genai_estimate_tokens

This page explains how to use the genai_estimate_tokens function in APL.

The genai_estimate_tokens function estimates the number of tokens in a text string. This estimation helps you predict API costs, validate input sizes, and monitor token usage before making actual API calls to LLM services.

You can use this function to validate prompt sizes, estimate costs before API calls, monitor content length, or analyze token efficiency across different prompts.

Usage

Syntax

APL

genai_estimate_tokens(text)

Parameters

Name	Type	Required	Description
text	string	Yes	The text string for which you want to estimate the token count.

Returns

Returns a long integer representing the estimated number of tokens in the input text.

Example

Estimate the number of tokens in a GenAI conversation prompt.

Query

APLRun in Playground

['otel-demo-genai']
| extend user_prompt = genai_extract_user_prompt(['attributes.gen_ai.input.messages'])
| extend estimated_tokens = genai_estimate_tokens(user_prompt)
| summarize avg_tokens = avg(estimated_tokens), max_tokens = max(estimated_tokens)

Output

avg_tokens	max_tokens
245	1024

This query analyzes prompt token usage patterns, helping you predict costs and validate input sizes.

genai_cost: Calculates the actual cost based on token usage. Use this in combination with token estimates to predict costs.
strlen: Returns string length in characters. Use this for a simpler character count without token estimation.
string_size: Returns string length in characters. Use this when you need character count instead of token count.
genai_input_cost: Calculates input token cost. Combine with token estimation to predict prompt costs.