Package: zlm
ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and RefinementForVideo Demonstrationvisit the YouTube link:https://youtu.be/Agl7ugyu1N4Project can be:Access as aWeb Toolfromhttps://job-aligned-resume.streamlit.app/Install as aPython Packagefromhttps://pypi.org/project/zlm/download asSource Codefromhttps://github.com/Ztrimus/job-llm.gitAll other known bugs, fixes, feedbacks, and feature requests can be reported on theGitHub issuespage.Empower others, just like they helped you!Contribute to this open source project & make a difference. ✨Create a branch, improve the code, & raise a pull request!Author & Contributor ListSaurabh Zinjad|Ztrimus|szinjad@asu.eduAmey Bhilegaonkar|ameygoes|abhilega@asu.eduAmrita Bhattacharjee|Amritabh|abhatt43@asu.edu1. Introduction:1.1. Motivation: LLMs as Components in an ML PipelineIn this project, we will investigate how to effectively use Large Language Models (LLMs) to automate various aspects of this pipeline.Because, Solving a task using machine learning methods requires a series of steps that often require large amounts of human effort or labor. Furthermore there might be more steps after the training the ML model, such as evaluation, explaining the behavior of the model, interpreting model outputs, etc. Many of these steps are also often human labor intensive.1.2. Our ProposalWe'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.1.3. Refer to thisPaperfor more details.2. Setup, Installation and Usage2.1. PrerequisitesOS : Linux, MacPython : 3.11.6 and aboveLLM API key:OpenAIORGemini Pro2.2. Package Installation - Use as LibrarypipinstallzlmUsagefromzlmimportAutoApplyModeljob_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 Projectgitclonehttps://github.com/Ztrimus/job-llm.gitcdjob-llmCreate and activate python environment (usepython -m venv .envor conda or etc.) to avoid any package dependency conflict.InstallPoetry package(dependency management and packaging tool)pipinstallpoetryInstall all required packages.Referpyproject.tomlorpoetry.lockfor list of packages.poetryinstallORIf above command not working, we also providedrequirements.txtfile. But, we recommend using poetry.pipinstall-rresources/requirements.txtWe also need to install following packages to conversion of latex to pdfFor linuxsudoapt-getinstalltexlive-latex-basetexlive-fonts-recommendedtexlive-fonts-extraNOTE: trysudo apt-get updateif terminal unable to locate package.For Macbrewinstallbasictex
sudotlmgrinstallenumitemfontawesomeRun following script to get result>>>pythonmain.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, together, g4f3. CitationsIf you find JobLLM useful in your research or applications, please consider giving us a star 🌟 and citing it.@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. LicenseJobLLM is under the MIT License and is supported for commercial usage.4. ReferencesPrompt engineering GuidelinesOverleaf LaTex Resume TemplateCombining LaTeX with PythonOpenAI Documentation