Automating My Job Application Process: A Frustrated Developer’s Journey

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import os
import sys
import logging
import pyperclip  # Importing pyperclip to handle clipboard operations
from groq import Groq  # Importing Groq for AI-powered text generation

# Set up logging to track the flow and any potential errors
logging.basicConfig(level=logging.INFO)

# Initialize the Groq client with the API key stored in environment variables
client = Groq(
    api_key=os.environ.get("GROQ_API_KEY"),
)

def ask_question(task):
    """
    Send a question to the Groq AI and get a response.

    Args:
        task (str): The question or task description to send to the AI.

    Returns:
        response: The AI's response to the question.
    """
    chat_completion = client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": task,
            }
        ],
        model="llama3-8b-8192",  # Specify the AI model to use
    )
    return chat_completion  # Return the AI's response

def read_file(file_path):
    """
    Read and return the content of a text file.

    Args:
        file_path (str): The path to the text file to read.

    Returns:
        str: The content of the file, or None if an error occurs.
    """
    try:
        with open(file_path, "r") as file:  # Open the file in read mode
            return file.read()  # Return the content of the file
    except Exception as e:
        logging.error(f"An error occurred while reading {file_path}: {e}")  # Log any errors
        return None  # Return None if there's an error

def create_cv_content(cv_text, job_posting, language):
    """
    Create tailored cv content for a job application based on CV and job posting.

    Args:
        cv_text (str): The content of the CV.
        job_posting (str): The job posting text.
        language (str): The language for the response ('es' for Spanish, 'en' for English).

    Returns:
        str: The generated cv content.
    """
    # Set the prompt based on the selected language
    language_prompt = "in Spanish" if language == "es" else "in English"
    task = (f"Write a tailored cv content for a job application {language_prompt}. "
            f"Here is my CV:\n\n{cv_text}\n\nAnd here is the job posting:\n\n{job_posting}")

    response = ask_question(task).choices[0].message.content  # Get the AI's response
    return response  # Return the generated cv content

def main():
    """
    Main function to execute the script.
    It handles user input, reads files, and generates tailored cv content.
    """
    if len(sys.argv) < 2:
        logging.error("Usage: python script.py <cv_path>")
        sys.exit(1)  # Exit if no CV path is provided

    cv_path = sys.argv[1]  # Get the CV file path from command-line arguments

    # Clear the clipboard before prompting the user
    pyperclip.copy("")
    input("Please copy the job position text to the clipboard, then press Enter to continue...")

    # Read the job position text from the clipboard
    job_posting_text = pyperclip.paste()

    cv_text = read_file(cv_path)  # Read the CV content from the specified file
    if cv_text is None:
        sys.exit(1)  # Exit if there's an error reading the CV

    # Ask for the user's language preference
    language = input("Select language for the response (es for Spanish, en for English): ").strip().lower()
    while language not in ['es', 'en']:
        language = input("Invalid choice. Please select 'es' for Spanish or 'en' for English: ").strip().lower()

    # Generate the tailored cv content using the CV and job posting
    cv_content = create_cv_content(cv_text, job_posting_text, language)

    # Copy the tailored cv content to the clipboard for easy pasting
    pyperclip.copy(cv_content)

    # Inform the user that the job is done and display the cv content
    print("----- Tailored Job Application CV -----")
    print(cv_content)
    print("\nThe tailored cv content has been copied to your clipboard. Job done!")

if __name__ == "__main__":
    main()  # Run the main function when the script is executed