Tailor your resume to match any job posting effortlessly
Project description
Features · Install · Usage · Discussions · Contributors
Tailor your resume to match any job posting effortlessly with ResumeGPT.
ResumeGPT allows you to simply provide your resume and a job posting link, and it will produce a formatted ATS friendly PDF resume that is optimized and personalize your resume to align with the specific requirements and keywords of the job.
Features
- Extracts relevant skills, qualifications, and keywords from a job posting.
- Tailors your curent resume to match job requirements.
- Generates professional ATS friendly PDF resumes.
- Allows for user verification and customization before finalizing the resume.
Installation
pip install ResumeGPT
or:
pip install git+https://github.com/takline/ResumeGPT.git
or:
git clone https://github.com/takline/ResumeGPT.git
cd ResumeGPT
pip install -r requirements.txt
Usage
- Add your resume to
ResumeGPT/data/sample_resume.yaml
(make sureResumeGPT.config.YOUR_RESUME_NAME
is set to your resume filename in the.data/
folder) - Provide ResumeGPT with the link to a job posting and it will tailot your resume to the job:
Single job posting usage
url = "https://[link to your job posting]"
resume_improver = ResumeGPT.services.ResumeImprover(url)
resume_improver.create_draft_tailored_resume()
ResumeGPT then creates a new resume YAML file in a new folder named after the job posting (ResumeGPT/data/[Company_Name_Job_Title]/resume.yaml
) with a YAML key/value: editing: true
. ResumeGPT will wait for you to update this key to verify the resume updates and allow them to make their own updates until users set editing=false
. Then ResumeGPT will create a PDF version of their resume.
Custom resume location usage
Initialize ResumeImprover
via a .yaml
filepath.:
resume_improver = ResumeGPT.services.ResumeImprover(url=url, resume_location="custom/path/to/resume.yaml")
resume_improver.create_draft_tailored_resume()
Post-initialization usage
resume_improver.update_resume("./new_resume.yaml")
resume_improver.url = "https://[new link to your job posting]"
resume_improver.download_and_parse_job_post()
resume_improver.create_draft_tailored_resume()
Background usage
You can run multiple ResumeGPT.services.ResumeImprover's concurrently via ResumeGPT's BackgroundRunner class (as it takes a couple of minutes for ResumeImprover to complete a single run):
background_configs = [
{
"url": "https://[link to your job posting 1]",
"auto_open": True,
"manual_review": True,
"resume_location": "/path/to/resume1.yaml",
},
{
"url": "https://[link to your job posting 2]",
"auto_open": False,
"manual_review": False,
"resume_location": "/path/to/resume2.yaml",
},
{
"url": "https://[link to your job posting 3]",
"auto_open": True,
"manual_review": True,
"resume_location": "/path/to/resume3.yaml",
},
]
background_runner = ResumeGPT.services.ResumeImprover.create_draft_tailored_resumes_in_background(background_configs=background_configs)
#Check the status of background tasks (saves the output to `ResumeGPT/data/background_tasks/tasks.log`)
background_runner["background_runner"].check_status()
#Stop all running tasks
background_runner["background_runner"].stop_all_tasks()
#Extract a ResumeImprover
first_resume_improver = background_runner["ResumeImprovers"][0]
You will follow the same workflow when using ResumeGPT's BackgroundRunner (ex: verify the resume updates via editing=false
in each ResumeGPT/data/[Company_Name_Job_Title]/resume.yaml
file). You can also find logs for the BackgroundRunner in ResumeGPT/data/background_tasks/tasks.log
.
Once all of the background tasks are complete:
background_runner["background_runner"].check_status()
Output:
['Task completed.',
'Task completed.',
'Task completed.',
'Task completed.',
'Task completed.',
'Task completed.',
'Task completed.',
'Task completed.',
'Task completed.']
Create the pdf for each ResumeImprovers
instance:
for improver in background_runner["ResumeImprovers"]:
pdf_generator = ResumeGPT.pdf_generation.ResumePDFGenerator()
resume_yaml_path = os.path.join(improver.job_data_location, "resume.yaml")
pdf_generator.generate_resume(improver.job_data_location, ResumeGPT.utils.read_yaml(filename=resume_yaml_path))
ResumeGPT PDF Output
Example ATS friendly resume created by ResumeGPT:
pdf_generator = ResumeGPT.pdf_generation.ResumePDFGenerator()
pdf_generator.generate_resume("/path/to/save/pdf/", ResumeGPT.utils.read_yaml(filename="/path/to/resume/resume.yaml"))
Discussions
Feel free to give feedback, ask questions, report a bug, or suggest improvements:
Contributors
⭐️ Please star, fork, explore, and contribute to ResumeGPT. There's a lot of work room for improvement so any contributions are appreciated.
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