information edit image and resize edit image and multistep edit image
Configured with Chain LLM, Edit Image, HTTP Request, LM Chat Google Gemini, and additional nodes. Review the connections and setup before adapting this template.
Node categories in this workflow
- Trigger
- AI & models
- Transform
- Files / media
- Code
- Web / API
Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.
Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.
How it works
The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.
| Node | Category | Type | Operation |
|---|---|---|---|
| When clicking ‘Test workflow’ | Trigger | Manual Trigger | See node parameters |
| Google Gemini Chat Model | AI & models | LM Chat Google Gemini | See node parameters |
| Structured Output Parser | Transform | Output Parser Structured | See node parameters |
| Get Info | Files / media | Edit Image | information |
| Resize For AI | Files / media | Edit Image | resize |
| Calculate Positioning | Code | Code | See node parameters |
| Apply Caption to Image | Files / media | Edit Image | multiStep |
| Merge Image & Caption | Transform | Merge | See node parameters |
| Merge Caption & Positions | Transform | Merge | See node parameters |
| Get Image | Web / API | HTTP Request | See node parameters |
| Image Captioning Agent | AI & models | Chain LLM | See node parameters |
Setup
- Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
- Connect your own credentials through n8n’s credential store. Replace
REPLACE_WITH_*values with your resource identifiers. - Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
- Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.
Requirements
An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.
Credential types declared in the source
googlePalmApi
Workflow notes
Try it out!
Try it out!
This workflow takes an image and generates a caption for it using AI. The OpenAI node has been able to do this for a while but this workflow demonstrates how to achieve the same with other multimodal vision models such as Google's Gemini.
Additional, we'll use the Edit Image node to overlay the generated caption onto the image. This can be useful for publications or can be repurposed for copyrights and/or watermarks.
Need Help?
1. Import an Image
1. Import an Image
Read more about the HTTP request node
For this demonstration, we'll grab an image off Pexels.com - a popular free stock photography site - by using the HTTP request node to download.
In your own workflows, this can be replaces by other triggers such as webhooks.
2. Using Vision Model to Generate Caption
2. Using Vision Model to Generate Caption
Learn more about the Basic LLM Chain
n8n's basic LLM node supports multimodal input by allowing you to specify either a binary or an image url to send to a compatible LLM. This makes it easy to start utilising this powerful feature for visual classification or OCR tasks which have previously depended on more dedicated OCR models.
Here, we've simply passed our image binary as a "user message" option, asking the LLM to help us generate a caption title and text which is appropriate for the given subject. Once generated, we'll pass this text along with the image to combine them both.
3. Overlay Caption on Image
3. Overlay Caption on Image
Read more about the Edit Image node
Finally, we’ll perform some basic calculations to place the generated caption onto the image. With n8n's user-friendly image editing features, this can be done entirely within the workflow!
The Code node tool is ideal for these types of calculations and is used here to position the caption at the bottom of the image. To create the overlay, the Edit Image node enables us to insert text onto the image, which we’ll use to add the generated caption.
Sticky Note4
FIG 1. Example input image with AI generated caption
information edit image and resize edit image and multistep edit image
information edit image and resize edit image and multistep edit image
Purpose and structure
This folder contains the information edit image and resize edit image and multistep edit image workflow. Its executable nodes use chainLlm, code, editImage, httpRequest, lmChatGoogleGemini, manualTrigger, merge, outputParserStructured. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.
Setup
Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.
Entry points
When clicking ‘Test workflow’
Verification
Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.
Attribution
https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Code/0577_Code_Editimage_Update_Webhook.json MIT; preserve source notices.