hyper-complete

bySahil Senjaliya

Build a complete AI-powered Resume Analyzer web application. Requirements: 1. Frontend: - Use React.js and Tailwind CSS. - Create a modern, responsive dashboard. - Add login and registration pages. - Allow users to upload PDF resumes. - Show ATS score, skills found, missing skills, experience, education, and improvement suggestions. - Add a dashboard with charts and score cards. 2. Backend: - Use Python FastAPI. - Create REST APIs for authentication, resume upload, resume analysis, and report generation. - Use proper error handling and validation. - Add API documentation. 3. AI/ML: - Extract text from uploaded PDF resumes. - Extract skills, education, experience, and keywords. - Compare the resume against a given job description. - Calculate an ATS-style matching score. - Generate personalized improvement suggestions. - Explain why the resume received the score. 4. Database: - Use PostgreSQL. - Store users, resumes, job descriptions, analysis results, and scores. - Design proper database relationships. 5. AI architecture: - Design the system using multiple specialized agents where appropriate: - Resume Parser Agent - Skill Extraction Agent - Job Matching Agent - Resume Evaluation Agent - Recommendation Agent - Explain how these agents communicate with each other. 6. Security: - Use JWT authentication. - Hash passwords securely. - Validate uploaded files. - Prevent unauthorized access to another user's resume. 7. Testing: - Create unit tests for important backend APIs. - Create tests for the resume-analysis workflow. - Include edge cases such as empty resumes, invalid PDFs, and missing job descriptions. 8. DevOps: - Create Dockerfiles for frontend and backend. - Create docker-compose configuration. - Provide environment variable configuration. - Explain how the application can be deployed to production. 9. Documentation: - Create a README. - Explain the architecture. - Explain API endpoints. - Explain database schema. - Explain AI-agent workflow. - Provide setup and run instructions. Important: Do not just give me code snippets. First create a complete project plan and architecture. Then implement the project step by step. Keep the project structure clean and production-oriented. After implementation, test the application and identify any issues that need fixing.