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CoderGPT

Project description

CoderGPT

Description

CoderGPT is a command line interface for generating/modifying code. It allows developers to enhance code by commenting, optimizing, documenting, and adding tests to their project using the power of LLM and GPT. This project is powered by langchain.


NOTE Before using CoderGPT, ensure that the environment variable OPENAI_API_KEY is set locally on your machine. This key is required for authentication with the OpenAI API which powers the underlying language model.

export OPENAI_API_KEY='your-api-key-here'

Replace your-api-key-here with your actual OpenAI API key. This step is crucial for the proper functioning of CoderGPT as it relies on the OpenAI API for generating and modifying code.


Installation

To use the CoderGPT CLI, clone the repository and install the required dependencies.

pip install codergpt

Usage

Run the CLI using the following syntax:

code [OPTIONS] COMMAND [ARGS]...

Options

  • -v, --verbose INTEGER: Set verbosity level (0, 1, or 2).
  • -q, --quiet: Enable quiet mode.
  • --version: Display version information.

Commands

  1. inspect: Inspect a package and display a file-language map.

    code inspect <path>
    

    Example

    $ code inspect code inspect src/codergpt/
    Inspecting the code.
    File                                        Language
    ------------------------------------------  ----------
    src/codergpt/constants.py                   Python
    src/codergpt/__init__.py                    Python
    src/codergpt/cli.py                         Python
    src/codergpt/extensions.yaml                YAML
    src/codergpt/main.py                        Python
    src/codergpt/optimizer/__init__.py          Python
    src/codergpt/utils/expression_evaluator.py  Python
    src/codergpt/utils/__init__.py              Python
    src/codergpt/commenter/commenter.py         Python
    src/codergpt/commenter/__init__.py          Python
    src/codergpt/explainer/explainer.py         Python
    src/codergpt/explainer/__init__.py          Python
    src/codergpt/test_writer/__init__.py        Python
    
  2. explain: Explain a specific function or class within a package.

    code explain <path> [--function <function_name>] [--classname <class_name>]
    

    Example

    $ code explain src/codergpt/explainer/explainer.py --function explain
    Explanation for the code:
    This code defines a method called `explain` that takes in three parameters: `code`, `function`, and `classname`. The `code` parameter is a string that represents the code file to be explained. The `function` parameter is an optional string that represents the name of a specific function within the code file that needs to be explained. The `classname` parameter is also an optional string that represents the name of a specific class within the code file that needs to be explained.
    
    The method first checks if the `function` parameter is provided. If it is, the method invokes a `chain` by passing a dictionary with an "input" key and a formatted string containing the code. The response from the `chain.invoke` call is then printed in a pretty format, including the name of the function being explained.
    
    If the `function` parameter is not provided but the `classname` parameter is, the same process is followed, but with the class name instead.
    
    If both `function` and `classname` parameters are not provided, the method assumes that the full code needs to be explained. It again invokes the `chain` with the code as input and prints the response in a pretty format, indicating that it is explaining the entire code.
    
  3. comment: Add comments to the code in a package. The user has the choice to overwrite the file or create a new one.

    code comment <path> [--overwrite/--no-overwrite]
    

    Example

    • Let's consider a python file greetings.py:
        def greet(name):
            return f"Hello, {name}!"
    
        if __name__ == "__main__":
            user_name = "Alice"
            print(greet(user_name))
    
    $ code comment greetings.py --overwrite
    

    results in ....

        def greet(name):
            """
            Generates a greeting message for the given name.
    
            :param name: (str) The name of the person to greet.
            :return: (str) The greeting message.
            """
            return f"Hello, {name}!"
    
    
        if __name__ == "__main__":
            user_name = "Alice"
            print(greet(user_name))
    
  4. optimize: Optimizes and adds commets to the code in a package. The user has the choice to overwrite the file or create a new one.

    code optimize <path> [--overwrite/--no-overwrite]
    

    Example

    • Let's consider a python file example.py:
    # example.py
    
    def calculate_sum(numbers):
        result = 0
        for number in numbers:
            result += number
        return result
    
    class MathOperations:
        def multiply(self, a, b):
            answer = 0
            for i in range(b):
                answer += a
            return answer
    
    $ code optimize example.py --overwrite
    

    results in ....

    """
    Optimized and Documented Code:
    
    """
    
    from typing import List
    
    
    def calculate_sum(numbers: List[int]) -> int:
        """
        Calculates the sum of a list of numbers.
    
        Parameters:
        numbers (List[int]): A list of integers.
    
        Returns:
        int: The sum of the numbers.
    
        """
        result = sum(numbers)
        return result
    
    
    class MathOperations:
        def multiply(self, a: int, b: int) -> int:
            """
            Multiplies two numbers.
    
            Parameters:
            a (int): The first number.
            b (int): The second number.
    
            Returns:
            int: The result of multiplying a and b.
    
            """
            answer = a * b
            return answer
    
    
    """
    Optimization:
    
    1. In the 'calculate_sum' function, we can use the built-in 'sum' function to calculate the sum of the numbers in the list. This is more efficient than manually iterating over the list and adding each number to the result.
    
    2. In the 'multiply' method of the 'MathOperations' class, we can directly multiply the two numbers using the '*' operator. This eliminates the need for a loop and improves performance.
    
    By using these optimizations, we improve the efficiency and readability of the code.
    """
    
  5. write-tests: Writes tests for the specified code file. The user can specify a function and/or a class within the file to target with the tests.

    code write-tests <path> [--function <function_name>] [--class <classname>]
    

    Example

    • Let's consider a python file example.py:
    # example.py
    
    def add(a, b):
        return a + b
    
    class Calculator:
        def subtract(self, a, b):
            return a - b
    
    $ code write-tests example.py --function add --class Calculator
    

    results in test files being generated that contain test cases for the add function and the Calculator class. The actual content of the test files will depend on the implementation of the coder.test_writer method but would typically look something like this:

    import unittest
    from example import add, Calculator
    
    class TestAddFunction(unittest.TestCase):
    
        def test_addition(self):
            self.assertEqual(add(3, 4), 7)
    
    class TestCalculator(unittest.TestCase):
    
        def setUp(self):
            self.calc = Calculator()
    
        def test_subtract(self):
            self.assertEqual(self.calc.subtract(10, 5), 5)
    

    In this example, running the command generates unit tests for both the add function and the Calculator class in the example.py file. The tests check if the add function correctly adds two numbers and if the Calculator's subtract method correctly subtracts one number from another.

  6. document: Generates documentation for the specified code file.

    code document <path>
    

    Example

    • Let's consider a python file example.py:
    # example.py
    
    def add(a, b):
        """Add two numbers and return the result."""
        return a + b
    
    class Calculator:
        """A simple calculator class."""
    
        def subtract(self, a, b):
            """Subtract b from a and return the result."""
            return a - b
    
    $ code document example.py
    

    results in documentation files being generated that contain documentation for all functions and classes within the example.py file. The actual content of the documentation files will depend on the implementation of the DocumentationGenerator.document method but would typically look something like this:

    add Function
    ------------
    
    .. autofunction:: example.add
    
    Calculator Class
    ----------------
    
    .. autoclass:: example.Calculator
    :members:
    

    In this example, running the command generates documentation for the entire example.py file, including both the add function and the Calculator class. The documentation includes descriptions of the function and class, as well as any public methods of the class.

Development

The CLI is built using Python and the click library. Below is an example of how to define a new command:

import click
from codergpt import CoderGPT

coder = CoderGPT()

@click.command()
@click.argument('path', type=click.Path(exists=True))
def new_command(path):
    # Command logic here
    pass

Contributing

Contributions are welcome! Please read our contributing guidelines before submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgements

This cookiecutter project was developed from the monarch-project-template template and will be kept up-to-date using cruft.

For more information on CoderGPT CLI, please visit the official documentation.

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