OpenAI

Generate text responses with OpenAI models

Actions

Text Prompt Generate a text response using OpenAI

Text Prompt

Component key: openai.textPrompt

The Text Prompt component generates text responses using OpenAI’s language models.

Use Cases

• Content generation: Generate text content, summaries, or descriptions
• Natural language processing: Process and transform text using AI
• Automated responses: Generate responses to user queries or events
• Data transformation: Convert structured data into natural language

Configuration

• Model: Select the OpenAI model to use (e.g., gpt-4, gpt-3.5-turbo)
• Prompt: The text prompt to send to the model (supports expressions)
• Files: (Optional) Attach files from the Files tab (images, PDFs, or text). They are uploaded to the OpenAI Files API and sent alongside the prompt.
• Structured Output: (Optional) Provide a JSON Schema for the response and the model returns JSON matching it, available on the parsed output. The schema is validated before the request and sent in OpenAI strict mode; strict mode marks every property required, so express optional fields by making their type nullable.

Output

Returns the generated response including:

• text: The generated text response
• model: The model used for generation
• usage: Token usage information (prompt tokens, completion tokens, total tokens)
• id: Response ID for tracking
• parsed: When Structured Output is configured, the response parsed into an object.

Notes

• Requires a valid OpenAI API key configured in the application settings
• Response quality and speed depend on the selected model
• Token usage is tracked and may incur costs based on your OpenAI plan
• Supports OpenAI-compatible providers by setting a custom Base URL in the integration settings (e.g., Azure OpenAI, Ollama, vLLM). Note: structured output uses the OpenAI Responses API text.format parameter and may not be supported by all compatible providers.

Example Output

{
  "data": {
    "id": "cmpl-1234567890",
    "model": "gpt-5.2",
    "parsed": {
      "language": "en",
      "summary": "Hello, world!"
    },
    "text": "Hello, world!",
    "usage": {
      "input_tokens": 10,
      "output_tokens": 10,
      "total_tokens": 20
    }
  },
  "timestamp": "2026-01-19T12:00:00Z",
  "type": "openai.response"
}