Automated AI Image Generation Workflow with n8n

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This n8n workflow automates the process of generating images using the Replicate API and a custom AI model, flux-schnell. Starting from a manual trigger, the workflow guides users through setting their API token, configuring image parameters, and initiating an image prediction request. It then intelligently monitors the prediction status, waiting for completion or failure, and provides a structured response with the final image URL or error details. Ideal for users who want to create AI-generated images efficiently, this workflow streamlines the entire process—from prompt input to image retrieval—making it suitable for content creators, designers, and developers seeking rapid visual content generation.

**Step-by-step process:**

1. The workflow begins with a manual trigger, allowing users to start the image creation process.

2. The API token for the Replicate service is set, ensuring authenticated access.

3. Image parameters such as prompt, seed, quality, and format are configured, either with defaults or custom inputs.

4. The workflow sends a POST request to the Replicate API to create an image prediction, providing all configured parameters.

5. It then waits for 5 seconds before checking the prediction status via a GET request.

6. The status is evaluated: if succeeded, it outputs the generated image URL; if failed, it handles the error gracefully.

7. For retries after failure, it waits an additional 10 seconds before rechecking.

8. The result, whether success or error, is displayed and logged for monitoring.

**Use cases:**

– Automated creation of AI-generated images for marketing content, social media, or personal projects.

– Integrating image generation into larger workflows for dynamic content updates.

– Rapid prototyping and visual brainstorming using AI images.

**Services integrated:**

– Replicate API for AI-based image synthesis.

– n8n for workflow automation, logging, and response handling.

This setup empowers users to generate bespoke images effortlessly, with built-in monitoring, error handling, and logging features for seamless operation.

Node Count

11 – 20 Nodes

Nodes Used

code, httpRequest, if, manualTrigger, set, stickyNote, wait

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