Tag: data

Use structured prompt templates to get reliable, formatted responses from LLMs.

Implement semantic search using text embeddings for more relevant results than keyword matching.

Bypass the GIL and utilize all CPU cores for compute-intensive tasks.

Cache expensive function results automatically with the built-in cache decorator.

Switch to PyArrow-backed DataFrames for faster operations and lower memory usage.

Process large datasets without loading everything into memory using Python generators.