Generate UGC videos from product images with GPT-4, Fal.ai & KIE.ai via Telegram
Ready for 3.0What this workflow does
This AI workflow has 22 nodes and runs on Telegram events (message). Along the way it connects Telegram, OpenAI and OpenAI Chat Model. It also calls queue.fal.run and api.kie.ai over HTTP.
How it runs
Trigger: On Telegram events (message).
- Botid (Edit Fields (Set)): sets 1 field: bot id
- Image Pqath (HTTP Request): calls an HTTP API
- Analyze image (OpenAI): analyze (image)
- Image Prompt (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Think)
- Create Image (HTTP Request): calls queue.fal.run (POST)
- Wait: waits 30 seconds
- Get the Image (HTTP Request): calls an HTTP API
- Video Prompt (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Think); output parser: Structured Output Parser
- Send a photo message (Telegram): send photo
- Split Out: splits a list into separate items
…plus 8 more steps. See the full node list below.
Services it uses
HTTP calls to: queue.fal.run, api.kie.ai
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (12)
- Telegram Trigger
n8n-nodes-base.telegramTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - OpenAI
@n8n/n8n-nodes-langchain.openAi - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Think Tool
@n8n/n8n-nodes-langchain.toolThink - Wait
n8n-nodes-base.wait - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Split Out
n8n-nodes-base.splitOut - Aggregate
n8n-nodes-base.aggregate - Telegram
n8n-nodes-base.telegram
From the author
Transform any product image into engaging UGC (User-Generated Content) videos and images using AI automation. This comprehensive workflow analyzes uploaded images via Telegram, generates realistic product images, and creates authentic UGC-style videos with…