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🚀 Auto-Apply AI

An Isolated AI Agent Suite & Automation Workspace for Smart Job Hunting, Resume & ATS Evaluation, Preferences-Guided Multi-Country Scraping, and Direct Gmail Auto-Apply.

FastAPI Next.js Python Tailwind PostgreSQL Ollama Playwright License

Auto-Apply AI Workspace Preview

🖥️ Auto-Apply AI — Sleek Dark-Grid Workspace Interface with Coral-Red Glow Accents & Real-Time Agent Automation

📌 Table of Contents

💡 Overview

Auto-Apply AI is an intelligent, autonomous multi-agent automation platform designed to transform modern job hunting into an efficient, hands-free workflow. Operating as an isolated AI agent workspace, it takes over the tedious tasks of editing resumes, searching across multiple job portals, and writing repetitive customized emails.

Instead of manual applications, Auto-Apply AI empowers candidates with:

  1. Intelligent PDF & Word (.docx) Parsing & ATS Grading: Natively extracts competencies, work histories, and executive summaries, scoring resumes against modern Applicant Tracking System (ATS) guidelines with interactive formatting feedback.
  2. Preferences-Guided Opportunity Search: Synthesizes your specific target roles, experience levels, remote preferences, and resume skills to execute hyper-targeted scans across up to 10 destination countries simultaneously (e.g., 🇺🇸 US, 🇨🇦 Canada, 🇬🇧 UK, 🇩🇪 Germany, 🇦🇪 UAE).
  3. LLM Matching Engine & AI Cover Letters: Dynamically evaluates opportunity compatibility using customized AI prompting, generating highly persuasive, tailored 3-paragraph cover letters for matching positions.
  4. Multi-Model LLM Vault (Offline & Cloud): Fully compatible with 100% free local offline models (Ollama / LM Studio), alongside secure integration with leading cloud providers (OpenAI, Google Gemini, Groq, DeepSeek, and OpenRouter).
  5. Direct Gmail Auto-Apply & Proofs Hub: Authenticates securely via Google OAuth2 or Gmail App Passwords (SMTP) to dispatch custom applications directly to hiring managers, logging verifiable message proofs straight in your Gmail "Sent" folder.
  6. One-Command Launcher: Effortlessly initialize both backend servers, frontend dashboards, and dependencies with a simple python start.py command.

🔥 Key Features

📄 1. Native PDF & Word (.docx) Resume Parsing Engine

  • No-C-Dependency Processing: Natively parses both .pdf and Word .docx documents using Python's clean structural extractors.
  • Deep Profile Breakdown: Automatically extracts executive summaries, technical skill arrays, employment experience tiers, and academic credentials.
  • Real-Time ATS Auditor: Evaluates formatting density, bullet point action verbs (e.g., Orchestrated, Optimized), section structure, and contact information availability.
  • Resilient Fallback Parsing: Seamlessly falls back to heuristic tech-stack extraction if an external LLM key is offline or out of quota.

🧠 2. Real-Time LLM Agent Workspace & Thinking UI

  • Live Agent Feed: Experience a responsive terminal-style log feed inside your dashboard that outputs real-time AI reasoning, skill extractions, and matcher evaluations.
  • Dark Grid & Coral-Red Aesthetic: Designed with state-of-the-art glassmorphic overlays, harmonious dark color palettes, and interactive micro-animations.

🌐 3. Preferences-Guided Multi-Country Job & Internship Aggregator

  • Target Country Multi-Selection: Select up to 10 target countries simultaneously via an interactive autocomplete dropdown with custom tag badges (✓ Country ✕).
  • Flexible Opportunity Filters: Search not only full-time roles, but also internships, scholarships, and hackathons with customizable salary bands and remote filters (Fully Remote, Hybrid, On-site).

🔑 4. Universal LLM Providers Vault

  • Free Local LLMs: Built-in, zero-config support for local Ollama and LM Studio endpoints (http://localhost:11434/v1), keeping your private career data 100% offline and free.
  • Cloud Providers Support: Connect seamlessly to OpenAI (gpt-4o-mini), Groq (llama-3.3-70b-versatile), Google Gemini (gemini-2.5-flash), DeepSeek, and OpenRouter.
  • Secure Secret Masking: All keys stored within the isolated workspace vault are encrypted and visually masked in the UI.

📧 5. Direct Gmail Auto-Apply & Proof Tracking

  • Dual Authentication: Establish connections either through Google OAuth2 or an encrypted 16-character Gmail App Password (SMTP).
  • History & Proofs Hub: Track all delivered applications with time-period filtering (Today / 24 Hours, Monthly, Yearly, or All Time).
  • Official Sent-Folder Logs: Every application email dispatched by the automation agent gets recorded directly in the candidate’s official Gmail "Sent" folder for transparent verification.

🏗️ System Architecture

graph TD
    User([Candidate / User]) <--> Workspace[Next.js 16 Isolated Workspace Dashboard]
    Workspace <--> REST[FastAPI Asynchronous REST Engine]
    
    subgraph Core Storage & Database
        REST <--> SQLite[(SQLite / PostgreSQL\nSQLAlchemy 2.0 ORM)]
        REST <--> Storage[Local & Firebase File Storage]
    end

    subgraph Autonomous Multi-Agent Suite
        REST <--> ResumeAgent[Resume & ATS Parsing Agent]
        REST <--> SearchAgent[Preferences-Guided Search Agent]
        REST <--> MatchAgent[LLM Matching & Eval Engine]
        REST <--> ApplyAgent[Cover Letter & Auto-Apply Agent]
    end

    subgraph External Models & Integrations
        ResumeAgent & MatchAgent & ApplyAgent --> LocalLLM[Ollama / LM Studio\n(100% Free Offline LLM)]
        ResumeAgent & MatchAgent & ApplyAgent --> CloudLLM[OpenAI / Gemini / Groq / DeepSeek]
        ApplyAgent --> Gmail[Gmail OAuth2 & SMTP Server]
        SearchAgent --> JobAPIs[Multi-Country Job Feed Scrapers & RSS]
    end
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🛠️ Tech Stack

Component Technology Highlights & Details
Frontend Platform Next.js 16 (App Router) React 19, TypeScript, dynamic UI state & interactive modals
UI Design System Tailwind CSS v4 + Vanilla Tokens Dark-grid aesthetics, coral-red glow effects, modern responsive layouts
Backend Engine Python 3.12+ / FastAPI Asynchronous performance, automatic Swagger/OpenAPI documentation
Database & ORM SQLAlchemy 2.0 (SQLite / PostgreSQL) Automatic table introspection & non-destructive schema synchronization
Document Processing PyPDF2, pdfplumber, python-docx High-fidelity structural parsing for PDF and Word formats
AI & LLM Engine Ollama, OpenAI, Google GenAI, Groq Multi-provider architecture with fallback capabilities
Automation Dispatcher Gmail API & Async SMTP Reliable background job delivery and verification tracking

📁 Repository Structure

Auto-Apply-AI/
├── start.py                        # 🚀 Single-command cross-platform full-stack launcher
├── backend/                        # FastAPI Backend Engine
│   ├── src/
│   │   └── app/
│   │       ├── api/                # REST API Endpoints
│   │       │   ├── applications.py # Application proof logs & verification
│   │       │   ├── auth.py         # Workspace user authentication
│   │       │   ├── auto_apply.py   # Autonomous job application triggers
│   │       │   ├── emails.py       # Cover letter generation & email sending
│   │       │   ├── gmail.py        # Gmail OAuth & SMTP credentials manager
│   │       │   ├── matching.py     # LLM evaluation & job score calculations
│   │       │   ├── resumes.py      # Resume uploading, parsing & ATS audit
│   │       │   ├── search.py       # Preferences-guided opportunity scanners
│   │       │   └── users.py        # User settings & API Vault manager
│   │       ├── services/           # Core AI & Business Services
│   │       │   ├── application/    # Intelligent AI Cover letter creator
│   │       │   ├── matching/       # Opportunity-to-resume evaluation engine
│   │       │   ├── search/         # Aggregators & preferences-guided agents
│   │       │   ├── ats_checker.py  # ATS criteria rating & formatting tips
│   │       │   └── pdf_parser.py   # Native document text extractor
│   │       ├── config.py           # Application config & environment loader
│   │       ├── database.py         # Engine startup & auto-sync schema setup
│   │       ├── main.py             # Server initialization & CORS policies
│   │       ├── models.py           # Declarative SQL database models
│   │       └── storage.py          # Local filesystem & Firebase file storage
│   ├── requirements.txt            # Backend Python dependencies
│   └── pyproject.toml              # Backend environment configs
├── frontend/                       # Next.js 16 Workspace Dashboard
│   ├── src/
│   │   └── app/
│   │       ├── components/         # Modular Dashboard Components & Tabs
│   │       │   ├── GmailModal.tsx  # Gmail authentication & SMTP modal
│   │       │   ├── HistoryTab.tsx  # Today / Monthly / Yearly application hub
│   │       │   ├── JobsTab.tsx     # Opportunity cards, score badges & filters
│   │       │   ├── Navbar.tsx      # Top branding bar & quick-access vault
│   │       │   ├── ProfileTab.tsx  # Resume parser upload & ATS report UI
│   │       │   └── SettingsTab.tsx # Multi-LLM provider & Preferences Vault
│   │       ├── context/            # Client Authentication & State Context
│   │       ├── layout.tsx          # Root styling and theme framework
│   │       └── page.tsx            # Main application navigation router
│   ├── package.json                # Node modules and build scripts
│   └── tailwind.config.ts          # UI styling & design tokens
├── docs/                           # Documentation & Preview Media
│   └── images/
│       └── login-preview.png       # Dark grid login workspace UI graphic
├── LICENSE                         # Standard MIT Open-Source License
└── README.md                       # Comprehensive repository documentation

⚡ Getting Started

Prerequisites

  • Python: v3.10 or higher
  • Node.js: v18.x or higher
  • Git

🚀 Single-Command Startup (Recommended)

The easiest way to boot the entire Auto-Apply AI platform on Windows, macOS, or Linux is using our cross-platform automation launcher:

python start.py

What start.py does automatically:

  1. ✅ Verifies and Installs missing Python packages (fastapi, uvicorn, sqlalchemy, etc.) via pip.
  2. ✅ Verifies and Installs missing Node packages (frontend/node_modules) via npm install.
  3. 🚀 Launches the FastAPI backend API server on http://localhost:8000 in the background.
  4. 🚀 Launches the Next.js workspace UI server on http://localhost:3000 in the background.
  5. 🌐 Automatically opens your default web browser straight to the Auto-Apply AI Workspace.
  6. 🛑 Streams real-time terminal logs and closes all server processes gracefully when you press Ctrl + C.

Manual Setup (Alternative)

If you prefer launching services independently across two terminals:

1. Backend API Server (Terminal 1)

cd backend
python -m venv venv

# Activate virtual environment:
# Windows (PowerShell): .\venv\Scripts\Activate.ps1
# Linux / macOS: source venv/bin/activate

pip install -r requirements.txt
python -m uvicorn src.app.main:app --reload --port 8000

API Documentation will be accessible at http://localhost:8000/docs.

2. Frontend Workspace Dashboard (Terminal 2)

cd frontend
npm install
npm run dev

Workspace UI will be accessible at http://localhost:3000.

Connecting Your Gmail Account

To authorize the automation agent to dispatch customized applications directly from your email:

  1. Log into your Auto-Apply AI Workspace and navigate to 🔑 API Vault (or the Settings tab).
  2. Under Connected Gmail Account, choose Gmail App Password (SMTP).
  3. Input your email address along with a secure 16-character App Password (easily generated via Google Account > Security > 2-Step Verification > App Passwords).
  4. Click Connect via App Password. All automated emails and cover letters dispatched by the AI will immediately be mirrored and verifiable in your official Gmail "Sent" folder!

🔑 Environment Variables

You can optionally configure default behaviors by creating a .env file inside the backend/ directory:

# Database Settings (Defaults to local SQLite auto_apply_local.db if left blank)
DATABASE_URL="sqlite:///./auto_apply_local.db"

# AI Models & Default LLM Providers (Optional: Leave empty when using local Ollama)
OPENAI_API_KEY="your_openai_api_key"
LLM_PROVIDER="openai"
LLM_MODEL="gpt-4o-mini"

# Gmail OAuth & Storage Configurations (Optional)
GMAIL_CLIENT_ID="your_google_client_id"
GMAIL_CLIENT_SECRET="your_google_client_secret"
FIREBASE_STORAGE_BUCKET="your-firebase-storage-bucket.appspot.com"

# Application Security
SECRET_KEY="super-secret-jwt-key-change-in-production"

📡 API Documentation

Interactive OpenAPI/Swagger documentation is automatically published whenever the backend server runs at http://localhost:8000/docs.

Endpoint Method Core Functionality
/api/v1/auth/login POST Authenticate candidate into their isolated workspace
/api/v1/resumes/upload POST Ingest PDF/DOCX resume file, extract structural data & compute ATS score
/api/v1/resumes/profile GET / PUT Manage extracted candidate qualifications, skills array & ATS metrics
/api/v1/search/trigger POST Invoke the Preferences-Guided Search Agent across multi-country feeds
/api/v1/search/opportunities GET Retrieve scraped job, internship & scholarship listings with filters
/api/v1/matching/evaluate POST Perform real-time AI evaluation and compatibility scoring against job postings
/api/v1/auto-apply/run POST Trigger autonomous cover letter synthesis and Gmail delivery pipeline
/api/v1/users/settings GET / PUT Store LLM API keys in secure vault & customize remote job preferences
/api/v1/applications GET Access verified transmission logs for Today, Monthly, Yearly or All periods

📄 License

Distributed under the MIT License. See LICENSE for full legal text and details.

Crafted with ❤️ by Nouman Sajid for Auto-Apply AI

About

Auto apply AI your personal AI assistant that can search daily base job according to your skills , and can apply automatically , make cover letter, analyze your resume/CV provide ATS scoring for job applying , You also attach your gmail with auto-apply-AI and see better result.

Topics

ats-friendlyauomationauto-applyautogenclaude-codegithubglm5-2gmail-integrationjob-searchmulti-agentmulti-agent-systemsopenaiopenclawpythonragreactjsresumeanalyzerruflosupporttypescript

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