AI image generator from text built on fal.ai

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

Who this template is for This template is for developers, content creators, or application builders who want to integrate an AI powered text to image generation service into their applications or s...

Best for

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

Tools used

n8n-nodes-base.webhook, n8n-nodes-base.httprequest, n8n-nodes-base.wait, n8n-nodes-base.if, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.respondtowebhook, @n8n/n8n-nodes-langchain.textclassifier, n8n-nodes-base.stickynote

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: AI image generator from text built on fal.ai
Workflow name: AI image generator from text built on fal.ai

Who this template is for

This template is for developers, content creators, or application builders who want to integrate an AI-powered text-to-image generation service into their applications or systems via an API endpoint.

Use case

Creating a secure API endpoint that converts text prompts into AI-generated images, with built-in content moderation to prevent inappropriate content generation. This can be used for creative applications, content creation tools, prototyping interfaces, or any system that needs on-demand image generation.

How this workflow works

Receives text prompt through a webhook endpoint
Filters the prompt for inappropriate content using AI moderation
Submits valid prompts to the Fal.ai Flux image generation service
Polls for completion status and retrieves the generated image when ready
Returns the image results in a structured JSON format to the client

Set up steps

Create a Fal.ai account and obtain API credentials
Configure the HTTP Header Auth credentials with your Fal.ai API key
Set up an OpenAI API key for the content moderation component
Deploy the workflow and note the webhook URL for your API endpoint
Test the endpoint by sending a POST request with a JSON body containing a "prompt" field

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 - Webhook

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

Block 2 - Fetch Status

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

Block 3 - Wait

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

Block 4 - Is Ready?

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 5 - Submit Request

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

Block 6 - Fetch Result

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

Block 7 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.1

Block 8 - 400 Error

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

Block 9 - Success

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

Block 10 - Content Safety Filter

Type / Role: @n8n/n8n-nodes-langchain.textClassifier - textClassifier
Config choices: Version 1

Block 11 - Sticky Note1

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

Block 12 - Sticky Note2

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

3. Summary Table

Workflow	AI image generator from text built on fal.ai
Complexity	intermediate
Nodes	12
Categories	Content Creation, Multimodal AI
Author	n8n Team
Published	16 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4108/4108.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 AI image generator from text built on fal.ai 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.

n8n Team

90 workflows

Nodes

n8n-nodes-base.webhook n8n-nodes-base.httprequest n8n-nodes-base.wait n8n-nodes-base.if @n8n/n8n-nodes-langchain.lmchatopenai n8n-nodes-base.respondtowebhook @n8n/n8n-nodes-langchain.textclassifier n8n-nodes-base.stickynote

Complexity

intermediate

Published 16 May 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/4108/4108.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.

AI image generator from text built on fal.ai

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Who this template is for

Use case

How this workflow works

Set up steps

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Webhook

Block 2 - Fetch Status

Block 3 - Wait

Block 4 - Is Ready?

Block 5 - Submit Request

Block 6 - Fetch Result

Block 7 - OpenAI Chat Model

Block 8 - 400 Error

Block 9 - Success

Block 10 - Content Safety Filter

Block 11 - Sticky Note1

Block 12 - Sticky Note2

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