Unit 6 · Solve long and complex tasks

Keep bulky evidence out of the prompt

You place large inputs in the runtime and expose only a preview and shape to the model. Declared contextFields keep the full value available by reference.

contextFields9 focused minutesNot started

Unit example (nearest native match)

See the idea in context

auto investigator = axllm::agent(signature, axllm::object({
    {"contextFields", axllm::array({"logs"})},
    {"contextPolicy", axllm::object({{"preset", "lean"}, {"budget", "balanced"}})},
    {"runtime", axllm::object({{"language", "JavaScript"}})},
}));

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/long-agents/incident_log_forensics.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