ContextCache: Persistent KV Cache with Content-Hash Addressing for Zero-Degradation Tool Schema Caching
Authors/Creators
Description
ContextCache is a persistent KV cache system that accelerates tool-augmented LLM inference by caching prefilled key-value states of tool schema prefixes with SHA-256 content-hash addressing. On cache hits, only the user query requires prefilling, reducing time-to-first-token by 6.9x (787ms to 114ms) with zero quality degradation — group-cached generation matches full prefill exactly on Tool Selection Accuracy across all evaluation splits. This work also documents a negative result: per-tool independent KV compilation with NoPE/deferred-RoPE fails (TSA ~0.1) due to cross-tool attention dependencies, motivating the group caching design. The system includes disk persistence, a model-agnostic adapter layer (Qwen, Llama, Mistral), FastAPI serving, and a browser-based UI, breaking even after just 2.1 requests.
Files
contextcache.pdf
Files
(373.1 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:a37046fb87d168a1dd15e22e535a757a
|
373.1 kB | Preview Download |
Additional details
Software
- Repository URL
- https://github.com/spranab/contextcache
- Development Status
- Active