Tailor your Google Docs CV to any job using Ollama and Groq

Description

🎯 CV Keyword Optimizer

An AI-powered n8n workflow that automatically tailors your resume to any job description by injecting relevant keywords — without touching your formatting, layout, or design.

How It Works

Architecture

┌─────────────────────────────────────────────────────────────────┐
│ User Input (Form) │
│ CV Google Docs Link + Job URL or Pasted JD │
└──────────────────────────┬──────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 1. Read CV from Google Docs API │
│ 2. Extract full CV text (handles tables, paragraphs, etc.) │
└──────────────────────────┬───────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 3. Get Job Description │
│ ├── URL provided? → Scrape job page, strip HTML to text │
│ │ └── Scrape failed? → Fall back to manual JD │
│ └── No URL? → Use manually pasted JD directly │
└──────────────────────────┬───────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 4. 🏠 Local Ollama (llama3.1:8b) │
│ Analyzes JD + CV → Extracts & ranks 10-20 ATS keywords │
│ Output: keyword, priority, target bullet, reason │
└──────────────────────────┬───────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 5. ☁️ Groq API (Llama 3.3 70B) │
│ Takes ranked keywords + CV → Produces find/replace pairs │
│ Naturally weaves keywords into experience bullet points │
└──────────────────────────┬───────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 6. Copy original CV via Google Drive API │
│ (preserves ALL formatting, tables, styles) │
│ │
│ 7. Apply replacements via Google Docs batchUpdate API │
│ (replaceAllText — formatting stays intact) │
└──────────────────────────┬───────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────┐
│ 8. Output │
│ ✅ New Google Doc link │
│ 📋 Changelog: original text → updated text + keywords added │
└──────────────────────────────────────────────────────────────────┘

Why Two AI Models?

| Step | Model | Why |
|------|-------|-----|
| Keyword Extraction | Ollama llama3.1:8b (local) | Free, private, no API costs. Reasoning about which keywords actually matter for ATS |
| Text Rewriting | Groq llama-3.3-70b-versatile (cloud) | Larger model = better at natural language. Produces find/replace pairs that read naturally |

What Gets Modified

✅ Experience/work bullet points
✅ Skills/technical skills lines
❌ Name, contact info, education, dates, company names, job titles — never touched

Formatting Preservation

The workflow copies your original Google Doc (not recreates it), then uses replaceAllText to swap text in-place. This means:

✅ Tables, columns, fonts, colors — all preserved
✅ Bold, italic, underline — all preserved
✅ Custom spacing, margins — all preserved
✅ Original doc is untouched (changes go to the copy)

Setup Steps

Prerequisites

Docker installed
Ollama installed locally
A Groq API key (free tier works)
Google account with Docs & Drive access

1. Install & Start Ollama

macOS
brew install ollama

Start the Ollama server
ollama serve

Pull the model (in another terminal)
ollama pull llama3.1:8b

Verify it's running:
curl http://localhost:11434/api/tags

2. Get a Groq API Key

Go to console.groq.com
Sign up / log in
Navigate to API Keys → Create a new key
Copy the key (starts with gsk_...)

3. Configure Environment

cd cv-generator

Create .env from template
cp .env.example .env

Edit .env and add your Groq key
GROQ_API_KEY=gsk_your_key_here

4. Start n8n

docker compose up -d

n8n will be available at http://localhost:5678

Default credentials:
Username: admin
Password: changeme

> ⚠️ Change these in docker-compose.yml for production use.

5. Import the Workflow

Open n8n at http://localhost:5678
Go to Workflows → Import from File
Select cv-keyword-optimizer.json
You'll see credential warnings on some nodes — that's expected

6. Set Up Google Credentials

In n8n, go to Settings → Credentials
Create a Google Docs OAuth2 credential
Follow n8n's OAuth2 setup guide for Google
Required scopes: https://www.googleapis.com/auth/documents
Create a Google Drive OAuth2 credential
Required scopes: https://www.googleapis.com/auth/drive
Click each node with a ⚠️ warning → select your credential from the dropdown

7. Activate & Use

Toggle the workflow Active
Open the form URL shown in the trigger node (or go to http://localhost:5678/form/cv-keyword-optimizer-form)
Fill in:
Google Docs CV Link (required)
Job Posting URL or Job Description (at least one)
Submit and wait ~30-60 seconds
Get your optimized CV link + detailed changelog

Project Structure

cv-generator/
├── cv-keyword-optimizer.json # n8n workflow definition
├── docker-compose.yml # n8n container config
├── .env # Environment variables (not committed)
├── .env.example # Template for .env
├── .gitignore # Ignores .env
└── README.md # This file

Troubleshooting

| Issue | Solution |
|-------|----------|
| Ollama connection refused | Make sure ollama serve is running. n8n reaches it via host.docker.internal:11434 |
| Groq 429 rate limit | Free tier has limits. Wait a minute and retry |
| Scraping fails on LinkedIn | LinkedIn blocks scrapers. Paste the JD manually instead |
| Google Docs auth error | Re-check OAuth2 credentials in n8n. Ensure correct scopes |
| Replacements don't apply | The AI's "find" text must exactly match the CV. Check the Changes Summary for what was attempted |
| Empty response from Ollama | Model may still be loading. First run takes longer. Timeout is set to 5 min |