Nano banana AI image editor via Telegram

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Nano Banana AI Image Editor Transform your Telegram photos with AI powered image processing using the revolutionary Nano Banana technology. This workflow automatically receives photos via Telegram,...

Best for

Content Creation automation workflows
Multimodal AI automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.telegramtrigger, n8n-nodes-base.telegram, n8n-nodes-base.extractfromfile, n8n-nodes-base.code, n8n-nodes-base.set, n8n-nodes-base.converttofile, n8n-nodes-base.stickynote, n8n-nodes-base.httprequest

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Roshan Ramani.

Original n8n.io source

1.1 Workflow description

Title: Nano banana AI image editor via Telegram
Workflow name: Nano banana AI image editor via Telegram

Nano Banana AI Image Editor

Transform your Telegram photos with AI-powered image processing using the revolutionary Nano Banana technology. This workflow automatically receives photos via Telegram, processes them through Google's advanced Gemini 2.5 Flash vision model, and sends back intelligently enhanced images - all powered by the innovative Nano Banana processing pipeline.

Who's it for

Perfect for content creators, social media managers, photographers, and anyone who wants to automatically enhance their Telegram photos with AI. Whether you're running a photo editing service, creating content for clients, or just want smarter image processing in your personal chats, the Nano Banana AI editor delivers professional-grade results.

How it works

The Nano Banana workflow creates an intelligent Telegram bot that processes images in real-time. When you send a photo with a caption to your bot, it automatically downloads the image, converts it to the proper format, sends it to Google's Gemini AI for analysis and enhancement, then returns the processed result. The Nano Banana engine optimizes every step for speed and quality.

How to set up

Create Telegram Bot: Get your bot token from @BotFather on Telegram
OpenRouter Account: Sign up at openrouter.ai for free Gemini access
Configure Credentials: Add your Telegram and OpenRouter API keys to n8n
Update Chat ID: Replace "YOUR_CHAT_ID_HERE" with your actual Telegram chat ID
Activate Webhook: Enable the Telegram trigger to start receiving messages

Requirements

n8n instance (cloud or self-hosted)
Telegram Bot API credentials
OpenRouter account (free tier available)
Basic understanding of webhook configuration

How to customize the workflow

The Nano Banana editor is highly customizable:

Change AI Model: Modify the model parameter in "Nano Banana Image Processor" node
Add Filters: Insert additional processing nodes before the AI analysis
Custom Prompts: Edit the text content sent to Gemini for different processing styles
Multiple Chats: Duplicate the final node for different Telegram destinations
Error Handling: Add conditional logic for failed processing attempts
Batch Processing: Extend to handle multiple images simultaneously

The Nano Banana technology ensures optimal performance while maintaining flexibility for your specific use cases.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Photo Message Receiver

Type / Role: n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices: Version 1.2

Block 2 - Download Telegram Photo

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 3 - Convert Photo to Base64

Type / Role: n8n-nodes-base.extractFromFile - extractFromFile
Config choices: Version 1

Block 4 - Format Image Data URL

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 5 - Parse AI Response Data

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 6 - Base64 to Binary File

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 7 - Send Processed Photo

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 8 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 9 - Nano Banana Image Processor

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

3. Summary Table

Workflow	Nano banana AI image editor via Telegram
Complexity	intermediate
Nodes	9
Categories	Content Creation, Multimodal AI
Author	Roshan Ramani
Published	31 Aug 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/8082/8082.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Content Creation workflows Multimodal AI workflows

Frequently asked questions

What does Nano banana AI image editor via Telegram do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Content Creation, Multimodal AI use case.

Roshan Ramani

27 workflows

Nodes

n8n-nodes-base.telegramtrigger n8n-nodes-base.telegram n8n-nodes-base.extractfromfile n8n-nodes-base.code n8n-nodes-base.set n8n-nodes-base.converttofile n8n-nodes-base.stickynote n8n-nodes-base.httprequest

Complexity

intermediate

Published 31 Aug 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/8082/8082.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Send daily LinkedIn post drafts with Tavily, Groq Llama 3.3 and Gmail

## Quick overview This workflow runs daily at 8 AM to rotate through a topic list, research it with Tavily web search, generate a LinkedIn post and image prompt with Groq (Llama 3.3 70B), create a Pollinations.ai image URL, and email you the post with the image attached via Gmail. ## How it works 1. Runs every day at 8:00 AM on a schedule. 2. Selects today’s topic from a rotating list based on the day of the year. 3. Searches the web with Tavily to fetch up-to-date results for the selected topic. 4. Uses a Groq-hosted Llama model to write a LinkedIn post and a matching image prompt grounded in the Tavily results. 5. Builds a Pollinations.ai image generation URL from the image prompt and downloads the generated image file. 6. Emails the post text with the image attached via Gmail, and sends a text-only fallback email if image generation or download fails. ## Setup 1. Add a Groq API credential to the Groq Chat Model node. 2. Create a Tavily API key and configure HTTP Header Auth with `Authorization: Bearer <YOUR_TAVILY_KEY>` for the Tavily Search request. 3. Connect a Gmail OAuth2 credential and update the recipient email address in both Gmail send steps. 4. Edit the topic list in the topic-selection code step if you want different rotating themes. ## Requirements - Groq API key (free tier available) - Tavily API key (free tier — 1,000 searches/month) - Gmail account (OAuth2) ## Customization - Edit the topic list inside the "Pick Today's Topic" code node to change what subjects the post rotates through. - Change the Groq model in the "Groq Chat Model" node if you want a different LLM (e.g. a smaller/faster or larger Groq model). - Adjust the schedule trigger if you want a different posting time, or swap the Gmail "send to" address to deliver the draft to someone else for review. ## Additional info This workflow emails you a draft for manual review before posting — it does not post to LinkedIn automatically. If image generation fails, a text-only fallback email is sent instead so you never miss the post text.

View

Generate VEO3 videos from form ideas with ChatGPT, fal.ai, Drive and Gmail

## Quick overview This workflow collects a video idea via an n8n Form, uses OpenAI to turn it into an optimized prompt, generates an 8-second VEO3 video with native audio via fal.ai, saves the MP4 to Google Drive, and emails the Drive link via Gmail. ## How it works 1. Receives a submission from an n8n Form with the requester’s email, a plain-English video idea, and a selected style. 2. Uses OpenAI (via an AI Agent) to convert the idea and style into a structured VEO3 title and detailed prompt returned as JSON. 3. Cleans and parses the AI JSON, creates a filename-safe title, and sets the generation parameters to 16:9 and 8 seconds. 4. Submits the prompt to fal.ai’s queue endpoint for the fal-ai/veo3 model and gets a request ID. 5. Polls fal.ai every 30 seconds until the job status returns COMPLETED. 6. Retrieves the final MP4 URL from fal.ai, downloads the video, uploads it to Google Drive, and emails the Google Drive web link to the requester via Gmail. ## Setup 1. Create a fal.ai account, generate an API key, and replace `YOUR_FAL_AI_API_KEY` in the fal.ai HTTP request headers. 2. Add an OpenAI API credential in the OpenAI Chat Model node and select the model you want to use. 3. Connect Google Drive OAuth2 and replace `YOUR_GDRIVE_FOLDER_ID` with the target folder ID where videos should be saved. 4. Connect Gmail OAuth2 for sending emails, then activate the workflow and use the Form URL (path `veo3-video-generator`) to submit requests.

View

Generate presentation decks from prompts with Encelade

## Quick overview This workflow starts a presentation generation job in Encelade from a prompt and outline hints, polls Encelade for completion, and outputs the finished deck link (or stops with an error if generation fails). ## How it works 1. Starts when you manually execute the workflow in n8n. 2. Sends the topic, slide count, audience, tone, theme settings, and outline hints to Encelade to generate a 6-slide presentation. 3. Waits 20 seconds and then checks the Encelade session status using the returned session ID. 4. If the session phase is not finished, it keeps waiting and rechecking until the phase changes. 5. When the phase is "done", it returns the generated deck link and project PID. 6. When the phase is "failed", it stops the workflow and raises an error with the failure details. ## Setup 1. Install and configure Encelade credentials in n8n for the Encelade node. 2. Update the generation inputs (topic, page count, outline hints, audience/tone, theme mode, and media provider) to match the deck you want to create. 3. Ensure the workflow has enough time to complete by adjusting the 20-second wait interval if your Encelade generations typically take longer.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Nano banana AI image editor via Telegram

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Nano Banana AI Image Editor

Who's it for

How it works

How to set up

Requirements

How to customize the workflow

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Photo Message Receiver

Block 2 - Download Telegram Photo

Block 3 - Convert Photo to Base64

Block 4 - Format Image Data URL

Block 5 - Parse AI Response Data

Block 6 - Base64 to Binary File

Block 7 - Send Processed Photo

Block 8 - Sticky Note

Block 9 - Nano Banana Image Processor

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions