optimize_prompt()

Optimize a prompt for reduced token usage.

Usage

Source

optimize_prompt(
    prompt,
    *,
    level=OptimizationLevel.MODERATE,
)

Applies text-level compression techniques that preserve semantic meaning while reducing token count. Useful when targeting models with small context windows (8K–32K).

Parameters

prompt: str | PromptBuilder

A prompt string or a ~talk_box.prompt_builder.PromptBuilder instance. If a PromptBuilder, its built output is used.

level: str | OptimizationLevel = OptimizationLevel.MODERATE


How aggressively to compress. "light" is formatting-only, "moderate" (default) condenses structure, "aggressive" maximizes compression.

Returns

OptimizeResult

The optimized text with before/after token counts.

Examples

import talk_box as tb

builder = (
    tb.PromptBuilder()
    .persona("analyst", "data science")
    .task_context("Analyze sales data")
    .constraint("Be concise")
    .example("Q: Revenue?", "A: $1.2M")
)
result = tb.optimize_prompt(builder)
print(f"Saved {result.reduction_pct:.0f}% tokens")
print(result.text)