Unit 4 · Connect AI steps into a workflow

Pass useful state from step to step

You make dependencies visible by passing state between sequential nodes. Use map() for ordinary transformations that do not need another model call.

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Unit example (nearest native match)

See the idea in context

auto step = axllm::ax("request:string -> route:class \"support, sales, engineering\"");
auto program = axllm::flow(axllm::object({{"id", "supportRouter"}}))
    .execute("classify", step)
    .returns(axllm::object({{"route", "classify"}}));

Run itIn your own project

include(FetchContent)
FetchContent_Declare(axllm GIT_REPOSITORY https://github.com/ax-llm/ax GIT_TAG main SOURCE_SUBDIR packages/cpp)
FetchContent_MakeAvailable(axllm)
target_link_libraries(your_app PRIVATE axllm::axllm)

#include <axllm/axllm.hpp>

auto llm = axllm::ai("openai", axllm::object({{"apiKey", std::getenv("OPENAI_API_KEY")}}));
auto classify = axllm::ax("review:string -> sentiment:class \"positive, negative, neutral\"");

Set OPENAI_APIKEY in your environment before running provider-backed code.

In the ax repo

From a clone of the ax repo:

npm run example -- cpp src/examples/cpp/flows/branch_flow.cpp

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

Keep exploring

See the idea in context

Show that you can use it

Source-backed follow-up