GitHub - michaeljohneduave/auto-applai · GitHub
Skip to content

About

No description, website, or topics provided.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Latest commit

 

History

142 Commits

Folders and files

Repository files navigation

Auto Apply Project Overview

The "Auto Apply" project automates the entire job application process, from gathering job details to submitting the application.

Diagram Link

Core Purpose

To automatically apply for jobs by:

  1. Scraping job post information.
  2. Generating a custom, optimized resume.
  3. Filling out and submitting application forms.

How It Works (Workflow)

The process involves five main steps:

  1. Information Extraction: Scrapes the job post URL to extract job details and application form fields.
  2. Resume Generation: Creates a customized resume PDF in LaTeX format, tailored for the specific job.
  3. Response Generation: Generates answers for the application form, potentially asking clarifying questions.
  4. Response Refinement: Evaluates and refines the generated responses based on feedback.
  5. Application Submission: Fills out the application form and submits it.

Key Technologies

  • LaTeX for Resumes: Utilized for precise formatting and declarative structure, aiding in AI-friendly resume generation.
  • Pandoc API: Converts generated LaTeX files into PDF resumes.
  • Puppeteer MCP + API: Manages browser automation for scraping and form submission, ensuring separation of concerns and isolated browser environments.

Inputs

  • Resume.md (Markdown resume)
  • Resume.tex (LaTeX resume)
  • Job post url (Link to the job posting)

Output

  • Application submitted

To Do List

  • Resume generation feedback, critique and gut check from "hiring manager" LLM.
  • Robust form parsing and correct fill up.
  • LLM response evaluations.

Deploy

See infrastructure deployment guide:

infra/DEPLOYMENT.md

About

No description, website, or topics provided.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages