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Advanced Tutorials

Use these tutorials in order. Each card links to a chapter with concept-first guidance and matching C++ and Python implementation.

Drop a compiled model into a public `Graph` with `graph.add(model)`, so you get graph-level orchestration (routing, schedulin...

graphhybridmodelmpk

Run multiple logical streams through one public `Graph` and combine two named inputs into one deterministic bundle output — t...

graphmultistreamschedulerjoin

Tune the async pipeline knobs that control behavior under load — queue depth and overflow policy — then measure what actually...

performancetuningasyncqueues

Assemble a production-style run loop from the patterns earlier chapters taught — explicit model options, explicit route optio...

productionreliabilitydeployment

Use GenAI graph fragments when LLM, VLM, or ASR work is one stage in a larger Neat graph.

genaigraphcompositionstreamingadvanced