📝 Job Description Generator using Groq LLaMA 3 & FastAPI

This project is an AI-powered Job Description Generator built using Groq's LLaMA 3-70B model and FastAPI. It generates clear, structured, and professional job descriptions based on user-provided input like role, experience, skills, job type, and location.

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🚀 Features

• 🧠 Powered by Groq's LLaMA 3-70B via OpenAI-compatible API
• ⚙️ Built with FastAPI for fast and scalable backend APIs
• ✅ Structured input with Pydantic validation
• 🧾 Clean output with basic markdown cleanup
• 🔐 Secure API integration using .env for keys

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🛠️ Tech Stack

• Language: Python
• Framework: FastAPI
• LLM: Groq LLaMA 3-70B (OpenAI-compatible)
• Input Validation: Pydantic
• Env Management: python-dotenv

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📁 Project Structure

Job_Description_Generator/ ├── .gitignore # Ignore sensitive files (e.g., .env) ├── .env # API key (not pushed to GitHub) ├── job_description_generator.py # Main FastAPI app └── README.md # Project overview

▶️ How to Run

1. Clone the repo

   git clone https://github.com/JeevanChevula/job-description-generator.git
   cd job-description-generator
   

2.Install dependencies

pip install fastapi uvicorn python-dotenv openai

3.Create a .env file

GROQ_API_KEY=your_actual_groq_api_key_here

4.Run the FastAPI app

uvicorn job_description_generator:app --reload

5.Test the endpoint at http://127.0.0.1:8000/docs

6.Output Example

POST /generate-jd

{ "role": "AI/ML Engineer", "experience": "2+ years", "must_have_skills": ["Python", "TensorFlow", "LLMs"], "preferred_skills": ["LangChain", "Docker"], "job_type": "Full-time", "location": "Remote" }