Send a daily GitHub Trending digest to Telegram using Google Gemini
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 14 nodes and runs on a schedule (every day at 03:00). Along the way it connects Google Gemini Chat Model and Telegram. It also calls github.com over HTTP.
How it runs
Trigger: On a schedule (every day at 03:00).
- Set Digest Config (Edit Fields (Set)): sets 1 field: n_repos
- Fetch GitHub Trending Page (HTTP Request): calls github.com
- Extract Trending Repository Links (HTML): parses or builds HTML
- Split Repository Links (Split Out): splits a list into separate items
- Build Repository URLs (Edit Fields (Set)): sets 2 fields: url, readme
- Limit Repositories (Code): runs custom JavaScript code
- Fetch Repository README (HTTP Request): calls an HTTP API
- Build AI Digest Payload (Code): runs custom JavaScript code
- Generate AI Repository Digest (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model; output parser: Structured Output Parser
- Format Telegram Message (Code): runs custom JavaScript code
…plus 1 more step. See the full node list below.
Services it uses
HTTP calls to: github.com
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Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (10)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Split Out
n8n-nodes-base.splitOut - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Telegram
n8n-nodes-base.telegram - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - HTML
n8n-nodes-base.html - Code
n8n-nodes-base.code - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm
From the author
Daily GitHub Trending AI Digest to Telegram This workflow generates a daily AI-powered GitHub Trending digest and sends it to Telegram using GitHub Trending, GitHub README data, and Google Gemini. It fetches trending repositories from GitHub, extracts the top…