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📡 Netizens API Documentation

Welcome to the official API reference for Netizens — AI Resume Analyzer & Instant Portfolio Generator

🔗 Live Application: https://netizens-six.vercel.app/

✨ Overview

Netizens provides an AI-powered resume analysis engine designed to evaluate resumes the way recruiters and ATS systems do.

It helps users:

  • 📊 Measure ATS compatibility
  • 🧠 Extract key skills
  • ⚠️ Identify missing keywords
  • 🎯 Generate actionable improvement suggestions

Core Principles: ⚡ Fast • 🧠 Intelligent • 🎯 Practical

🔗 Base URLs

🧪 Local Development

http://localhost:5000

🌐 Production (Frontend)

https://netizens-six.vercel.app/

⚠️ Note: Backend APIs are typically accessed via a locally running server unless separately deployed.

🧠 Processing Flow

Upload Resume
   ↓
Text Extraction
   ↓
AI Processing (Gemini)
   ↓
Structured JSON Response
   ↓
Dashboard Insights

🚀 API Endpoints

🔹 1. Health Check

📍 Endpoint

GET /health

📖 Description

Checks if the backend server is up and running.

✅ Response

{
  "status": "ok"
}

🔹 2. Resume Upload & Analysis

📍 Endpoint

POST /upload

📖 Description

Uploads a resume file and returns a structured AI-powered analysis including:

  • ATS Score
  • Extracted Skills
  • Missing Keywords
  • Improvement Suggestions

📥 Request Specification

🔸 Headers

Content-Type: multipart/form-data

🔸 Body Parameters

  • file (required) Resume file in PDF or DOCX format

📤 Response Structure

{
  "ats_score": 85,
  "skills": ["React", "Python", "Machine Learning"],
  "missing_keywords": ["Docker", "CI/CD"],
  "suggestions": [
    "Improve formatting consistency",
    "Add measurable achievements",
    "Include more action verbs"
  ]
}

⚠️ Error Handling

❌ Invalid File Format

{
  "error": "Invalid file format"
}

❌ No Text Extracted

{
  "error": "No text extracted from resume"
}

❌ Internal Server Error

{
  "error": "Internal server error"
}

🧪 Example Request (cURL)

curl -X POST http://localhost:5000/upload \
  -F "file=@resume.pdf"

🛠️ Tech Stack

  • Backend Framework: Flask (Python)
  • Text Extraction: pdfplumber, python-docx
  • AI Engine: Google Gemini 1.5 Flash

📌 Important Notes

  • Only PDF and DOCX formats are supported
  • Resume must contain selectable text (no scanned images)
  • API key must be configured in the .env file
  • Processing time depends on file size and content

🔄 Future Enhancements

  • 📄 Portfolio generation endpoint
  • 📊 PDF report export
  • 🎯 Job description matching
  • 🔐 Authentication & user sessions

💜 Maintained by Netizens

Built with passion to simplify resume analysis using AI.

If you found this useful, consider ⭐ starring the repository!