📨 AI Cover Letter Generator (Node.js + Ollama)

This project is an Express.js application that generates professional cover letters using your CV (PDF) and a Job Description. It uses Ollama for local LLM inference and embeddings.

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🚀 Features

• Upload a PDF CV
• Extracts text content from the PDF
• Generates vector embeddings using ollama (model: gemma:2b)
• Creates a tailored, AI-generated cover letter using your CV and job description

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🧰 Requirements

Before running the app, ensure you have the following installed:

• Node.js (version ≥ 18)

• npm

• Ollama (for local model inference)

• Model pulled locally:

  ollama pull gemma:2b

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📦 Installation

1. Clone this repository

   git clone https://github.com/abdulganiyy/cvwriter.git
   cd cvwriter

2. Install dependencies

   npm install

3. Make sure Ollama is running locally

   • Open a terminal and start Ollama if it’s not running:

     ollama serve

   • Verify it works:

     ollama list

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🏃 Run the App

Start the development server:

node index.js

By default, the server will start at:

http://localhost:8000

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🧪 API Endpoints

POST /upload

Generates a cover letter based on the uploaded CV and job description.

Request body:

{
  "fileContent": "<base64-encoded PDF data>",
  "description": "Software engineer position focusing on full-stack web development..."
}

Response:

{
  "coverLetter": "Dear Hiring Manager, ..."
}

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🗂 Project Structure

.
├── build/                # Optional frontend build (e.g., React app)
├── index.js              # Main Express app
├── package.json
└── README.md

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⚙️ Notes

• You can integrate a frontend that uploads the CV (PDF) and job description via fetch('/upload').

• The current embedding model is gemma:2b. You can switch to another available embedding model by changing:

  model: "gemma:2b";

  to something like "Qwen2:0.5b"

• Ensure your machine has enough RAM and CPU to run gemma:2b.

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🧩 Example Frontend Fetch Request

const handleUpload = async (pdfBase64, description) => {
  const res = await fetch("http://localhost:8000/upload", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({
      fileContent: pdfBase64,
      description,
    }),
  });

  const data = await res.json();
  console.log("Generated Cover Letter:", data.coverLetter);
};

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