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The Chat action sends a single prompt to an OpenAI model. Use it for free-form text generation, questions about images or PDFs, web-assisted research, and responses that must match a JSON schema.
Chat is stateless: each run sends the current prompt, system prompt, and files. It does not remember earlier workflow runs or previous Chat actions.

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Quick start

1

Connect an OpenAI account

Add an OpenAI account when the node asks for a Third-party account. The account must contain a valid OpenAI API key.
2

Provide a prompt

Connect a string to Prompt, or set a fixed value on the node. Include all of the context the model needs for this run.
3

Choose a model

GPT-5.1 is selected by default. Standard models expose web search and temperature controls; reasoning models expose reasoning effort instead.
4

Use the response

Connect Response to the next action. If you enable structured output, connect properties from Structured Response instead.

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Inputs

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Model controls

Standard models support:
  • Web Search — Lets the model search the web before answering. Defaults to off.
  • Temperature — Controls how varied the response can be, from 0 (more focused) to 2 (more varied). Defaults to 1.
Available models:
  • GPT-5.1
  • GPT-5 Nano
  • GPT-5 Mini
  • GPT-5
  • GPT-4.1 Mini
  • GPT-4.1
  • GPT-4o Mini
  • GPT-4o
If model-specific controls disappear after you change models, the node has switched control sets. Standard and reasoning controls are mutually exclusive.

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Outputs

When Structured Output is off, the node has one output:

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Return structured data

Structured output is useful when later actions need predictable fields instead of prose. For example, this schema turns a support message into a summary, priority, and category:
1

Enable structured output

Turn on Structured Output. The JSON Schema input and Structured Response output appear, while the text Response output is removed.
2

Add the schema

Paste a valid JSON schema into JSON Schema. It must parse as JSON and contain an outer type of object with a properties map.
3

Expose the fields you need

Use Add detected properties to output on the node to add summary, priority, and category as connectable properties.
4

Connect downstream actions

Route priority into conditional logic, store category, or send summary in a notification without parsing a text response.
Enabling structured output changes the node’s output from Response to Structured Response. Check downstream connections when you toggle this setting on an existing workflow.

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Work with files

Add one Files item for each image or PDF the model should inspect. Every file is sent in the same user message as the prompt. Good prompts state what to do with the attachments:
When structured output is enabled, describe the expected fields in the schema instead of asking the model to invent a response format in the prompt.

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Example: triage a support request

Use Chat in the middle of a workflow to turn an incoming message into fields that other actions can route:
Configure the node with:
  • Prompt — The incoming subject and message body.
  • System Prompt — Classify the request using only the supplied message.
  • Structured Output — On.
  • JSON Schema — The support-triage schema above.
The routing action can use category directly, while notifications and logs can use summary and priority.

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Troubleshooting

Check that the value is valid JSON, the outer type is object, and properties is an object. JSON does not allow comments or trailing commas.
You selected a reasoning model. Choose a standard model to use Web Search or Temperature.
Structured Output is enabled. The node now returns Structured Response instead of Response.
Chat does not preserve conversation history. Include the required history in the current prompt or load it from another action before Chat runs.