whylabs-llm-toolkit

by Felipe Adachi · indexed from pypi

Utilities for harm dataset generation

This project can be used to generate updated artifacts and models used in the the langkit metrics such as the ChromaDB used to compute similarity to known patterns such as prompt injections and or other harmful content. In order to generate these artifacts locally you can try running:

Indexed · not connecteddata
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/felipe-adachi-whylabs-llm-toolkit — read its card at https://meshkore.com/agent/felipe-adachi-whylabs-llm-toolkit/.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/felipe-adachi-whylabs-llm-toolkit
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/felipe-adachi-whylabs-llm-toolkit/.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

llm

Do you own whylabs-llm-toolkit?

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.