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job-prep's Introduction

Job Preparation Application

CI Pipeline Streamlit Version OpenAI GPT-3.5 MongoDB Atlas

This Job Preparation Application is designed to streamline the job search and application process. It offers six distinct sections to help users manage their job search effectively.

jon_prep_architecture

Features

Demo.mp4

1. Upload Resume

In the "Upload Resume" section, users can upload their resume in PDF format. The application stores the document in a MongoDB database for easy access and retrieval.

2. Search Jobs

The "Search Jobs" section allows users to specify desired job roles and locations. The application utilizes a LinkedIn API to extract job descriptions, URLs, job details, and salary information. The results are displayed in a table format, and users can mark their application status with checkboxes, which are also saved to the database.

3. Generate Resume

The "Generate Resume" section lets users customize their resume according to the job description. Users simply paste the job description, click submit, and receive a tailored resume in DOCX format. This document can be downloaded and edited as needed.

4. Generate Cover Letter

In the "Generate Cover Letter" section, users can create a customized cover letter based on the job description. The application generates a cover letter in DOCX format, which users can download and further customize.

5. Applications

In the "Applications" section, users can view the jobs they've applied for. This provides a convenient overview of their job application history.

Technologies Used

  • UI: Streamlit
  • Database: MongoDB Atlas
  • LinkedIn API: RapidAPI
  • Text Generation: OpenAI, Langchain

Getting Started

  1. RapidAPI Key: Before starting the application, ensure you have obtained a RapidAPI key and add it to the .env.example file.
  2. OpenAI API Key: You will also need OpenAI API Key to use the GPT models. Add the key to .env.example file.
  3. MongoDB URI: This application currently supports a MongoDB Database for backend storage. Add the URI to .env.example file.
  4. Execute the following code to get started.
cp .env.example .env
docker build -t job-prep .
docker run -d --env-file .env -p 8501:8501 job-prep

Roadmap

  • Implement user authentication
  • Save job data for each search ID to reduce redundant API calls
  • Add dropdown for Search IDs on the Search Jobs Page
  • Add Dashboard page for job market insights for current Search ID

License

This project is licensed under the MIT License

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