orchestra

byAman

Build a production-ready AI-powered Mock Interview and Interview Preparation Platform. PROJECT NAME: InterviewPilot GOAL: Create a web application that helps candidates prepare for technical and HR interviews using AI. The platform should analyze a candidate's resume and target job description, generate a personalized interview plan, conduct a dynamic mock interview, evaluate answers, and generate a detailed performance report. TARGET USERS: Students, fresh graduates, and job seekers preparing for interviews. CORE USER FLOW: 1. LANDING PAGE Create a modern, professional landing page explaining: - AI-powered mock interviews - Personalized interview preparation - Resume and job description analysis - Real-time answer evaluation - Performance analytics Include: - Get Started button - Login/Register - Features section - How It Works section - Example performance metrics 2. USER AUTHENTICATION Implement: - Registration - Login - Logout - Password hashing - Protected user dashboard 3. USER DASHBOARD After login, show: - Previous interviews - Average interview score - Technical score - Communication score - Problem-solving score - Recent interview sessions - Start New Interview button 4. RESUME AND JOB DESCRIPTION ANALYSIS Allow the user to: - Upload a PDF resume - Upload or paste a job description Extract and analyze: - Education - Skills - Projects - Experience - Certifications - Technologies - Job requirements Compare the resume with the job description and generate: - Matching skills - Missing skills - Recommended interview topics - Difficulty level - Personalized interview plan 5. AI INTERVIEWER AGENT Create an AI interviewer that conducts a dynamic interview. The interviewer should: - Ask one question at a time - Start with an introduction - Ask questions based on the target job - Use the candidate's resume and job description - Adapt the next question based on the previous answer - Increase or decrease difficulty depending on performance - Ask technical, behavioral, and project-related questions - Avoid repeating questions - Maintain interview context Example: If the candidate says they used Random Forest in a project, the interviewer should be able to ask a follow-up question such as: "Why did you choose Random Forest instead of Gradient Boosting?" 6. INTERVIEW MODES Provide three modes: TECHNICAL: Python, SQL, Machine Learning, Data Science, AI, APIs, databases, etc. HR: Introduction, strengths, weaknesses, teamwork, challenges, career goals, etc. PROJECT: Questions generated specifically from the candidate's resume projects. 7. ANSWER EVALUATION After every answer, evaluate it using an AI evaluator. Score each answer from 0–10 based on: - Relevance - Technical correctness - Completeness - Clarity - Depth - Confidence indicators - Communication quality Provide short constructive feedback. Do not reveal the evaluation before the interview is finished unless the user enables practice mode. 8. FINAL INTERVIEW REPORT After the interview, generate a detailed report containing: Overall Score Technical Knowledge Problem Solving Communication Answer Quality Confidence Resume Knowledge Job Relevance Also show: - Strongest answers - Weakest answers - Topics that need improvement - Recommended study topics - Personalized next steps 9. AI KNOWLEDGE ASSISTANT Create a knowledge assistant that allows the candidate to ask questions about interview preparation. It should provide: - Concept explanations - Interview questions - Examples - Follow-up questions - Study recommendations The assistant should use uploaded interview-preparation documents as a knowledge source if documents are available. 10. INTERVIEW QUESTION GENERATOR Allow users to generate a customized interview set based on: - Job role - Experience level - Skills - Difficulty - Interview type Example: Data Scientist + Fresher + Medium Difficulty + 10 questions 11. INTERVIEW HISTORY Store completed interviews. For each interview show: - Date - Job role - Interview type - Overall score - Individual category scores - Number of questions - Duration Allow users to open previous reports. 12. PERFORMANCE ANALYTICS Create charts showing: - Score over time - Technical performance - Communication performance - Weak topics - Strong topics 13. DATABASE Use a relational database. Create appropriate tables for: - Users - Resumes - Job descriptions - Interview sessions - Questions - Answers - Evaluations - Performance reports 14. ADMIN DASHBOARD Create a simple admin dashboard showing: - Number of users - Number of interviews - Average score - Most common job roles - Most common weak topics 15. SECURITY Implement: - Password hashing - Authentication - Authorization - Input validation - Secure file upload handling - File type validation - Maximum file size - Protection against unauthorized access 16. ERROR HANDLING Implement proper error handling for: - Invalid files - Empty resumes - Invalid job descriptions - AI failures - Database errors - Authentication errors - API failures Show useful user-friendly error messages. 17. RESPONSIVE UI Create a clean modern SaaS-style interface that works on: - Desktop - Tablet - Mobile Use clear navigation and professional dashboard components. 18. TESTING Create automated tests for: - Authentication - File upload - Resume processing - Interview creation - Question generation - Answer evaluation - Database operations - Authorization - API endpoints Also perform end-to-end testing of the main user flow: Register → Login → Upload Resume → Add Job Description → Generate Interview → Complete Interview → Receive Report. 19. API ARCHITECTURE Use a clean REST API architecture. Separate: - Authentication - Resume processing - Job analysis - Interview generation - Answer evaluation - Reports - Analytics 20. DOCUMENTATION Generate project documentation explaining: - Architecture - Database schema - API endpoints - AI components - User flow - Setup instructions - Testing - Deployment IMPORTANT PRODUCT REQUIREMENTS: - Do not create a simple chatbot. - Build this as a complete multi-page SaaS application. - Keep the architecture modular. - Use AI agents where appropriate. - Clearly separate interviewer, evaluator, and knowledge-assistant responsibilities. - Maintain interview context between questions. - Make the UI professional and easy for a first-time user. - Include realistic sample data so the application can be demonstrated without uploading a real resume. - Prioritize reliability, security, maintainability, and user experience.