Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/shubhamprajapati7748/resume-perfector.ai
ResumePerfector.ai is an AI-powered tool that helps job seekers optimize their resumes for ATS by analyzing job descriptions and offering insights, feedback, and personalized suggestions. Using the Google Gemini LLM model, it assesses resume-job description matches, identifies skills gaps, and ensures ATS compatibility.
https://github.com/shubhamprajapati7748/resume-perfector.ai
gemini-api genai google-generative-ai resume-builder resume-perfector streamlit
Last synced: 12 days ago
JSON representation
ResumePerfector.ai is an AI-powered tool that helps job seekers optimize their resumes for ATS by analyzing job descriptions and offering insights, feedback, and personalized suggestions. Using the Google Gemini LLM model, it assesses resume-job description matches, identifies skills gaps, and ensures ATS compatibility.
- Host: GitHub
- URL: https://github.com/shubhamprajapati7748/resume-perfector.ai
- Owner: shubhamprajapati7748
- License: gpl-3.0
- Created: 2024-12-28T19:28:03.000Z (27 days ago)
- Default Branch: main
- Last Pushed: 2024-12-28T20:01:15.000Z (27 days ago)
- Last Synced: 2024-12-28T20:26:07.791Z (27 days ago)
- Topics: gemini-api, genai, google-generative-ai, resume-builder, resume-perfector, streamlit
- Language: Python
- Homepage: https://resume-prefector-ai.streamlit.app
- Size: 0 Bytes
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ResumePerfector.ai
## About The Project
**ResumePerfector.ai** is an GENAI-powered platform designed to optimize resumes for applicant tracking systems (ATS). By leveraging the **Google Gemini LLM Model**, the system enhances the likelihood of your resume passing through ATS filters and matching specific job descriptions.
### 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀:
- 💡 𝗝𝗼𝗯 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Tailor your resume to match the job description perfectly!
- 🤖 𝗔𝗧𝗦 𝗖𝗼𝗺𝗽𝗮𝘁𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗖𝗵𝗲𝗰𝗸: Ensure your resume passes ATS filters with ease!
- 📊 𝗦𝗸𝗶𝗹𝗹𝘀 𝗚𝗮𝗽 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Identify missing skills compared to the job requirements.
- ✅ 𝗥𝗲𝘀𝘂𝗺𝗲 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: Get actionable tips for improvement.
- 🎯 𝗥𝗲𝘀𝘂𝗺𝗲 𝗠𝗮𝘁𝗰𝗵 %: See how closely your resume fits the JD.
- 📄 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗖𝗼𝘃𝗲𝗿 𝗟𝗲𝘁𝘁𝗲𝗿𝘀: Generate a personalized cover letter instantly.
- ⚡ 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝗥𝗲𝘀𝘂𝗺𝗲: Craft an optimized resume that stands out!
## Screenshot
## Demo
You can view the demo [here](https://vimeo.com/1042704420)
## Social Media Post
You can check out more about this project on [LinkedIn Post](https://www.linkedin.com/posts/shubhamprajapati7748_ai-resumeoptimization-jobsearch-activity-7279023942827233280-z1rR/)
## Key Technologies:
- **Google Gemini LLM Model**: Advanced AI for analyzing resumes and job descriptions.
- **pdf2image**: Converts PDF resumes into image formats for preprocessing.
- **fpdf**: Generates PDF documents programmatically for enhanced resume creation.
- **PyPDF2**: Extracts, merges, and manipulates PDF content efficiently.
## Use Cases:
- **Resume Optimization**: Tailors resumes to pass Applicant Tracking System (ATS) filters.
- **Job Description Analysis**: Analyzes job postings to provide actionable feedback for resume refinement.
- **PDF Manipulation**: Simplifies resume uploads and adjustments by enabling seamless PDF processing.
## Why Choose ResumePerfector.ai?
- **Personalized Feedback**: Provides insights to close skill gaps and align with job requirements.
- **ATS Compatibility**: Formats and structures resumes to meet ATS standards, improving selection odds.
- **AI-Powered Efficiency**: Uses advanced AI models and tools for precise, automated resume enhancement.
## Table of Contents
- [Prerequisites](#prerequisites)
- [Getting Started](#getting-started)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
- [Acknowledgements](#acknowledgements)
### Prerequisites
Before getting started, make sure you have the following:
- **GOOGLE GEMINI API Key**: You’ll need an API key for interaction with the Google Gemini LLM.
### Getting Started
To get started with this project locally, you’ll need Python 3.10+ installed on your machine along with the necessary Python packages. You can either clone the repository and install dependencies manually or use Docker for an isolated environment.
## Installation Steps
1. **Clone the repository**:
- Open your terminal or command prompt.
- Navigate to the directory where you want to install the project.
- Run the following command to clone the GitHub repository:
```bash
git clone https://github.com/shubhamprajapati7748/resume-perfector.ai
```
2. **Create a Virtual Environment (Optional)**:
- It's recommended to use a virtual environment to manage dependencies. Run the following command:
```bash
conda create -p python== -y
```
3. **Activate the Virtual Environment (Optional)**:
- Activate the virtual environment based on your operating system:
```bash
conda activate /
```
4. **Install Dependencies**:
- Navigate to the project directory:
```bash
cd [project_directory]
```
- Run the following command to install project dependencies:
```bash
pip install -r requirements.txt
```
5. **Create `.env` file and add your API keys**:
- Create a `.env` file in the root directory and add your Google Gemini API key for LLM interaction.
6. **Run the Project**:
- To start the application, run the following command:
```bash
streamlit run app.py
```
7. **Access the Project**:
- Visit `http://localhost:8501` in your browser to use the app.
## Contributing
Contributions to the Google Gemini-Pro Chat Application are welcome! If you have suggestions, enhancements, or bug fixes, please follow the steps below:
1. Fork the project.
2. Create your feature branch (`git checkout -b feature/YourFeature`).
3. Commit your changes (`git commit -m 'Add some feature'`).
4. Push to the branch (`git push origin feature/YourFeature`).
5. Open a pull request.
## License
Distributed under the MIT License. See `LICENSE.txt` for more information.
## Contact
- Shubham Prajapati - [[email protected]](mailto:[email protected])
## Acknowledgements
- **Google Gemini** for providing LLM to process the user requests and generate the response in this project.