Prompt to image workflow
Use an LLM to prepare better prompts before image generation.
- 1Generate an image prompt with an LLM
- 2Send the prompt to an image model
- 3Create variations
- 4Collect the generated images
AI-Flow
Connect AI Models
Connect one AI model's output to the next model's input so text, image, audio, and document steps work together.
Nano Banana 2
Google
GPT Image 2
OpenAI
Claude Sonnet 4.6
Anthropic
“Subtle fashion film. Woman wearing tortoiseshell sunglasses, slight confident head turn, warm studio light gliding across the lenses. Hair moves gently. Slow motion, luxury campaign feel. No background change, keep studio setting.”
Seedance 2
ByteDance
Flux 2 Max
Replicate
Nano Banana 2Google
GPT Image 2OpenAI
Claude Sonnet 4.6Anthropic
“Subtle fashion film. Woman wearing tortoiseshell sunglasses, slight confident head turn, warm studio light gliding across the lenses. Hair moves gently. Slow motion, luxury campaign feel. No background change, keep studio setting.”
Seedance 2ByteDance
Flux 2 MaxReplicate
Move outputs into the next AI step
Build the practical output-to-input connections that turn separate AI calls into a useful workflow.Connect output to input
Take the result of one model and pass it directly into the next step: text to image, audio to summary, analysis to generation, or variations to export.
- GPT
- Claude
- Gemini
- GPT
- Claude
- Gemini
Keep data moving through the workflow
Use each node's result as structured context for the next node, then display, download, or send the final output through an API endpoint.
Output-to-input workflow examples
Practical workflows with clear inputs, model steps, and final outputs.
Audio repurposing workflow
Turn spoken content into publishable written assets.
- 1Transcribe audio
- 2Summarize the transcript
- 3Create social posts
- 4Export the final copy
Product image workflow
Use image understanding before generating new commercial visuals.
- 1Analyze a product image
- 2Generate commercial scene prompts
- 3Create product shots
- 4Select and export results
Variation workflow
Create many outputs, then keep only the ones that matter.
- 1Create content variations
- 2Collect model outputs
- 3Compare results
- 4Display or export the winners
Related workflow pages
Frequently Asked Questions
What does it mean to connect AI models?
It means using one model's output as the next model's input, such as sending an LLM-generated image prompt into an image model.
Can I connect text, image, and audio models?
Yes. You can chain text, image, audio, video, and utility nodes depending on what your workflow needs to produce.
Can I transform output before sending it to another model?
Yes. You can add steps that summarize, rewrite, format, or otherwise prepare an output before passing it into the next node.
Can I collect results from several model steps?
Yes. You can create variations, compare outputs, and display or export the final selected results from your workflow.
Do I need custom code to connect models?
No. AI-FLOW is designed so you can connect model outputs and inputs visually on the workflow canvas.