Unit 6 · Solve long and complex tasks

Control how much history the model sees

You choose how aggressively earlier actions are summarized without deleting live runtime values. Checkpointed with a balanced budget is the practical starting point.

contextPolicy8 focused minutesNot started

Unit example (nearest native match)

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investigator = agent(signature, {
    "contextFields": ["logs"],
    "contextPolicy": {"preset": "lean", "budget": "balanced"},
    "runtime": {"language": "JavaScript"},
})

Run itIn your own project

pip install axllm

from axllm import ai, ax

llm = ai('openai', api_key=os.environ['OPENAI_API_KEY'])
classify = 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 -- python src/examples/python/long-agents/incident-log-forensics.py

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

Keep exploring

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Show that you can use it

Source-backed follow-up