Joeven — Learn Autonomous AI Agents

Python loads on first run

from typing import Callable

JOBS = {
    17: {"status": "failed", "error": "timeout talking to vendor"},
    42: {"status": "ok", "error": None},
}

def tool_get_job(job_id):
    if job_id not in JOBS:
        return {"error": "not found"}
    return JOBS[job_id]

def tool_finish(answer):
    return {"final": answer}

TOOLS: dict[str, Callable] = {
    "get_job": lambda **kw: tool_get_job(int(kw["job_id"])),
    "finish": lambda **kw: tool_finish(str(kw["answer"])),
}

def fake_model(transcript):
    # Pretend the LLM read the user goal and tool docs.
    if not any(t.get("role") == "tool" for t in transcript):
        return {"tool": "get_job", "args": {"job_id": 17}}
    job = transcript[-1]["content"]
    status = str(job.get("status", job.get("error", "unknown")))
    err = job.get("error")
    if err is None:
        err_text = "none"
    else:
        err_text = str(err)
    answer = "Job 17 is " + status + ": " + err_text
    return {"tool": "finish", "args": {"answer": answer}}

def run_agent(goal, max_steps=4):
    transcript = [{"role": "user", "content": goal}]
    for step in range(1, max_steps + 1):
        decision = fake_model(transcript)
        name = decision["tool"]
        args = decision["args"]
        result = TOOLS[name](**args)
        print(
            "step "
            + str(step)
            + ": "
            + name
            + "("
            + str(args)
            + ") -> "
            + str(result)
        )
        if name == "finish":
            return result["final"]
        transcript.append({"role": "tool", "name": name, "content": result})
    return "budget exceeded"

print("ANSWER:", run_agent("What is the status of job 17?"))
print("unknown job probe:", tool_get_job(99))

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