readme: both GIFs (search + smooth beacon) — search re-recorded with smooth observer capture (287 frames, triangle found)

README.md

@@ -20,11 +20,12 @@ The agent can also be sent on an autonomous search: an orange triangle is
 hidden on the back side of one of the crates, and the model must explore the
 room with real vision, spot it, and report it. This recording shows the run
 from three angles — the top-down map, the actual first-person frames the
-model saw, and its chat/reasoning:
+model saw, and its chat/reasoning (recorded with smooth motion, ~2 Hz):
 
 ![search mission](search_mission.gif)
 
-Regenerate it with `python -m testbed.record_search --provider polza --out search_mission.gif`.
+Regenerate it with `python -m testbed.record_search --provider polza --goal search
+--out search_mission.gif --capture-hz 2.0 --cruise 0.8 --steps 60`.
 
 ## Smooth & proactive movement
 

testbed/record_search.py

@@ -236,8 +236,8 @@ async def run(args: argparse.Namespace) -> int:
                         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
+                        if len(frames) > 350:  # keep the GIF bounded
-                            frames[:100] = []
+                            frames[:150] = []
                         await asyncio.sleep(1.0 / args.capture_hz)
 
             agent_done = asyncio.Event()