mirror of
https://github.com/headroomlabs-ai/headroom.git
synced 2026-08-27 14:17:10 -04:00
7a05808e0f
Implements a comprehensive cache optimization layer for LLM providers: - Provider-specific optimizers (Anthropic, OpenAI, Google) with distinct caching strategies: explicit breakpoints, prefix stabilization, and CachedContent API respectively - Scalable dynamic content detector using three strategies: 1. Structural detection: "Label: value" patterns (language-agnostic) 2. Entropy-based detection: high-entropy strings (IDs, tokens, hashes) 3. Universal patterns: ISO 8601, UUIDs, JWTs, hex hashes - NO hardcoded locale-specific patterns (no month names, etc.) - Semantic caching layer with LRU eviction and TTL support - Plugin registry for provider selection and custom optimizers - 131 tests, real-world benchmarks showing 20-55% compression at <0.3ms
1 line
47 B
Python
1 line
47 B
Python
"""Tests for the cache optimization module."""
|