See what your agent did and whyYou keep task input, context, orientation, memories, and skills in the right lifecycle. Runtime hooks then show the turns, tool calls, traces, status, and usage behind the answer.cppacademyacademy/topics/agent-context-observabilitywebsite/content-src/academy/course.mjsacademySee what your agent did and why
You keep task input, context, orientation, memories, and skills in the right lifecycle. Runtime hooks then show the turns, tool calls, traces, status, and usage behind the answer.
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Unit example (nearest native match)
See the idea in context
auto helper = axllm::agent("question:string -> answer:string");
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/short-agents/tools_agent.cpp