Getting Started

Relevant source files

The following files were used as context for generating this wiki page:

• README.md
• package.json
• SUPABASE_SETUP.md
• schema.prisma
• api/enhance-resume/[id]/route.ts
• api/resumes/upload/route.ts
• INTEGRATION_GUIDE.md
• enhance/[id]/_components/enhance-interface.tsx
• page.tsx

This guide provides a comprehensive overview of the GUC Resume Enhancer project, including setup instructions, architectural details, and core feature explanations. The project is an AI-powered platform designed to help job seekers optimize their resumes using various AI providers like OpenAI, Anthropic, and Google Gemini. It is built with Next.js, TypeScript, and Prisma.

The application supports two modes: a "Full Mode" with user authentication, resume history, and API key management, and a "Light Mode" for quick enhancements without an account. Key features include PDF/DOCX uploads, side-by-side comparisons of original and enhanced resumes, and PDF downloads of the final version.

Sources: README.md:3-5, README.md:18-26, page.tsx:98-101

Prerequisites

Before setting up the project, ensure the following are installed and configured:

• Node.js: Version 18+
• Database: A PostgreSQL database. The project is configured for Supabase.
• File Storage: An AWS S3 bucket or Supabase Storage bucket.
• AI Provider API Keys: At least one key for OpenAI, Anthropic, or Google Gemini.

Sources: README.md:41-46, INTEGRATION_GUIDE.md:14

Installation and Setup

Follow these steps to get the development environment running.

1. Clone and Install Dependencies

First, clone the repository and install the required npm packages.

git clone https://github.com/GustheTrader/GUC-Resume-Enhancer.git
cd GUC-Resume-Enhancer
npm install

Sources: README.md:49-56

2. Environment Variables

Create a .env file in the root directory and populate it with the necessary credentials. The project uses Supabase for its database and file storage.

Variable	Description	Example
DATABASE_URL	Connection string for the PostgreSQL database.	postgresql://postgres:your-password@db.vpvvcwvebjtibafsceqx.supabase.co:5432/postgres
NEXTAUTH_SECRET	A secret key for NextAuth session encryption.	your-random-secret-key-min-32-characters-here
NEXTAUTH_URL	The base URL of your application.	http://localhost:3000
NEXT_PUBLIC_SUPABASE_URL	The public URL for your Supabase project.	https://vpvvcwvebjtibafsceqx.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY	The anonymous/public key for your Supabase project.	your-supabase-anon-key
SUPABASE_SERVICE_ROLE_KEY	The secret service role key for Supabase admin operations.	your-supabase-service-role-key
ENCRYPTION_KEY	A 32-character key for encrypting user API keys.	your-32-character-encryption-key
OPENAI_API_KEY	(Optional) System-wide OpenAI API key.	sk-your-openai-key
ANTHROPIC_API_KEY	(Optional) System-wide Anthropic API key.	sk-ant-your-anthropic-key
GOOGLE_API_KEY	(Optional) System-wide Google Gemini API key.	your-google-key

Sources: README.md:60-78, SUPABASE_SETUP.md:63-79, INTEGRATION_GUIDE.md:81-93

3. Supabase Configuration

The application relies on Supabase for database and file storage.

Storage Bucket

Create a private storage bucket named resumes.

Sources: SUPABASE_SETUP.md:23-30

Storage Policies

Apply the following RLS policies to the resumes bucket to control access. These policies ensure that users can only manage their own files.

• Allow authenticated users to upload their own files:

  CREATE POLICY "Users can upload their own resumes"
  ON storage.objects FOR INSERT
  TO authenticated
  WITH CHECK (
    bucket_id = 'resumes'
    AND auth.uid()::text = (storage.foldername(name))[1]
  );
  

• Allow users to read their own files:

  CREATE POLICY "Users can read their own resumes"
  ON storage.objects FOR SELECT
  TO authenticated
  USING (
    bucket_id = 'resumes'
    AND auth.uid()::text = (storage.foldername(name))[1]
  );
  

• Allow users to delete their own files:

  CREATE POLICY "Users can delete their own resumes"
  ON storage.objects FOR DELETE
  TO authenticated
  USING (
    bucket_id = 'resumes'
    AND auth.uid()::text = (storage.foldername(name))[1]
  );
  

Sources: SUPABASE_SETUP.md:36-59

The file storage structure within the Supabase bucket is organized by user ID.

4. Database Setup

Use Prisma to push the schema to your PostgreSQL database.

npx prisma generate
npx prisma db push

Sources: README.md:81-84, SUPABASE_SETUP.md:63-69

5. Run the Application

Start the development server, which will be accessible at http://localhost:3000.

npm run dev

Sources: README.md:87-92

Architecture

Tech Stack

The project utilizes a modern web stack for both frontend and backend development.

Category	Technology
Framework	Next.js 14.2 (with App Router)
Language	TypeScript 5.2
Database	PostgreSQL with Prisma ORM
Authentication	NextAuth.js
File Storage	Supabase Storage (or AWS S3)
Styling	Tailwind CSS
UI Components	Radix UI, shadcn/ui
State Management	Zustand, Jotai
AI Providers	OpenAI, Anthropic, Google Gemini
File Processing	pdf-parse, mammoth

Sources: README.md:28-40, package.json

Database Schema

The database schema is defined in schema.prisma and includes models for users, resumes, enhancements, and API keys.

This ER diagram illustrates the relationships between the main database models.

Key Models

• User: Stores user account information, including authentication details and role.
• Resume: Contains metadata about uploaded resumes, including the original file name, storage path, and extracted text content.
• ResumeEnhancement: Records each AI enhancement performed on a resume, linking back to the original Resume and storing the generated content.
• UserApiKey: Securely stores encrypted API keys for different AI providers, associated with a user.

Sources: schema.prisma:41-122

Core Workflow

The following diagram shows the high-level data flow for a user enhancing a resume.

Features

Resume Upload

Users can upload resumes in PDF (.pdf) and Word (.docx) formats. The system imposes a 10MB file size limit. On upload, the file's text content is extracted and stored in the database.

• API Endpoint: POST /api/resumes/upload
• File Parsers: pdf-parse for PDFs, mammoth for DOCX.

Sources: api/resumes/upload/route.ts:46-70, dashboard/_components/upload-section.tsx:43-49

AI Enhancement

The core feature is the AI-powered enhancement. Users can choose from several enhancement types.

Enhancement Types

Value	Label	Description
skills_certifications	Skills & Certifications	Highlight trade skills, licenses, and certifications.
project_experience	Project Experience	Showcase completed work and technical expertise.
client_quality	Client Success & Quality	Emphasize customer satisfaction and quality work.

Sources: enhance/[id]/_components/enhance-interface.tsx:63-82, api/enhance-resume/[id]/route.ts:143-149

AI Providers & Models

The system supports multiple AI providers, determined by the user's active API key.

• OpenAI: gpt-4o, gpt-4o-mini, gpt-4-turbo
• Anthropic: claude-3-5-sonnet, claude-3-opus, claude-3-sonnet
• Google Gemini: gemini-1.5-pro, gemini-1.5-flash

Sources: README.md:133-149, api/enhance-resume/[id]/route.ts:20-139

The enhancement process is initiated via a POST request, which calls the appropriate AI provider based on the user's configured and active UserApiKey.