ResumeFlow

ResumeFlow

Simplify and improve the job hunting experience by integrating LLMs to automate tasks such as resume and cover letter generation, as well as application submission, saving users time and effort.

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ResumeFlow is an automated system that leverages Large Language Models (LLMs) to streamline the job application process. By integrating LLM technology, the tool aims to automate various stages of job hunting, making it easier for users to apply for jobs. Users can access ResumeFlow as a web tool, install it as a Python package, or download the source code from GitHub. The tool requires Python 3.11.6 or above and an LLM API key from OpenAI or Gemini Pro for usage. ResumeFlow offers functionalities such as generating curated resumes and cover letters based on job URLs and user's master resume data.

README:

ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement

Demo Page ACM Digital Library arxiv paper PyPI Latest Release PyPI Downloads GitHub issues open License: MIT

Click here to see image of "Auto Job Aligned Personalized Resume Generation Pipeline"
For Video Demonstration visit the YouTube link: https://youtu.be/Agl7ugyu1N4

Project can be:

All other known bugs, fixes, feedbacks, and feature requests can be reported on the GitHub issues page.

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Author & Contributor List

1. Introduction:

1.1. Our Proposal

We're aiming to create a automated system that makes applying for jobs a breeze. Job hunting has many stages, and we see a chance to automate things and use LLM (Language Model) to make it even smoother. We're looking at different ways, both the usual and some new ideas, to integrate LLM into the job application process. The goal is to reduce how much you have to do and let LLM do its thing, making the whole process easier for you.

1.2. References

1.3. Refer to this Paper for more details.

2. Setup, Installation and Usage

2.1. Prerequisites

2.2. Package Installation - Use as Library

pip install zlm
  • Usage
from zlm import AutoApplyModel

job_llm = AutoApplyModel(
    api_key="PROVIDE_API_KEY", 
    provider="ENTER PROVIDER <gemini> or <openai>",
    downloads_dir="[optional] ENTER FOLDER PATH WHERE FILE GET DOWNLOADED, By default, 'downloads' folder"
)

job_llm.resume_cv_pipeline(
    "ENTER_JOB_URL", 
    "YOUR_MASTER_RESUME_DATA" # .pdf or .json
) # Return and downloads curated resume and cover letter.

2.4. Setup & Run Code - Use as Project

git clone https://github.com/Ztrimus/job-llm.git
cd job-llm
  1. Create and activate python environment (use python -m venv .env or conda or etc.) to avoid any package dependency conflict.
  2. Install Poetry package (dependency management and packaging tool)
    pip install poetry
  3. Install all required packages.
    • Refer pyproject.toml or poetry.lock for list of packages.
      poetry install
      OR
    • If above command not working, we also provided requirements.txt file. But, we recommend using poetry.
      pip install -r resources/requirements.txt
  4. We also need to install following packages to conversion of latex to pdf
    • For linux
      sudo apt-get install texlive-latex-base texlive-fonts-recommended texlive-fonts-extra
      NOTE: try sudo apt-get update if terminal unable to locate package.
    • For Mac
      brew install basictex
      sudo tlmgr install enumitem fontawesome
  5. If you want to run ollama models
    ollama pull llama3.1
  6. Run following script to get result
>>> python main.py /
    --url "JOB_POSTING_URL" /
    --master_data="JSON_USER_MASTER_DATA" /
    --api_key="YOUR_LLM_PROVIDER_API_KEY" / # put api_key considering provider
    --downloads_dir="DOWNLOAD_LOCATION_FOR_RESUME_CV" /
    --provider="openai" # openai, gemini

3. Citations

If you find JobLLM useful in your research or applications, please consider giving us a star 🌟 and citing it.

@inproceedings{10.1145/3626772.3657680,
author = {Zinjad, Saurabh Bhausaheb and Bhattacharjee, Amrita and Bhilegaonkar, Amey and Liu, Huan},
title = {ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement},
series = {SIGIR '24},
booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626772.3657680},
url = {https://doi.org/10.1145/3626772.3657680},
year = {2024},
isbn = {9798400704314},
location = {Washington DC, USA},
address = {New York, NY, USA},
}
@misc{zinjad2024resumeflow,
      title={ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement}, 
      author={Saurabh Bhausaheb Zinjad and Amrita Bhattacharjee and Amey Bhilegaonkar and Huan Liu},
      year={2024},
      eprint={2402.06221},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

4. License

JobLLM is under the MIT License and is supported for commercial usage.

5. TODO

Need to find way to install following command in streamlit

ollama
playwright
"ollama pull llama3.1"
"ollama pull bge-m3"

4. References

For Tasks:

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For Jobs:

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