From b133c91d5d9adc98023380077256e1ded0c9f5d2 Mon Sep 17 00:00:00 2001
From: "liqiankun.1111" <liqiankun.1111@bytedance.com>
Date: Wed, 7 Oct 2026 22:04:05 +0800
Subject: [PATCH] feat(policy): add replaceable action-chunk inference API

Add a typed Policy.infer interface and HTTP service for task text, timestamped observations and history to decoded Microduck joint action chunks. FakePolicy and HttpPolicy share the interface, allowing a learned backend to replace rules without changing robotd.

The runner consumes latest robot.state feedback, trims expired predictions without rebasing timestamps, and submits through the existing robotd Action Session. It releases ownership on completion or failure and cannot reacquire control after an external stop. Add interface documentation, runnable examples and CI coverage.

Validation: make fix and make lint passed (Ruff formatting/lint and strict mypy). On Debian devbox, robotd built from this checkout with Rust 1.99; all 14 Python tests passed, including four real HTTP/Unix IPC/robotd/FakeIo tests for measured head motion, replacement, stop during inference, errors and timeout cleanup. git diff --check passed.

Scope: FakeIo execution is verified. Camera acquisition, trained VLA integration, MuJoCo balance and physical robot operation are not implemented or validated by this change; the existing fake/sim-only action admission remains unchanged.
---
 .github/workflows/ci.yml               |  22 +-
 README.md                              |   3 +-
 docs/README.md                         |   1 +
 docs/design/policy-interface.md        | 179 ++++++++
 policy/.gitignore                      |   5 +
 policy/Makefile                        |  10 +
 policy/README.md                       |  30 ++
 policy/pyproject.toml                  |  29 ++
 policy/src/duckmind_policy/__init__.py |   1 +
 policy/src/duckmind_policy/cli.py      |  37 ++
 policy/src/duckmind_policy/policy.py   |  45 ++
 policy/src/duckmind_policy/robot.py    | 159 +++++++
 policy/src/duckmind_policy/runner.py   | 104 +++++
 policy/src/duckmind_policy/schema.py   | 111 +++++
 policy/src/duckmind_policy/service.py  |  59 +++
 policy/tests/conftest.py               |  30 ++
 policy/tests/test_policy.py            | 128 ++++++
 policy/tests/test_robotd.py            | 164 +++++++
 policy/uv.lock                         | 598 +++++++++++++++++++++++++
 19 files changed, 1713 insertions(+), 2 deletions(-)
 create mode 100644 docs/design/policy-interface.md
 create mode 100644 policy/.gitignore
 create mode 100644 policy/Makefile
 create mode 100644 policy/README.md
 create mode 100644 policy/pyproject.toml
 create mode 100644 policy/src/duckmind_policy/__init__.py
 create mode 100644 policy/src/duckmind_policy/cli.py
 create mode 100644 policy/src/duckmind_policy/policy.py
 create mode 100644 policy/src/duckmind_policy/robot.py
 create mode 100644 policy/src/duckmind_policy/runner.py
 create mode 100644 policy/src/duckmind_policy/schema.py
 create mode 100644 policy/src/duckmind_policy/service.py
 create mode 100644 policy/tests/conftest.py
 create mode 100644 policy/tests/test_policy.py
 create mode 100644 policy/tests/test_robotd.py
 create mode 100644 policy/uv.lock

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index edbd00a..093749a 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -1,6 +1,6 @@
 # Checks on every push and pull request.
 #
-# Split into three parallel jobs deliberately, so the wait is the slowest one rather than the
+# Rust checks split into three parallel jobs deliberately, so the wait is the slowest one rather than the
 # total: `check` is fast and catches most things, `board` catches the class of problem that only
 # appears off the dev machine (cross-linking, glibc floors, unix-socket and permission
 # semantics), and `coverage` needs its own instrumented build.
@@ -43,6 +43,17 @@ env:
   RUSTFLAGS: -D warnings
 
 jobs:
+  policy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.9.2"
+          python-version: "3.11"
+      - run: uv sync --locked --directory policy
+      - run: make -C policy lint test
+
   check:
     runs-on: ubuntu-latest
     steps:
@@ -66,6 +77,15 @@ jobs:
       - run: cargo fmt --all --check
       - run: cargo clippy --workspace --all-targets
       - run: cargo test --workspace
+      - uses: astral-sh/setup-uv@v6
+        with:
+          version: "0.9.2"
+          python-version: "3.11"
+      - name: Policy through real robotd and FakeIo
+        run: |
+          cargo build --locked -p robotd
+          uv sync --locked --directory policy
+          ROBOTD_BIN="$PWD/target/debug/robotd" uv run --directory policy pytest -q tests/test_robotd.py
 
       # These are the pieces of this repo that run without being compiled — four on a robot,
       # and `provision-board.sh` and `dev-push.sh` on a developer's machine — so nothing else
diff --git a/README.md b/README.md
index fee0d46..3112325 100644
--- a/README.md
+++ b/README.md
@@ -18,7 +18,8 @@ Text + body state/history → learned policy → action chunk → robotd → rob
 
 Start with a language-conditioned motion policy, then add visual observations to explore
 vision-language-action (VLA) models. The model learns the motion; `robotd` owns timed execution
-and feedback. Training and model integration are ongoing work.
+and feedback. A [replaceable Policy interface and Fake backend](policy/README.md) exercise this
+execution path before training a model. Training and learned model integration are ongoing work.
 
 ## Origin
 
diff --git a/docs/README.md b/docs/README.md
index 36f5717..bcfc762 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -1,6 +1,7 @@
 # Docs
 
 Duckmind model execution: [Action Chunk API and timing contract](design/action-chunks.md).
+Model boundary and runner: [Policy inference interface](design/policy-interface.md).
 
 The [README](../README.md) is the front door — what a microduck is, and where to go. If you have
 one in front of you and want to drive it, start at the [cheat sheet](robot/cheatsheet.md).
diff --git a/docs/design/policy-interface.md b/docs/design/policy-interface.md
new file mode 100644
index 0000000..f123ccb
--- /dev/null
+++ b/docs/design/policy-interface.md
@@ -0,0 +1,179 @@
+# Policy inference interface
+
+The model boundary is `Policy.infer(PredictRequest) → ActionChunk`, implemented in
+[`policy/`](../../policy/README.md). A rule, local neural network, or remote model adapter can
+implement it. Inference does not acquire a robot or write motors; the runner owns a robotd
+Action Session and submits predictions to the existing executor.
+
+```text
+text + latest body observation + history
+                  ↓
+        Policy.infer / HTTP service       FakePolicy today; learned adapter later
+                  ↓
+        decoded joint ActionChunk
+                  ↓
+        Runner on robotd's machine        discard expired prefix; submit remaining timeline
+                  ↓ Unix JSON-RPC
+        robotd → Safety → RobotIo → body
+                  ↑
+              robot.state
+```
+
+This separates the **model contract** from the **execution contract**. The latter, including
+control ownership, admission, replacement, stops and hold behavior, belongs to
+[Action Chunks](action-chunks.md). No Rust IPC or control-loop behavior changes in this layer.
+
+## Model contract: microduck-joints-v1
+
+The Pydantic types in [`schema.py`](../../policy/src/duckmind_policy/schema.py) are the source
+of truth; FastAPI publishes their JSON Schema through `/openapi.json`. This is a Duckmind
+body-specific contract, not an industry standard and not a promise of cross-embodiment control.
+
+`POST /v1/policy/predict` accepts:
+
+| Field | Meaning |
+|---|---|
+| `schema_version` | `microduck-joints-v1`; defaults to this value, other versions reject. |
+| `task` | Free-form nonempty text. The API has no command enum. |
+| `observation.t_ns` | Positive robotd monotonic timestamp in nanoseconds, from `robot.state`. |
+| `observation.positions` | 15 measured absolute joint angles, radians, in robotd `JOINT_NAMES` order. |
+| `observation.velocities` | Optional 15 measured velocities, rad/s; absent means unavailable. |
+| `observation.imu` | Optional `gyro` (trunk rad/s), `quat` (trunk→world, scalar-first wxyz). |
+| `observation.images` | Optional map of camera name to `{t_ns, jpeg_base64}`; image capture time uses the same robot clock and cannot be newer than the observation. |
+| `history` | Up to eight earlier observations in strictly increasing timestamp order; excludes the current sample. |
+
+History is explicit and each inference request is independent: there is no server-side
+conversation or hidden per-robot temporal state. A model needing a context window builds it
+from these samples; a model needing a different history contract requires a versioned change.
+The stock runner sends recent body states only, with IMU/velocities when available. Camera
+capture, synchronization, and JPEG conversion are not implemented by this runner yet. An
+image-aware collector should use the existing WebRTC consumer path, preserve capture times,
+and form the same `PredictRequest`; do not invent a separate camera transport.
+
+The response contains:
+
+| Field | Meaning |
+|---|---|
+| `schema_version` | `microduck-joints-v1`. |
+| `observation_t_ns` | Exact timestamp from the request; ties the prediction to its observation. |
+| `step_ns` | Exactly 20,000,000 ns (50 Hz). |
+| `positions` | H × 15 finite absolute-radian targets, 1 ≤ H ≤ 100. |
+
+Frame `i` belongs to `[observation_t_ns + i*step_ns, observation_t_ns + (i+1)*step_ns)`.
+Inference latency consumes part of this horizon. The response contains no session ID or
+execution sequence: those belong to the runner, not the model. A response predicts motion;
+it does not report task success.
+
+A model adapter owns preprocessing, image decoding/resizing, state normalization, inference,
+action denormalization and joint mapping. It must return this decoded action space. Upstream
+Microduck's 14 normalized locomotion outputs are **not** directly compatible: the adapter must
+apply its model's offsets/scales and supply all 15 targets, including the mouth. The ±π wire
+bound is only a coarse numeric envelope, not collision checking or a balance guarantee.
+
+`GET /v1/policy` exposes joint order, timestep and action-space metadata. The runner also checks
+robotd's acquisition response against its expected joint order/timestep before inference.
+
+## Replace a backend
+
+The Python protocol has one method. No particular model architecture, trainer or GPU is required.
+
+```python
+from duckmind_policy.policy import FakePolicy, Policy
+from duckmind_policy.schema import ActionChunk, PredictRequest
+from duckmind_policy.service import HttpPolicy, create_app
+import uvicorn
+
+# Local implementation, useful before training exists:
+policy: Policy = FakePolicy()
+
+# The HTTP client implements the very same interface:
+remote: Policy = HttpPolicy("http://127.0.0.1:8081")
+
+# A future adapter implements this signature and performs its model-specific conversions:
+# def infer(self, request: PredictRequest) -> ActionChunk: ...
+uvicorn.run(create_app(policy), host="127.0.0.1", port=8081)
+```
+
+The built-in FakePolicy supports `向左看`/`往左看`/`look left`, right equivalents, and
+`保持姿势`/`hold`. It copies observed non-head joints and approaches an absolute head-yaw target
+at at most 0.5 rad/s in its predictions. Unsupported tasks fail explicitly; these aliases are
+only the fake backend's test vocabulary. A learned implementation can accept any task it has
+learned without changing the API.
+
+The server serializes inference and rejects overlap with HTTP 503 rather than queueing old
+observations. Invalid requests/unsupported tasks return 422, backend failures return 500.
+The HTTP client has one pooled connection, configured I/O timeout, and no automatic retries.
+A timed-out server inference may finish, but its result cannot submit itself to robotd. The
+service binds to loopback by default; remote access/authentication deployment is outside this
+prototype. The runner and robotd remain on the same machine; a GPU policy service can be remote.
+
+## Runner timing and lifecycle
+
+The runner acquires one Action Session, drains `robot.state` on a separate thread, and runs one
+inference request at a time. It keeps only the latest feedback and rejects feedback older than
+250 ms. It uses robot timestamps plus locally elapsed receive time; wall clocks and the model
+server's clock do not determine execution time.
+
+After inference, it verifies the session is still active, removes expired frames plus two ticks
+of admission lead, and submits the remaining targets with their **original timestamps**.
+It never rebases old predictions to "now". A completely expired response fails. Replanning occurs
+at most 200 ms after admission (earlier for a short remaining horizon); robotd retains the prior
+prefix until replacement starts. Models must produce a horizon long enough for inference,
+admission and the next prediction. A 1–2-frame response is schema-valid but too short for this
+runner's two-tick lead; slow inference can exhaust even a longer horizon. Admission failures stop
+the run rather than silently skipping, retrying or acquiring a new session.
+
+Normal duration completion, inference failure, Ctrl-C and lost feedback all leave through a
+`finally` block that ends this runner's session. An external stop invalidates it; a late result
+is discarded or rejected by robotd. Cleanup never issues a global stop against a newer owner.
+If the process dies or IPC is unavailable, robotd's own bounded timeline/expiry remains the
+fallback. Session end/expiry holds the last pose; it is not an active balance or recovery policy.
+
+## Run and verify
+
+Build robotd using the repository's Rust prerequisites, then start an isolated fake instance:
+
+```sh
+cargo build -p robotd -p robotctl
+printf '[audio]\nenabled=false\n[chorale]\naccept=false\n' > /tmp/duckmind-policy.toml
+./target/debug/robotd --fake --no-policy --socket /tmp/duckmind-policy.sock \
+  --params /tmp/duckmind-policy.toml
+```
+
+In another terminal, initialize it and allow the home transition to finish:
+
+```sh
+./target/debug/robotctl --robot-socket /tmp/duckmind-policy.sock robot init
+cd policy
+uv sync --locked
+uv run duckmind-policy serve
+```
+
+Then start inference/execution:
+
+```sh
+cd policy
+uv run duckmind-policy run --socket /tmp/duckmind-policy.sock --task '向左看' --duration 5
+```
+
+Unit/HTTP tests run with `make test`. Setting `ROBOTD_BIN` also runs real-daemon tests that
+launch their own fake robotd, initialize it, serve HTTP, submit/replan chunks, assert measured
+joint feedback, and verify a stop during inference rejects the late result. Without that variable
+those tests report skips, not success. CI sets it after building robotd.
+
+This validates the software path using FakeIo. A frozen-leg head-turn rule is not a MuJoCo
+walking/balancing policy; neither physics performance, camera-driven VLA behavior nor a physical
+robot is validated here. The existing robotd Action Chunk API remains restricted to fake/sim.
+
+## Precedents
+
+[OpenPI BasePolicy](https://github.com/Physical-Intelligence/openpi/blob/main/packages/openpi-client/src/openpi_client/base_policy.py)
+provides an interchangeable `infer(obs)` boundary and its WebSocket client implements that same
+abstraction. [OpenPI remote inference](https://github.com/Physical-Intelligence/openpi/blob/main/docs/remote_inference.md)
+separates the model server from robot execution.
+[LeRobot PreTrainedPolicy](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/pretrained.py)
+exposes `predict_action_chunk`, and its
+[async server tests](https://github.com/huggingface/lerobot/blob/main/tests/async_inference/test_policy_server.py)
+use a mock policy. Duckmind borrows the separation and replaceability, not their wire protocols
+or dependencies. Continuous execution during synchronous remote inference is supported; RTC,
+parallel inference requests and model training are not implemented by this package.
diff --git a/policy/.gitignore b/policy/.gitignore
new file mode 100644
index 0000000..c8dce3e
--- /dev/null
+++ b/policy/.gitignore
@@ -0,0 +1,5 @@
+.venv/
+__pycache__/
+.pytest_cache/
+.mypy_cache/
+.ruff_cache/
diff --git a/policy/Makefile b/policy/Makefile
new file mode 100644
index 0000000..340c974
--- /dev/null
+++ b/policy/Makefile
@@ -0,0 +1,10 @@
+.PHONY: fix lint test
+fix:
+	uv run ruff format .
+	uv run ruff check --fix .
+lint:
+	uv run ruff check .
+	uv run ruff format --check .
+	uv run mypy src
+test:
+	uv run pytest -q
diff --git a/policy/README.md b/policy/README.md
new file mode 100644
index 0000000..d8d94a9
--- /dev/null
+++ b/policy/README.md
@@ -0,0 +1,30 @@
+# Duckmind Policy
+
+A replaceable `Policy.infer(request) → ActionChunk` boundary. The same request/response can
+run locally or over HTTP; the runner connects predictions to the existing robotd executor.
+The included FakePolicy exercises plumbing with head turns and hold. It is not a trained VLA.
+
+From this directory:
+
+```sh
+uv sync --locked
+uv run duckmind-policy serve
+# Another terminal, after initializing robotd --fake or the simulated robot:
+uv run duckmind-policy run --socket /tmp/robot.sock --task '向左看' --duration 5
+```
+
+`--url` selects another compatible policy service; `--timeout` bounds HTTP I/O (default 0.8 s).
+The model service exposes `POST /v1/policy/predict`, `GET /v1/policy`, and OpenAPI at `/docs`.
+To serve a learned adapter, implement `Policy.infer` and pass it to `create_app(adapter)`.
+No runner or robotd changes are required if the adapter meets the contract.
+
+See [the Policy interface design](../docs/design/policy-interface.md) for schemas, timing,
+backend replacement, simulation setup, and current limits.
+
+```sh
+make fix
+make lint
+make test
+# Run the real HTTP → robotd → FakeIo integration tests too:
+ROBOTD_BIN="$(pwd)/../target/debug/robotd" make test
+```
diff --git a/policy/pyproject.toml b/policy/pyproject.toml
new file mode 100644
index 0000000..55e7c82
--- /dev/null
+++ b/policy/pyproject.toml
@@ -0,0 +1,29 @@
+[project]
+name = "duckmind-policy"
+version = "0.1.0"
+description = "Replaceable action-chunk policies for Duckmind"
+requires-python = ">=3.11"
+dependencies = ["fastapi>=0.115,<1", "httpx>=0.28,<1", "pydantic>=2.10,<3", "uvicorn>=0.34,<1"]
+
+[project.scripts]
+duckmind-policy = "duckmind_policy.cli:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[dependency-groups]
+dev = ["pytest>=8,<10", "ruff>=0.11,<1", "mypy>=1.15,<2"]
+
+[tool.ruff]
+target-version = "py311"
+line-length = 100
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "UP", "B"]
+
+[tool.mypy]
+strict = true
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
diff --git a/policy/src/duckmind_policy/__init__.py b/policy/src/duckmind_policy/__init__.py
new file mode 100644
index 0000000..fd317f1
--- /dev/null
+++ b/policy/src/duckmind_policy/__init__.py
@@ -0,0 +1 @@
+"""Model-independent policy inference and the robotd execution bridge."""
diff --git a/policy/src/duckmind_policy/cli.py b/policy/src/duckmind_policy/cli.py
new file mode 100644
index 0000000..6d55caf
--- /dev/null
+++ b/policy/src/duckmind_policy/cli.py
@@ -0,0 +1,37 @@
+"""Local serving and a bounded simulation runner."""
+
+import argparse
+import logging
+
+import uvicorn
+
+from duckmind_policy.policy import FakePolicy
+from duckmind_policy.robot import RobotClient
+from duckmind_policy.runner import run
+from duckmind_policy.service import HttpPolicy, create_app
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    commands = parser.add_subparsers(dest="command", required=True)
+    serve = commands.add_parser("serve", help="serve the built-in FakePolicy")
+    serve.add_argument("--host", default="127.0.0.1")
+    serve.add_argument("--port", type=int, default=8081)
+    runner = commands.add_parser("run", help="run an initialized fake/sim robot through HTTP")
+    runner.add_argument("--socket", required=True)
+    runner.add_argument("--url", default="http://127.0.0.1:8081")
+    runner.add_argument("--task", required=True)
+    runner.add_argument("--duration", type=float, default=5.0)
+    runner.add_argument("--timeout", type=float, default=0.8, help="HTTP timeout in seconds")
+    args = parser.parse_args()
+    logging.basicConfig(level=logging.INFO)
+    if args.command == "serve":
+        uvicorn.run(create_app(FakePolicy()), host=args.host, port=args.port)
+    else:
+        policy = HttpPolicy(args.url, timeout=args.timeout)
+        try:
+            run(RobotClient(args.socket), policy, args.task, args.duration)
+        except KeyboardInterrupt:
+            pass  # run's finally block releases its action session.
+        finally:
+            policy.close()
diff --git a/policy/src/duckmind_policy/policy.py b/policy/src/duckmind_policy/policy.py
new file mode 100644
index 0000000..4b78f08
--- /dev/null
+++ b/policy/src/duckmind_policy/policy.py
@@ -0,0 +1,45 @@
+"""Implement this protocol with rules, a local model, or a remote model adapter."""
+
+from typing import Protocol
+
+from duckmind_policy.schema import ActionChunk, PredictRequest
+
+
+class UnsupportedTask(ValueError):
+    """A backend cannot interpret the requested task."""
+
+
+class Policy(Protocol):
+    def infer(self, request: PredictRequest) -> ActionChunk:
+        """Predict targets; all temporal context is explicit in request.history."""
+        ...
+
+
+class FakePolicy:
+    """Deterministic head-only demo, not a learned policy or a balance controller."""
+
+    def infer(self, request: PredictRequest) -> ActionChunk:
+        targets = {
+            "向左看": 0.15,
+            "往左看": 0.15,
+            "look left": 0.15,
+            "向右看": -0.15,
+            "往右看": -0.15,
+            "look right": -0.15,
+            "保持姿势": None,
+            "hold": None,
+        }
+        task = request.task.strip().lower()
+        if task not in targets:
+            raise UnsupportedTask("FakePolicy supports: 向左看 / 向右看 / 保持姿势")
+        initial = request.observation.positions
+        goal = targets[task]
+        positions = []
+        for i in range(50):
+            frame = initial.copy()
+            if goal is not None:
+                # Absolute goal avoids accumulating a new relative turn on every replan.
+                delta = max(-0.5 * (i + 1) * 0.02, min(goal - initial[7], 0.5 * (i + 1) * 0.02))
+                frame[7] += delta
+            positions.append(frame)
+        return ActionChunk(observation_t_ns=request.observation.t_ns, positions=positions)
diff --git a/policy/src/duckmind_policy/robot.py b/policy/src/duckmind_policy/robot.py
new file mode 100644
index 0000000..1a1e91d
--- /dev/null
+++ b/policy/src/duckmind_policy/robot.py
@@ -0,0 +1,159 @@
+"""Small Unix JSON-RPC client and a latest-only robot.state subscription."""
+
+import json
+import socket
+import threading
+import time
+from pathlib import Path
+from typing import Literal
+
+from pydantic import BaseModel, JsonValue
+
+from duckmind_policy.schema import Imu, Observation, Vector15
+
+
+class RpcFailure(RuntimeError):
+    pass
+
+
+class RpcError(BaseModel):
+    code: int
+    message: str
+
+
+class Envelope(BaseModel):
+    id: int | None = None
+    method: str | None = None
+    result: JsonValue = None
+    params: JsonValue = None
+    error: RpcError | None = None
+
+
+class ActionStatus(BaseModel):
+    session_id: str | None = None
+    phase: Literal["idle", "waiting", "running", "ended"]
+    t_ns: int
+    reason: str | None = None
+    remaining: int = 0
+    last_write_ok: bool | None = None
+
+
+class State(BaseModel):
+    # robot.state has unrelated telemetry; this consumer reads only its declared subset.
+    t_ns: int
+    joints: Vector15
+    velocities: list[float] | None = None
+    imu: Imu | None = None
+    actions: ActionStatus | None = None
+
+    def observation(self) -> Observation:
+        return Observation(
+            t_ns=self.t_ns,
+            positions=self.joints,
+            velocities=self.velocities or None,
+            imu=self.imu,
+        )
+
+
+class Session(BaseModel):
+    session_id: str
+    t_ns: int
+    step_ns: int
+    joint_names: list[str]
+    positions: Vector15
+
+
+class RobotClient:
+    def __init__(self, path: str | Path, timeout: float = 1.0):
+        self.path = str(path)
+        self.timeout = timeout
+
+    def connect(self) -> socket.socket:
+        stream = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
+        try:
+            stream.settimeout(self.timeout)
+            stream.connect(self.path)
+        except OSError:
+            stream.close()
+            raise
+        return stream
+
+    def call(self, method: str, params: dict[str, JsonValue] | None = None) -> JsonValue:
+        with self.connect() as stream, stream.makefile("rb") as reader:
+            stream.sendall(encode(method, params or {}))
+            response = Envelope.model_validate_json(reader.readline())
+            if response.error is not None:
+                raise RpcFailure(f"{method}: {response.error.code} {response.error.message}")
+            if response.id != 1:
+                raise RpcFailure(f"{method}: mismatched response ID")
+            return response.result
+
+
+def encode(method: str, params: dict[str, JsonValue]) -> bytes:
+    return (
+        json.dumps({"jsonrpc": "2.0", "id": 1, "method": method, "params": params}) + "\n"
+    ).encode()
+
+
+class StateFeed:
+    """Drain feedback during inference; never replay a backlog as fresh observations."""
+
+    def __init__(self, robot: RobotClient):
+        self._stream = robot.connect()
+        self._stream.sendall(encode("robot.subscribe", {"hz": 50}))
+        self._condition = threading.Condition()
+        self._state: State | None = None
+        self._received_ns = 0
+        self._error: Exception | None = None
+        self._closed = False
+        self._thread = threading.Thread(target=self._read, daemon=True, name="robot-state")
+        self._thread.start()
+
+    def _read(self) -> None:
+        try:
+            with self._stream.makefile("rb") as reader:
+                while line := reader.readline():
+                    response = Envelope.model_validate_json(line)
+                    if response.error is not None:
+                        raise RpcFailure(response.error.message)
+                    if response.method != "robot.state":
+                        continue
+                    state = State.model_validate(response.params)
+                    with self._condition:
+                        if self._state is not None and state.t_ns <= self._state.t_ns:
+                            raise RpcFailure("robot clock stopped or regressed")
+                        self._state = state
+                        self._received_ns = time.monotonic_ns()
+                        self._condition.notify_all()
+                raise RpcFailure("robot.state stream closed")
+        except Exception as exc:
+            with self._condition:
+                self._error = exc
+                self._condition.notify_all()
+
+    def latest(self, timeout: float = 1.0) -> tuple[State, int]:
+        with self._condition:
+            self._condition.wait_for(
+                lambda: self._state is not None or self._error is not None, timeout=timeout
+            )
+            if self._error is not None:
+                raise RpcFailure("robot.state unavailable") from self._error
+            if self._state is None:
+                raise RpcFailure("no robot.state received")
+            age = time.monotonic_ns() - self._received_ns
+            if age > 250_000_000:
+                raise RpcFailure("robot.state is stale")
+            # Local elapsed time advances the last robot timestamp; Unix IPC adds little delay.
+            # This is not a wall-clock conversion and does not assume shared host boot times.
+            return self._state, self._state.t_ns + age
+
+    def close(self) -> None:
+        if self._closed:
+            return
+        self._closed = True
+        try:
+            self._stream.shutdown(socket.SHUT_RDWR)
+        except OSError:
+            pass
+        self._stream.close()
+        self._thread.join(timeout=2)
diff --git a/policy/src/duckmind_policy/runner.py b/policy/src/duckmind_policy/runner.py
new file mode 100644
index 0000000..7bd2d88
--- /dev/null
+++ b/policy/src/duckmind_policy/runner.py
@@ -0,0 +1,104 @@
+"""Receding-horizon inference. robotd remains the only timed action executor."""
+
+import logging
+import time
+
+from pydantic import JsonValue
+
+from duckmind_policy.policy import Policy
+from duckmind_policy.robot import RobotClient, RpcFailure, Session, StateFeed
+from duckmind_policy.schema import JOINT_NAMES, STEP_NS, ActionChunk, Observation, PredictRequest
+
+logger = logging.getLogger(__name__)
+
+
+def submission(
+    chunk: ActionChunk,
+    request: PredictRequest,
+    session: Session,
+    sequence: int,
+    now_ns: int,
+) -> dict[str, JsonValue]:
+    if chunk.observation_t_ns != request.observation.t_ns:
+        raise ValueError("policy returned a different observation timestamp")
+    # Actions are anchored at the observation, not inference completion. Allow two robot ticks
+    # for IPC admission, trim elapsed predictions, and never move an old prediction into the future.
+    first = max(0, (now_ns + 2 * STEP_NS - chunk.observation_t_ns + STEP_NS - 1) // STEP_NS)
+    if first >= len(chunk.positions):
+        raise ValueError("entire predicted chunk expired during inference")
+    return {
+        "session_id": session.session_id,
+        "sequence": sequence,
+        "observation_t_ns": chunk.observation_t_ns,
+        "start_t_ns": chunk.observation_t_ns + first * STEP_NS,
+        "step_ns": chunk.step_ns,
+        "positions": [list(frame) for frame in chunk.positions[first:]],
+    }
+
+
+def run(
+    robot: RobotClient,
+    policy: Policy,
+    task: str,
+    duration: float = 5.0,
+) -> int:
+    """Run an already-initialized fake/sim robot. Return admitted chunk count, not task success."""
+    if duration <= 0:
+        raise ValueError("duration must be positive")
+    session = Session.model_validate(robot.call("robot.actions.begin"))
+    feed: StateFeed | None = None
+    count = 0
+    try:
+        if tuple(session.joint_names) != JOINT_NAMES or session.step_ns != STEP_NS:
+            raise ValueError("robotd body contract differs from microduck-joints-v1")
+        feed = StateFeed(robot)
+        history: list[Observation] = []
+        deadline = time.monotonic() + duration
+        logger.info("policy session acquired: %s", session.session_id)
+        while time.monotonic() < deadline:
+            state, _ = feed.latest()
+            ensure_active(
+                state.actions.session_id if state.actions else None,
+                state.actions.phase if state.actions else None,
+                session,
+            )
+            observation = state.observation()
+            request = PredictRequest(task=task, observation=observation, history=history)
+            chunk = policy.infer(request)
+            # A stop/timeout while inference was running must not reacquire control.
+            state, now_ns = feed.latest()
+            ensure_active(
+                state.actions.session_id if state.actions else None,
+                state.actions.phase if state.actions else None,
+                session,
+            )
+            if time.monotonic() >= deadline:
+                break
+            payload = submission(chunk, request, session, count + 1, now_ns)
+            robot.call("robot.actions.submit", payload)
+            count += 1
+            logger.info("chunk admitted: session=%s sequence=%d", session.session_id, count)
+            history = [*history, observation][-8:]
+            # Replan before the tail expires; execution continues independently inside robotd.
+            end_ns = chunk.observation_t_ns + len(chunk.positions) * STEP_NS
+            delay = min(0.2, max(0.0, (end_ns - now_ns) / 1e9 / 2))
+            time.sleep(min(delay, max(0.0, deadline - time.monotonic())))
+        return count
+    finally:
+        if feed is not None:
+            feed.close()
+        try:
+            robot.call("robot.actions.end", {"session_id": session.session_id})
+        except (OSError, RpcFailure) as exc:
+            # Ending is scoped to our session. Never issue a global stop against a newer owner.
+            logger.warning(
+                "could not end policy session %s; it may already be invalidated: %s",
+                session.session_id,
+                exc,
+            )
+        logger.info("policy session finished: %s admitted=%d", session.session_id, count)
+
+
+def ensure_active(owner: str | None, phase: str | None, session: Session) -> None:
+    if owner != session.session_id or phase not in ("waiting", "running"):
+        raise RpcFailure("action session ended; discard prediction without reacquiring control")
diff --git a/policy/src/duckmind_policy/schema.py b/policy/src/duckmind_policy/schema.py
new file mode 100644
index 0000000..9691851
--- /dev/null
+++ b/policy/src/duckmind_policy/schema.py
@@ -0,0 +1,111 @@
+"""Versioned model boundary. Every action is already decoded into robotd joint space."""
+
+import base64
+import binascii
+import math
+from typing import Annotated, Literal
+
+from pydantic import BaseModel, ConfigDict, Field, FiniteFloat, field_validator, model_validator
+
+STEP_NS: Literal[20_000_000] = 20_000_000
+JOINT_NAMES = (
+    "left_hip_yaw",
+    "left_hip_roll",
+    "left_hip_pitch",
+    "left_knee",
+    "left_ankle",
+    "neck_pitch",
+    "head_pitch",
+    "head_yaw",
+    "head_roll",
+    "mouth",
+    "right_hip_yaw",
+    "right_hip_roll",
+    "right_hip_pitch",
+    "right_knee",
+    "right_ankle",
+)
+Vector15 = Annotated[list[FiniteFloat], Field(min_length=15, max_length=15)]
+Target15 = Annotated[
+    list[Annotated[FiniteFloat, Field(ge=-math.pi, le=math.pi)]],
+    Field(min_length=15, max_length=15),
+]
+Timestamp = Annotated[int, Field(strict=True, gt=0)]
+
+
+class Contract(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+
+
+class Imu(Contract):
+    """Trunk angular velocity (rad/s), orientation trunk→world as [w,x,y,z]."""
+
+    gyro: Annotated[list[FiniteFloat], Field(min_length=3, max_length=3)]
+    quat: Annotated[list[FiniteFloat], Field(min_length=4, max_length=4)]
+
+
+class Image(Contract):
+    """JPEG bytes in base64; capture time must be expressed in robotd's clock."""
+
+    t_ns: Timestamp
+    jpeg_base64: Annotated[str, Field(min_length=1, max_length=4_000_000)]
+
+    @field_validator("jpeg_base64")
+    @classmethod
+    def encoded_jpeg(cls, value: str) -> str:
+        try:
+            data = base64.b64decode(value, validate=True)
+        except binascii.Error as exc:
+            raise ValueError("invalid base64 image") from exc
+        if not data.startswith(b"\xff\xd8"):
+            raise ValueError("image must contain JPEG bytes")
+        return value
+
+
+class Observation(Contract):
+    t_ns: Timestamp
+    positions: Vector15
+    velocities: Vector15 | None = None
+    imu: Imu | None = None
+    images: Annotated[dict[str, Image], Field(max_length=4)] = Field(default_factory=dict)
+
+    @model_validator(mode="after")
+    def capture_times(self) -> "Observation":
+        if any(image.t_ns > self.t_ns for image in self.images.values()):
+            raise ValueError("image capture time is newer than the observation")
+        return self
+
+
+class PredictRequest(Contract):
+    schema_version: Literal["microduck-joints-v1"] = "microduck-joints-v1"
+    task: Annotated[str, Field(min_length=1, max_length=4096)]
+    observation: Observation
+    history: Annotated[list[Observation], Field(max_length=8)] = Field(default_factory=list)
+
+    @field_validator("task")
+    @classmethod
+    def nonblank_task(cls, value: str) -> str:
+        if not value.strip():
+            raise ValueError("task must not be blank")
+        return value
+
+    @model_validator(mode="after")
+    def ordered_history(self) -> "PredictRequest":
+        times = [sample.t_ns for sample in self.history] + [self.observation.t_ns]
+        if any(a >= b for a, b in zip(times, times[1:], strict=False)):
+            raise ValueError("history must precede the observation in timestamp order")
+        return self
+
+
+class ActionChunk(Contract):
+    schema_version: Literal["microduck-joints-v1"] = "microduck-joints-v1"
+    observation_t_ns: Timestamp
+    step_ns: Literal[20_000_000] = STEP_NS
+    positions: Annotated[list[Target15], Field(min_length=1, max_length=100)]
+
+
+class PolicyInfo(Contract):
+    schema_version: Literal["microduck-joints-v1"] = "microduck-joints-v1"
+    joint_names: tuple[str, ...] = JOINT_NAMES
+    step_ns: Literal[20_000_000] = STEP_NS
+    action_space: Literal["absolute_joint_position_rad"] = "absolute_joint_position_rad"
diff --git a/policy/src/duckmind_policy/service.py b/policy/src/duckmind_policy/service.py
new file mode 100644
index 0000000..abfb55e
--- /dev/null
+++ b/policy/src/duckmind_policy/service.py
@@ -0,0 +1,59 @@
+"""The HTTP transport carries the same typed contract as local Policy.infer."""
+
+import logging
+import threading
+
+import httpx
+from fastapi import FastAPI, HTTPException
+
+from duckmind_policy.policy import Policy, UnsupportedTask
+from duckmind_policy.schema import ActionChunk, PolicyInfo, PredictRequest
+
+logger = logging.getLogger(__name__)
+
+
+def create_app(policy: Policy) -> FastAPI:
+    app = FastAPI(title="Duckmind Policy", version="1")
+    gate = threading.Lock()
+
+    @app.get("/v1/policy")
+    def info() -> PolicyInfo:
+        return PolicyInfo()
+
+    @app.post("/v1/policy/predict")
+    def predict(request: PredictRequest) -> ActionChunk:
+        # GPU backends need bounded concurrency; never queue stale observations behind inference.
+        if not gate.acquire(blocking=False):
+            raise HTTPException(503, "policy is busy")
+        try:
+            result = policy.infer(request)
+            if result.observation_t_ns != request.observation.t_ns:
+                raise ValueError("policy returned a chunk for a different observation")
+            return result
+        except UnsupportedTask as exc:
+            raise HTTPException(422, str(exc)) from exc
+        except Exception as exc:
+            logger.exception("policy inference failed")
+            raise HTTPException(500, "policy inference failed") from exc
+        finally:
+            gate.release()
+
+    return app
+
+
+class HttpPolicy:
+    def __init__(self, url: str, timeout: float = 0.8):
+        self._client = httpx.Client(
+            base_url=url.rstrip("/"),
+            timeout=timeout,
+            trust_env=False,
+            limits=httpx.Limits(max_connections=1, max_keepalive_connections=1),
+        )
+
+    def infer(self, request: PredictRequest) -> ActionChunk:
+        response = self._client.post("/v1/policy/predict", json=request.model_dump(mode="json"))
+        response.raise_for_status()
+        return ActionChunk.model_validate_json(response.content)
+
+    def close(self) -> None:
+        self._client.close()
diff --git a/policy/tests/conftest.py b/policy/tests/conftest.py
new file mode 100644
index 0000000..e66b316
--- /dev/null
+++ b/policy/tests/conftest.py
@@ -0,0 +1,30 @@
+import socket
+import threading
+import time
+from collections.abc import Iterator
+from contextlib import contextmanager
+
+import uvicorn
+
+from duckmind_policy.policy import Policy
+from duckmind_policy.service import create_app
+
+
+@contextmanager
+def serve(policy: Policy) -> Iterator[str]:
+    with socket.socket() as listener:
+        listener.bind(("127.0.0.1", 0))
+        port = listener.getsockname()[1]
+        server = uvicorn.Server(uvicorn.Config(create_app(policy), log_level="error"))
+        thread = threading.Thread(target=server.run, kwargs={"sockets": [listener]}, daemon=True)
+        thread.start()
+        try:
+            deadline = time.monotonic() + 5
+            while not server.started:
+                assert thread.is_alive() and time.monotonic() < deadline
+                time.sleep(0.01)
+            yield f"http://127.0.0.1:{port}"
+        finally:
+            server.should_exit = True
+            thread.join(timeout=5)
+            assert not thread.is_alive()
diff --git a/policy/tests/test_policy.py b/policy/tests/test_policy.py
new file mode 100644
index 0000000..c9a4213
--- /dev/null
+++ b/policy/tests/test_policy.py
@@ -0,0 +1,128 @@
+import base64
+import re
+import threading
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import httpx
+import pytest
+from conftest import serve
+from pydantic import ValidationError
+
+from duckmind_policy.policy import FakePolicy
+from duckmind_policy.robot import Session
+from duckmind_policy.runner import submission
+from duckmind_policy.schema import (
+    JOINT_NAMES,
+    STEP_NS,
+    ActionChunk,
+    Observation,
+    PredictRequest,
+)
+from duckmind_policy.service import HttpPolicy
+
+
+def request(task="向左看", t_ns=1_000_000_000):
+    return PredictRequest(task=task, observation=Observation(t_ns=t_ns, positions=[0.0] * 15))
+
+
+def test_contract_tracks_robotd_joint_order():
+    root = Path(__file__).resolve().parents[2]
+    source = (root / "duck-ipc-proto/src/lib.rs").read_text()
+    array = re.search(r"pub const JOINT_NAMES[^=]*=\s*\[(.*?)\];", source, re.S).group(1)
+    assert tuple(re.findall(r'"([a-z_]+)"', array)) == JOINT_NAMES
+    assert (
+        f"ACTION_STEP_NS: u64 = {STEP_NS:_}" in (root / "duck-ipc-proto/src/actions.rs").read_text()
+    )
+
+
+@pytest.mark.parametrize("bad", [[0.0] * 14, [float("nan")] * 15, [4.0] * 15])
+def test_rejects_invalid_model_actions(bad):
+    with pytest.raises(ValidationError):
+        ActionChunk(observation_t_ns=1, positions=[bad])
+
+
+def test_text_images_history_share_one_contract():
+    data = request().model_dump()
+    data["observation"]["images"] = {
+        "front": {"t_ns": 900_000_000, "jpeg_base64": base64.b64encode(b"\xff\xd8demo").decode()}
+    }
+    data["history"] = [request(t_ns=800_000_000).observation.model_dump()]
+    parsed = PredictRequest.model_validate(data)
+    assert parsed.observation.images["front"].t_ns < parsed.observation.t_ns
+    data["history"][0]["t_ns"] = data["observation"]["t_ns"]
+    with pytest.raises(ValidationError, match="history"):
+        PredictRequest.model_validate(data)
+
+
+def test_fake_paraphrases_and_absolute_goal_preserve_other_joints():
+    policy = FakePolicy()
+    chunk = policy.infer(request())
+    assert chunk == policy.infer(request("往左看"))
+    assert chunk.positions[-1][7] == pytest.approx(0.15)
+    assert all(q == 0.0 for frame in chunk.positions for i, q in enumerate(frame) if i != 7)
+    req = request(t_ns=2_000_000_000)
+    req.observation.positions = chunk.positions[-1]
+    assert policy.infer(req).positions[-1] == chunk.positions[-1]
+    assert policy.infer(request("hold")).positions[-1] == [0.0] * 15
+
+
+def test_http_transport_is_an_interchangeable_policy():
+    with serve(FakePolicy()) as url:
+        policy = HttpPolicy(url)
+        try:
+            assert policy.infer(request()) == FakePolicy().infer(request())
+            with pytest.raises(httpx.HTTPStatusError) as exc:
+                policy.infer(request("推球"))
+            assert exc.value.response.status_code == 422
+        finally:
+            policy.close()
+
+
+def test_service_rejects_misaligned_response_and_invalid_request():
+    class WrongTime:
+        def infer(self, req):
+            return ActionChunk(observation_t_ns=req.observation.t_ns + 1, positions=[[0.0] * 15])
+
+    with serve(WrongTime()) as url, httpx.Client(base_url=url) as client:
+        assert client.post("/v1/policy/predict", json=request().model_dump()).status_code == 500
+        assert client.post("/v1/policy/predict", json={"task": "hold"}).status_code == 422
+        assert client.get("/v1/policy").json()["joint_names"] == list(JOINT_NAMES)
+
+
+def test_busy_backend_does_not_queue_stale_observations():
+    entered, release = threading.Event(), threading.Event()
+
+    class Slow:
+        def infer(self, req):
+            entered.set()
+            assert release.wait(3)
+            return FakePolicy().infer(req)
+
+    with serve(Slow()) as url, ThreadPoolExecutor(1) as pool:
+        first = pool.submit(httpx.post, f"{url}/v1/policy/predict", json=request().model_dump())
+        try:
+            assert entered.wait(2)
+            assert (
+                httpx.post(f"{url}/v1/policy/predict", json=request().model_dump()).status_code
+                == 503
+            )
+        finally:
+            release.set()
+        assert first.result().status_code == 200
+
+
+def test_runner_trims_elapsed_prefix_without_rebasing_time():
+    req = request()
+    chunk = FakePolicy().infer(req)
+    session = Session(
+        session_id="s", t_ns=1, step_ns=STEP_NS, joint_names=list(JOINT_NAMES), positions=[0.0] * 15
+    )
+    payload = submission(chunk, req, session, 3, req.observation.t_ns + 5 * STEP_NS)
+    assert payload["start_t_ns"] == req.observation.t_ns + 7 * STEP_NS
+    assert payload["positions"] == chunk.positions[7:]
+    assert payload["sequence"] == 3
+    with pytest.raises(ValueError, match="expired"):
+        submission(chunk, req, session, 4, req.observation.t_ns + 50 * STEP_NS)
+    with pytest.raises(ValueError, match="timestamp"):
+        submission(chunk, request(t_ns=2_000_000_000), session, 4, 2_000_000_000)
diff --git a/policy/tests/test_robotd.py b/policy/tests/test_robotd.py
new file mode 100644
index 0000000..fb077ba
--- /dev/null
+++ b/policy/tests/test_robotd.py
@@ -0,0 +1,164 @@
+"""Real HTTP → Runner → Unix IPC → robotd/FakeIo → measured state, no replacement executor.
+
+Set ROBOTD_BIN to a robotd built from this checkout. Without it these integration tests skip.
+"""
+
+import os
+import subprocess
+import threading
+import time
+from concurrent.futures import ThreadPoolExecutor
+
+import httpx
+import pytest
+from conftest import serve
+
+from duckmind_policy.policy import FakePolicy
+from duckmind_policy.robot import RobotClient, RpcFailure, StateFeed
+from duckmind_policy.runner import run
+from duckmind_policy.service import HttpPolicy
+
+
+@pytest.fixture
+def robot(tmp_path):
+    binary = os.environ.get("ROBOTD_BIN")
+    if not binary:
+        pytest.skip("set ROBOTD_BIN for real robotd/FakeIo integration")
+    socket = tmp_path / "robot.sock"
+    params = tmp_path / "robotd.toml"
+    params.write_text("[audio]\nenabled=false\n[chorale]\naccept=false\n")
+    with subprocess.Popen(
+        [binary, "--fake", "--no-policy", "--socket", str(socket), "--params", str(params)],
+        env={**os.environ, "RUST_LOG": "error"},
+        stdout=subprocess.DEVNULL,
+    ) as process:
+        try:
+            deadline = time.monotonic() + 8
+            while not socket.exists():
+                assert process.poll() is None and time.monotonic() < deadline
+                time.sleep(0.01)
+            client = RobotClient(socket)
+            client.call("robot.init")
+            # Readiness includes warm IMU and completion of the home transition.
+            while True:
+                try:
+                    session = client.call("robot.actions.begin")
+                    client.call("robot.actions.end", {"session_id": session["session_id"]})
+                    break
+                except RpcFailure:
+                    assert time.monotonic() < deadline
+                    time.sleep(0.02)
+            yield client
+        finally:
+            process.terminate()
+            try:
+                process.wait(timeout=5)
+            except subprocess.TimeoutExpired:
+                process.kill()
+                process.wait()
+
+
+def wait_state(feed, predicate):
+    deadline = time.monotonic() + 4
+    while time.monotonic() < deadline:
+        state, _ = feed.latest()
+        if predicate(state):
+            return state
+        time.sleep(0.01)
+    pytest.fail("expected measured feedback not received")
+
+
+def test_http_policy_drives_measured_joints_and_releases_session(robot):
+    feed = StateFeed(robot)
+    with serve(FakePolicy()) as url, ThreadPoolExecutor(1) as pool:
+        policy = HttpPolicy(url)
+        try:
+            initial, _ = feed.latest()
+            result = pool.submit(run, robot, policy, "向左看", 1.5)
+            reached = wait_state(feed, lambda s: abs(s.joints[7] - 0.15) < 1e-6)
+            assert reached.actions.last_write_ok is True
+            assert reached.joints[:7] == pytest.approx(initial.joints[:7])
+            assert reached.joints[8:] == pytest.approx(initial.joints[8:])
+            assert result.result(timeout=4) >= 2  # replacement/replanning, not one static write
+            wait_state(feed, lambda s: s.actions.phase == "ended")
+        finally:
+            policy.close()
+            feed.close()
+
+
+def test_stop_during_inference_discards_late_prediction(robot):
+    entered, release = threading.Event(), threading.Event()
+
+    class Delayed:
+        def infer(self, req):
+            entered.set()
+            assert release.wait(3)
+            return FakePolicy().infer(req)
+
+    feed = StateFeed(robot)
+    with serve(Delayed()) as url, ThreadPoolExecutor(1) as pool:
+        policy = HttpPolicy(url, timeout=2)
+        try:
+            result = pool.submit(run, robot, policy, "向左看", 3)
+            assert entered.wait(2)
+            robot.call("robot.stop")
+            stopped = wait_state(feed, lambda s: s.actions.phase == "ended")
+            release.set()
+            # Feedback and HTTP arrive independently: either the runner or robotd may reject it.
+            with pytest.raises(RpcFailure):
+                result.result(timeout=3)
+            time.sleep(0.1)
+            after, _ = feed.latest()
+            assert after.joints == stopped.joints
+            assert after.actions.phase == "ended"
+        finally:
+            release.set()
+            policy.close()
+            feed.close()
+
+
+def test_http_failure_ends_session(robot):
+    feed = StateFeed(robot)
+    with serve(FakePolicy()) as url:
+        policy = HttpPolicy(url)
+        try:
+            with pytest.raises(httpx.HTTPStatusError):
+                run(robot, policy, "unsupported task")
+            wait_state(feed, lambda s: s.actions.phase == "ended")
+        finally:
+            policy.close()
+            feed.close()
+
+
+def test_inference_timeout_cancels_previously_admitted_tail(robot):
+    entered, release = threading.Event(), threading.Event()
+
+    class TimeoutOnReplan:
+        calls = 0
+
+        def infer(self, req):
+            self.calls += 1
+            if self.calls > 1:
+                entered.set()
+                assert release.wait(3)
+            return FakePolicy().infer(req)
+
+    feed = StateFeed(robot)
+    with serve(TimeoutOnReplan()) as url, ThreadPoolExecutor(1) as pool:
+        policy = HttpPolicy(url, timeout=0.15)
+        try:
+            result = pool.submit(run, robot, policy, "向左看", 3)
+            assert entered.wait(2)
+            moving, _ = feed.latest()
+            assert moving.actions.phase == "running"
+            with pytest.raises(httpx.TimeoutException):
+                result.result(timeout=2)
+            stopped = wait_state(feed, lambda s: s.actions.phase == "ended")
+            release.set()
+            time.sleep(0.1)
+            after, _ = feed.latest()
+            assert after.joints == stopped.joints
+        finally:
+            release.set()
+            policy.close()
+            feed.close()
diff --git a/policy/uv.lock b/policy/uv.lock
new file mode 100644
index 0000000..1d4a3f9
--- /dev/null
+++ b/policy/uv.lock
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