On-Demand Email Newsletter Summaries from Gmail to Telegram with GPT-4.1-mini

Description

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

2) 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

3) 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)

4) Safety and formatting
Keep parse_mode=HTML in Telegram
The Sanitize node is designed for ` and ` 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)
Bold topic title

One-sentence description

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

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 `, `
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