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Use the RunComfy Postman collection to discover models, run ComfyUI workflows, generate images and videos, and manage AI Toolkit LoRA training. It includes 20 requests across account and model discovery, Model API, ComfyUI workflow API, and Trainer API.

Open the public Postman workspace

Fork the collection into your own Postman workspace.

Read the Postman documentation

Browse request examples and their configuration instructions.

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Download and import

Download the collection JSON and environment JSON. In Postman, select Import, choose both files, and select RunComfy — local values only as the active environment. Get an API token from your RunComfy Profile. Set runcomfy_api_token in your private/local environment values. The download contains no API token or account-specific request, deployment, dataset, or training job IDs. Keep shared credential values empty.

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Start with a read-only request

Run Search models, Get model input schema, or List ComfyUI deployments to check your setup. Use model_search to find a supported family such as Seedance, Wan, FLUX, LTX, or Seedream. Inspect the exact model ID, price, and input schema before configuring a request. The default model example edits an image with FLUX.1 Kontext Pro. Other AI image models and AI video models have their own inputs; select a current model ID and build model_input_json from its schema. See the Model API quickstart and current models.

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Submit once, then check status and results

Paid inference and training requests are disabled by default. Review the selected model or deployment, inputs, and price, then set allow_paid_requests to true locally when you are ready to send one request. After a successful submission, the response script saves its returned ID in the selected environment for the matching status and result requests. Poll status until the request completes, then retrieve its results. Re-sending a submission starts another job and can incur another charge. Dataset creation and uploads are separate requests and do not use the paid-request switch. For ComfyUI, choose an existing deployment and inspect its stored payload before setting workflow overrides. These examples use the current v2 workflow endpoints. For LoRA training, upload matching media and captions, wait for the dataset to be READY, and supply a complete reviewed AI Toolkit YAML configuration and supported GPU type. A STOPPED status alone does not prove training completed; inspect its progress and result artifacts. See the Trainer API quickstart.