agi-diy

Python client for api.agi.diy. Lease a VLA policy, run it over the LeRobot remote-inference protocol (zenoh). One call = one token per action in the chunk.

pip install "agi-diy[lerobot]"
agi login
agi run act/so101 --probe

import agi

with agi.Policy("act/so101") as session:
    actions = session.predict(
        {"observation.state": state, "observation.images.front": frame},
        task="pick up the cube",
    )  # np.ndarray [n_action_steps, dof]

The key comes from AGI_API_KEY or ~/.agi/credentials (AGI_API_KEY=agi_sk_live_…).

Surface

agi.Policy("act/so101")          # POST /v1/sessions → lease; raises agi.NoSlots / agi.InsufficientCredits / agi.AuthError
session.endpoint                 # "ws/zenoh.api.agi.diy:80"
session.deployment               # "d_…"
session.url                      # "zenoh+ws://zenoh.api.agi.diy:80/d_…"
session.connect()                # admitted lerobot.remote_inference.RemoteClient
session.predict(obs, task="…")   # one chunk, np.ndarray
session.policy()                 # strands-robots policy: arm.run(session.policy(), seconds=30)
session.rollout_args()           # flags for lerobot-rollout
session.close()                  # DELETE /v1/sessions/:id (also a context manager)
agi.models(); agi.me(); agi.usage(); agi.sessions(); agi.health()

CLI: agi login · agi models · agi session act/so101 · agi run act/so101 --probe · agi rollout act/so101 -- --robot.type=so101_follower … · agi usage.

connect(), predict() and rollout need pip install "agi-diy[lerobot]". The REST part has no dependencies.

Errors subclass agi.Error with .error, .status, .retry_after_s.