How to Generate and Send Dall-E 3 Images on Telegram with n8n

Why this workflow is so useful

Imagine chatting on Telegram and casually asking your bot, “Hey, can you draw a cyberpunk cat playing chess?” and a few seconds later, a shiny Dall-E 3 image pops up in your chat. Pretty cool, right?

That is exactly what this n8n workflow template helps you do. It connects Telegram, OpenAI GPT-4, and Dall-E 3 so your bot can:

• Understand what users are asking in plain language
• Reply with smart, natural messages
• Generate images with Dall-E 3 when someone asks for one
• Send those images back directly in the Telegram chat

You set it up once, and from then on your Telegram bot can act like a friendly AI assistant that both talks and draws on demand.

What this n8n template actually does

Under the hood, the workflow is split into two main parts that work together smoothly:

1. Chatting on Telegram and understanding requests

This part handles all the back-and-forth with your users. It:

• Listens for new messages on Telegram using a Telegram Trigger
• Passes those messages to an AI Agent powered by GPT-4
• Keeps track of recent chat history so replies feel natural and consistent
• Decides when the user is actually asking for an image, not just text
• Sends a text response back to the user on Telegram

2. Generating and sending Dall-E 3 images

When the AI agent realizes the user wants an image, it calls a separate part of the workflow that:

• Triggers an internal workflow dedicated to image generation
• Calls OpenAI’s /v1/images/generations endpoint with the Dall-E 3 model
• Grabs the generated image URL from the API response
• Sends that image as a photo message to the user on Telegram
• Adds a response field so the workflow can confirm the image was delivered successfully

The result is a fully automated loop: user asks, AI understands, image gets created, Telegram sends it back.

When should you use this template?

This workflow is perfect if you:

• Already have a Telegram bot or community and want to make it more interactive
• Want users to generate AI images without leaving Telegram
• Are building a creative assistant, art bot, or visual brainstorming tool
• Prefer a low-code approach using n8n instead of writing everything from scratch

If you have people asking for “visuals,” “mockups,” “concept art,” or “show me what this looks like,” this template saves you from manually creating and sending images every time.

Key components of the n8n workflow

Let’s walk through the main pieces so you know what each one is doing behind the scenes.

1. Telegram Trigger – listening for new messages

The workflow starts with a Telegram Trigger node. Its job is simple but crucial: it listens for incoming messages from your Telegram users.

Whenever someone sends a message to your bot, this trigger fires and kicks off the entire workflow. That is how your automation stays reactive and real-time.

2. AI Agent – the brain of the operation

The AI Agent is the central decision-maker. It is powered by GPT-4 and is responsible for:

• Analyzing what the user is saying
• Maintaining context using memory, so it does not forget what you said two messages ago
• Deciding whether to respond with text only or call the image generation tool

Think of it as the “personality” of your bot. It reads the conversation, understands when someone is asking for an image, and then delegates that job to the Dall-E 3 tool.

3. OpenAI Chat Model – GPT-4 configuration

Behind the AI Agent is the OpenAI Chat Model node, configured with GPT-4. In this template, it uses:

• Temperature: 0.7 for a good balance between creativity and reliability
• A frequency penalty to reduce repetitive answers

This setup helps your bot give responses that feel natural, informative, and not like it is repeating itself every time someone asks a similar question.

4. Window Buffer Memory – keeping the conversation flowing

To keep your bot from sounding forgetful, the workflow uses a Window Buffer Memory component.

It stores up to 10 recent messages in the conversation. That way, the AI Agent can see a bit of history and respond in a way that fits the ongoing chat, not just the last message in isolation.

For example, if a user says “Make it blue instead” right after requesting an image, the AI still knows what “it” refers to.

5. Dall-E 3 Tool – the image specialist

The Dall-E 3 Tool is a dedicated interface between the AI Agent and the image generation workflow.

Instead of the AI directly calling the OpenAI image API, it uses this tool as a bridge. The tool receives the prompt from the AI Agent and then hands it off to the image generation part of the workflow.

This keeps things modular and easier to maintain or extend later.

6. Execute Workflow Trigger & Image Generation

When the AI Agent decides an image is needed, it activates an Execute Workflow Trigger node that starts the nested image generation workflow.

In that nested workflow, n8n makes a request to:

/v1/images/generations

using the Dall-E 3 model.

The user’s prompt is passed along to this endpoint, Dall-E 3 generates an image based on the description, and the workflow retrieves the resulting image URL.

7. Sending the image back on Telegram

Once the image URL is available, another Telegram node kicks in to send the image as a photo message directly to the user.

So from the user’s perspective, they just asked for an image and received it right in the same chat. No extra links, no switching apps.

8. Error handling – fixing message delivery issues

Things are not always perfect, so the workflow also includes an error correction step.

If there is an issue sending the initial message or image, this node tries to correct the problem and resend. That way, your users are less likely to see failures or broken responses, and the overall experience stays smooth.

Why this integration makes your life easier

So why go through the trouble of setting this up in n8n instead of wiring everything manually?

• Fully automated, yet interactive
  The AI Agent handles both text and image requests, so you are not stuck manually responding or generating images yourself.
• Context-aware conversations
  Thanks to the memory buffer, your bot can respond in a way that feels more human, remembering what was said earlier in the chat.
• Rich media in Telegram
  You are not limited to plain text. Users can receive AI-generated images directly inside Telegram, which makes your bot feel much more engaging.
• Scalable and modular setup
  Because everything is built in n8n, you can easily:
  • Add more tools for different tasks
  • Adjust prompts, memory length, or model settings without rewriting code

Getting started with the template

If you are ready to give your Telegram bot some visual superpowers, this template is a great starting point. You can import it into n8n, plug in your OpenAI and Telegram credentials, and then tweak the prompts and behavior to match your use case.

From there, you can experiment with different prompts, styles, or additional tools to make your AI assistant even smarter and more creative.

Try the n8n template for Dall-E 3 images on Telegram

Want to see it in action and start customizing it for your own bot?

Use this ready-made n8n workflow template to connect GPT-4, Dall-E 3, and Telegram, and start sending AI-generated images in your chats with almost no manual work.