A tool-calling agent picks one registered function per turn and answers with JSON. Six steps, six round trips, every branch routed back through the model.
Here the action is a program. The model writes one Nu term, an immutable expression tree, that reads, branches and writes against the Refs you bound. nuagent runs it and feeds back what it yielded plus the state it left behind.
def out():
return nu.ForEachDo(
nu.Iter(nu.Literal(["mon", "tue", "wed"])),
Notes.items.append(nu.AttrRef("item")),
) >> Notes.count.set(nu.Len(Notes.items)) >> Run.done.set(True)A loop, three writes, a derived count and the run ending itself. One reply.
- Nothing to register, no schema to keep in sync. Capability is the set of Refs bound around the loop, so bind a different set and it is a different agent with the same code.
- Reach is whatever Nu reaches: a dict, a
nustd.kvstore on disk, an http service, anything a fabric backs. The shipped catalogue is nucore only, so finding a fabric's verbs costs the model a turn. - The loop is a term as well: a
WhileDoover the turn, no python driver. SwapMemSessionforKVSessionand the same run is durable.
Requires Python 3.10+.
pip install nuagentAn agent over a notes list. The app's Shape goes into the prompt, so the model opens the run already knowing the slot names and their types.
import nu
import nustd
import nuagent
class Notes(nu.Shape):
items = nustd.mem.ListRef.slot(str)
count = nustd.mem.IntRef.slot()
class Bot(nu.Service):
chat = nustd.llm.ChatRef.method(temperature=0)
TASK = """\
Append one note per weekday to `items`, then set `count` to how many notes are
in the list. Do it as one program, and derive the count."""
system = nuagent.system_prompt(
TASK,
sections=nuagent.inserted(nuagent.DEFAULT_SECTIONS, nuagent.surface_section((Notes,))),
)
loop = nuagent.agent(
session=nuagent.MemSession,
chat=Bot.chat,
state=nu.Dict.of(items=Notes.items, count=Notes.count),
start=nuagent.MemSession.messages.set(
nu.List.of(nu.Dict.of(role="system", content=nu.Str(system))),
)
>> Notes.items.set([])
>> Notes.count.set(0),
report=nu.print(nu.Str("\nnotes: ") + nu.ToStr(nu.Repr(Notes.items))),
)
nu.run(
nu.With(
nu.Provide(dict, {}),
nustd.llm.ollama(Bot, host="localhost", model="qwen2.5:7b-instruct"),
body=loop,
)
)Early. The API is not settled yet.