Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/saritaphd/end-to-end-resume-application-tracking-system-llm-
ATS Resume Expert is a Streamlit-based web application that allows users to upload their resumes in PDF format and receive an analysis based on a provided job description. The application uses the Gemini Pro model from Google's Generative AI to generate detailed feedback and evaluate the alignment of the resume with the job description.
https://github.com/saritaphd/end-to-end-resume-application-tracking-system-llm-
Last synced: 3 days ago
JSON representation
ATS Resume Expert is a Streamlit-based web application that allows users to upload their resumes in PDF format and receive an analysis based on a provided job description. The application uses the Gemini Pro model from Google's Generative AI to generate detailed feedback and evaluate the alignment of the resume with the job description.
- Host: GitHub
- URL: https://github.com/saritaphd/end-to-end-resume-application-tracking-system-llm-
- Owner: SaritaPhD
- License: apache-2.0
- Created: 2024-07-25T10:04:54.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-07-25T12:34:59.000Z (4 months ago)
- Last Synced: 2024-07-26T13:29:00.800Z (4 months ago)
- Language: Python
- Homepage:
- Size: 814 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# End-to-End-Resume-Application-Tracking-System-LLM
## ATS Resume Expert
## Overview
- ATS Resume Expert is a Streamlit-based web application that allows users to upload their resumes in PDF format and receive an analysis based on a provided job description. The application uses the Gemini Pro model from Google's Generative AI to generate detailed feedback and evaluate the alignment of the resume with the job description.
## Features
- Job Description Input: Users can enter the job description in a text area.
- Resume Upload: Users can upload their resume in PDF format.
- Professional Evaluation: The application provides a detailed professional evaluation of the resume against the job description.
- Percentage Match: The application calculates the percentage match between the resume and the job description, highlighting missing keywords and providing final thoughts.
## Requirements
- Python 3.10+
- Streamlit
- dotenv
- base64
- PIL (Pillow)
- PyPDF2
- google-generativeai
### Dependencies: If pdf2image is used instaed of pyPDF2 then pdf2image requires poppler to be installed on your system. Make sure poppler is installed:
- On macOS: brew install poppler
- On Ubuntu: sudo apt-get install -y poppler-utils
## Installation
- Clone the repository: git clone [email protected]:SaritaPhD/End-to-End-Resume-Application-Tracking-System-LLM-.git
- cd End-to-End-Resume-Application-Tracking-System-LLM-
- Create a virtual environment: python -m venv venv
- source venv/bin/activate # On Windows use `venv\Scripts\activate`
I- nstall the required packages: pip install -r requirements.txt
## Set up your Google API key:
- Create a .env file in the project root directory and add your Google API key:
GOOGLE_API_KEY=your_google_api_key
## Usage
- Run the Streamlit app: streamlit run app.py
- Open your web browser and go to http://localhost:8501.
- Enter the job description in the provided text area.
- Upload your resume in PDF format.
- Click on the "Submit" button to get a professional evaluation or the "Percentage match" button to get a percentage match evaluation.
![Alt text]()