Unit 4 · Connect AI steps into a workflow

Branch, loop, and run work in parallel

You keep important branches, loops, and parallel work under application control. The model handles typed steps instead of improvising the orchestration plan.

9 focused minutesNot started

Unit example (nearest native match)

See the idea in context

std::string mermaid = R"(flowchart TD
  %%ax classify: request:string -> route:class "support, sales"
  classify{route})";
auto program = axllm::flow(mermaid);
std::cout << program.str();

Run itIn your own project

cmake_minimum_required(VERSION 3.20)
project(ax_quick_start LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 17)

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

add_executable(quick_start quick_start.cpp)
target_link_libraries(quick_start PRIVATE axllm::axllm)

#include <axllm/axllm.hpp>
#include <cstdlib>
#include <iostream>

int main() {
  auto llm = axllm::ai("openai", axllm::object({{"apiKey", std::getenv("OPENAI_API_KEY")}}));
  auto classify = axllm::ax("review:string -> sentiment:class \"positive, negative, neutral\"");
  auto result = classify.forward(*llm, axllm::object({
    {"review", "Useful and boring in the best way."}
  }));

  auto sentiment = axllm::Core::get(result, "sentiment");
  std::cout << "sentiment: " << std::get<std::string>(sentiment.data) << "\n";
}

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