Resume Analysis App

Resume Analysis App built with:

• Frontend: HTML / CSS / JavaScript
• Backend: Python + Flask
• AI: LangChain + (placeholder) Gemini integration (instructions included)

Features included:

• PDF upload endpoint and simple parsing pipeline (PDF -> extracted text)
• Keyword & skill extraction (basic rule-based + spaCy ready)
• Resume scoring skeleton (clarity, impact, keywords, completeness)
• Section-wise suggestions and summary generator hooks (uses LangChain/Gemini)
• Job title skills gap analysis endpoint
• Interactive editor front-end (in-browser) with rewrite suggestions placeholder
• ATS preview generation endpoint
• Account scaffolding notes (no auth implemented by default)

How to run (local)

1. Create and activate a virtualenv:

   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

2. Set environment variables (example):

   # For Gemini/LangChain usage, create a .env or export keys:
   export GEMINI_API_KEY="your_gemini_api_key_here"

3. Run the app:

   flask run --host=0.0.0.0 --port=5000

4. Open http://127.0.0.1:5000 in your browser.

Gemini / LangChain Notes

• This scaffold includes ai_services.py with placeholder code showing how you would call an LLM through LangChain.
• Replace placeholders with your provider-specific client/credentials. The code comments provide guidance.