Transform Selfies into Professional LinkedIn Headshots with Nano Banana Pro & Telegram

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Built by Davide Boizza Davide Boizza
Created on June 05, 2026

Description

This workflow automates the process of transforming user-submitted photos (also bad selfie) into professional CV and LinkedIn headshots using the Nano Banana Pro AI model.

| From selfie | To CV/Linkedin Headshot |
|:----------------:|:-----------------------------------------:|
| | |

Key Advantages

1. ✅ Fully Automated Professional Image Enhancement

From receiving a photo to delivering a polished LinkedIn-style headshot, the workflow requires zero manual intervention.

2. ✅ Seamless Telegram Integration

Users can simply send a picture via Telegram—no need to log into dashboards or upload images manually.

3. ✅ Secure Access Control

Only the authorized Telegram user can trigger the workflow, preventing unauthorized usage.

4. ✅ Reliable API Handling with Auto-Polling

The workflow includes a robust status-checking mechanism that:

Waits for the Fal.ai model to finish
Automatically retries until the result is ready
Minimizes the chance of failures or partial results

5. ✅ Flexible Input Options

You can run the workflow either:

Via Telegram
Or manually by setting the image URL if no FTP space is available

This makes it usable in multiple environments.

6. ✅ Dual Storage Output (Google Drive + FTP)

Processed images are automatically stored in:

Google Drive (organized and timestamped)
FTP (ideal for websites, CDN delivery, or automated systems)

7. ✅ Clean and Professional Output

Thanks to detailed prompt engineering, the workflow consistently produces:

Realistic headshots
Studio-style lighting
Clean backgrounds
Professional attire adjustments

Perfect for LinkedIn, CVs, or corporate profiles.

8. ✅ Modular and Easy to Customize

Each step is isolated and can be modified:

Change the prompt
Replace the storage destination
Add extra validation
Modify resolution or output formats

How It Works

The workflow supports two input methods:

Telegram Trigger Path: Users can send photos via Telegram, which are then processed through FTP upload and transformed into professional headshots.

Manual Trigger Path: Users can manually trigger the workflow with an image URL, bypassing the Telegram/FTP steps for direct processing.

The core process involves:
Receiving an input image (from Telegram or manual URL)
Sending the image to Fal.ai's Nano Banana Pro API with specific prompts for professional headshot transformation
Polling the API for completion status
Downloading the generated image and uploading it to both Google Drive and FTP storage
Using a conditional check to ensure processing is complete before downloading results

Set Up Steps
Authorization Setup:
Replace in the "Sanitaze" node with your actual Telegram user ID
Configure Fal.ai API key in the "Create Image" node (Header Auth: Authorization: Key YOURAPIKEY)
Set up Google Drive and FTP credentials in their respective nodes

Storage Configuration:
In the "Set FTP params" node, configure:
ftp_path: Your server directory path (e.g., /public_html/images/)
base_url: Corresponding base URL (e.g., https://website.com/images/)
Configure Google Drive folder ID in the "Upload Image" node

Input Method Selection:
For Telegram usage: Ensure Telegram bot is properly configured
For manual usage: Set the image URL in the "Fix Image Url" node or use the manual trigger

API Endpoints:
Ensure all Fal.ai API endpoints are correctly configured in the HTTP Request nodes for creating images, checking status, and retrieving results

File Naming:
Generated files use timestamp-based naming: yyyyLLddHHmmss-filename.ext
Output format is set to PNG with 1K resolution

The workflow handles the complete pipeline from image submission through AI processing to storage distribution, with proper error handling and status checking throughout.

Need help customizing?
Contact me for consulting and support or add me on Linkedin.

Nodes Used (5)

Code
n8n-nodes-base.code
FTP
n8n-nodes-base.ftp
Google Drive
n8n-nodes-base.googleDrive
HTTP Request
n8n-nodes-base.httpRequest
Telegram
n8n-nodes-base.telegram