ojuschugh1/sqz — Compress LLM context to save tokens and reduce costs

Description and use

**sqz** is an open‑source utility that compresses the context of large language model (LLM) prompts, enabling developers to represent the same information using far fewer tokens. By encoding and decoding conversational history on the backend, it helps lower API usage costs while preserving the quality of LLM responses. Ideal for AI/ML applications, backend services, and developer tooling that need efficient token management.

Problem

ojuschugh1/sqz helps add AI capability without starting from a blank model stack.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Compress LLM context to save tokens and reduce costs

Source