Extract

Introduction

The extract function demonstrates PromptQL's ability to intelligently identify and structure relevant information from text, even when that information appears in different forms or contexts. While you provide a basic schema of what you're interested in, PromptQL automatically recognizes various ways information might be expressed - understanding that "no nuts" and "nut allergy" represent the same dietary restriction, or that "celebrating our 10th" implies an anniversary.

Example

Here's an example showing how PromptQL handles reservation notes with minimal guidance:

"I need to go through all these reservation notes and pull out any special requests - you know, like if people have food allergies, if they're celebrating something, or if they want specific tables. Can you help me organize all that information?"

extracted_info = executor.extract(
        json_schema=json_schema,
        instructions="""
        Extract any mentioned dietary requirements, special occasions, or seating preferences from the reservation notes.
        For dietary requirements, include any allergies, restrictions, or preferences mentioned.
        For special occasions, look for mentions of birthdays, anniversaries, celebrations etc.
        For seating preferences, identify if they specifically requested indoor, outdoor, bar seating etc.
        If any field is not mentioned, omit it from the output.
        """,
        inputs=notes_to_extract
    )

In this example, the instructions outline basic categories without having to specify every possible way information might be phrased. PromptQL automatically handles variations in language, implied information, and contextual clues - understanding that "by the window" is a seating preference or that "gluten-free" belongs under dietary requirements, even without explicit mapping of these terms.

Next steps

Once PromptQL has extracted structured information, it can automatically visualize patterns and trends in that data - for example, turning extracted dietary requirements and seating preferences into interactive charts that reveal popular accommodations or seasonal trends in special occasion bookings.