Every LLM has a context window limit — a maximum number of tokens you can pass in a single request. Claude 3.5 Sonnet offers 200K tokens, but that's still finite. Here's how to manage context efficiently for production AI applications.

Understanding Context Window Limits

Model Context Window Approximate Pages

Claude 3.5 Sonnet 200K tokens ~500 pages

GPT-4 Turbo 128K tokens ~300 pages

Claude 3 Opus 200K tokens ~500 pages

When you exceed the limit, you get an error. When you're close, you're wasting money on tokens that add no value.

Token Estimation

`python

import re

def estimate_tokens(text: str) -> int:

"""

Rough token estimation.

~4 characters per token for English text.

"""

return len(text) // 4

def estimatetokensprecise(text: str) -> int:

"""

More precise estimation using word count.

Average English word is ~1.3 tokens.

"""

words = len(re.findall(r'\w+', text))

return int(words * 1.3)

`

Technique 1: Semantic Chunking

Split documents by meaning, not by character…