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loom-py

Python client for the loom multi-agent fabric. Wraps the driver-agent MCP surface as a fluent workflow API. Zero runtime Python deps; one external dep: the driver-agent Go binary.

Install (dev)

pip install -e multi-agent/python

Then make sure driver-agent is reachable via one of:

  • $LOOM_DRIVER_BIN=/abs/path/to/driver-agent
  • driver-agent on $PATH
  • repo-local multi-agent/tests/prod_test/bin/driver-agent.linux-amd64

Quickstart

1. Happy chat

import loom

with loom.workflow(goal="say HELLO") as wf:
    res = wf.chat("Reply with HELLO and stop.",
                  target="slave-local-prod").wait()
print(res.output)

2. Human in the loop (ask_user)

import loom

with loom.workflow(goal="pick a color") as wf:
    res = (
        wf.chat('Call ask_user(question="pick a color", options=["red","blue"]) '
                "then reply with that color.",
                target="slave-local-prod")
          .expect_or_ask()        # default handler reads stdin from terminal
          .wait()
    )
print(res.output)

For non-interactive contexts pass a custom handler:

def handler(q: loom.Question) -> str:
    if q.kind == "request_permission":
        return "approve" if policy_check(q) else "deny"
    return ask_my_chat_ui(q.question, q.options)

res = wf.chat(...).expect_or_ask(handler).wait()

3. Find a capable slave

import loom

with loom.workflow(goal="weather lookup") as wf:
    try:
        slave = wf.find_slave(mcp_tool="weather_forecast")
    except loom.SlaveNotFound:
        slave = wf.find_slave(skill="register_mcp")  # bootstrap
        # ... scaffold + register the MCP, then retry
    res = wf.chat("Will it rain in Beijing tomorrow?", target=slave).wait()

4. File I/O via placeholders

import loom

with loom.workflow(goal="CSV → summary") as wf:
    res = wf.chat(
        "Read {input:data} and write a summary to {output:report}.",
        target="slave-local-prod",
        inputs={"data": "./data.csv"},
        outputs={"report": "./report.md"},
    ).wait()
print(res.outputs["report"])  # './report.md' (already populated locally)

Status

v0 covers:

  • core task semantics (submit / wait / get / cancel)
  • humanloop pause/resume (expect_or_ask)
  • capability discovery + dynamic MCP (list_slaves / find_slave / MCPSpec)
  • file I/O via inputs / outputs placeholders
  • workflow context manager with fluent verbs

Not yet (planned for v0.2):

  • DAG / fanout
  • Codex backend differences
  • TASK_CONTRACT envelope compilation (see spec § 6 for trigger criteria)
  • retry / metrics / PyPI publish

See docs/superpowers/specs/2026-05-27-loom-python-library-design.md.