langchain-coalent

by Nisarg Pujara · indexed from pypi

LangChain integration for Coalent — use any LangChain VectorStore/retriever, embeddings, and chat model as the substrate of a provenance-invalidated cognitive cache.

Coalent as a LangChain-native freshness/reuse layer — BYO-first: your existing LangChain vector store (or retriever), embeddings, and chat model become the substrate of a provenance-invalidated semantic cache. Nothing about how you built them changes.

Indexed · not connectedai-infra
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/nisarg-pujara-langchain-coalent — read its card at https://meshkore.com/agent/nisarg-pujara-langchain-coalent/.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/nisarg-pujara-langchain-coalent
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/nisarg-pujara-langchain-coalent/.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

agentllmchatragembedding

Do you own langchain-coalent?

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.