LLMployable - AI-Powered Resume Builder

LLMployable is a sophisticated full-stack platform designed to automate the creation of hyper-tailored resumes. By leveraging LLM-based analysis and semantic matching, LLMployable bridges the gap between your technical profile (GitHub/LinkedIn) and specific job requirements.

Live on: https://mployable.onrender.com/

Devpost: https://devpost.com/software/llmployable

Latest Features

• Modern Full-Stack Architecture: React 19.2 frontend with Framer Motion animations and a robust Flask backend.
• AI-Powered Interview Preparation: Generates tailored interview questions and preparation tips based on specific job descriptions.
• Interactive Mock Interviews: Voice-enabled practice sessions integrated with ElevenLabs AI for realistic interview simulation.
• Semantic Tech-Stack Matching: Intelligent selection of GitHub repositories that best align with job descriptions using skill scoring.
• Hybrid Profile Sourcing:
  • GitHub: Automatic repository scraping and language analysis.
  • LinkedIn: Structured data import via LinkedIn Data Export ZIP.
• MongoDB Persistence: Full database integration for user profiles, resume versioning, job application tracking, and intelligence caching using MongoDB Atlas.
• Gemini AI Integration: Advanced job description analysis to identify required skills and experience levels using Gemini 2.0 Flash models.
• Professional LaTeX Generation: Dynamic compilation of resume content into high-quality, ATS-friendly PDFs.

Technology Stack

Frontend

• React 19.2: Utilizing modern hooks and patterns.
• Vite: Ultra-fast build tool and development server.
• Tailwind CSS: Utility-first CSS framework for clean, responsive UI.
• Framer Motion: Smooth, high-performance web animations.
• Lucide React: Clean and consistent iconography.
• ElevenLabs API: AI-driven voice synthesis for mock interview simulations.

Backend

• Python / Flask: Scalable RESTful API service.
• MongoDB: Document-oriented database for flexible data storage.
• Google Gemini API: state-of-the-art LLM for intelligent text analysis.
• PyGithub & BeautifulSoup: Specialized scraping tools for profile data.
• LaTeX (pdflatex): Industry-standard typesetting for professional PDFs.

DevOps

• Docker & Docker Compose: Containerized environment for consistent deployment.
• Nginx: High-performance web server and reverse proxy.

Prerequisites

• Python 3.10+
• Node.js 18+ & npm
• MongoDB: Local instance or MongoDB Atlas URI (dnspython required).
• LaTeX Distribution: TeX Live (Linux/macOS) or MiKTeX (Windows).
• API Keys: Google Gemini API and optionally ElevenLabs API.

Getting Started

1. Clone & Setup Environments

git clone https://github.com/HrishikeshUchake/LLMployable.git
cd LLMployable
cp .env.example .env

2. Backend Installation

# It is recommended to use a virtual environment
python -m venv venv
source venv/bin/activate  # venv\Scripts\activate on Windows
pip install -r requirements.txt

3. Frontend Installation

cd frontend
npm install
cd ..

4. Running the Application

Option A: Manual Start

# Terminal 1: Backend (Port 5001)
python app.py

# Terminal 2: Frontend (Port 5173)
cd frontend
npm run dev

Option B: Docker (Recommended)

docker-compose up --build

How it Works

1. Profile Connection: Enter your GitHub username. LLMployable fetches your repos, languages, and contributions.
2. Contextual Input: Provide your LinkedIn Data Export for professional experience.
3. Job Analysis: Paste a job description. The AI extracts key requirements, tech stack, and experience levels.
4. Smart Selection: LLMployable's semantic matcher identifies which of your GitHub projects most closely match the job's tech stack.
5. PDF Generation: A customized LaTeX template is filled with the matched data and compiled into a downloadable PDF.
6. Interview Preparation: Generate behavioral and technical questions tailored to the job, and practice with voice-enabled AI mock interviews.

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Built for developers who want to stand out.