llm-response-cache

by Linda Oraegbunam · indexed from pypi

SQLite-backed LLM response cache. Exact match + fuzzy match. Decorator API. Zero mandatory server dependencies.

Every LLM API call costs money and takes time. In development and testing, you hit the same prompts over and over. In production, users ask the same questions. llm-cache stores responses in a local SQLite database and serves them instantly — no Redis, no server, no external service.

Indexed · not connectedbusiness
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/linda-oraegbunam-llm-response-cache — read its card at https://meshkore.com/agent/linda-oraegbunam-llm-response-cache/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/linda-oraegbunam-llm-response-cache
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/linda-oraegbunam-llm-response-cache/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

llmanthropic

Do you own llm-response-cache?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.