Summarize

Introduction

If you're dealing with lengthy content and need the key points, PromptQL automatically engages the summarize primitive to create concise versions that capture what matters. You don't need to explicitly request summarization; it recognizes when condensing information would be helpful.

Example

Imagine asking PromptQL something like:

"I have a bunch of restaurant reservations and I need quick overviews of each one - just the restaurant name and anything important I should know about each booking."

The summarize function doesn't just condense text - it intelligently determines what information is most relevant based on context. While you can guide the summarization with specific instructions, PromptQL automatically identifies important details, relationships, and key points that should be preserved. In this restaurant reservation example, PromptQL knows to maintain crucial booking details even without being explicitly told about every field:

summaries = executor.summarize(
    instructions="""
    Create a concise summary of each reservation focusing on:
    - The restaurant name
    - Any special notes or important details
    Keep each summary to 1-2 sentences.
    """,
    inputs=reservation_texts
)

Next steps

Now that you know more about how PromptQL can summarize large bodies of text and data, learn how it can intelligently classify data into categories.