https://github.com/hxu296/nlp-resume-parser

NLP-powered, GPT-3 enabled Resume Parser from PDF to JSON.
https://github.com/hxu296/nlp-resume-parser

gpt-3 nlp nlp-parsing open-ai parser resume resume-parer

Last synced: 2 months ago
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NLP-powered, GPT-3 enabled Resume Parser from PDF to JSON.

• Host: GitHub
• URL: https://github.com/hxu296/nlp-resume-parser
• Owner: hxu296
• Created: 2022-04-03T05:00:59.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2023-06-17T15:37:16.000Z (over 1 year ago)
• Last Synced: 2024-08-02T01:23:03.061Z (6 months ago)
• Topics: gpt-3, nlp, nlp-parsing, open-ai, parser, resume, resume-parer
• Language: Python
• Homepage:
• Size: 1.29 MB
• Stars: 231
• Watchers: 4
• Forks: 50
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-ChatGPT-repositories - nlp-resume-parser - NLP-powered, GPT-3 enabled Resume Parser from PDF to JSON. (NLP)

README

        
## Resume Parser Service

GPT-3 based resume parser as a REST API that transforms a [resume PDF like this](https://github.com/hxu296/resume-parser-service/blob/main/examples/SDE_May2023_HuanXu.pdf) to a [JSON like this](https://github.com/hxu296/resume-parser-service/blob/main/examples/resume.json).

Parsing a resume PDF takes around 15 seconds and costs about $0.01 for every 500 tokens using `text-davinci-002` engine (that's why there is no live demo website). Note that a typical request and response may use 1500 tokens ($0.03), 3000 tokens ($0.06) or more.

Please note that more accurate results may be achieved by fine-tuning GPT-3, but the out-of-the-box results from this repo are already very impressive.

### Quick Start

1. Install Python 3 and pip3. For macOS, see note below.

1. Install all dependencies of `pdftotext` ([see here](https://github.com/jalan/pdftotext)).

1. In a new terminal, update pip3 if needed: `python3 -m pip install --upgrade pip`

1. In another new terminal, clone the repository and move Terminal to the directory.

    * Please close the other terminals and continue in this terminal.

1. Check the versions: `python3 --version` and `pip3 --version`.

1. Run the `./build.sh` in the project root.

1. Get your [OpenAI API Key](https://openai.com/api/).

1. Create a file named `.env` and set your API key in it: `OPENAI_API_KEY=YOURKEY` or set the key in an environment variable: `export OPENAI_API_KEY=YOURKEY`.

1. Run `./run.sh` in the project root.

A Flask server will start listening to port 5001 of localhost. Feel free to [check it out with your browser](http://0.0.0.0:5001/).

#### Note for MacOS

You need to install either XCode or GCC tools ([see here](https://docs.python-guide.org/starting/install3/osx/#doing-it-right)).

* If you install XCode, make sure to run it to complete the setup.

* Then run `xcode-select --install` and complete command-line tools installation.

* Finally install [Homebrew](https://brew.sh/), and use `brew install python` to install Python 3.

### Supported Fields

- Basic Information

  - [x] first name

  - [x] last name

  - [x] full name

  - [x] email 

  - [x] U.S. phone number

  - [x] location

  - [x] portfolio website URL

  - [x] LinkedIn URL

  - [x] GitHub main page URL

- Education

  - [x] university

  - [x] education level

  - [x] graduation year

  - [x] graduation month

  - [x] majors

  - [x] GPA

- Job Experience

  - [x] job title

  - [x] company

  - [x] location

  - [x] duration

  - [x] job content

- Project Experience

  - [x] project name

  - [x] project description