record: observer-based capture (--capture-hz) + --goal beacon; smooth_mission.gif artifact (136 frames, gliding motion verified); README section

README.md

@@ -26,6 +26,18 @@ model saw, and its chat/reasoning:
 
 Regenerate it with `python -m testbed.record_search --provider polza --out search_mission.gif`.
 
+## Smooth & proactive movement
+
+The same recording setup with a beacon mission and the cruise mode — the
+capsule glides with animated `move`/`turn` calls and keeps moving while the
+model thinks (`--cruise`). Frames are sampled at ~2.5 Hz by an observer
+client, so the GIF shows the actual motion, not step endpoints:
+
+![smooth mission](smooth_mission.gif)
+
+Regenerate with `python -m testbed.record_search --provider polza --goal beacon
+--out smooth_mission.gif --capture-hz 2.5 --cruise 1.0`.
+
 ## Layout
 
 ```

testbed/record_search.py

@@ -139,24 +139,22 @@ async def run(args: argparse.Namespace) -> int:
         api_key=args.api_key,
         model=args.model,
     )
+    from testbed.llm_agent import MISSION
+
     bridge = build_bridge()
+    if args.goal == "search":
         # Fixed marker so the GIF tells a clear story (crate_blue, east face).
         bridge.world.marker = {
-        "box": "crate_blue",
+            "box": "crate_blue", "face": "x1", "u": 0.5, "v": 0.55,
-        "face": "x1",
+            "size": 0.42, "color": (255, 150, 40),
-        "u": 0.5,
-        "v": 0.55,
-        "size": 0.42,
-        "color": (255, 150, 40),
         }
         m = bridge.world.marker_world_pos()
-    print(
+        print(f"[record] triangle marker on crate_blue east face at {tuple(round(v, 2) for v in m)}")
-        f"[record] triangle marker on crate_blue east face at {tuple(round(v, 2) for v in m)}"
-    )
 
     frames: list[Image.Image] = []
     chat = ChatPane()
     marker_seen = False
+    samples: list[tuple[float, float]] = []  # capsule positions per captured frame
 
     def log(role: str, msg: str) -> None:
         print(f"  [{role}] {msg}")
@@ -168,25 +166,33 @@ async def run(args: argparse.Namespace) -> int:
         async with AICCClient(transport) as client:
             manifest = await client.handshake()
             ctl = LLMController(
-                client,
+                client, manifest,
-                manifest,
+                base_url=base_url, api_key=api_key, model=model,
-                base_url=base_url,
+                system_prompt=SEARCH_MISSION if args.goal == "search" else MISSION,
-                api_key=api_key,
-                model=model,
-                system_prompt=SEARCH_MISSION,
                 log=log,
             )
+            if args.goal == "search":
                 ctl.messages = [
                     ctl.messages[0],
-                {
+                    {"role": "user", "content": (
-                    "role": "user",
-                    "content": (
                         "MISSION: explore the room, find the orange triangle on the "
                         "back of a crate, and report it. Keep exploring until found."
-                    ),
+                    )},
-                },
                 ]
                 chat.add("mission", "MISSION: find the orange triangle")
+            else:
+                ctl.messages.append({
+                    "role": "user",
+                    "content": (
+                        "MISSION: reach the beacon and activate it. "
+                        "Keep calling tools until it is done. Move smoothly (use "
+                        "duration on move/turn). The capsule cruises while you think."
+                    ),
+                })
+                chat.add("mission", "MISSION: reach and activate the beacon")
+
+            if args.goal == "search" and not args.capture_hz:
+                # capture at frame-attach events (one frame per step)
                 orig_frame = ctl._frame_message
 
                 def record_frame(png: str, note: str):
@@ -198,6 +204,7 @@ async def run(args: argparse.Namespace) -> int:
                     )
                     top = _topdown_frame(bridge, ctl.path, len(frames), marker_seen)
                     frames.append(_compose(top, view, chat.render()))
+                    samples.append((bridge.world.capsule.x, bridge.world.capsule.z))
                     return orig_frame(png, note)
 
                 ctl._frame_message = record_frame  # type: ignore[method-assign]
@@ -205,25 +212,50 @@ async def run(args: argparse.Namespace) -> int:
             def is_success(turn):
                 nonlocal marker_seen
                 for c in turn.calls:
-                    if (
+                    if c.name == "report" and c.ok and c.output and c.output.get("verified"):
-                        c.name == "report"
-                        and c.ok
-                        and c.output
-                        and c.output.get("verified")
-                    ):
                         marker_seen = True
                         return True
                 return False
 
-            summary = await run_llm_agent_loop(
+            async def observer(agent_done: asyncio.Event) -> None:
-                ctl,
+                """Sample the world at a fixed rate so the GIF shows the actual
-                args.steps,
+                gliding motion (mid-animation frames), not just step endpoints."""
-                log=log,
+                obs_transport = WebSocketClientTransport("ws://127.0.0.1:8765")
-                look_every=1,
+                async with AICCClient(obs_transport) as obs:
-                cruise=args.cruise,
+                    await obs.handshake()
-                autonomous=True,
+                    while not agent_done.is_set():
-                is_success=is_success,
+                        try:
+                            out = (await obs.call_tool("vision", {})).output
+                        except Exception:  # noqa: BLE001 - session teardown
+                            break
+                        view = (
+                            Image.open(io.BytesIO(base64.b64decode(out["png_b64"])))
+                            .convert("RGB")
+                            .resize((PANEL, PANEL))
                         )
+                        samples.append((bridge.world.capsule.x, bridge.world.capsule.z))
+                        top = _topdown_frame(bridge, ctl.path, len(frames), marker_seen)
+                        frames.append(_compose(top, view, chat.render()))
+                        if len(frames) > 500:  # keep the GIF bounded
+                            frames[:100] = []
+                        await asyncio.sleep(1.0 / args.capture_hz)
+
+            agent_done = asyncio.Event()
+            obs_task = None
+            if args.capture_hz:
+                obs_task = asyncio.create_task(observer(agent_done))
+            try:
+                summary = await run_llm_agent_loop(
+                    ctl, args.steps, log=log,
+                    look_every=2 if args.goal == "beacon" else 1,
+                    cruise=args.cruise,
+                    autonomous=args.goal == "search",
+                    is_success=is_success if args.goal == "search" else None,
+                )
+            finally:
+                agent_done.set()
+                if obs_task is not None:
+                    await obs_task
 
     # Final frame: end state of the map.
     if marker_seen:
@@ -236,6 +268,19 @@ async def run(args: argparse.Namespace) -> int:
     )
     frames.append(_compose(top, last_view, chat.render()))
 
+    # Smoothness check: mean movement between consecutive captured frames.
+    if len(samples) > 2:
+        from itertools import pairwise
+
+        deltas = [
+            ((b[0] - a[0]) ** 2 + (b[1] - a[1]) ** 2) ** 0.5
+            for a, b in pairwise(samples)
+        ]
+        moving = [d for d in deltas if d > 0.02]
+        if moving:
+            print(f"[record] motion between frames: mean {sum(moving)/len(moving):.2f} m "
+                  f"(max {max(moving):.2f}) over {len(moving)} moving samples")
+
     out = Path(args.out)
     if frames:
         frames[0].save(
@@ -248,21 +293,34 @@ async def run(args: argparse.Namespace) -> int:
         frames[-1].save(out.with_suffix(".png"))
         print(f"[record] wrote {out} ({len(frames)} frames, {args.duration} ms/frame)")
     print(f"[record] mission result: {summary.get('result')}")
-    return 0 if marker_seen else 1
+    return 0 if (marker_seen or summary.get("interacted")) else 1
 
 
 def main() -> int:
     parser = argparse.ArgumentParser(
-        description="Record a search mission into a three-view GIF."
+        description="Record a mission into a three-view GIF (map | first person | chat)."
     )
     parser.add_argument("--out", default="search_mission.gif")
+    parser.add_argument(
+        "--goal",
+        choices=["search", "beacon"],
+        default="search",
+        help="which mission to record (default search)",
+    )
     parser.add_argument("--provider", default=None)
     parser.add_argument("--base-url", default=None)
     parser.add_argument("--api-key", default=None)
     parser.add_argument("--model", default=None)
     parser.add_argument("--steps", type=int, default=45)
     parser.add_argument("--cruise", type=float, default=0.6)
-    parser.add_argument("--duration", type=int, default=350, help="ms per GIF frame")
+    parser.add_argument("--duration", type=int, default=150, help="ms per GIF frame")
+    parser.add_argument(
+        "--capture-hz",
+        type=float,
+        default=0.0,
+        help="sample frames at this rate (Hz) with an observer client to show "
+        "gliding motion; 0 = one frame per step (search default)",
+    )
     args = parser.parse_args()
     try:
         return asyncio.run(run(args))