Let an agent investigate and actYou give a typed task an iterative runtime where the model can inspect evidence, call tools, and delegate. It still finishes through your declared output contract.cppacademyacademy/topics/agent-corewebsite/content-src/academy/course.mjsacademyLet an agent investigate and act
You give a typed task an iterative runtime where the model can inspect evidence, call tools, and delegate. It still finishes through your declared output contract.
agent()8 focused minutesNot started
Unit example (nearest native match)
See the idea in context
auto helper = axllm::agent("question:string -> answer:string");
Declare the whole task
The signature keeps the request and final resolution typed.
Provide allowed capabilities
functions limits the tools the runtime may choose.
Start one agent run
forward() lets the agent inspect, act, and finish with a resolution.
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/short-agents/tools_agent.cpp