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
```bash
pip install ResumeGPT
```
or:
```bash
pip install git+https://github.com/takline/ResumeGPT.git
```
or:
```bash
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 sure `ResumeGPT.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
```python
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.:
```python
resume_improver = ResumeGPT.services.ResumeImprover(url=url, resume_location="custom/path/to/resume.yaml")
resume_improver.create_draft_tailored_resume()
```
### Post-initialization usage
```python
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):
```python
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:
```python
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:
```python
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:
```python
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:
- [Discussions](https://github.com/takline/ResumeGPT/discussions)
- [Issues](https://github.com/takline/ResumeGPT/issues)
## Contributors
⭐️ Please star, fork, explore, and contribute to ResumeGPT. There's a lot of work room for improvement so any contributions are appreciated.
