Add π0 VLA model support (#4222)

Signed-off-by: Yichen Wang <yichen.wang@bytedance.com>
Signed-off-by: Didan Deng <33117903+wtomin@users.noreply.github.com>
Co-authored-by: Didan Deng <33117903+wtomin@users.noreply.github.com>
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Yichen WangandDidan Deng authored and GitHub committed 2026-08-17 14:29:17 +08:00
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# π0 (Pi-Zero) VLA — OpenPI realtime serving
[π0](https://www.physicalintelligence.company/blog/pi0) is a Vision-Language-Action
model from Physical Intelligence: multi-camera images + a language instruction +
robot proprioceptive state → a continuous action chunk via flow-matching denoising
(it does **not** emit text tokens). This example serves π0 over the OpenPI realtime
websocket protocol at `/v1/realtime/robot/openpi`.
## Install extras
The core `pip install -e .` does not include the OpenPI client used here:
- `openpi-client` (from the [openpi](https://github.com/Physical-Intelligence/openpi)
repo: `pip install -e packages/openpi-client`), `websockets`, `msgpack`, `msgpack-numpy`
## Weights
π0 uses the LeRobot `lerobot/pi0_base` checkpoint (HF, ~13 GB). Either let the server
download it (`MODEL=lerobot/pi0_base`) or point at a local copy
(`MODEL=/path/to/pi0_base`).
## Run the server
```bash
vllm serve lerobot/pi0_base --omni --port 8000 \
--served-model-name pi0 \
--deploy-config vllm_omni/deploy/pi0.yaml \
--enforce-eager --disable-log-stats
```
The deploy config (`vllm_omni/deploy/pi0.yaml`) declares a single diffusion stage
(`Pi0Pipeline`), float32, `max_num_seqs: 1`, and the `policy_server_config` handshake
metadata (3 cameras, `joint_position`, action horizon 50, action dim 32).
### Commonly adjusted `model_config` keys
These live under `stages[0].model_config` in `vllm_omni/deploy/pi0.yaml`:
| Key | Default | Meaning |
|---|---|---|
| `chunk_size` | `50` | Action-chunk length (timesteps) the model predicts per inference. |
| `num_inference_steps` | `10` | Flow-matching Euler denoising steps. |
| `max_action_dim` | `32` | Action dimensionality (state/action are padded to this). |
| `max_state_dim` | `32` | Proprioceptive-state dimensionality (zero-padded to this). |
| `image_resolution` | `[224, 224]` | Per-camera input size (square; SigLIP). |
| `tokenizer_max_length` | `48` | Max PaliGemma prompt tokens. |
| `max_cameras` | `3` | Camera slots the model attends to (real + `-1`-padded). |
| `image_feature_keys` | 3 `observation.images.*` keys | Camera order the model attends to. |
| `image_key_map` | `{}` | Map raw obs camera keys → `image_feature_keys` (empty = verbatim). |
The `policy_server_config` block below them is the OpenPI handshake metadata
advertised to the client; keep its `action_horizon` / `action_dim` /
`image_resolution` in sync with the `model_config` values above. The e2e test
`tests/e2e/online_serving/test_pi0_expansion.py::test_pi0_openpi_online` connects to a
live server and asserts the advertised metadata matches these `pi0.yaml` values.
## Run the client
```bash
python examples/online_serving/pi0/openpi_client.py --host 127.0.0.1 --port 8000 \
--prompt "pick up the red block and place it in the bin"
```
It connects, prints the server metadata, sends robot observations, and prints the
returned `[action_horizon, action_dim] = [50, 32]` action chunks. Replace the blank
cameras / zero state in `_make_dummy_obs` with real frames (HWC uint8) and
proprioceptive state to drive a robot.
### Observation format
The client sends a flat dict per inference:
```python
{
"observation.images.base_0_rgb": np.uint8[H, W, 3],
"observation.images.left_wrist_0_rgb": np.uint8[H, W, 3],
"observation.images.right_wrist_0_rgb":np.uint8[H, W, 3],
"state": np.float32[state_dim], # zero-padded to max_state_dim=32 server-side
"prompt": "pick up the red block",
"session_id": "<uuid>", # accepted but ignored (π0 is stateless)
}
```
Camera keys must match the server's `image_feature_keys` (the checkpoint's
`input_features` order). If your robot uses different camera names, set
`model_config.image_key_map` in `pi0.yaml` to map raw obs keys → feature keys.
## Correctness
π0's flow-matching kernel is bit-for-bit matched to the LeRobot `PI0Policy` reference
(`max|Δ| = 7.15e-07`, CPU/float32, fixed noise; see
`tests/diffusion/models/pi0/test_pi0_parity.py::test_pi0_vllm_omni_vs_lerobot`) and is
version-stable across transformers releases (the version-stability checks in
`tests/diffusion/models/pi0/test_pi0_units.py`). An OpenPI websocket online-serving e2e
lives in `tests/e2e/online_serving/test_pi0_expansion.py::test_pi0_openpi_online`.
## Limitations
- **Normalization stats**: `lerobot/pi0_base` uses identity normalization, which is
fully supported (state passes through, actions are returned in the model's space).
Per-dataset `norm_stats` declared in a checkpoint's `config.json` are honored, but
stats stored only in LeRobot's `policy_preprocessor.json` companion safetensors are
not yet loaded — a fine-tuned checkpoint that relies on those would need that bridge
added before its actions are in real-world units.
@@ -0,0 +1,119 @@
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Minimal OpenPI client for the π0 (Pi-Zero) VLA policy server.
Connects to a running π0 server (see README.md), sends a single robot
observation (3 cameras + state + language instruction), and prints the returned
continuous action chunk ``[action_horizon, action_dim]``.
The server speaks the OpenPI websocket protocol:
connect -> server sends msgpack(policy_server_config metadata)
infer -> client sends msgpack(obs), server replies msgpack(actions ndarray)
Usage:
python openpi_client.py --host 127.0.0.1 --port 8000 \
--prompt "pick up the red block"
"""
from __future__ import annotations
import argparse
import logging
import sys
import uuid
from pathlib import Path
from typing import Any
import numpy as np
try:
# Avoid shadowing the installed ``openpi_client`` package with this dir.
example_dir = str(Path(__file__).resolve().parent)
removed = sys.path and sys.path[0] == example_dir
if removed:
sys.path.pop(0)
try:
from openpi_client.websocket_client_policy import WebsocketClientPolicy
finally:
if removed:
sys.path.insert(0, example_dir)
except ImportError as exc: # pragma: no cover - runtime dependency guard
raise ImportError("π0 OpenPI example requires `openpi-client`.") from exc
logger = logging.getLogger("pi0_openpi_client")
DEFAULT_HOST = "127.0.0.1"
DEFAULT_PORT = 8000
DEFAULT_PATH = "/v1/realtime/robot/openpi"
DEFAULT_PROMPT = "pick up the red block and place it in the bin"
# π0 / pi0_base camera identities (must match the server's image_feature_keys).
CAMERA_KEYS = (
"observation.images.base_0_rgb",
"observation.images.left_wrist_0_rgb",
"observation.images.right_wrist_0_rgb",
)
STATE_DIM = 32
def _make_dummy_obs(prompt: str, session_id: str, image_size: int = 224) -> dict[str, Any]:
"""Build a single π0 observation with blank cameras + zero state.
Replace the zeros with real camera frames (HWC uint8) and proprioceptive
state to drive an actual robot.
"""
obs: dict[str, Any] = {cam: np.zeros((image_size, image_size, 3), dtype=np.uint8) for cam in CAMERA_KEYS}
obs["state"] = np.zeros(STATE_DIM, dtype=np.float32)
obs["prompt"] = prompt
obs["session_id"] = session_id
return obs
def _ws_uri(host: str, port: int, path: str) -> str:
"""Build the full websocket URI. WebsocketClientPolicy takes the whole URI as
``host`` (it has no separate path arg)."""
if host.startswith(("ws://", "wss://")):
return host
return f"ws://{host}:{port}{path}"
def _as_action_array(response: Any) -> np.ndarray:
if isinstance(response, dict) and response.get("type") == "error":
raise RuntimeError(f"Inference failed: {response.get('message', response)}")
return np.asarray(response, dtype=np.float32)
def main() -> int:
parser = argparse.ArgumentParser(description="π0 OpenPI client")
parser.add_argument("--host", default=DEFAULT_HOST)
parser.add_argument("--port", type=int, default=DEFAULT_PORT)
parser.add_argument("--path", default=DEFAULT_PATH)
parser.add_argument("--prompt", default=DEFAULT_PROMPT)
parser.add_argument("--num-steps", type=int, default=2, help="Inference observations to send.")
args = parser.parse_args()
logging.basicConfig(level=logging.INFO, format="%(message)s")
policy = WebsocketClientPolicy(host=_ws_uri(args.host, args.port, args.path))
metadata = dict(policy.get_server_metadata())
logger.info("Server metadata: %s", metadata)
session_id = str(uuid.uuid4())
for step in range(args.num_steps):
obs = _make_dummy_obs(args.prompt, session_id)
actions = _as_action_array(policy.infer(obs))
logger.info(
"[step %d] actions shape=%s mean=%.4f std=%.4f",
step,
actions.shape,
float(actions.mean()),
float(actions.std()),
)
if not np.isfinite(actions).all():
raise RuntimeError("Server returned non-finite actions.")
logger.info("Done — π0 OpenPI round-trip OK.")
return 0
if __name__ == "__main__":
raise SystemExit(main())