User Request
    ↓
Workflow Orchestrator
    ↓
┌─────────────────┬──────────────────┬─────────────────┐
│ LinkedIn        │ Resume           │ ATS             │
│ Scraper         │ Analyzer         │ Optimizer       │
│ (Playwright)    │ (Pandoc+Docx)    │ (NLP)           │
└─────────────────┴──────────────────┴─────────────────┘
    ↓
Gap Analyzer (Compare skills)
    ↓
Question Generator (Interview prep)
    ↓
Final Report (Summary + File locations)

bash /mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/.claude/skills/browsing-with-playwright/scripts/start-server.sh

# Core tools
sudo apt-get install pandoc python3 python3-pip nodejs npm

# Optional (for PDF export)
sudo apt-get install libreoffice poppler-utils

pip install python-docx spacy nltk pandas requests
python -m spacy download en_core_web_sm
python -m nltk.downloader punkt stopwords

npm install -g @playwright/mcp

python3 scripts/workflow_orchestrator.py \
  --job-keywords "AI Engineer remote" \
  --job-count 2

python3 scripts/workflow_orchestrator.py \
  --resume-path "/path/to/your/resume.docx" \
  --job-keywords "Machine Learning Engineer" \
  --job-count 2 \
  --output-dir "./custom_output"

bash /mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/.claude/skills/browsing-with-playwright/scripts/start-server.sh

curl http://localhost:8808

python3 scripts/linkedin_scraper.py \
  --keywords "AI Engineer remote" \
  --count 2 \
  --output jobs.json

[
  {
    "title": "Senior AI Engineer",
    "company": "TechCorp",
    "url": "https://linkedin.com/jobs/view/12345",
    "description": "Full job description...",
    "required_skills": ["Python", "TensorFlow", "MLOps"],
    "preferred_skills": ["Kubernetes", "AWS"]
  }
]

# Convert DOCX to markdown
pandoc --track-changes=accept /mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/resume/resume06012026.docx -o resume.md

# Extract skills
python3 scripts/resume_analyzer.py --resume-md resume.md --output base_skills.json

python3 scripts/ats_optimizer.py \
  --base-resume /mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/resume/resume06012026.docx \
  --job-description jobs.json \
  --job-index 0 \
  --output "resume_tailored_Senior_AI_Engineer.docx"

python3 scripts/gap_analyzer.py \
  --base-skills base_skills.json \
  --job-requirements jobs.json \
  --output gap_analysis.json

[
  {
    "job_title": "Senior AI Engineer",
    "skill_gaps": [
      {
        "skill": "Kubernetes",
        "gap_type": "missing",
        "importance": "high",
        "related_experience": ["Docker experience in current role"]
      }
    ],
    "interview_questions": [
      "Explain your understanding of Kubernetes orchestration...",
      "How would you design a Kubernetes deployment for ML models?",
      "..."
    ],
    "linkedin_updates": {
      "about_section": "Add: 'Experienced in containerization with Docker, transitioning to Kubernetes for production ML deployments'",
      "skills_to_add": ["Kubernetes", "Container Orchestration", "MLOps"]
    }
  }
]

python3 scripts/question_generator.py \
  --gap-analysis gap_analysis.json \
  --questions-per-gap 10 \
  --output interview_prep.md

bash /mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/.claude/skills/browsing-with-playwright/scripts/stop-server.sh

{
  "resume_path": "/mnt/d/Ali_Home/Learning/AgenticAI/AI-P009/Assignments/ProjectA1/resume_optimizer/resume/resume06012026.docx",
  "output_directory": "./resume_optimizer/output",
  "playwright_port": 8808,
  "job_search": {
    "default_keywords": "AI Engineer remote",
    "default_count": 2,
    "location": "Remote"
  },
  "ats_optimization": {
    "keyword_density_target": 0.75,
    "exact_match_priority": true,
    "preserve_formatting": true
  },
  "interview_prep": {
    "questions_per_gap": 10,
    "include_behavioral": true,
    "include_technical": true
  }
}

Before: "Worked on machine learning projects"
After: "Developed TensorFlow-based ML models, reducing inference time by 30%"

Before: "Built backend systems"
After: "Built scalable backend systems using Python, Docker, and Kubernetes on AWS infrastructure"

if len(jobs) == 0:
    print("No jobs found matching criteria. Suggestions:")
    print("- Broaden search keywords")
    print("- Remove 'remote' filter")
    print("- Try alternative job titles")
    sys.exit(1)

try:
    resume_text = extract_resume(resume_path)
except FileNotFoundError:
    print(f"Resume not found at {resume_path}")
    print("Please provide valid resume path with --resume-path")
    sys.exit(1)
except Exception as e:
    print(f"Error reading resume: {e}")
    print("Ensure resume is valid .docx format")
    sys.exit(1)

# Implement exponential backoff
for attempt in range(3):
    try:
        job_data = scrape_job(url)
        break
    except RateLimitError:
        wait_time = 2 ** attempt * 5  # 5s, 10s, 20s
        time.sleep(wait_time)

# Job Search Results Summary

## Jobs Found: 2

### Job 1: Senior AI Engineer - TechCorp
- **LinkedIn URL**: https://linkedin.com/jobs/view/12345
- **Tailored Resume**: ./resume_optimizer/output/resume_tailored_Senior_AI_Engineer.docx
- **Key Requirements**: Python, TensorFlow, MLOps, Kubernetes
- **Skill Gaps**: Kubernetes (High priority), AWS Sagemaker (Medium)
- **Interview Prep Questions**: 20 questions generated (see interview_prep.md)

### Job 2: Machine Learning Engineer - AI Startup
- **LinkedIn URL**: https://linkedin.com/jobs/view/67890
- **Tailored Resume**: ./resume_optimizer/output/resume_tailored_Machine_Learning_Engineer.docx
- **Key Requirements**: PyTorch, Docker, CI/CD, Model deployment
- **Skill Gaps**: PyTorch (High priority - similar TensorFlow experience)
- **Interview Prep Questions**: 15 questions generated (see interview_prep.md)

## LinkedIn Profile Recommendations

### About Section Updates
- Add: "Specialized in MLOps with focus on production-scale deployments"
- Emphasize: Kubernetes orchestration experience
- Highlight: Cross-functional collaboration in AI product development

### Skills to Add
1. Kubernetes (High priority - both jobs)
2. MLOps (Critical keyword)
3. Model Deployment
4. CI/CD for ML

## Next Steps
1. Review tailored resumes in ./resume_optimizer/output/
2. Study interview prep questions in interview_prep.md
3. Update LinkedIn profile per recommendations above
4. Apply to jobs with tailored resumes

[
  {
    "title": "AI Engineer",
    "company": "CompanyName",
    "url": "https://linkedin.com/jobs/view/12345",
    "description": "Paste full job description here..."
  }
]

python3 scripts/workflow_orchestrator.py \
  --manual-jobs jobs_manual.json \
  --skip-linkedin

python3 scripts/ats_optimizer.py \
  --base-resume resume.docx \
  --job-description jobs.json \
  --job-index 0 \
  --custom-keywords "Python,TensorFlow,Kubernetes,AWS" \
  --output tailored_resume.docx