wiredmatt / cv_converter

CV Format Standardizer

Overview

CV Format Standardizer is an application designed for organizations receiving CVs in various formats, aiming to standardize them into a specified, branded format. This tool streamlines the process of formatting resumes, ensuring consistency and professionalism in the presentation of applicant information.

Features

• Multiple File Format Support: Handles .txt, .pdf, and .docx files, extracting text for processing.
• Automated CV Transcription and Editing: Utilizes AI agents for transcribing and refining CV content.
• Custom Branding: Integrates company logo and standardized formatting in the final output.
• PDF Generation: Converts standardized CV content into a professional PDF format.
• Interactive Web Interface: Built with Streamlit, providing an easy-to-use platform for file uploads and downloads.

Installation

Prerequisites

Before running this project, you need to have wkhtmltopdf installed on your system as it's required by the pdfkit library to convert HTML to PDF.

Installation Instructions

• Linux (Debian/Ubuntu):

  sudo apt-get install wkhtmltopdf

To set up CV Format Standardizer, follow these steps:

1. Clone the Repository:

   git clone [repository-link]

2. Install Dependencies:

   pip install -r requirements.txt

   This will install necessary libraries such as docx, PyPDF2, streamlit, and others.

3. Set Environment Variables: Create a .env file in the root directory and add the following keys:

   OPENAI_API_KEY=[Your OpenAI API Key]
   LOGO_URL=[URL of your company logo]
   

   Replace the placeholders with your actual API key and logo URL.

Usage

To run the application:

1. Start the Streamlit server:

   streamlit run app.py

2. Navigate to the displayed URL in your web browser.
3. Upload a CV in one of the supported formats.
4. Click 'Process' to standardize the format and view the result.
5. Optionally, edit the markdown content and download the standardized CV as a PDF.

How it Works

• File Upload: Users upload a CV, which the system reads and processes.
• Text Extraction: The ReaderTool class extracts text from the uploaded file.
• AI-Driven Processing: AI agents (cv_transcriber and cv_editor) analyze and edit the CV content, ensuring relevance and conciseness.
• Markdown to PDF Conversion: The application converts the final markdown content into a stylized PDF, incorporating the company logo and date. Note: The file can be manually edited onscreen and downloaded if a human deems necessary to make any correction or addition.

Make it fly!

Deploy to fly.io!

Build the docker image (optional)

docker build -t cv-converter .

Set the app secrets

fly secrets set OPENAI_API_KEY='sk-your-key-here' LOGO_URL='https://company.com/logo.svg'

Deploy the app

fly deploy

Contributing

Contributions to CV Format Standardizer are welcome. Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a clear description of your changes.

License

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

Contact

For support or queries, please contact [contact-email].

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Note: This README is a guide for setting up and using the CV Format Standardizer. Modify it as necessary to match the specifics of your repository and project structure.