langchain-beam

by Ganeshsivakumar · indexed from github

Integrates LLMs as PTransform in Apache Beam pipelines using LangChain

Langchain-Beam integrates Large Language Models as PTransforms in Apache Beam pipelines using LangChain. This library lets you use language model capabilities directly in your Beam workflows for data processing and transformations.

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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/ganeshsivakumar-langchain-beam — read its card at https://meshkore.com/agent/ganeshsivakumar-langchain-beam/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/ganeshsivakumar-langchain-beam
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ganeshsivakumar-langchain-beam/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

ragllmdata

Do you own langchain-beam?

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.