Project Plan: AI-Powered Resume-to-Portfolio Converter (Blazor Server App)

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Project Overview

A no-login Blazor Server application where users upload resumes (PDF/DOC) to generate a single-page portfolio. Includes feedback and donation screens, SQLite database, and AI-driven content parsing.

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Phase 1: Setup & Infrastructure (Week 1-2)

Tasks

1. Project Setup

   • Create Blazor Server App (.NET 6+).
   • Install NuGet packages:
     • Syncfusion.Blazor (UI components)
     • IronPdf, DocX (file processing)
     • Microsoft.EntityFrameworkCore.Sqlite (database)
     • OpenAI (text analysis)
   • Configure dependency injection for services.

2. Database Design

   • SQLite schema with tables:
     • Resumes: Id (GUID), FileName, FileContent, CreatedAt, ParsedJson, PortfolioHtml
     • Feedbacks: Id, Name, Email, Message, Rating (1-5), CreatedAt
     • Donations: Id, Amount, Email, TransactionId, CreatedAt
   • Use EF Core Code-First migrations.

3. Basic UI Layout

   • Create MainLayout.razor with navigation menu (Home, Feedback, Donate).
   • Style using Syncfusion themes or custom CSS.

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Phase 2: Core Functionality (Week 3-4)

Tasks

1. File Upload Component

   • Razor component with <InputFile> accepting PDF/DOC/DOCX.
   • Client-side validation (file size ≤5MB, correct format).
   • Server-side processing:
     • Convert PDF to text with IronPdf.
     • Extract DOC/DOCX text with DocX.

2. AI-Powered Resume Parsing

   • Use OpenAI API to analyze extracted text:
     • Prompt: "Extract name, summary, skills, experience, education, and contact info from this resume."
   • Map parsed data to a ResumeModel class.

3. Portfolio Generator

   • Razor component template with sections (Summary, Skills, Experience).
   • Dynamic data binding using parsed ResumeModel.
   • Add "Download as HTML/PDF" button (use IronPdf).

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Phase 3: Feedback & Donation Screens (Week 5)

Tasks

1. Feedback Screen

   • Form with fields: Name (optional), Email (optional), Rating (dropdown), Message.
   • Submit to FeedbackService (stores in SQLite).

2. Donation Screen

   • Integrate PayPal/Stripe payment links (no backend processing).
   • Simple UI with "Support Us" message and redirect buttons.

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Phase 4: Testing & Debugging (Week 6)

Tasks

1. Unit Tests

   • Test file conversion (mock PDF/DOC files).
   • Validate AI parsing logic with sample resumes.
   • Test database CRUD operations.

2. UI Testing

   • Test upload, error handling, and mobile responsiveness.
   • Use Selenium for automated browser tests.

3. User Testing

   • Recruit 5-10 users to test end-to-end flow.
   • Fix issues (e.g., slow AI response, layout bugs).

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Phase 5: Deployment (Week 7)

Tasks

1. Azure Hosting

   • Deploy to Azure App Service (Windows/Linux).
   • Configure SQLite database path (appsettings.json).

2. CI/CD Pipeline

   • Set up GitHub Actions for automated deployment.
   • Add scripts for EF Core migrations.

3. Monitoring

   • Integrate Azure Application Insights for logging/analytics.

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Phase 6: Post-Launch (Week 8+)

Tasks

1. User Feedback Loop

   • Monitor feedback for common issues (e.g., parsing errors).

2. Maintenance

   • Schedule monthly database cleanup (delete records >30 days old).
   • Update OpenAI prompts for better accuracy.

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Timeline

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Risk Mitigation

• Large File Uploads: Restrict to 5MB; compress files if needed.
• AI Errors: Fallback to manual text parsing for key sections.
• Payment Failures: Use trusted providers (PayPal/Stripe) with HTTPS.

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Budget

• Development: $5k (2 months part-time)
• Hosting: $50/month (Azure B1 tier)
• OpenAI API: $100/month (based on usage)

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