📱 Generate personalized language learning news digests with LLaMA-3.1 & DeepSeek AI
⚡ 151 views · 📱 Social Media & Email Marketing
Description
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Automatically generate and email level-appropriate language learning content based on trending news.
This workflow reads learner preferences from Google Sheets (language, level, and topic of interest), uses an AI web search model to fetch relevant news, and formats the result into a structured HTML digest featuring grammar explanations and vocabulary highlights.
Emails are sent automatically to each learner in a clean, mobile-friendly format.
⚙️ What it does
- ⏰ Daily Trigger at 6 AM
- 📄 Pulls learner data from Google Sheets (Language, Level, Topic)
- 🔍 Fetches news using
perplexity/llama-3.1-sonar-small-128k-online - ✨ Formats it into HTML using
deepseek-chat, tailored to the learner’s level - 🧠 Adds grammar breakdowns and vocabulary highlights
- 📬 Sends personalized HTML email to each learner
🧠 AI Models Used
perplexity/llama-3.1-sonar-small-128k-online– web-connected LLM for up-to-date newsdeepseek-chat– formatting and simplifying articles for language learners
📚 Examples
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🔗 Technologies used
- Google Sheets – Learner database
- OpenRouter API – AI access and online reasoning
- LangChain AI Agent + Output Parser – Clean HTML structuring
- Gmail Node – Email dispatch per user
💡 Use Cases
- 🧑🏫 Classroom-ready language micro-lessons
- 🌍 Personalized news digests for multilingual learners
- ✉️ Daily practice delivery via email
- 📚 Reading + grammar + vocab in one workflow
🔗 Nodes Used
Cron, Google Sheets, HTTP Request, Gmail, AI Agent, OpenAI Chat Model
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File