Real estate guide
Token compression for property listings
LLMs can generate compelling property descriptions from listing data, but sending every property feature costs tokens. Compression keeps only the features worth highlighting.
Compressing listing data
from supercompress import Compressor
comp = Compressor()
def generate_listing(property_data, style_guide):
result = comp.compress(property_data, "Generate a listing description")
return llm.generate(
f"Write a listing:\n{result.compressed_text}"
)Frequently asked questions
Does compression lose important features?
No. Only generic or redundant features are removed. Unique selling points are preserved.
Can I generate listings in bulk?
Yes. Compress and generate 50+ listings per minute with batch processing.
Build with less context
Put compression in front of your next LLM call.
Use the hosted API or run SuperCompress locally. Keep the evidence, drop the token waste, and measure the savings before it reaches your model.