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LangGraph Adapter

Use this adapter when your application organizes LLM work as LangGraph nodes or LangChain runnable flows.

Integration shape​

LangGraph is usually best integrated through one shared helper rather than by scattering gate logic across nodes.

That helper should:

  • read request context from runnable metadata
  • derive feature_code
  • perform authorize
  • execute the model call
  • extract usage from the final response
  • perform commit
  • cancel best-effort on failure

Why this shape works​

Graph-based systems often have:

  • multiple semantic LLM nodes
  • optional streaming
  • tool nodes between model nodes
  • graph-level retries and branching

One shared helper keeps the runtime semantics consistent across all nodes.

Runtime rules​

  • treat each model node invocation as its own billable operation
  • pass context through RunnableConfig.metadata or equivalent per-run state
  • do not attach billing only at the outer graph entrypoint if multiple model calls happen inside

Artifact roles​

  • vluna_adapter.*
    • This is the file to copy if your project already uses LangGraph or LangChain.
    • It is intended as the reusable helper layer for gated node calls.
  • example.*
    • This is a demo graph showing how to route node-level model calls through the adapter.
    • Use it to understand invocation shape, not as the primary production file.

Downloadable artifacts​

Python:

TypeScript: