CareerBoost AI 🚀

CareerBoost AI is a complete, production-ready, AI-powered Resume Analyzer and Interview Preparation Coach built using Next.js App Router, TypeScript, Tailwind CSS, and the Google Gemini AI API.

Job seekers upload their PDF resume to instantly receive an ATS compliance score, resume formatting suggestions, strengths, weaknesses, and a custom deck of 25 interview questions (Technical, HR, and Project-based) complete with suggested reference answers customized specifically to the experiences listed on their resume.

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📌 Demo Link

🔗 https://careerboost-ai-jayjadhav.vercel.app/

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🏗️ System Architecture

This application is built as a single-session web app, keeping all candidate data secure and private by processing resume contents strictly in-memory without a database.

graph TD
    %% Frontend Layer
    subgraph Client [Browser - Client Side]
        UI[React Components <br/> /src/components]
        Theme[Theme Toggle <br/> Light / Dark Mode]
    end

    %% Backend Server Action Layer
    subgraph Server [Next.js Server Actions - Secure Node.js]
        Actions[actions.ts <br/> 'use server' entrypoint]
        Parser[pdfExtractor.ts <br/> pdf-parse engine]
        Gemini[gemini.ts <br/> Gemini API Wrapper]
    end

    %% Google Cloud Models Layer
    subgraph API [Google Gemini API Layer]
        Model[Gemini 2.5 Flash <br/> Model Output Mime: JSON]
    end

    %% Flow Connections
    UI -->|1. Upload PDF Resume| Actions
    Actions -->|2. Buffer Processing| Parser
    Parser -->|3. Extracted Plain Text| Actions
    Actions -->|4. Prompt Query| Gemini
    Gemini -->|5. Encrypted Request| Model
    Model -->|6. Structured JSON| Gemini
    Gemini -->|7. Validated ATS Object| Actions
    Actions -->|8. State Update| UI
    Theme -->|9. Toggle .dark class| UI

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🔄 Core Application Workflow

1. Upload & Parser (In-Memory): The candidate uploads a resume PDF. The React upload component converts the file into a Node buffer and executes text extraction using pdf-parse strictly on the server.
2. ATS Scoring Rubric: The plain text is fed to gemini-2.5-flash with a temperature setting of 0 to guarantee deterministic and stable scores. The prompt calculates a score out of 100 based on standard formatting and key credentials.
3. Reference Q&As: Generates 10 Technical, 10 Behavioral, and 5 Project questions, including a 1-to-2 sentence answer guide showing the user how to talk about their achievements.
4. Interactive Accordion UI: Renders results in a responsive tabbed view where candidate questions feature toggleable accordion panels to reveal reference answer guides.

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📷 Screenshots & Visual Demo

1. Landing Page & Upload Dropzone

This landing screen invites job seekers to upload their resume using a drag-and-drop file uploader. The UI features an animated radial grid backdrop and a sleek light/dark mode header selector.

2. ATS Analysis Dashboard

Displays the calculated ATS score inside a custom-styled circular progress gauge with rating indicators. Features detailed cards for professional summaries, key strengths, formatting weaknesses, missing skills, and suggestions.

3. Interview Preparation Q&As

Renders Technical, HR, and Project interview questions in a clean tabbed panel. Each card can be clicked to slide open a "Reference Answer Guide" displaying custom, resume-specific guidance.

4. Adaptive Dark Mode View

Shows the entire SaaS interface adapted to a premium dark theme using HSL slate variables. Provides high-contrast readability and glowing ambient blur blobs for a premium user experience.

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🚀 Local Development Setup

To run CareerBoost AI locally on your machine, follow these steps:

1. Clone the Directory & Install:

   cd careerboost-ai
   npm install

2. Configure Environment variables:

   cp .env.local.example .env.local

   Open .env.local and replace your_gemini_api_key_here with your API key from Google AI Studio.

3. Start Local Server:

   npm run dev

   Open http://localhost:3000 in your browser.

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📦 Deploying to Vercel

1. Push your repository to GitHub.
2. Connect your GitHub account to Vercel and import this project.
3. Add the following Environment Variable in the Vercel project configuration page:
   • Key: GEMINI_API_KEY
   • Value: YOUR_AI_STUDIO_API_KEY_HERE
4. Click Deploy. Vercel will host your site on its secure, global serverless framework.

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👨‍💻 Developer Profile

Jay Jadhav

• Email: jaydjadhav1111@gmail.com

• LinkedIn: in/jayjadhav04

• GitHub: github.com/jayjadhav04

• Portfolio: jay-jadhav-portfolio.vercel.app