See 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. cpp academy academy/topics/agent-context-observability website/content-src/academy/course.mjs academy See what your agent did and why
Unit 5 · Build an agent that can use tools

See 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
Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1
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Source-backed follow-up