ManualTrigger Automate

For ManualTrigger Automate, this workflow enables users to effortlessly generate AI-driven captions for images. By integrating LangChain and EditImage, it automatically resizes images, creates captions, and overlays them, enhancing visual content for publications or branding. This streamlined process saves time and improves the quality of image presentations.

7/8/2025
16 nodes
Complex
manualcomplexlangchaineditimagesticky noteadvancedapiintegration
Categories:
Complex WorkflowManual TriggeredCreative Design Automation
Integrations:
LangChainEditImageSticky Note

Target Audience

Target Audience


- Content Creators: Individuals who create visual content and need captions to enhance engagement.
- Marketers: Professionals looking to automate image captioning for social media and advertising campaigns.
- Developers: Those interested in integrating AI-driven image processing into their applications.
- Researchers: Academics studying AI applications in multimedia.
- Small Business Owners: Owners who want to improve their online presence with visually appealing content.

Problem Solved

Problem Solved


This workflow addresses the challenge of generating captions for images automatically. It utilizes advanced AI models to create relevant and engaging captions based on the content of the image. This is particularly useful for:
- Time Efficiency: Reduces the manual effort of caption writing.
- Consistency: Ensures a uniform style and tone across multiple images.
- Creativity: Leverages AI to generate unique captions that may not have been considered manually.

Workflow Steps

Workflow Steps


1. Manual Trigger: The workflow begins when the user clicks the ‘Test workflow’ button.
2. Get Image: An image is fetched from a specified URL (e.g., a stock photo from Pexels).
3. Resize Image: The image is resized to 512 x 512 pixels to optimize it for AI processing.
4. Get Image Information: Metadata about the image is retrieved to assist in caption generation.
5. Image Captioning: The resized image is sent to an AI model (Google Gemini) to generate a caption.
6. Structured Output Parser: The output from the AI is structured to extract the caption title and text.
7. Calculate Positioning: A code node calculates the optimal position for overlaying the caption on the image.
8. Merge Caption & Positions: The caption data and calculated positions are merged for the next step.
9. Apply Caption to Image: The caption is overlaid onto the image using the Edit Image node.
10. Output: The final image with the caption is produced, ready for use.

Customization Guide

Customization Guide


- Change Image Source: Modify the URL in the ‘Get Image’ node to use different images.
- Adjust AI Model: You can switch to a different AI model in the ‘Google Gemini Chat Model’ node by changing the modelName parameter.
- Edit Caption Style: Customize the caption style and formatting in the ‘Apply Caption to Image’ node to match your branding.
- Add Additional Processing: Insert more nodes to perform additional image processing tasks, such as filters or effects, before applying the caption.
- Modify Trigger: Instead of a manual trigger, integrate a webhook or other event-based triggers to automate the workflow further.