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🤖 AI Job Automation Agent - Agentic AI Job Application Ecosystem

Python Version License ┌─────────────────────────────────────────────────────────────────────────────┐ │ AI JOB AUTOMATION AGENT ECOSYSTEM │ └─────────────────────────────────────────────────────────────────────────────┘

Code ┌──────────────────────┐ │ Master Orchestrator │ │ (master_run.py) │ └──────────┬───────────┘ �� ┌──────────────────┼──────────────────┐ │ │ │ ┌─────────▼────────┐ ┌──────▼──────┐ ┌──────▼──────────┐ │ Job Discovery │ │ Job Analysis│ │ Automation │ │ Workflow │ │ Workflow │ │ Workflow │ └─────────┬────────┘ └──────┬──────┘ └──────┬──────────┘ │ │ │ ┌─────────▼────────────────────────────────────▼────┐ │ CORE SYSTEM ENGINES (Modular) │ ├────────────────────────────────────────────────────┤ │ │ │ ┌──────────────┐ ┌──────────────┐ │ │ │ Scraper Eng. │ │ AI Engine │ │ │ └──────────────┘ └──────────────┘ │ │ │ │ ┌──────────────┐ ┌──────────────┐ │ │ │ Resume Eng. │ │Notion Eng. │ │ │ └──────────────┘ └──────────────┘ │ │ │ │ ┌──────────────┐ ┌──────────────┐ │ │ │Automation Eng│ │MCP Client │ │ │ └──────────────┘ └──────────────┘ │ │ │ └────────────────────────────────────────────────────┘ │ ┌───────────────────┼───────────────────┐ │ │ │ ┌───▼────────┐ ┌──────▼──────┐ ┌────────▼───┐ │ Notion DBs │ │ External │ │ N8N WF │ │ (Job Data) │ │ Integrations│ │ Automation │ └────────────┘ └─────────────┘ └────────────┘ Code

Module Organization

aarjunm04/AI_Job_Automation_Agent/ ├── master_run.py ← Main Entry Point (Orchestrator) ├── requirements.txt ← Python Dependencies ├── docker-compose.yml ← Docker Configuration │ ├── core/ ← Core Engine Implementations │ ├── ai_engine.py ← AI & Analysis Engine │ ├── scraper_engine.py ← Web Scraping Engine │ ├── resume_engine.py ← Resume Generation Engine │ ├── notion_engine.py ← Notion Database Engine │ ├── automation_engine.py ← Form Automation Engine │ └── init.py │ ├── agents/ ← AI Agent Implementations │ ├── discovery_agent.py ← Job Discovery Agent │ ├── analysis_agent.py ← Job Analysis Agent │ ├── application_agent.py ← Application Submission Agent │ └── coordinator_agent.py ← Multi-Agent Coordinator │ ├── scrapers/ ← Platform-Specific Scrapers │ ├── linkedin_scraper.py │ ├── indeed_scraper.py │ ├── glassdoor_scraper.py │ └── multi_platform_scraper.py │ ├── integrations/ ← External Service Integrations │ ├── notion_integration.py │ ├── openai_integration.py │ ├── anthropic_integration.py │ └── gmail_integration.py │ ├── mcp/ ← Model Context Protocol │ ├── mcp_client.py │ └── mcp_server.py │ ├── automation/ ← Automation Utilities │ ├── playwright_actions.py │ ├── form_filler.py │ └── browser_automation.py │ ├── rag_systems/ ← Retrieval Augmented Generation │ ├── job_rag_system.py │ ├── company_rag_system.py │ └── embeddings.py │ ├── config/ ← Configuration Management │ ├── settings.py │ ├── database_config.py │ └── prompts.yaml │ ├── chrome_extension/ ← Browser Extension (Frontend) │ ├── manifest.json │ ├── popup.html / popup.js │ └── content.js │ ├── n8n/ ← N8N Workflow Automation │ ├── discovery_workflow.json │ ├── analysis_workflow.json │ └── application_workflow.json │ ├── scripts/ ← Utility Scripts │ ├── setup_env.sh │ ├── migrate_data.py │ └── health_check.py │ └── assets/ ← Documentation Assets ├── diagrams/ ├── screenshots/ └── templates/

Code

🛠️ Tech Stack

Language Composition

  • Python 69.2% - Core automation engine, AI, and logic
  • JavaScript 17.8% - Chrome extension, frontend interactions
  • CSS 5.4% - Styling for UI components
  • HTML 4.3% - Extension and web templates
  • Shell 3.3% - Deployment and setup scripts

Key Technologies

Category Technologies
AI & LLMs Anthropic Claude, OpenAI, Perplexity AI
Web Scraping Scrapy, Selenium, Playwright, BeautifulSoup4, Splash
Automation Playwright, Undetected-ChromeDriver
Database Notion API, PostgreSQL, MongoDB, Redis
Web Framework FastAPI, Flask, Starlette
Data Processing Pandas, NumPy, Scikit-learn
Document Processing PyPDF2, pdfplumber, PyLaTeX, ReportLab
Vision/OCR EasyOCR, OpenCV, Pytesseract
Protocol Model Context Protocol (MCP)
Async asyncio, aiohttp, asyncpg
Task Queue Celery
DevOps Docker, Docker Compose

Python Dependencies Highlights

Core: anthropic, openai, perplexityai Scraping: scrapy, selenium, playwright, beautifulsoup4, lxml, selectolax Automation: undetected-chromedriver, playwright Data: pandas, numpy, scikit-learn, sentence-transformers AI/ML: tiktoken, nltk, spacy, textblob APIs: notion-client, google-api-python-client, requests Web: fastapi, flask, flask-cors, starlette, uvicorn Database: sqlalchemy, asyncpg, redis Document: PyPDF2, pdfplumber, pylatex, reportlab, pillow Testing: pytest, pytest-asyncio, pytest-cov, pytest-mock

Code

📦 Installation

Prerequisites

  • Python 3.9 or higher
  • Docker & Docker Compose (optional but recommended)
  • Git
  • PostgreSQL (optional, for advanced features)
  • Modern web browser (Chrome/Chromium for extensions)

Step 1: Clone Repository

bash git clone https://github.com/aarjunm04/AI_Job_Automation_Agent.git cd AI_Job_Automation_Agent Step 2: Set Up Python Environment bash

Create virtual environment

python -m venv venv

Activate virtual environment

On Linux/Mac:

source venv/bin/activate

On Windows:

venv\Scripts\activate Step 3: Install Dependencies bash pip install --upgrade pip pip install -r requirements.txt

Optional: Install development dependencies

pip install pytest pytest-cov pytest-asyncio Step 4: Configure Environment Variables bash

Copy example environment file

cp .env.example .env

Edit configuration with your API keys and credentials

nano .env # or use your preferred editor Required Environment Variables:

bash

AI APIs

ANTHROPIC_API_KEY=your_anthropic_key OPENAI_API_KEY=your_openai_key PERPLEXITY_API_KEY=your_perplexity_key

Job Platforms

LINKEDIN_EMAIL=[email protected] LINKEDIN_PASSWORD=your_password INDEED_API_KEY=your_indeed_key

Database

NOTION_API_KEY=your_notion_token DATABASE_URL=postgresql://user:password@localhost/db_name

Integrations

GMAIL_CLIENT_ID=your_gmail_client_id GMAIL_CLIENT_SECRET=your_gmail_client_secret OVERLEAF_API_KEY=your_overleaf_key

System

TIMEZONE=Asia/Kolkata DAILY_RUN_TIME=09:00 Step 5: (Optional) Using Docker bash

Build and start services

docker-compose up -d

Initialize database

docker exec ai_job_automation python scripts/migrate_data.py

Check container status

docker-compose ps Step 6: Verify Installation bash

Run health check

python master_run.py --mode health-check

You should see output like:

✅ System Health Check: All components healthy

🚀 Quick Start Basic Usage - Discover Jobs bash

Discover new jobs from all platforms

python master_run.py --mode discover

Discover with custom limit

python master_run.py --mode discover --limit 100 Analyze Discovered Jobs bash

Analyze jobs for matching

python master_run.py --mode analyze

Analyze with limit

python master_run.py --mode analyze --limit 20 Submit Applications bash

Apply to high-priority jobs

python master_run.py --mode apply

Apply with limit

python master_run.py --mode apply --limit 5 Complete End-to-End Automation bash

Full automation: Discover → Analyze → Apply

python master_run.py --mode full-automation Health Check bash

Verify all systems are operational

python master_run.py --mode health-check Debug Mode bash

Run with detailed logging

python master_run.py --mode discover --debug 📊 Workflow Diagrams

  1. Job Discovery Workflow Code ┌─────────────────────────────────────────────────────────────────────┐ │ JOB DISCOVERY WORKFLOW - SCRAPE & COLLECT │ └─────────────────────────────────────────────────────────────────────┘

┌──────────────────┐ │ Start Discovery │ └────────┬─────────┘ │ ▼ ┌─────────────────────────┐ │ Load Search Criteria │ │ - Job Titles │ │ - Locations │ │ - Salary Range │ └────────────┬────────────┘ │ ┌────────────▼────────────────────────────────────────┐ │ Multi-Platform Scraping (Parallel) │ ├────────────────────────────────────────────────────┤ │ ┌─────────────┐ ┌──────────────┐ ┌────────────┐ │ │ │ LinkedIn │ │ Indeed │ │ Glassdoor │ │ │ └──────┬──────┘ └───────┬──────┘ └─────┬──────┘ │ │ │ │ │ │ │ ┌──────▼──────┐ ┌──────▼──────┐ ┌─────▼──────┐ │ │ │ AngelList │ │ Dice │ │ ZipRecruit│ │ │ └──────┬──────┘ └───────┬──────┘ └─────┬──────┘ │ │ └──────────────┬──────────────────┘ │ └──────────────────┬───────────────────────────────┘ │ ▼ ┌──────────────────────────┐ │ Deduplication & Cleaning │ │ - Remove Duplicates │ │ - Normalize Data │ │ - Extract Metadata │ └────────────┬─────────────┘ │ ▼ ┌──────────────────────────┐ │ Convert to Standard │ │ JobApplication Format │ └────────────┬─────────────┘ │ ▼ ┌──────────────────────────┐ │ Save to Notion DB │ │ (Applications Database) │ └────────────┬─────────────┘ │ ▼ ┌──────────────────────────┐ │ Return Discovery Summary │ │ - Jobs Found: X │ │ - Duplicates: Y │ │ - Stored: Z │ └──────────────────────────┘ 2. Job Analysis & Matching Workflow Code ┌─────────────────────────────────────────────────────────────────────┐ │ JOB ANALYSIS WORKFLOW - AI-POWERED MATCHING │ └─────────────────────────────────────────────────────────────────────┘

┌───────��──────────┐ │ Start Analysis │ └────────┬─────────┘ │ ▼ ┌─────────────────────────┐ │ Load Jobs from Notion │ │ Filter: DISCOVERED │ │ Status │ └────────────┬────────────┘ │ ▼ ┌──────────────────┐ │ Load User Profile│ │ - Skills │ │ - Experience │ │ - Preferences │ └────────┬─────────┘ │ ▼ ┌───────────────────────────┐ │ AI Analysis Loop (Per Job)│ ├───────────────────────────┤ │ │ │ ┌─────────────────────┐ │ │ │ Extract Job Details │ │ │ │ - Title, Company │ │ │ │ - Description │ │ │ │ - Requirements │ │ │ └──────────┬──────────┘ │ │ │ │ │ ┌──────────▼──────────┐ │ │ │ Semantic Matching │ │ │ │ - Compare Skills │ │ │ │ - Experience Level │ │ │ │ - Requirements │ │ │ └──────────┬──────────┘ │ │ │ │ │ ┌──────────▼──────────┐ │ │ │ Calculate Match │ │ │ │ Score (0-100%) │ │ │ └──────────┬──────────┘ │ │ │ │ │ ┌──────────▼──────────┐ │ │ │ Determine Status │ │ │ │ ≥85% → AUTO_APPLY │ │ │ │ 70-85% → REVIEW │ │ │ │ <70% → REJECT │ │ │ └──────────┬──────────┘ │ │ │ │ │ ┌──────────▼──────────┐ │ │ │ Generate Strategy │ │ │ │ - Key Skills │ │ │ │ - Cover Letter Tips │ │ │ └──────────┬──────────┘ │ │ │ │ │ ┌──────────▼──────────┐ │ │ │ Update in Notion │ │ │ │ - Match Score │ │ │ │ - Status │ │ │ │ - Analysis │ │ │ └────────────────────┘ │ │ │ │ └───────────┼──────────────┘ │ ▼ (Next Job) ┌────────────┐ │ More Jobs? │ └──┬──────┬──┘ Yes│ │No │ └────────────────────┐ │ │ ▼ ▼ (Repeat Loop) ┌──────────────────────┐ │ Return Analysis │ │ Summary │ │ - Analyzed: X │ │ - High Priority: Y │ │ - Ready to Apply: Z │ └──────────────────────┘ 3. Automated Application Submission Workflow Code ┌──────────────────────────────��───────────────────────────────────────┐ │ AUTOMATED APPLICATION WORKFLOW - SUBMIT APPLICATIONS │ └──────────────────────────────────────────────────────────────────────┘

┌──────────────────┐ │ Start Apply Mode │ └────────┬─────────┘ │ ▼ ┌──────────────────────────┐ │ Get High-Priority Jobs │ │ Filter: STAGED_FOR_APPLY │ │ Sort: Match Score DESC │ └────────────┬─────────────┘ │ ▼ ┌───────────────────────────────────┐ │ Application Processing Loop │ ├───────────────────────────────────┤ │ │ │ ┌────────────────────────────┐ │ │ │ Load Job & User Profile │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Generate Optimized Resume │ │ │ │ - Parse Job Description │ │ │ │ - Extract Keywords │ │ │ │ - Prioritize Skills │ │ │ │ - Generate ATS-Friendly │ │ │ │ - Calculate ATS Score │ │ │ │ - Export PDF │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Company Intelligence │ │ │ │ Research │ │ │ │ - Company Overview │ │ │ │ - Culture Insights │ │ │ │ - Recent News │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Generate Cover Letter │ │ │ │ - AI-Personalized Content │ │ │ │ - Company-Specific │ │ │ │ - Role-Aligned │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Prepare Application Job │ │ │ │ Package Data │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Automated Form Submission │ │ │ │ - Open Application URL │ │ │ │ - Detect Form Fields │ │ │ │ - Fill with Parsed Data │ │ │ │ - Handle CAPTCHA │ │ │ │ - Submit Application │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Handle Result │ │ │ │ - Success: Move to Tracker │ │ │ │ - Failure: Log & Notify │ │ │ └────────────┬───────────────┘ │ │ │ │ │ ┌────────────▼───────────────┐ │ │ │ Rate Limiting │ │ │ │ Wait 60 seconds │ │ │ └────────────┬────────���──────┘ │ │ │ │ └───────────────┼───────────────────┘ │ ▼ (Next Job) ┌────────────┐ │ More Jobs? │ └──┬──────┬──┘ Yes│ │No │ └─────────────────────────┐ │ │ ▼ ▼ (Repeat Loop) ┌──────────────────────┐ │ Return Summary │ │ - Attempted: X │ │ - Successful: Y │ │ - Success Rate: Z% │ └──────────────────────┘ 4. End-to-End Automation Workflow Code ┌─────────────────────────────────────────────────────────────────────┐ │ FULL AUTOMATION WORKFLOW - COMPLETE PIPELINE │ └─────────────────────────────────────────────────────────────────────┘

                ┌──────────────────────┐
                │ START FULL AUTOMATION │
                └──────────┬───────────┘
                           │
                ┌──────────▼──────────┐
                │  PHASE 1: DISCOVER  │
                ├──────────────────────┤
                │ • Scrape Jobs       │
                │ • Deduplicate       │
                │ • Store in DB       │
                └──────────┬──────────┘
                           │
                    ⏳ Wait 30s
                           │
                ┌──────────▼──────────┐
                │  PHASE 2: ANALYZE   │
                ├──────────────────────┤
                │ • Load Jobs         │
                │ • AI Matching       │
                │ • Score & Rank      │
                │ • Update Status     │
                └──────────┬──────────┘
                           │
                    ⏳ Wait 30s
                           │
                ┌──────────▼──────────┐
                │  PHASE 3: APPLY     │
                ├──────────────────────┤
                │ • Get High Priority │
                │ • Generate Resumes  │
                │ • Create CL         │
                │ • Submit Apps       │
                └──────────┬──────────┘
                           │
                ┌──────────▼──────────┐
                │ CONSOLIDATE RESULTS │
                │ - Discovered: X     │
                │ - Analyzed: Y       │
                │ - Applied: Z        │
                │ - Success Rate: W%  │
                └──────────┬──────────┘
                           │
                ┌──────────▼──────────┐
                │ END FULL AUTOMATION  │
                └──────────────────────┘

🔧 Components Documentation

  1. Master Orchestrator (master_run.py) The central command center that coordinates all system components.

Key Class: MasterOrchestrator

Main Methods:

initialize_system() - Boot all engines and verify health run_job_discovery(max_jobs_per_platform=50) - Discover jobs run_job_analysis(limit=20) - Analyze discovered jobs run_automated_applications(max_applications=10) - Submit apps run_full_automation() - Complete end-to-end workflow run_system_health_check() - Verify system integrity Usage:

bash python master_run.py --mode discover --limit 50 python master_run.py --mode analyze --limit 20 python master_run.py --mode apply --limit 10 python master_run.py --mode full-automation python master_run.py --mode health-check --debug Output: JSON summary with execution statistics

  1. Core Engine: Scraper Engine Responsible for discovering and extracting job listings from multiple platforms.

Module: core/scraper_engine.py

Key Features:

Multi-platform scraping (20+ platforms) Duplicate detection and removal Data normalization Real-time progress tracking Configurable retry logic Rate limiting and throttling Supported Platforms:

LinkedIn Jobs Indeed Glassdoor AngelList Dice ZipRecruiter Monster CareerBuilder And 12+ more Key Methods:

Python async scrape_all_platforms( search_terms: List[str], max_jobs_per_platform: int = 50 ) -> List[ScrapingResult]

convert_to_job_applications(jobs: List) -> List[JobApplication] 3. Core Engine: AI Engine Provides AI-powered job analysis, matching, and content generation.

Module: core/ai_engine.py

Key Features:

Semantic job-to-profile matching Match scoring algorithm (0-100%) Company intelligence research Personalized cover letter generation Application strategy recommendations Multi-LLM support (Anthropic, OpenAI, Perplexity) Key Methods:

Python async analyze_job_opportunity( job_data: Dict, user_profile: Dict, session_id: str ) -> JobAnalysis

async research_company_intelligence( company_name: str, job_role: str ) -> CompanyIntelligence

async generate_personalized_cover_letter( job_data: Dict, company_intel: CompanyIntelligence, user_profile: Dict, resume_highlights: List[str] ) -> CoverLetter 4. Core Engine: Resume Engine Generates and optimizes resumes for each job application.

Module: core/resume_engine.py

Key Features:

Job-specific resume generation ATS (Applicant Tracking System) optimization Skill prioritization based on job description Multiple export formats (PDF, DOCX, HTML) Overleaf integration for advanced resumes Performance scoring and recommendations Key Methods:

Python async generate_optimized_resume( request: ResumeGenerationRequest ) -> ResumeResult

async optimize_for_ats(resume_data: Dict) -> OptimizationResult 5. Core Engine: Notion Engine Manages all database operations with Notion.

Module: core/notion_engine.py

Key Features:

Job application tracking database Status management (Discovered, Staged, Applied, Rejected) Batch operations for efficiency Real-time updates and synchronization Filtering and sorting capabilities Database Schema:

Applications DB: Stores discovered jobs with metadata Job Tracker DB: Tracks application status and results Key Methods:

Python async batch_create_job_applications( applications: List[JobApplication] ) -> List[str]

async get_jobs_by_status(status: ApplicationStatus) -> List[Dict]

async update_job_application( page_id: str, updates: Dict ) -> bool 6. Core Engine: Automation Engine Handles browser automation and form filling for job applications.

Module: core/automation_engine.py

Key Features:

Playwright-based browser automation Intelligent form field detection Captcha handling and detection Smart field mapping Error handling and recovery Screenshot capture on failure Key Methods:

Python async apply_to_job( application_job: ApplicationJob ) -> ApplicationAttempt

async fill_application_form( url: str, form_data: Dict ) -> bool 7. Supporting Systems A. Configuration System (config/settings.py) Centralized configuration management Environment variable integration Type-safe settings with Pydantic Multiple configuration profiles B. RAG Systems (rag_systems/) Retrieval Augmented Generation for job analysis Company knowledge base Embeddings-based semantic search Context-aware information retrieval C. MCP Integration (mcp/) Model Context Protocol support Extended AI capabilities Standardized tool interfaces Integration with Claude and other AI models D. N8N Workflows (n8n/) Visual workflow automation Complex multi-step automation Conditional logic and branching Integration with external services E. Chrome Extension (chrome_extension/) Browser-based user interface Real-time job discovery notifications One-click job application Quick access to automation features 📘 Usage Guide Scenario 1: Automated Daily Job Applications bash

Run every morning at 9 AM

0 9 * * * cd /path/to/AI_Job_Automation_Agent && python master_run.py --mode full-automation Scenario 2: Manual Review Before Applying bash

Step 1: Discover new jobs

python master_run.py --mode discover --limit 100

Step 2: Analyze and review in Notion (manual review)

python master_run.py --mode analyze

Step 3: Submit high-confidence applications only

python master_run.py --mode apply --limit 5 Scenario 3: Targeted Job Search bash

Configure in .env or settings.yaml

SEARCH_CRITERIA={ "job_titles": ["ML Engineer", "AI Engineer", "Data Scientist"], "locations": ["Remote", "San Francisco", "NYC"], "salary_min": 120000, "experience_level": ["Senior", "Lead"] }

Run discovery

python master_run.py --mode discover --limit 50 Scenario 4: Monitoring and Health Checks bash

Check system health

python master_run.py --mode health-check

Get detailed logs

python master_run.py --mode discover --debug

Monitor running process

tail -f automation.log ⚙️ Configuration Environment Variables Create a .env file in the project root:

bash

===== AI/LLM Configuration =====

ANTHROPIC_API_KEY=sk-ant-xxx OPENAI_API_KEY=sk-xxx PERPLEXITY_API_KEY=ppl-xxx

===== Job Platform Credentials =====

LINKEDIN_EMAIL=[email protected] LINKEDIN_PASSWORD=your_secure_password INDEED_API_KEY=indeed_key_xxx GLASSDOOR_API_KEY=glassdoor_key_xxx

===== Database Configuration =====

NOTION_API_KEY=notion_token_xxx NOTION_DATABASE_ID_APPLICATIONS=xxx NOTION_DATABASE_ID_TRACKER=xxx

===== External Services =====

GMAIL_CLIENT_ID=client_id GMAIL_CLIENT_SECRET=client_secret OVERLEAF_API_KEY=overleaf_key

===== System Configuration =====

TIMEZONE=Asia/Kolkata DAILY_RUN_TIME=09:00 MAX_APPLICATIONS_PER_DAY=15 SCRAPING_DELAY_MIN=2 SCRAPING_DELAY_MAX=5 PLAYWRIGHT_HEADLESS=true Advanced Configuration Edit config/settings.py for advanced settings:

Python

Search criteria

SEARCH_CRITERIA = { 'job_titles': ['ML Engineer', 'Data Scientist', 'AI Engineer'], 'locations': ['Remote', 'San Francisco'], 'salary_range': {'min': 100000, 'max': 200000}, 'experience_level': ['Mid', 'Senior', 'Lead'] }

Automation settings

AUTOMATION = { 'max_retries': 3, 'timeout': 30, 'headless': True, 'rate_limit': 60 # seconds between applications }

AI/Analysis settings

AI_ANALYSIS = { 'min_match_score_for_apply': 85, 'min_match_score_for_review': 70, 'use_multi_llm': True, 'llm_models': ['claude-3-opus', 'gpt-4'] } 👥 Contributing We welcome contributions! Here's how to get involved:

Development Setup bash

Clone and setup

git clone https://github.com/aarjunm04/AI_Job_Automation_Agent.git cd AI_Job_Automation_Agent python -m venv venv source venv/bin/activate pip install -r requirements.txt

Install dev dependencies

pip install pytest pytest-cov black flake8 mypy

Run tests

pytest tests/ -v --cov

Format code

black . --line-length 100

Type checking

mypy . Contributing Guidelines Fork the Repository Create a Feature Branch: git checkout -b feature/amazing-feature Make Changes: Follow PEP 8 style guide Write Tests: Ensure new functionality is tested Run Quality Checks: bash pytest tests/ black . flake8 . mypy . Commit Changes: git commit -m 'Add amazing feature' Push to Branch: git push origin feature/amazing-feature Create Pull Request: Describe changes clearly Areas for Contribution Additional job platform scrapers Improved AI matching algorithms Enhanced form filling accuracy Better CAPTCHA handling Additional language support Performance optimizations Documentation improvements Bug fixes and issue resolution 📄 License This project is licensed under the MIT License - see the LICENSE file for details.

In simple terms:

✅ You can use this project for personal and commercial purposes ✅ You can modify and distribute the code ✅ You must include the license and copyright notice ❌ The authors provide no warranty 📞 Support & Contact Get Help 📧 Email: [email protected] 🐛 Issues: GitHub Issues 💬 Discussions: GitHub Discussions 📖 Documentation: Wiki Troubleshooting Q: Application keeps failing A: Check automation.log for detailed error messages. Run health check:

bash python master_run.py --mode health-check Q: Notion API errors A: Verify your Notion API key and database permissions. Test with:

bash python -c "from core.notion_engine import NotionEngine; print('✅ Connected')" Q: Resume not generating A: Check OpenAI/Anthropic API keys. Verify Overleaf integration if using LaTeX.

Q: Jobs not being scraped A: Platform credentials may be invalid. Update credentials in .env and test individual scraper.

🌟 Acknowledgments Built with ❤️ by the AI Job Automation Team Powered by cutting-edge AI/ML technologies Community contributions and feedback Open-source libraries and frameworks 📈 Project Statistics Code ┌─────────────────────────────────────────┐ │ Language Composition │ ├─────────────────────────────────────────┤ │ Python ████████████████░░░ 69.2%│ │ JavaScript ████░░░░░░░░░░░░░░░ 17.8%│ │ CSS ██░░░░░░░░���░░░░░░░░ 5.4%│ │ HTML ██░░░░░░░░░░░░░░░░░ 4.3%│ │ Shell █░░░░░░░░░░░░░░░░░░ 3.3%│ └─────────────────────────────────────────┘

Key Metrics:

  • 20+ Supported Job Platforms
  • 100+ Python Dependencies
  • 5 Core Engine Modules
  • 3 Main Workflow Modes
  • Async/Await Architecture
  • Enterprise-Grade Reliability
Made with ❤️ by Aarjun Mahule

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Agentic AI Job Application Ecosystem

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