

I made an Automated/AI Resume Screener with auto-reply & AI Provider fallbacks. Let me know your thoughts on it (e.g. improvement and other things)
Hey everyone,
I wanted to share a 24/7 automation tool I built using two Python scripts to handle the tedious parts of hiring and screening applicants without risking API downtime.
1. resume_screener.py (The Assistant)
This script handles all the structural operations and logistics:
Checks Mail: Safely polls your inbox every minute for unread application emails.
Parses Files: Automatically extracts text from attached PDF and Word resumes.
Logs & Organizes: Evaluates candidates, dumps metrics into a color-coded Excel sheet, and pushes an instant summary straight to your private Telegram chat.
Auto-Replies: Instantly dispatches a tailored SMTP email back to applicants depending on their initial screening score.
2. gemini_ai.py (The Resilient AI Brain)
This module acts like an automated relay race to guarantee evaluation uptime:
7-Layer Cloud Fallback: It targets Google Gemini first. If a rate limit or failure occurs, it instantly cascades down a backup API chain: Groq -> OpenRouter -> Mistral -> Cohere -> NVIDIA NIM -> Cloudflare Workers AI.
The Ultimate Offline Backup: If the internet drops out entirely, it activates a small local model on my own computer's hardware to finish processing resumes offline.
3. job_description.txt (The Grading Benchmark)
Targeted Scoring: Acts as the absolute source of truth. Rather than generic filtering, the AI performs a direct side-by-side gap analysis against the exact criteria outlined in this file (e.g., scoring a Senior Logistics & Operations Manager profile against requirements like ERP/WMS proficiency and supply chain KPIs).
Structured Output: Delivers a clear match rating (0-100), key candidate strengths, and explicitly calls out missing technical skills.
Would love to hear your thoughts or if you've implemented similar things, 'cuz I know for a fact that ERP systems like Oracle and SAP use this thing too!