The Attribute Extraction operation maps data from a source record into a predefined target schema using an AI language model (OpenAI / Azure OpenAI). It is particularly useful when source and target structures use different attribute names or when the mapping requires content-based interpretation.
Prerequisite: An OPENAI_PROVIDER with the use case Attribute Extraction must be configured.
1. Creating an Attribute Extraction
The operation is added to the flow like any other operation — drag it from the graphical flow editor onto the canvas and connect it to a data source.
2. Configuration
Basic Settings
| Field | Description |
|---|---|
| Name | Label for the operation |
| Target Schema | The schema that defines the target attributes with their keys, descriptions, and optional fixed values |
| Source Attributes | Optional filter: only the listed attributes from the source record are passed to the AI. Leave empty to pass all attributes |
| Preserve Source Attributes (Prefix) | If a prefix is provided, all source attributes are additionally included in the result record as <prefix>_<attributeName> |
| Prompt | Optional Handlebars template to control the AI request. Leave empty to use the system-wide default prompt |
How the AI uses the Target Schema
For each attribute in the target schema the following fields are passed to the AI:
key– the target attribute keydescription– the name or description of the attribute (the longer of the two texts is used)defaultValue– if set, passed to the AI as a hintfixedValues– if set, the AI may only use values from this list
3. Execution
After configuration, the operation is started via the Extract Attributes button. The AI processes each source record individually and produces an output record with the target attributes populated.
The execution card header shows the current GPT status of the configured provider:
| Status | Meaning |
|---|---|
| available | The provider is ready |
| rate limited | The request quota is exhausted; reset in X seconds |
4. Result
The output record contains the attributes defined by the target schema, populated with values extracted from the source record. Attributes for which no matching value was found may be empty or set to the defaultValue.
If Preserve Source Attributes is configured, all original source attributes are additionally included in the result under the specified prefix.
5. Notes
- AI processing is sequential per record. For large datasets with active rate limits, the operation automatically waits until the quota is available again.
- If no OPENAI_PROVIDER with the use case Attribute Extraction is configured, the execution fails with a corresponding error message.
- The GPT status in the UI reflects the server-side observed state since the last backend start — after a restart the status is initially always shown as “available”.