Mindket

OpenAI chat examples: summary, German, SVG and quick replies

Newversion 1 · updated

Overview

An n8n workflow with five small examples of calling OpenAI chat models on one sample text. It summarises, translates to German, writes an image prompt, asks for SVG code and drafts quick replies.

OpenAI chat examples: summary, German, SVG and quick replies is an n8n workflow in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in
  • n8n Cloud: import the file there and run a branch
  • Your own n8n server: the same file and steps
  • The audio branch: only on a machine where n8n can read your audio file
  • Your own flows: copy a branch into them

Platform

Connects 1 app

How it works

Trigger

Manual start

It starts when you run a branch by hand in n8n. Each branch works on the same sample text:

  • The sample text in the Code node Text-example
  • An audio file, in the switched off branch

Actions

  1. A chat model writes a summary, and a second call translates it to German
  2. A system message makes the model add five emojis to its answer
  3. A list of messages goes to the chat endpoint through an HTTP Request node, and the answer becomes a prompt for a cover image
  4. The model writes HTML with an SVG, and the HTML is rendered
  5. The model drafts three short replies to a sample email

Result

Five examples of OpenAI chat calls, each with its answer in the node’s output

Integrations

What you need before you start.

OpenAI

Language model

Answers every example call, and transcribes the audio branch when it is switched on.

NeedsOpenAI API key with access to gpt-5.6-terra

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
14 steps, starting by hand
AI
6 steps call an AI model: ChatGPT-ex1.1, ChatGPT-ex1.2, ChatGPT-ex2, ChatGPT-ex3.2, ChatGPT-ex4 and 1 more
Sign-ins
Signs in to: OpenAI
API keys
No API key is left in the file
Step types
Mindket’s checker reads all 7 of its step types

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow is a sampler of five ways to call OpenAI’s chat models, all fed the same short text. It writes a summary and translates it, adds a system message, and sends a list of messages through the HTTP Request node. It also writes a prompt for a cover image, asks for SVG code and drafts three quick email replies. A sixth branch, switched off, transcribes an audio file. Fourteen nodes run it, beside nine sticky notes.

Who it suits

People who learn n8n’s OpenAI node by running it and builders who want a call pattern to copy. Skip it if you want one finished automation, since every branch is only an example. The original’s text completion, text edit and DALL-E 2 steps are gone, because those calls no longer exist.

Who uses it, and how
IndustryWho uses itHow they use itExample
EducationTrainersShow a class how each call style worksA trainer runs one branch at a time and compares the answers.
SoftwareDevelopersCopy a call pattern into their own flowA developer lifts the HTTP Request example into a flow of their own.
SupportSupport leadsTry short reply draftsA lead runs the quick replies branch on a customer message.
MarketingContent teamsTry summary and translation promptsA team turns a summary into German in two steps.

You need a little n8n: import a file, add one credential and run one branch at a time.

Where to use it

Any n8n that can reach OpenAI will run it. The answers show in each node’s output panel.

  • n8n Cloud: import the file there and run a branch
  • Your own n8n server: the same file and steps
  • The audio branch: only on a machine where n8n can read your audio file
  • Your own flows: copy a branch into them

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Setup takes one OpenAI credential, selected in seven nodes.

What you need first
NeedDetail
n8nOn n8n Cloud or on a server of your own
OpenAIAn API key with access to gpt-5.6-terra
Audio fileOnly for the switched off branch, in a folder n8n can read
  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. Add an OpenAI credential and select it in ChatGPT-ex1.1, ChatGPT-ex1.2, ChatGPT-ex2, ChatGPT-ex3.2, ChatGPT-ex4 and ChatGPT-ex. In the HTTP Request node ChatGPT-ex3.1, choose the OpenAI credential type and select the same one.
  3. Run one branch at a time: open its last node, such as ChatGPT-ex1.2, and execute it with its earlier nodes.
  4. For the audio branch, set your file’s path in LoadMP3, turn on LoadMP3 and Whisper-transcribe, and turn Text-example off.

How to use it

Run a branch and read each node’s output. The summary and the German text come from the first branch, the emoji answer from the second, and the image prompt from the third. The fourth branch gives SVG code and the fifth gives three short replies.

What to change for a different result
To changeWhere
The sample textThe Code node Text-example
The modelThe Model value in each OpenAI node and the model body parameter of ChatGPT-ex3.1
The instructionsThe system messages in ChatGPT-ex2, Code-ex3.1, ChatGPT-ex3.2 and ChatGPT-ex
How many replies the fifth branch draftsNumber of Completions in ChatGPT-ex

Example

A trainer opens the workflow in front of a class and runs ChatGPT-ex1.2. The first call turns the herb garden text into a short summary, and the second call turns the summary into German.

She then runs ChatGPT-ex2 and shows how a system message adds five emojis to the same summary. Last she runs ChatGPT-ex and the class reads three short replies to a sample email.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. Here every branch is one small lesson in how to ask a chat model for something. Start with the first branch and read its two prompts.

For experts. Six branches use n8n’s older OpenAI node, which n8n hides from its node list, and one calls the chat completions endpoint through an HTTP Request node.

Where to look closer
NodeWhat it doesWhat to know
ChatGPT-ex1.1 and ChatGPT-ex1.2Send only user messages, a summary and then a translationThe second reads message.content from the first
Code-ex3.1 and ChatGPT-ex3.1Build a list of system and user messages and send it as one requestThe body holds only model and messages
ChatGPT-ex4 and HTML-ex4Ask for HTML with an SVG and render itThe Set node Set-ex4 holds the prompt
ChatGPT-exDrafts replies with n set to 3Check that your model accepts a count above 1

Good to know

Most of the original’s OpenAI calls named models that OpenAI has retired, so this copy swaps the model and drops three nodes.

  • Cut: the text completion and text edit nodes on text-davinci-003, which OpenAI’s deprecations page, read on 12 November 2026, says shut down on 4 January 2024. The DALL-E 2 image node is cut too, since dall-e-2 was removed on 12 May 2026
  • Models: gpt-3.5-turbo-0301 shut down on 13 September 2024 and gpt-3.5-turbo on 23 October 2026, with gpt-5.6-terra as the replacement. All seven chat calls now name it
  • Settings dropped: the original’s token limits and temperatures, so each call uses the model’s own settings
  • The sample text: the original used a podcast transcript, and this copy has a short text of its own
  • Run one branch at a time: each is a separate call to OpenAI, and a note in the file says the whole workflow is slow
  • Audio: whisper-1 shuts down on 26 February 2027, and OpenAI names gpt-live-transcribe or gpt-transcribe as the replacement
  • Your data: the text goes to OpenAI
  • Credentials: the JSON holds none

README and files

README

OpenAI chat examples: summary, German, SVG and quick replies

An n8n workflow with five small examples of calling OpenAI's chat models, all fed the same short sample text. It
summarises the text and translates the summary. It adds a system message and sends a list of messages through the HTTP
Request node. It also writes a prompt for a cover image, asks for SVG code and drafts quick email replies. A sixth branch,
switched off, transcribes an audio file.

What is inside

  • workflow.json: the workflow as n8n exports it, twenty-three nodes: fourteen that do the work and nine sticky notes.
    It holds no credential.
  • README.md: these notes.

What we changed from the original copy

  • The credential links are gone. Select your own OpenAI account.
  • The original opened with a branch that used OpenAI's text completion and text edit calls on text-davinci-003. OpenAI's
    deprecations page, read on 12 November 2026, says that model and the /v1/edits endpoint shut down on 4 January 2024,
    and it names no edit replacement apart from chat completions. Mindket's copy drops those two nodes and the note that
    introduced them.
  • The last step of the third example made four pictures with DALL-E 2. The same page says dall-e-2 and dall-e-3 were
    removed on 12 May 2026. That node is gone too, and the example now ends with the written picture prompt.
  • Every chat node named gpt-3.5-turbo-0301, or named nothing and took the node's default, gpt-3.5-turbo. The first shut down
    on 13 September 2024. The second shut down on 23 October 2026, and OpenAI names gpt-5.6-terra as its replacement.
    All seven now name gpt-5.6-terra.
  • The original also set a token limit and a temperature on several chat nodes. Mindket's copy drops both, so each call uses
    the model's own settings. The fifth example still asks for three replies.
  • The example text was a transcript of a podcast episode. It is now a short text of our own about herbs in a window box.
  • The sample audio path now reads YOUR_AUDIO_FILE.mp3.
  • Three typos in the prompts, "wollowing", "followint" and "promt", are corrected.
  • Nothing else.

Before you start

  • An n8n instance, on n8n Cloud or your own server.
  • An OpenAI API key.
  • For the audio branch only: an audio file on the machine that runs n8n, in a folder n8n can read.

Set it up

  1. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
  2. Add an OpenAI credential. Select it in the six OpenAI nodes ChatGPT-ex1.1, ChatGPT-ex1.2, ChatGPT-ex2,
    ChatGPT-ex3.2, ChatGPT-ex4 and ChatGPT-ex. In ChatGPT-ex3.1, the HTTP Request node, choose the OpenAI
    credential type and select the same one.
  3. Open the last node of a branch, such as ChatGPT-ex1.2, and execute it with its earlier nodes. Do one branch, then
    the next.
  4. For the audio branch, set the path of your file in LoadMP3 and turn on LoadMP3 and Whisper-transcribe. Turn
    Text-example off so the transcript passes through. Read the note on whisper-1 below before you rely on this branch.

How a run goes

When clicking "Execute Workflow" starts the example branches. Each one reads the sample text from Text-example, or
carries its own.

  1. Example 1: ChatGPT-ex1.1 writes a summary and ChatGPT-ex1.2 translates it to German. Only user messages are sent.
  2. Example 2: ChatGPT-ex2 sends a system message that asks for five emojis at the end, then the user message.
  3. Example 3: Code-ex3.1 builds the list of system and user messages. ChatGPT-ex3.1 sends it through the HTTP Request
    node, and ChatGPT-ex3.2 turns the answer into the image prompt.
  4. Example 4: Set-ex4 holds a prompt that asks for HTML with an SVG. ChatGPT-ex4 answers and HTML-ex4 renders the code.
  5. Example 5: ChatGPT-ex drafts three short replies to an email, five to eight words each.
  6. Audio, switched off: LoadMP3 reads the file, and Whisper-transcribe sends it to the transcription call.

Change the look

  • The sample text: the Code node Text-example.
  • The model: the Model value in each OpenAI node and the model body parameter of ChatGPT-ex3.1.
  • The instructions: the system messages in ChatGPT-ex2, Code-ex3.1, ChatGPT-ex3.2 and ChatGPT-ex.
  • How many replies the fifth example drafts: Number of Completions in ChatGPT-ex.

Good to know

  • Each branch is a separate call to OpenAI, and a sticky note in the file warns that the whole workflow is slow.
  • Each OpenAI node here is n8n's older OpenAI node, which n8n hides from its node list. It still runs from this file.
  • The third example's HTTP Request node sends only model and messages. The original also set a temperature, a token
    limit and a count of one, which are gone.
  • The fifth example keeps its request for three replies. Check that your model accepts it, and set the count to 1 if it
    does not.
  • whisper-1 shuts down on 26 February 2027, and OpenAI's deprecations page names gpt-live-transcribe or gpt-transcribe
    as the replacement.
  • The text goes to OpenAI.
  • The JSON holds no credential.
Files
NOTICE.md  616 B
README.md  5 KB
workflow.json  14 KB

3 files, 20 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

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