https://github.com/Rivalcoder/Resume-Sorter
ATS Resume Analayser WIth Justification
https://github.com/Rivalcoder/Resume-Sorter
gemini-api sdk vercel
Last synced: 6 months ago
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ATS Resume Analayser WIth Justification
- Host: GitHub
- URL: https://github.com/Rivalcoder/Resume-Sorter
- Owner: Rivalcoder
- Created: 2025-01-08T09:08:53.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2025-01-28T04:18:53.000Z (over 1 year ago)
- Last Synced: 2025-01-28T05:22:44.467Z (over 1 year ago)
- Topics: gemini-api, sdk, vercel
- Language: JavaScript
- Homepage: https://ats-resume-analyser.onrender.com
- Size: 2.67 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 📄 Resume Sorter
This project is a **Resume Checker** that allows users to upload their resumes and get instant feedback on their chances of getting hired. It uses Next.js for the frontend and backend, and integrates with the Google Generative AI API to analyze the resumes.
## ✨ Features
- 📄 Upload resume in PDF format
- 🔍 Get feedback on various criteria such as ATS Parse Rate, Quantifying Impact, Repetition, Spelling & Grammar, and more
- ⚡ Real-time processing and feedback display
- 🎨 Clean and user-friendly UI
## 🛠️ Installation
1. **Clone the repository**:
```sh
git clone
cd
```
2. **Install the dependencies**:
```sh
npm install
```
3. **Create a `.env` file** in the root directory and add your Google Generative AI API key:
```env
GOOGLE_GENERATIVE_AI_API_KEY=your_api_key
```
4. **Run the development server**:
```sh
npm run dev
```
The app will be available at `http://localhost:3000`.
## 📦 Dependencies
Here are the main dependencies used in this project:
- `next`
- `react`
- `formidable`
- `dotenv`
- `fs`
- `path`
You can find the complete list of dependencies in the `package.json` file.
## 🚀 Running the Application
1. **Start the development server**:
```sh
npm run dev
```
2. **Open your browser** and navigate to `http://localhost:3000`.
## 📸 Usage
### **Upload Resume**:
- Click the "Upload Resume Here.." button or drag and drop your file.
- The app will process your resume and display feedback based on the specified criteria.
### **Feedback Criteria**:
The app evaluates the resume based on the following criteria:
1. **ATS Parse Rate**: Assess how well the document adheres to ATS standards.
2. **Quantifying Impact**: Check if achievements or key points are measurable with quantifiable results.
3. **Repetition**: Identify repeated phrases or overused terms.
4. **Spelling & Grammar**: Highlight any errors in spelling or grammar.
5. **File Format & Size**: Determine whether the document is compatible with ATS systems.
6. **Document Length**: Evaluate if the length is appropriate (e.g., a concise document for most professional applications).
7. **Long Bullet Points**: Check if bullet points are concise and action-oriented.
8. **Contact Information**: Verify the presence and accuracy of essential details (email, phone, LinkedIn, etc.).
9. **Essential Sections**: Confirm if the document includes critical sections (such as Skills, Experience, and Education).
10. **Hard Skills**: Evaluate the relevance of technical proficiencies or hard skills listed.
11. **Soft Skills**: Assess the clarity and relevance of soft skills included.
12. **Active Voice**: Check if bullet points use active voice rather than passive voice.
13. **Buzzwords & Clichés**: Identify overused buzzwords or vague terms and suggest improvements.
14. **Design**: Review the document design for readability and ATS compatibility.
## 📤 Export Options
- **Analyze page**
- Export README.md: Downloads the AI analysis as a Markdown README.
- Print PDF: Opens a print-friendly view to save as PDF from your browser.
- **Bulk page**
- Export JSON: Downloads the ranked candidates and summaries as JSON.
- Export README.md: Downloads a Markdown table of ranked results.
- Print PDF: Opens a printable table view you can save as PDF.
Tip: Use your browser’s “Save as PDF” in the print dialog for high-quality PDFs.
## 🌐 API Endpoints
### **POST** `/api/server`
- **Description**: Handles file upload and processes the resume using the Google Generative AI API.
- **Request Body**: `multipart/form-data` containing the resume file.
- **Response**: JSON object with a message containing detailed feedback about the resume.
### Example Request
```http
POST /api/server
Content-Type: multipart/form-data
{
"resume": ""
}
```
### ❤️ HAPPY CODING ❤️