Flows | Ax

These C++ examples are real runnable files. Edit the source file first; this page is rebuilt from the checked-in example and its metadata header.

C++ Sequential Flow

Runs a two-step Ax flow against OpenAI.

Provider: openai
Env: OPENAI_API_KEY, OPENAI_APIKEY
Level: beginner
Run: npm run example -- cpp src/examples/cpp/flows/sequential_flow.cpp
Source: src/examples/cpp/flows/sequential_flow.cpp

C++

#include "axllm/axllm.hpp"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <sstream>


int main() {
  const char* key = std::getenv("OPENAI_API_KEY");
  if (key == nullptr || std::string(key).empty()) key = std::getenv("OPENAI_APIKEY");
  if (key == nullptr || std::string(key).empty()) {
    std::cerr << "Set OPENAI_API_KEY or OPENAI_APIKEY to run this example.\n";
    return 2;
  }
  const char* model = std::getenv("AX_OPENAI_MODEL");
  axllm::OpenAICompatibleClient client(axllm::object({
      {"api_key", key},
      {"model", model == nullptr || std::string(model).empty() ? "gpt-5.4-mini" : model},
      {"model_config", axllm::object({{"temperature", 0}})},
  }));
  axllm::AxGen step = axllm::ax("documentText:string -> summaryText:string");
  axllm::AxFlow program = axllm::flow(axllm::object({{"id", "examples.sequentialFlow"}}))
      .execute("step", step)
      .map("note", [](axllm::Value) { return axllm::object({{"note", "Mapped flow state after the provider-backed step."}}); })
      .returns(axllm::object({{"step", "step"}, {"note", "note"}}));
  axllm::Value output = program.forward(client, axllm::object({{"documentText", "Ax gives developers signatures, provider clients, agents, flows, tracing, and optimization."}}));
  std::cout << axllm::stringify(output) << "\n";
}

C++ Branching Flow

Routes a classification through follow-up flow logic backed by OpenAI.

Provider: openai
Env: OPENAI_API_KEY, OPENAI_APIKEY
Level: intermediate
Run: npm run example -- cpp src/examples/cpp/flows/branch_flow.cpp
Source: src/examples/cpp/flows/branch_flow.cpp

C++

#include "axllm/axllm.hpp"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <sstream>


int main() {
  const char* key = std::getenv("OPENAI_API_KEY");
  if (key == nullptr || std::string(key).empty()) key = std::getenv("OPENAI_APIKEY");
  if (key == nullptr || std::string(key).empty()) {
    std::cerr << "Set OPENAI_API_KEY or OPENAI_APIKEY to run this example.\n";
    return 2;
  }
  const char* model = std::getenv("AX_OPENAI_MODEL");
  axllm::OpenAICompatibleClient client(axllm::object({
      {"api_key", key},
      {"model", model == nullptr || std::string(model).empty() ? "gpt-5.4-mini" : model},
      {"model_config", axllm::object({{"temperature", 0}})},
  }));
  axllm::AxGen step = axllm::ax("request:string -> route:class "support, sales, engineering"");
  axllm::AxFlow program = axllm::flow(axllm::object({{"id", "examples.branchFlow"}}))
      .execute("step", step)
      .map("note", [](axllm::Value) { return axllm::object({{"note", "Mapped flow state after the provider-backed step."}}); })
      .returns(axllm::object({{"step", "step"}, {"note", "note"}}));
  axllm::Value output = program.forward(client, axllm::object({{"request", "A customer says checkout is down for their enterprise account."}}));
  std::cout << axllm::stringify(output) << "\n";
}

C++ Composed Flow

Composes multiple typed programs into one OpenAI-backed flow.

Provider: openai
Env: OPENAI_API_KEY, OPENAI_APIKEY
Level: advanced
Run: npm run example -- cpp src/examples/cpp/flows/composed_flow.cpp
Source: src/examples/cpp/flows/composed_flow.cpp

C++

#include "axllm/axllm.hpp"
#include <cstdlib>
#include <fstream>
#include <iostream>
#include <sstream>


int main() {
  const char* key = std::getenv("OPENAI_API_KEY");
  if (key == nullptr || std::string(key).empty()) key = std::getenv("OPENAI_APIKEY");
  if (key == nullptr || std::string(key).empty()) {
    std::cerr << "Set OPENAI_API_KEY or OPENAI_APIKEY to run this example.\n";
    return 2;
  }
  const char* model = std::getenv("AX_OPENAI_MODEL");
  axllm::OpenAICompatibleClient client(axllm::object({
      {"api_key", key},
      {"model", model == nullptr || std::string(model).empty() ? "gpt-5.4-mini" : model},
      {"model_config", axllm::object({{"temperature", 0}})},
  }));
  axllm::AxGen step = axllm::ax("topic:string -> outline:string[]");
  axllm::AxFlow program = axllm::flow(axllm::object({{"id", "examples.composedFlow"}}))
      .execute("step", step)
      .map("note", [](axllm::Value) { return axllm::object({{"note", "Mapped flow state after the provider-backed step."}}); })
      .returns(axllm::object({{"step", "step"}, {"note", "note"}}));
  axllm::Value output = program.forward(client, axllm::object({{"topic", "How Ax moves from typed generation to agents, flows, and optimization"}}));
  std::cout << axllm::stringify(output) << "\n";
}