that implements the segmented sieve algorithm with a wheel optimization. This algorithm efficiently finds all prime numbers up to a given upper limit `n` by dividing the input range into smaller segments. It uses the Sieve of Eratosthenes method to eliminate non-prime numbers and stores the prime numbers in a list, which is returned as the result. The code also includes a main function that prompts the user to input the upper limit `n` and prints the list of prime numbers up to that limit. | | [IncrementalSieve.py](https://github.com/FilipJaskovic/SieveOfEratosthenes/blob/main/IncrementalSieve.py) | This code implements an incremental sieve algorithm called "Sieve of Eratosthenes" to generate prime numbers. It starts by yielding the first two primes (2 and 3), and then it iteratively finds and yields new prime numbers. It keeps track of discovered primes in a list and identifies composite (non-prime) numbers by storing them as keys in a dictionary, along with the corresponding increment (step) associated with each prime. The code also includes a test to print an infinite sequence of prime numbers until interrupted by the user. |

--- ## 🚀 Getting Started ***Dependencies*** Please ensure you have the following dependencies installed on your system: `- ℹ️ Dependency 1` `- ℹ️ Dependency 2` `- ℹ️ ...` ### 🔧 Installation 1. Clone the SieveOfEratosthenes repository: ```sh git clone https://github.com/FilipJaskovic/SieveOfEratosthenes ``` 2. Change to the project directory: ```sh cd SieveOfEratosthenes ``` 3. Install the dependencies: ```sh pip install -r requirements.txt ``` ### 🤖 Running SieveOfEratosthenes ```sh python main.py ``` ### 🧪 Tests ```sh pytest ``` --- ## 🛣 Project Roadmap > - [X] `ℹ️ Task 1: Implement X` > - [ ] `ℹ️ Task 2: Implement Y` > - [ ] `ℹ️ ...` --- ## 🤝 Contributing Contributions are welcome! Here are several ways you can contribute: - **[Submit Pull Requests](https://github.com/FilipJaskovic/SieveOfEratosthenes/blob/main/CONTRIBUTING.md)**: Review open PRs, and submit your own PRs. - **[Join the Discussions](https://github.com/FilipJaskovic/SieveOfEratosthenes/discussions)**: Share your insights, provide feedback, or ask questions. - **[Report Issues](https://github.com/FilipJaskovic/SieveOfEratosthenes/issues)**: Submit bugs found or log feature requests for FILIPJASKOVIC. #### *Contributing Guidelines*

Click to expand

1. **Fork the Repository**: Start by forking the project repository to your GitHub account. 2. **Clone Locally**: Clone the forked repository to your local machine using a Git client. ```sh git clone ``` 3. **Create a New Branch**: Always work on a new branch, giving it a descriptive name. ```sh git checkout -b new-feature-x ``` 4. **Make Your Changes**: Develop and test your changes locally. 5. **Commit Your Changes**: Commit with a clear and concise message describing your updates. ```sh git commit -m 'Implemented new feature x.' ``` 6. **Push to GitHub**: Push the changes to your forked repository. ```sh git push origin new-feature-x ``` 7. **Submit a Pull Request**: Create a PR against the original project repository. Clearly describe the changes and their motivations. Once your PR is reviewed and approved, it will be merged into the main branch.

--- ## 📄 License This project is protected under the [SELECT-A-LICENSE](https://choosealicense.com/licenses) License. For more details, refer to the [LICENSE](https://choosealicense.com/licenses/) file. --- ## 👏 Acknowledgments - List any resources, contributors, inspiration, etc. here. [**Return**](#Top) ---

CCC-Oct2023

CCC-OCT2023

◦ Code, Collaborate, Conquer!

◦ Developed with the software and tools below.

--- ## 📖 Table of Contents - [📖 Table of Contents](#-table-of-contents) - [📍 Overview](#-overview) - [📦 Features](#-features) - [📂 repository Structure](#-repository-structure) - [⚙️ Modules](#modules) - [🚀 Getting Started](#-getting-started) - [🔧 Installation](#-installation) - [🤖 Running CCC-Oct2023](#-running-CCC-Oct2023) - [🧪 Tests](#-tests) - [🛣 Roadmap](#-roadmap) - [🤝 Contributing](#-contributing) - [📄 License](#-license) - [👏 Acknowledgments](#-acknowledgments) --- ## 📍 Overview The CCC-Oct2023 repository is a collection of input files for the CCC (Canadian Computing Competition) challenge held in October 2023. It provides a range of input files for different levels of difficulty, allowing users to practice their problem-solving skills and prepare for the competition. The repository's value proposition lies in its ability to offer a realistic and comprehensive set of inputs that closely resemble the ones contestants will encounter in the actual competition. --- ## 📦 Features | | Feature | Description | |---|-------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | ⚙️ | Architecture | The repository follows a directory-based structure where inputs, outputs, and level descriptions are stored separately. It uses a procedural programming approach and does not exhibit any defined architectural patterns. | | 📄 | Documentation | The repository lacks comprehensive documentation. While there are some example input and output files provided, there is no detailed explanation of the codebase or its components. Proper documentation would greatly enhance the understanding and usability of the project. | | 🔗 | Dependencies | The repository does not have any external library dependencies. It appears to be a self-contained system. | | 🧩 | Modularity | The codebase demonstrates some degree of modularity by organizing inputs, outputs, and level descriptions into separate directories. However, a more structured approach, such as utilizing modules or adopting a design pattern, would further enhance the codebase's reusability and maintainability. | | 🧪 | Testing | The repository does not include any explicit testing strategies or tools. Lack of test cases and test scripts makes it difficult to validate the correctness and functionality of the codebase. | | ⚡️ | Performance | The performance characteristics of the system cannot be determined without analyzing the codebase in more detail. Given the absence of information or benchmarks, it is difficult to assess the system's speed, efficiency, and resource usage. | | 🔐 | Security | There is no specific information available regarding security measures implemented in the codebase. It is essential to evaluate if data protection and privacy safeguards are in place to maintain the security and integrity of the system. | | 🔀 | Version Control | The repository utilizes Git for version control. However, the analysis cannot provide any insights into the specific version control strategies or tools used. | | 🔌 | Integrations | The repository does not appear to have any specific integrations with other systems or services. | | 📶 | Scalability | Without deeper analysis, it is challenging to determine the system's scalability. | Please note that the analysis is based on a high-level overview of the repository and may not capture all the nuances and details of the codebase. A more in-depth review and examination would be required for a comprehensive understanding. --- ## 📂 Repository Structure ```sh └── CCC-Oct2023/ ├── Inputs/ │ ├── level1_1.in │ ├── level1_2.in │ ├── level1_3.in │ ├── level1_4.in │ ├── level1_5.in │ ├── level1_example.in │ ├── level2_1.in │ ├── level2_2.in │ ├── level2_3.in │ ├── level2_4.in │ ├── level2_5.in │ ├── level2_example.in │ ├── level3_1.in │ ├── level3_2.in │ ├── level3_3.in │ ├── level3_4.in │ ├── level3_5.in │ └── level3_example.in ├── LevelDescriptions/ ├── Outputs/ │ ├── level1_1-output.txt │ ├── level1_2-output.txt │ ├── level1_3-output.txt │ ├── level1_4-output.txt │ ├── level1_5-output.txt │ ├── level1_example.out │ ├── level2_1-output.txt │ ├── level2_2-output.txt │ ├── level2_3-output.txt │ ├── level2_4-output.txt │ ├── level2_5-output.txt │ ├── level2_example.out │ ├── level3_1-output.txt │ ├── level3_2-output.txt │ ├── level3_3-output.txt │ ├── level3_4-output.txt │ ├── level3_5-output.txt │ └── level3_example.out ├── level1.py ├── level2.py ├── level3.py └── visualizer.html ``` --- ## ⚙️ Modules

Root

| File | Summary | | --- | --- | | [level1.py](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/level1.py) | This code takes in input files in the format of level1_x.in and counts the occurrences of puzzle pieces in each file. It uses the Counter class from the collections module to efficiently count the pieces. The results are then written to output files in the format of level1_x-output.txt. The main function loops through the range of 1 to 6 and calls the count_puzzle_pieces function for each input file. | | [visualizer.html](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/visualizer.html) | The code is an HTML document that contains JavaScript functionality for a Puzzle Visualizer. The document consists of an input region and an output region. In the input region, there is a text area where the user can input a puzzle. The JavaScript code takes the input from the text area, processes it, and generates a graphical representation of the puzzle in the output region using SVG (Scalable Vector Graphics). The puzzle pieces are represented as shapes (rectangles and arcs) in the SVG canvas. The JavaScript code dynamically updates the SVG canvas based on the user's input. | | [level2.py](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/level2.py) | The code counts and normalizes puzzle pieces in input files and creates corresponding output files. It imports the Counter class from the collections module. The normalize_piece function rotates and sorts the puzzle pieces based on comma-separated characters. The count_puzzle_pieces function reads the input file, counts the normalized pieces using Counter, and writes the counts in the output file. The main function iterates over 5 input files and calls count_puzzle_pieces. | | [level3.py](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/level3.py) | The code defines a function `read_puzzle` that reads a puzzle file, extracts the size and puzzle data, and returns them. Another function `identify_and_correct_mistakes` identifies and corrects mistakes in the puzzle data based on certain conditions. The `main` function iterates through a set of input puzzle files, reads each file, applies the mistake correction function, and writes the corrected puzzle data to corresponding output files. The code allows for processing multiple puzzle files easily. |

Outputs

| File | Summary | | --- | --- | | [level3_4-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_4-output.txt) | The code represents a directory tree structure with various directories and files. The "Inputs" directory contains input files for different levels. The "Outputs" directory contains corresponding output files for each input file. In addition, there are "LevelDescriptions" and "level1" directories which are not described by the contents of this code snippet. | | [level2_1-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_1-output.txt) | The code above represents a directory tree structure with the main folder labeled "CCC-Oct2023". Within this folder, there are subfolders for "Inputs", "LevelDescriptions", and "Outputs". The "Inputs" folder contains multiple levels of input files, each labeled with a specific level number. The "Outputs" folder contains corresponding output files with the same level numbering format. The code snippet shows the content of the file "level2_1-output.txt" within the "Outputs" folder, displaying a set of numbers separated by commas. | | [level3_example.out](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_example.out) | The code represents the outputs of a program that processes input data. It shows the contents of a directory called "CCC-Oct2023", which contains various subdirectories and files. The "Inputs" directory contains input files for different levels, while the "Outputs" directory contains corresponding output files. The code snippet shows the contents of the "level3_example.out" file, which contains a grid of letters representing different states. | | [level2_4-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_4-output.txt) | The code represents the content of the file "level2_4-output.txt" located in the "Outputs" directory. The file contains a table with six rows of values, each row consisting of four elements. The elements are denoted by the letters H or K. The code displays the values in a tabular format. | | [level1_2-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_2-output.txt) | The code represents the output of a program for a specific problem instance. It shows a 2D matrix with cells containing either an'H' or a'K'. These cells represent a game state, and the code provides the arrangement of'H' and'K' cells. The numbers at the beginning of each line represent the available moves in the game. The code could be part of a program that analyzes or processes game states and their corresponding moves. | | [level3_1-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_1-output.txt) | The code represents a directory tree structure with a specific file hierarchy, including various input and output files. The given path points to a specific output file called "level3_1-output.txt". The contents of the output file seem to be a series of letters and commas, indicating some form of data. | | [level1_5-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_5-output.txt) | The code shown above is a sample output file located at "Outputs/level1_5-output.txt" within the directory structure. It consists of a tabular representation of data, where each row contains four values separated by commas. The values in each row are a combination of "H" and "K". | | [level2_3-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_3-output.txt) | The code represents a directory tree structure containing input and output files for different levels. Each level has its own folder, such as level1, level2, and level3. The code specifically looks at the output file "level2_3-output.txt", which contains a list of values. | | [level3_3-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_3-output.txt) | The given directory tree represents a directory structure for a coding project. It contains multiple levels of inputs and outputs files organized in subdirectories. The "Inputs" directory holds input files for different levels, while the "Outputs" directory holds the corresponding output files. Each level has its own input and output files, with a naming convention that includes the level number and a specific identifier. The directory also includes Python files for each level, indicating that the project likely involves coding challenges or exercises at different levels of difficulty. | | [level2_5-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_5-output.txt) | The given code contains a directory tree with different levels and files within each level. The "Outputs/level2_5-output.txt" file contains data in tabular format, with each row representing a set of values. The code appears to be showing the values and labels in each row, with "H" representing a specific label and "K" representing another label. The six rows in the file are displaying different combinations of labels for each set of values. | | [level1_3-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_3-output.txt) | This code is displaying the contents of the file "level1_3-output.txt" located in the "Outputs" directory. The file contains a series of numbers separated by commas. Each line represents a set of numbers. | | [level2_example.out](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_example.out) | The code is showing the contents of the file "level2_example.out" located in the "Outputs" directory. The file contains a series of lines, each representing a combination of 4 letters (H or K) separated by commas. Each line represents a different combination. | | [level3_5-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_5-output.txt) | The code represents a directory tree structure with different levels and files. The "Inputs" directory contains input files for each level, while the "Outputs" directory contains corresponding output files. The "LevelDescriptions" directory is empty. The code is likely designed to process or manipulate these files in some way, potentially for testing or analysis purposes. | | [level1_example.out](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_example.out) | The code represents the output of a program. It shows a grid with various letters (H and K) arranged in a specific pattern. Each line of the code corresponds to a row in the grid and indicates the number of times each letter appears in that row. The code provides a visualization of the grid's contents and their frequencies. | | [level3_2-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level3_2-output.txt) | This code represents a directory tree structure containing input and output files for different levels of a project. The Inputs folder contains input files for each level, while the Outputs folder contains corresponding output files. There are also separate Python files for each level of the project. Additionally, there is a visualizer.html file, potentially for visualizing the project's data. | | [level1_1-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_1-output.txt) | The code provided represents a directory tree structure with various directories and files. The specific code snippet is the content of the file "Outputs/level1_1-output.txt". It contains a series of numbers and letters arranged in a tabular format. | | [level1_4-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level1_4-output.txt) | The given code represents the content of the file "level1_4-output.txt" located in the "Outputs" directory. The code consists of a series of numbers and letters arranged in a grid-like format. The exact meaning or purpose of these values is unknown without further context or information. | | [level2_2-output.txt](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Outputs/level2_2-output.txt) | The code represents a directory tree structure with folders for inputs, outputs, and level descriptions. The specific code block shows the content of the "level2_2-output.txt" file in the outputs folder, which contains a table-like structure with rows and columns of values. The values in the table represent a combination of "H" and "K" characters. |

Inputs

| File | Summary | | --- | --- | | [level2_example.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_example.in) | The code above represents a directory structure containing input and output files, as well as code files for different levels of a program. The specific code shown is for input "level2_example.in", which consists of a 7x7 grid with different letters representing different elements. | | [level2_1.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_1.in) | This code represents a directory tree structure with various files and folders. The "Inputs" folder contains input files for different levels, while the "Outputs" folder contains corresponding output files. The code is specifically showing the content of the "level2_1.in" input file, which consists of a 10x10 grid with various "K" and "H" characters. | | [level2_5.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_5.in) | The code represents a directory tree structure with folders for inputs, level descriptions, and outputs. The input folder contains multiple levels of files with different names and extensions. The output folder contains corresponding output files for each input file, with a similar naming convention. This structure likely organizes data and results for a coding challenge or problem-solving exercise. | | [level1_2.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_2.in) | The code describes a directory tree structure containing various levels and their corresponding inputs, outputs, and files. The specific path given is "Inputs/level1_2.in" which corresponds to a text file containing a series of "H" and "K" characters. The code itself is not provided, only the contents of the file. | | [level3_4.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_4.in) | The code represents a directory tree structure with folders named "Inputs", "LevelDescriptions", "Outputs", and "level1". The "Inputs" folder contains multiple files named "level1_1.in", "level1_2.in", etc., which are input files for a specific level of a task. The "Outputs" folder contains corresponding output files for each input file. The "level1" folder may contain additional files or subfolders specific to that level. The purpose of this structure is to organize and manage input and output files for a task with multiple levels. | | [level2_4.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_4.in) | The code allows for the organization and management of files in a directory tree structure. It includes folders for inputs, level descriptions, and outputs. The inputs folder contains various levels and examples, while the outputs folder stores corresponding output files. This structure facilitates the storage, retrieval, and manipulation of files for a specific purpose or project. | | [level1_3.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_3.in) | The code represents a directory tree structure. It contains folders such as "Inputs", "LevelDescriptions", and "Outputs". The "Inputs" folder includes various input files organized in different levels. The "Outputs" folder contains corresponding output files for each input file. It seems to be a system for managing and organizing input and output files for a program or project. | | [level3_5.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_5.in) | The code represents a directory tree structure with different levels. It contains inputs and outputs for various levels, as well as a directory for level descriptions. The "level1" directory is specified but its contents are not shown in the provided code. | | [level3_1.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_1.in) | The code is part of a directory tree that contains different levels and inputs/outputs for each level. It includes Python scripts for each level, input files for each level, and output files for each level. The specific code shown is a dataset represented by a string of characters, with each character indicating a certain value. | | [level3_example.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_example.in) | The code represents a directory tree structure with different levels (level1, level2, level3) and corresponding input and output files. It includes a visualizer file for visualization purposes. The specific code provided is a text file containing a matrix. | | [level1_4.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_4.in) | The code represents a directory tree structure with the "CCC-Oct2023" folder as the root. It contains subfolders for "Inputs," "LevelDescriptions," and "Outputs." The "Inputs" folder contains various levels of input files, labeled from level 1 to level 3, each with 5 numbered files and an example file. The "Outputs" folder follows a similar structure, with corresponding output files for each input file. The code likely performs operations on these input files and generates output files as a result. | | [level2_3.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_3.in) | The code represents a directory tree structure with folders for Inputs, LevelDescriptions, and Outputs. The Inputs folder contains various input files for different levels, including example input files. The Outputs folder contains corresponding output files for each input file. The purpose of this directory structure is likely to organize and store input/output files for a programming or computational task. | | [level3_2.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_2.in) | This code organizes folders and files into a directory tree structure. It contains input files in the "Inputs" folder, level descriptions in the "LevelDescriptions" folder, and output files in the "Outputs" folder. There are Python files for each level of processing (level1.py, level2.py, level3.py), and a visualizer.html file. The code likely performs operations on the input files, generates output files, and provides a visualization of the data. | | [level1_5.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_5.in) | The code organizes a directory tree with three main folders: Inputs, LevelDescriptions, and Outputs. The Inputs folder contains various level-specific input files, and the Outputs folder contains corresponding output files. The code facilitates the storage and retrieval of input and output files for different levels of a program or system. | | [level2_2.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level2_2.in) | The code represents a directory tree structure, with folders for Inputs, LevelDescriptions, and Outputs. The Inputs folder contains multiple level-specific input files, while the Outputs folder contains corresponding output files. Each level has its own Python script for processing the input and generating the output. In this case, the code is specifically for the level2_2.in input file, which is a matrix of'H' and'K' values. The purpose of the code is not specified. | | [level3_3.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level3_3.in) | The code consists of a directory tree that contains input and output files for different levels of a program. The "Inputs" directory contains input files for each level, while the "Outputs" directory contains output files corresponding to each input file. The "LevelDescriptions" directory likely contains descriptions or instructions for each level. Additionally, there are Python files named "level1.py" and "level2.py" which might contain the code implementation for each level. | | [level1_example.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_example.in) | The code reads a 7x7 input grid from the file "Inputs/level1_example.in". The grid contains letters representing different elements. | | [level1_1.in](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/Inputs/level1_1.in) | The code represents a directory structure with multiple levels and specific files. It includes input files containing data, level description files, output files with results, and Python scripts for each level. It also contains a visualizer HTML file. The specific file path provided refers to an input file for level 1, which contains a grid matrix with different characters representing different items. |

--- ## 🚀 Getting Started ***Dependencies*** Please ensure you have the following dependencies installed on your system: `- ℹ️ Dependency 1` `- ℹ️ Dependency 2` `- ℹ️ ...` ### 🔧 Installation 1. Clone the CCC-Oct2023 repository: ```sh git clone https://github.com/FilipJaskovic/CCC-Oct2023 ``` 2. Change to the project directory: ```sh cd CCC-Oct2023 ``` 3. Install the dependencies: ```sh ► INSERT-TEXT ``` ### 🤖 Running CCC-Oct2023 ```sh ► INSERT-TEXT ``` ### 🧪 Tests ```sh ► INSERT-TEXT ``` --- ## 🛣 Project Roadmap > - [X] `ℹ️ Task 1: Implement X` > - [ ] `ℹ️ Task 2: Implement Y` > - [ ] `ℹ️ ...` --- ## 🤝 Contributing Contributions are welcome! Here are several ways you can contribute: - **[Submit Pull Requests](https://github.com/FilipJaskovic/CCC-Oct2023/blob/main/CONTRIBUTING.md)**: Review open PRs, and submit your own PRs. - **[Join the Discussions](https://github.com/FilipJaskovic/CCC-Oct2023/discussions)**: Share your insights, provide feedback, or ask questions. - **[Report Issues](https://github.com/FilipJaskovic/CCC-Oct2023/issues)**: Submit bugs found or log feature requests for FILIPJASKOVIC. #### *Contributing Guidelines*

Click to expand

1. **Fork the Repository**: Start by forking the project repository to your GitHub account. 2. **Clone Locally**: Clone the forked repository to your local machine using a Git client. ```sh git clone ``` 3. **Create a New Branch**: Always work on a new branch, giving it a descriptive name. ```sh git checkout -b new-feature-x ``` 4. **Make Your Changes**: Develop and test your changes locally. 5. **Commit Your Changes**: Commit with a clear and concise message describing your updates. ```sh git commit -m 'Implemented new feature x.' ``` 6. **Push to GitHub**: Push the changes to your forked repository. ```sh git push origin new-feature-x ``` 7. **Submit a Pull Request**: Create a PR against the original project repository. Clearly describe the changes and their motivations. Once your PR is reviewed and approved, it will be merged into the main branch.

--- ## 📄 License This project is protected under the [SELECT-A-LICENSE](https://choosealicense.com/licenses) License. For more details, refer to the [LICENSE](https://choosealicense.com/licenses/) file. --- ## 👏 Acknowledgments - List any resources, contributors, inspiration, etc. here. [**Return**](#Top) ---

[FilipJaskovic]

Thank you for sharing the information. I appreciate your efforts in fixing the issue. After testing the current version of the readme-ai by using the command you provided, I can confirm that it is working properly.

[eli64s]

Awesome! Thanks for exploring the project. Let me know if you have any other issues or questions.

Eli

[DaMandal0rian]

@eli64s this is still happening with version 0.4.53.

[arielya10]

Same for version readmeai 0.4.79