On-demand email newsletter summaries from Gmail to Telegram with GPT-4.1-mini

Summary

Send a number to your Telegram bot (e.g., 2) and get a neatly formatted digest of all Gmail newsletters received since that date. Each email is summarized by an LLM into concise topics, merged into a single Telegram message, automatically split into chunks to fit Telegram limits, and safely formatted as HTML.

What this workflow does

• Triggers on your Telegram message containing a number of days, e.g., 1, 2, 7
• Fetches all Gmail messages since that date using a custom search query, optionally filtered by senders
• Retrieves and decodes each email’s HTML, subject, sender name, date
• Prompts an LLM (GPT‑4.1‑mini) to produce a consistent JSON summary of topics per email
• Merges topics from all emails into a single digest
• Builds a readable, enumerated message (with bold titles)
• Splits it into 3 500‑char parts and sanitizes Markdown to Telegram‑safe HTML
• Sends the digest to your Telegram chat with preview disabled

Apps and credentials

• Gmail OAuth2: Gmail account
• Telegram: Telegram account (bot)
• OpenAI: OpenAi account

Typical use cases

• Personal or team daily/weekly newsletter digests in Telegram
• Curated feeds from selected senders compiled on demand
• Lightweight knowledge briefings without leaving Telegram

How it works (node-by-node)

• Telegram Trigger
  • Waits for your message (e.g., "2"). Chat ID is restricted to your Telegram ID for safety.
• Get days (Code)
  • Takes the numeric daysAgo from the Telegram message text
  • Computes YYYY/MM/DD for Gmail’s after: filter
• Get many messages (Gmail → getAll, returnAll: true)
  • Uses a custom q filter like: =(from:@.com) OR (from:@.com) OR (from:@.com -"____") after:{{ $json.dateString }}
  • Returns a list of message IDs
• Loop Over Items (Split in Batches)
  • Iterates through each message ID
• Get a message (Gmail → get)
  • Retrieves the full message/payload for the current email
• Get message data (Code)
  • Extracts HTML from Gmail’s payload (body/parts)
  • Normalizes sender to just the name
    • Formats the date as DD.MM.YYYY
    • Passes html, subject, from, date forward
• Clean (Code)
  • Converts DD.MM.YYYY → MM.DD (for prompt brevity)
  • Passes html, subject, from, date to the LLM
• Message a model (OpenAI, model: gpt‑4.1‑mini, JSON output)
  • Prompt instructs: - Produce JSON: { "topics": [ { "title", "descr", "subject", "from", "date" } ] }
    • Split multi-news blocks into separate topics
    • Combine or ignore specific blocks for particular senders (placeholders ____)
    • Keep subject untranslated; other values in ____ language
    • Injects subject/from/date/html from the current email
• Loop Over Items (continues)
  • After all iterations complete, the aggregated per-email results are available
• Merge (Code)
  • Flattens the topics arrays from all processed emails into one combined topics list
• Create TG message (Code)
  • Renders an enumerated list:
    • 1. Title (bold)
    • Short description
    • Original subject
    • From — Date
• Split (Code)
  • Splits into 3 500‑character chunks to stay below Telegram’s 4 096 limit with HTML overhead
• Sanitize (Code)
  • Escapes &, <, >
  • Fixes unbalanced * and _
  • Converts basic Markdown markers to Telegram HTML
• Send a message (Telegram)
  • Sends each part with parse_mode=HTML, previews disabled

Node map

Node	Type	Purpose
Telegram Trigger	Trigger	Receive daysAgo command from Telegram
Get days	Code	Compute Gmail after:YYYY/MM/DD from daysAgo
Get many messages	Gmail (getAll)	Search emails since date with custom from: filters
Loop Over Items	Split in Batches	Iterate messages one-by-one
Get a message	Gmail (get)	Fetch full message payload
Get message data	Code	Extract HTML/subject/from/date; normalize sender and date
Clean	Code	Reformat date and forward fields to LLM
Message a model	OpenAI	Summarize email into JSON topics
Merge	Code	Merge topics from all emails
Create TG message	Code	Build human-friendly digest text
Split	Code	Chunk into 3 500‑char parts
Sanitize	Code	Escape HTML and map Markdown to Telegram HTML
Send a message	Telegram	Deliver digest to Telegram chat

Before you start

• Create a Telegram bot and get its token (via @BotFather)
• Get your Telegram user ID to restrict access
• Connect Gmail OAuth2 in n8n
• Add your OpenAI API key
• Import the provided workflow JSON into n8n

Setup instructions

1. Telegram

• Telegram Trigger node:
  • additionalFields.chatIds = your Telegram user ID
• Send a message node:
  • chatId = your Telegram user ID
  • parse_mode = HTML
  • disable_web_page_preview = true

1. Gmail

• Connect a Gmail OAuth2 credential (Gmail account)
• In Get many messages, adjust filters.q to your senders and rules:
  • Example: =(from:[email protected]) OR (from:[email protected] -"promo") after:{{ $json.dateString }}
• If needed, add label: or category: filters

1. OpenAI

• Message a model:
  • Model: gpt‑4.1‑mini (can swap to gpt‑4o‑mini or your preferred)
  • Update the prompt placeholders: - ____ language → your target language - ____ sender rules → your special cases (combine blocks, ignore sections)

1. Safety and formatting

• Keep parse_mode=HTML in Telegram
• The Sanitize node is designed for <b> and <i> only; avoid other HTML tags
• The Split node uses 3 500 chars per part to stay safe under Telegram limits

How to use

• In Telegram, send a number indicating “days ago”
  • Example: 2 → will query Gmail after the date 2 days ago
• The workflow compiles and returns a digest in your chat
• Rerun anytime with a new number

Customization ideas

• Labels instead of global search: q = label:Newsletters after:{{ $json.dateString }}
• Time window control: add before: or exact date ranges
• Different language: set the ____ language in the LLM prompt
• Model choice: swap to cheaper/faster models if volume is high
• Chunk size: adjust from 3 500 to your needs
• Formatting: tweak Create TG message to include links parsed from HTML (if you add an HTML parser step)

Limits and notes

• Telegram messages are limited to ~4 096 characters; we chunk to 3 500 per part
• Gmail “after:” uses YYYY/MM/DD and Google’s interpretation of dates; your n8n server time influences the computed date
• LLM usage incurs cost and latency proportional to email size and count
• HTML extraction is robust for typical Gmail structures but may need tweaks for exotic MIME layouts

Privacy and safety

• Emails are sent to OpenAI for summarization—ensure that’s acceptable for your data policies
• The Telegram Trigger restricts chat access; keep your chatIds locked down
• Avoid sending raw HTML to Telegram; rely on the Sanitize node

Sample output format (Telegram)

1. Bold topic title

One-sentence description

Original Subject Line → Sender Name — DD.MM.YYYY

1. Next topic title

...

Tips and troubleshooting

• Got empty digests? Check Gmail filters.q and make sure there really are emails after the computed date
• Model errors or empty JSON? Lower prompt complexity or switch model
• HTML formatting issues in Telegram? Ensure parse_mode=HTML and keep only <b>, <i>
• Long messages not fully delivered? Reduce chunk size from 3 500

Tags

• gmail, telegram, openai, llm, newsletters, digest, summarization, automation

Changelog

• v1: Initial release with sender filters, topic merging, Telegram HTML sanitization, and on-demand time window via Telegram message