Text Extraction
This Engine extracts data from any text source into your desired structure.
Text Extraction Engine Inputs
Text Extraction Configuration
The Text Extraction Engine Configuration has four parameters that take in values:
- instruction: optional. A string used to prompt the Agent during job execution.
- text: required. The text input to extract from.
- model: required. The model to use for extraction.
- output_schema: optional. Defines the exact structure of the JSON output that the extracted data will populate. Follows the standard JSON schema specification.
See Template Strings for dynamic parameter configuration.
Text Extraction Output
The output will always be a JSON value of the structure specified in the output_schema (if you defined it).
Text Extraction Example
Let’s run through an example using this engine together.
Create an Agent
Click on the “Add Agent” button in the top right corner of the Agents page.
Enter a name and an optional description of your Agent.
Select the Text Extraction Engine
Remove the model input from Agent Input Definition
Remove the model Agent input
Configure the engine as follows
-
instruction: $instruction
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text: $text
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model: gpt-4o
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output_schema: Copy and paste the JSON schema below (hit Use Text) or refer to the image below for using the UI widget to define the JSON schema.
Defining output_schema using the UI Widget
Create the Agent
Hit the Create button. Now, let’s run it on text input through the UI.
View the Agent you just created
Create a new Agent job
Fill in the Agent inputs
Paste in the following text for the text input field:
Here are the filled-in Agent inputs:
Run the job
Hit the Create button at the bottom to start the text extraction job.
View the Results
Click View of the respective job to view its status and results.
Scroll down the Agent Job Details page and you’ll see the job outputs.