Documentation

Installation Guide

AI GitHub Project Reviewer — Recruiter-Ready Profile Analyzer Using Python and Groq LLM

Step-by-step Setup Verified Instructions Chat Support
Back to Project
Complete Guide
PROJECT: AI GitHub Project Reviewer STACK: Python 3.10+, Streamlit, GitHub REST API, Groq API (llama-3.3-70b-versatile), python-dotenv INSTALLATION STEPS: 1. Clone or extract the project folder and navigate into it via terminal. 2. Create a virtual environment: python -m venv venv 3. Activate it: venv\Scripts\activate on Windows or source venv/bin/activate on macOS/Linux 4. Install dependencies: pip install -r requirements.txt 5. Create a .env file in the root directory using .env.example as reference. 6. Add GROQ_API_KEY from console.groq.com (free tier available). 7. Optionally add GITHUB_TOKEN (personal access token) to raise the GitHub API rate limit from 60 to 5000 requests per hour. 8. Run the app: streamlit run app.py 9. The app opens automatically in the browser at localhost:8501 10. Enter a GitHub username or repository URL in the sidebar and click analyze to generate the report. FILE STRUCTURE: app.py - main Streamlit entry point github_service.py - handles all GitHub API calls scorer.py - rule based scoring logic ai_analyzer.py - Groq prompt construction and response parsing .env.example - placeholder for API keys requirements.txt - all Python dependencies COMMON ISSUES: Rate limit errors usually mean no GitHub token was added, add one in .env. Groq API errors are commonly caused by an invalid or expired API key, regenerate it from the Groq console.

Need Help?

Our team is here to assist you with installation and setup.

Chat with Us
Chat with us