Implement a system for controlling LLM output length precisely. ## Length Requirements {{length_requirements}} ## Content Priorities {{content_priorities}} ## Quality Constraints {{quality_constraints}} Build the controller: ```python class OutputLengthController: def estimate_output_length(self, prompt: str, task_type: str) -> int: """Predict expected output tokens""" pass def calibrate_prompt(self, prompt: str, target_tokens: int) -> str: """ Add length guidance: - Explicit token limits - Structural constraints - Detail level instructions """ pass def truncate_smartly(self, output: str, max_tokens: int) -> str: """ Preserve: - Complete sentences - Key information - Structural integrity """ pass def expand_to_minimum(self, output: str, min_tokens: int, context: str) -> str: """Expand output to meet minimum length""" pass ``` Include: - Token counting accuracy - Length distribution analysis - Retry strategies
Constrained Output Length Controller
Build an output length controller with estimation, prompt calibration, smart truncation, and expansion for precise length control.
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CodingUse Cases
Length controlOutput formattingToken management
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claude-sonnet-4-20250514gpt-4o
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