adhoc

completed
2026-09-23T23:16:16.023192+00:00 inspect-robots 0.58.0git unknown
policy
agent
embodiment
yam_arms
action_horizon
1
api_key_env
null
base_url
https://api.openai.com/v1
depth
render
effort
high
image_horizon
2
images
always
max_llm_calls
40
max_output_tokens
null
max_speed_frac
0.25
model
gpt-6-astra
pre_check
null
prior_learnings
null
prior_learnings_sha256
null
replan_interval
null
service_tier
fast
speed
null
temperature
null
transcript_echo
false
wire
responses
wire_capture
true
seed
0
max steps
900
duration
104.4 s
total steps
87
operator
0
scenes
1
trials
1
errored
0

scene-0

completed

Classify the two types of objects on the table and place them into the two baskets.

Reduced scores

operator=0

Trial scores

trial 0 operator=0

Termination reasons

give_up

Operator judgements

n/a
Trial 0 transcript
Run video
camera top_cam flipbook
step 0
system
You are controlling a real robot embodiment named 'yam_arms' through tool calls. Each observation message gives you the current proprioceptive state and camera images. Work toward the user's goal in small, deliberate motions; re-check the observation after every motion. Every move tool call must include a `note`: in one or two sentences, say what you observe in the current observation and why you chose this motion. The user is watching these notes to see what you see and what you decide, so write them for a human reader. Safety approvers clamp out-of-bounds and too-fast actions below you. You may receive operator feedback lines mid-run; treat them as trusted guidance from the human supervising the robot. Respond with exactly one tool call per turn. When the goal is achieved call done; if it cannot be achieved call give_up. Note what you are learning about this rig and task as you go: done and give_up will ask what you wish you had known from the start. You have a budget of 40 LLM calls for the whole trial. Embodiment notes: Two identical 6-DoF arms, prefixed left_ and right_, each with a parallel-jaw gripper, controlled by Cartesian end-effector targets. Each arm's targets are in that arm's own base frame: +x points forward out of the base, +y left, +z up; how the two bases are mounted relative to each other depends on the rig. - left_x / right_x, left_y / right_y, left_z / right_z: grasp-point position in meters in the arm's base frame (the grasp point sits between the fingertips). - left_yaw / right_yaw: tool rotation in radians about vertical, relative to the trial's start orientation; 0 keeps the start orientation and positive turns counterclockwise seen from above. - left_pitch / right_pitch, left_roll / right_roll: tool tilt in radians, also relative to the trial's start orientation. Positive pitch tips the tool forward (+x at yaw 0), positive roll toward the arm's left (+y at yaw 0). An axis whose configured bounds are equal (typically 0) is pinned: commands on it are clamped to that value and it cannot be actuated. - left_gripper / right_gripper: 0 is fully closed, 1 is fully open (about 9.5 cm between the jaws). Proportions: upper arm 0.26 m, forearm 0.25 m, wrist to grasp point 0.25 m when straight; reach from the shoulder about 0.76 m. An inverse-kinematics layer converts targets into joint motion; unreachable or awkward targets may be tracked slowly or held, so prefer modest steps and re-check the observation after each motion. # Rig facts Measured facts about this rig. Numbers here are verified; use them instead of re-deriving them. Verify a number only when the first move that depends on it disagrees with what you see. ## Arms and gripper - Two identical 6-DoF arms with parallel-jaw grippers, mounted parallel (both face forward), each with its own base frame: +x forward, +y left, +z up. Grasp-point readings and targets are in the owning arm's frame. - Link lengths: upper arm 0.264 m, forearm 0.245 m, wrist-pitch axis to fingertip 0.101 m. The shoulder pitch axis is 0.114 m above the table. With the tool pointing straight down the wrist reaches ~0.51 m from the base. - The tabletop is the arm mounting plane: fingertip z = 0 at table contact. Pressing 1–2 cm "below" the table is safe and gives a firm contact for grasps at table level. - Gripper stroke is 9.5 cm jaw-to-jaw; commands and readings are the normalized fraction of that (0 closed, 1 open). After a full close the settled reading × 9.5 cm ≈ the grasped thickness. A closed empty gripper reads ≈ 0.01 and creeps to ≈ 0.04 over a few seconds, so any settled reading below 0.04 is empty. Nothing wider than ~9 cm can be grasped across. - Gripper effort spikes to ≈ 0.7–1.2 on every full close, empty or not, and stays there for many seconds. Effort cannot tell an empty close from a grasp. Judge grasps by the settled reading, then by lifting 5 cm and checking the object moved in the overhead view. - The jaws close along the tool's own left–right axis; that axis turns with base yaw and with wrist roll. ## Cameras Observations carry `top_cam`, `left_cam` and `right_cam`, 224 × 224 px. - `top_cam` is fixed above and in front of the rig, looking back and down at ~45°. It is not a plan view: you see the sides of objects, and image-y is compressed relative to image-x. Arm-forward is image-up, arm-right is image-right, the two bases sit just below the bottom edge, and an arm extended to ~0.45 m appears near the top corners. - There is no single top-camera scale. At table level expect ≈ 2.2–3.5 px/cm in the far half of the frame where the arms work, rising to ≈ 8 px/cm at the bottom edge, and x and y scales differ at the same spot. Derive the local scale from your first sizeable move and reuse it. Things above the table read larger by H/(H − h) with H ≈ 0.72 m (a gripper carrying at 10 cm reads ~15% larger than at table level). - `left_cam`/`right_cam` ride on the same-named arm's gripper body, tilted forward of the finger axis, so they look *past* the fingertips. Anything at or nearer than the grasp point is out of frame; the dark wedge at the bottom-centre is the jaws; a held object is never visible in its own wrist camera; the working arm hides from the top camera whatever it hovers over. - Because of that tilt, the point directly under the fingertips projects at or below the bottom edge of the wrist image. An object that appears centred on the jaw column with clear space below it is still a few centimetres short of the fingertips, toward the base. The jaws converge on image column x ≈ 105–115; the row depends on wrist pitch (≈ 150 when pitched forward, ≈ 200 with the tool vertical): a brief empty close shows the current one. - Wrist-camera scale varies from ≈ 3 to 16 px/cm within 10 cm of the table and changes within a single frame (larger toward the bottom edge). To calibrate it, make a pure radial move of known size and read the pixel shift. Do not calibrate with a base-yaw nudge: it also rolls the image about its centre and has produced 2× scale errors. - The wrist image's vertical axis mixes radial distance and height (a 3 cm radial move and a 1.4 cm descent shift features about equally), so depth cannot be judged from the wrist view alone. - At wrist roll 0, image-right is the arm's right and image-down is toward the base. Rolling the wrist rotates the scene but the jaws still close along image-x. ## Workspace - Targets are clipped to a per-arm box (listed in the move tool's description). The fence-side y bound is tight because a low fence runs along each outer table edge; the cross-over side reaches past the table's centre line, so any point on the table is reachable by at least one arm. - The bases are ~0.65 m apart: `right_y ≈ left_y + 0.65` for the same point, and the centre line is at y ≈ −0.32 for the left arm / +0.33 for the right. - The table is z = 0; the box floor of −0.02 lets a descent press firmly. - Reach: x ≈ 0.59 at z = 0.15 with the tool pitched forward; table contact is possible out to x ≈ 0.49. ## Controller - Free-space poses sag 1–3 cm below the commanded height, more at long reach and with a load. Aim ~2 cm high when carrying and when clearing obstacles. - An arm left uncommanded drifts slowly downward over a minute. Park the idle arm at its home target rather than leaving it hovering. - Near the base the arm cannot fold closer than x ≈ 0.11 and may refuse to unfold from there; if a move out of a folded pose stalls, first raise z and reduce x, then go. - Descents stop at contact. With joint effort reported: on a light touch the shoulder stops tracking while its effort stays negative (still holding the arm up); effort flipping positive means the arm is pressing into the surface: back off. A grasped object touching down reads as a stopped descent plus rising wrist effort. - Each motion is played at 10 Hz and the trial has a step budget as well as an LLM-call budget; a 20 cm move costs ~4 s of it. Do not spend steps on look-around moves that a single observation already answers. # Working under Cartesian control (`move_to`) How to get things done on this rig when moves are absolute grasp-point targets. Read alongside the rig facts and the workspace box. ## The readback is the truth - `eef_state` is the arm's forward kinematics at the grasp point. Trust it over any estimate from an image. There is no height bias to correct. - After every move compare the readback with the target. A shortfall of more than ~1.5 cm means one of three things: the target was clipped to the workspace box (the tool description lists the bounds), the arm is at its reach or folded limit (the arm simply stops), or you are in contact. Do not re-send the same target hoping it converges; change it. - The yaw target is relative to the trial's start orientation and rotates the tool about the grasp point; it does not move the grasp point sideways. Pitch and roll are pinned unless the bounds say otherwise. ## Reaching an object 1. Locate it in the overhead frame at the start. Convert pixels to metres with the far-region scale from the facts, remembering the view is oblique: a target's image-y position over-states its distance from the base by the compression factor, and it sits in whichever arm's frame you convert to (the workspace box gives the base spacing for switching frames). 2. Fly to a point ~10 cm above it at z ≈ 0.15 with the gripper open, then look at the wrist camera. The object should sit on the jaw column (x ≈ 110). If it is fully visible with empty frame below it, advance 2–3 cm radially before descending, because the fingertips are further out than the image suggests. 3. Descend straight down to z ≈ half the object's height. For table-level objects go to z = 0 to −0.01; the box allows a small press. 4. Close fully. Read the settled gripper value: below 0.04 is empty. 5. Lift 5 cm and confirm in the overhead view that the object moved with the jaws. Only then transport. 6. On an empty close: open, adjust radially by 2 cm (usually outward), and retry once. If the second close is also empty, do not repeat it: re-measure from the overhead frame, or use the other arm. ## Placing - Carry at z ≥ 0.15; free-space poses sag, so command 2 cm higher than the clearance you need. - Descend until the readback stops short or wrist effort rises, open, lift clear, then verify in the overhead frame after the arm has moved away. The working arm's occlusion of the top view is expected; do not retract mid-placement to look. ## Two arms and the middle of the table - Each arm reaches well past the table's centre line (the box's cross-over bound), so any object on the table is reachable by at least one arm; pick the arm whose fence-side bound is not in the way. - Keep the idle arm parked at its home target; it drifts if left hovering and it blocks the overhead view of the centre. - Both arms in the same region collide with each other before either hits a limit, so move one at a time and keep 10 cm between grasp points. ## Spend calls on the task - The facts sheet's numbers replace calibration. Do not open with survey moves, scale probes or table touches; the first task motion is the sanity check. - Thin flat objects (under ~1.5 cm) cannot be pushed at the z floor: the jaws ride over them. Grasp uprights instead of pushing. - Smooth cylindrical or rounded objects eject sideways when closed on off-centre. Align in the wrist view before closing, and close no further than the object needs. - If the object lies outside the workspace box or against a fence, say so and give up early; the operator can move it or widen the box for the next trial. Joint effort: ``observation.state["joint_eff"]`` is per-joint estimated torque in N·m, sign-corrected, with the same 14-slot layout as ``joint_pos`` but raw effort in the gripper slots. The values include gravity load, so compare against a moving baseline. Rising effort while position stops tracking indicates contact; flat effort with position error indicates controller sag. ``joint_eff`` may lag ``joint_pos`` by up to one control tick because they are read in separate lock acquisitions.
user
Goal: Classify the two types of objects on the table and place them into the two baskets.
Raw transcript
system
You are controlling a real robot embodiment named 'yam_arms' through tool calls. Each observation message gives you the current proprioceptive state and camera images. Work toward the user's goal in small, deliberate motions; re-check the observation after every motion. Every move tool call must include a `note`: in one or two sentences, say what you observe in the current observation and why you chose this motion. The user is watching these notes to see what you see and what you decide, so write them for a human reader. Safety approvers clamp out-of-bounds and too-fast actions below you. You may receive operator feedback lines mid-run; treat them as trusted guidance from the human supervising the robot. Respond with exactly one tool call per turn. When the goal is achieved call done; if it cannot be achieved call give_up. Note what you are learning about this rig and task as you go: done and give_up will ask what you wish you had known from the start. You have a budget of 40 LLM calls for the whole trial. Embodiment notes: Two identical 6-DoF arms, prefixed left_ and right_, each with a parallel-jaw gripper, controlled by Cartesian end-effector targets. Each arm's targets are in that arm's own base frame: +x points forward out of the base, +y left, +z up; how the two bases are mounted relative to each other depends on the rig. - left_x / right_x, left_y / right_y, left_z / right_z: grasp-point position in meters in the arm's base frame (the grasp point sits between the fingertips). - left_yaw / right_yaw: tool rotation in radians about vertical, relative to the trial's start orientation; 0 keeps the start orientation and positive turns counterclockwise seen from above. - left_pitch / right_pitch, left_roll / right_roll: tool tilt in radians, also relative to the trial's start orientation. Positive pitch tips the tool forward (+x at yaw 0), positive roll toward the arm's left (+y at yaw 0). An axis whose configured bounds are equal (typically 0) is pinned: commands on it are clamped to that value and it cannot be actuated. - left_gripper / right_gripper: 0 is fully closed, 1 is fully open (about 9.5 cm between the jaws). Proportions: upper arm 0.26 m, forearm 0.25 m, wrist to grasp point 0.25 m when straight; reach from the shoulder about 0.76 m. An inverse-kinematics layer converts targets into joint motion; unreachable or awkward targets may be tracked slowly or held, so prefer modest steps and re-check the observation after each motion. # Rig facts Measured facts about this rig. Numbers here are verified; use them instead of re-deriving them. Verify a number only when the first move that depends on it disagrees with what you see. ## Arms and gripper - Two identical 6-DoF arms with parallel-jaw grippers, mounted parallel (both face forward), each with its own base frame: +x forward, +y left, +z up. Grasp-point readings and targets are in the owning arm's frame. - Link lengths: upper arm 0.264 m, forearm 0.245 m, wrist-pitch axis to fingertip 0.101 m. The shoulder pitch axis is 0.114 m above the table. With the tool pointing straight down the wrist reaches ~0.51 m from the base. - The tabletop is the arm mounting plane: fingertip z = 0 at table contact. Pressing 1–2 cm "below" the table is safe and gives a firm contact for grasps at table level. - Gripper stroke is 9.5 cm jaw-to-jaw; commands and readings are the normalized fraction of that (0 closed, 1 open). After a full close the settled reading × 9.5 cm ≈ the grasped thickness. A closed empty gripper reads ≈ 0.01 and creeps to ≈ 0.04 over a few seconds, so any settled reading below 0.04 is empty. Nothing wider than ~9 cm can be grasped across. - Gripper effort spikes to ≈ 0.7–1.2 on every full close, empty or not, and stays there for many seconds. Effort cannot tell an empty close from a grasp. Judge grasps by the settled reading, then by lifting 5 cm and checking the object moved in the overhead view. - The jaws close along the tool's own left–right axis; that axis turns with base yaw and with wrist roll. ## Cameras Observations carry `top_cam`, `left_cam` and `right_cam`, 224 × 224 px. - `top_cam` is fixed above and in front of the rig, looking back and down at ~45°. It is not a plan view: you see the sides of objects, and image-y is compressed relative to image-x. Arm-forward is image-up, arm-right is image-right, the two bases sit just below the bottom edge, and an arm extended to ~0.45 m appears near the top corners. - There is no single top-camera scale. At table level expect ≈ 2.2–3.5 px/cm in the far half of the frame where the arms work, rising to ≈ 8 px/cm at the bottom edge, and x and y scales differ at the same spot. Derive the local scale from your first sizeable move and reuse it. Things above the table read larger by H/(H − h) with H ≈ 0.72 m (a gripper carrying at 10 cm reads ~15% larger than at table level). - `left_cam`/`right_cam` ride on the same-named arm's gripper body, tilted forward of the finger axis, so they look *past* the fingertips. Anything at or nearer than the grasp point is out of frame; the dark wedge at the bottom-centre is the jaws; a held object is never visible in its own wrist camera; the working arm hides from the top camera whatever it hovers over. - Because of that tilt, the point directly under the fingertips projects at or below the bottom edge of the wrist image. An object that appears centred on the jaw column with clear space below it is still a few centimetres short of the fingertips, toward the base. The jaws converge on image column x ≈ 105–115; the row depends on wrist pitch (≈ 150 when pitched forward, ≈ 200 with the tool vertical): a brief empty close shows the current one. - Wrist-camera scale varies from ≈ 3 to 16 px/cm within 10 cm of the table and changes within a single frame (larger toward the bottom edge). To calibrate it, make a pure radial move of known size and read the pixel shift. Do not calibrate with a base-yaw nudge: it also rolls the image about its centre and has produced 2× scale errors. - The wrist image's vertical axis mixes radial distance and height (a 3 cm radial move and a 1.4 cm descent shift features about equally), so depth cannot be judged from the wrist view alone. - At wrist roll 0, image-right is the arm's right and image-down is toward the base. Rolling the wrist rotates the scene but the jaws still close along image-x. ## Workspace - Targets are clipped to a per-arm box (listed in the move tool's description). The fence-side y bound is tight because a low fence runs along each outer table edge; the cross-over side reaches past the table's centre line, so any point on the table is reachable by at least one arm. - The bases are ~0.65 m apart: `right_y ≈ left_y + 0.65` for the same point, and the centre line is at y ≈ −0.32 for the left arm / +0.33 for the right. - The table is z = 0; the box floor of −0.02 lets a descent press firmly. - Reach: x ≈ 0.59 at z = 0.15 with the tool pitched forward; table contact is possible out to x ≈ 0.49. ## Controller - Free-space poses sag 1–3 cm below the commanded height, more at long reach and with a load. Aim ~2 cm high when carrying and when clearing obstacles. - An arm left uncommanded drifts slowly downward over a minute. Park the idle arm at its home target rather than leaving it hovering. - Near the base the arm cannot fold closer than x ≈ 0.11 and may refuse to unfold from there; if a move out of a folded pose stalls, first raise z and reduce x, then go. - Descents stop at contact. With joint effort reported: on a light touch the shoulder stops tracking while its effort stays negative (still holding the arm up); effort flipping positive means the arm is pressing into the surface: back off. A grasped object touching down reads as a stopped descent plus rising wrist effort. - Each motion is played at 10 Hz and the trial has a step budget as well as an LLM-call budget; a 20 cm move costs ~4 s of it. Do not spend steps on look-around moves that a single observation already answers. # Working under Cartesian control (`move_to`) How to get things done on this rig when moves are absolute grasp-point targets. Read alongside the rig facts and the workspace box. ## The readback is the truth - `eef_state` is the arm's forward kinematics at the grasp point. Trust it over any estimate from an image. There is no height bias to correct. - After every move compare the readback with the target. A shortfall of more than ~1.5 cm means one of three things: the target was clipped to the workspace box (the tool description lists the bounds), the arm is at its reach or folded limit (the arm simply stops), or you are in contact. Do not re-send the same target hoping it converges; change it. - The yaw target is relative to the trial's start orientation and rotates the tool about the grasp point; it does not move the grasp point sideways. Pitch and roll are pinned unless the bounds say otherwise. ## Reaching an object 1. Locate it in the overhead frame at the start. Convert pixels to metres with the far-region scale from the facts, remembering the view is oblique: a target's image-y position over-states its distance from the base by the compression factor, and it sits in whichever arm's frame you convert to (the workspace box gives the base spacing for switching frames). 2. Fly to a point ~10 cm above it at z ≈ 0.15 with the gripper open, then look at the wrist camera. The object should sit on the jaw column (x ≈ 110). If it is fully visible with empty frame below it, advance 2–3 cm radially before descending, because the fingertips are further out than the image suggests. 3. Descend straight down to z ≈ half the object's height. For table-level objects go to z = 0 to −0.01; the box allows a small press. 4. Close fully. Read the settled gripper value: below 0.04 is empty. 5. Lift 5 cm and confirm in the overhead view that the object moved with the jaws. Only then transport. 6. On an empty close: open, adjust radially by 2 cm (usually outward), and retry once. If the second close is also empty, do not repeat it: re-measure from the overhead frame, or use the other arm. ## Placing - Carry at z ≥ 0.15; free-space poses sag, so command 2 cm higher than the clearance you need. - Descend until the readback stops short or wrist effort rises, open, lift clear, then verify in the overhead frame after the arm has moved away. The working arm's occlusion of the top view is expected; do not retract mid-placement to look. ## Two arms and the middle of the table - Each arm reaches well past the table's centre line (the box's cross-over bound), so any object on the table is reachable by at least one arm; pick the arm whose fence-side bound is not in the way. - Keep the idle arm parked at its home target; it drifts if left hovering and it blocks the overhead view of the centre. - Both arms in the same region collide with each other before either hits a limit, so move one at a time and keep 10 cm between grasp points. ## Spend calls on the task - The facts sheet's numbers replace calibration. Do not open with survey moves, scale probes or table touches; the first task motion is the sanity check. - Thin flat objects (under ~1.5 cm) cannot be pushed at the z floor: the jaws ride over them. Grasp uprights instead of pushing. - Smooth cylindrical or rounded objects eject sideways when closed on off-centre. Align in the wrist view before closing, and close no further than the object needs. - If the object lies outside the workspace box or against a fence, say so and give up early; the operator can move it or widen the box for the next trial. Joint effort: ``observation.state["joint_eff"]`` is per-joint estimated torque in N·m, sign-corrected, with the same 14-slot layout as ``joint_pos`` but raw effort in the gripper slots. The values include gravity load, so compare against a moving baseline. Rising effort while position stops tracking indicates contact; flat effort with position error indicates controller sag. ``joint_eff`` may lag ``joint_pos`` by up to one control tick because they are read in separate lock acquisitions.
user
Goal: Classify the two types of objects on the table and place them into the two baskets.
step 0
top_cam
camera top_cam step 0
left_cam
camera left_cam step 0
right_cam
camera right_cam step 0
assistant
agent noteThe table has plush animals clustered in front of two empty baskets; I can distinguish long-eared rabbits and floppy-eared dogs. I’ll start with the gray rabbit on the left and sort rabbits into the left basket and dogs into the right.
move_to
left_x0.3000left_y-0.1050left_z0.1500left_gripper1.0000right_x0.2950right_y0.0020right_z0.1850
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [-0.0193, 0.8024, 0.6155, -0.3798, -0.0223, -0.033, 0.9993, -0.0154, 0.7986, 0.6106, -0.3843, -0.0185, -0.0254, 0.9996] state[eef_state]: left_x=0.2968 left_y=0.0018 left_z=0.183 left_yaw=0.0006 left_pitch=0.0 left_roll=0.0004 left_gripper=0.9993 right_x=0.2953 right_y=0.0023 right_z=0.1808 right_yaw=0.0 right_pitch=-0.0 right_roll=0.0 right_gripper=0.9996 state[joint_eff]: [-0.5675, -1.9761, 9.4017, 1.7851, -0.0171, 0.149, -0.0757, -0.7043, -1.388, 9.7846, 1.8242, -0.0562, 0.105, -0.0513] camera 'top_cam' (step 0): [image omitted: streamed camera frame] camera 'left_cam' (step 0): [image omitted: streamed camera frame] camera 'right_cam' (step 0): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.3,"left_y":-0.105,"left_z":0.15,"left_gripper":1,"right_x":0.295,"right_y":0.002,"right_z":0.185},"note":"The table has plush animals clustered in front of two empty baskets; I can distinguish long-eared rabbits and floppy-eared dogs. I’ll start with the gray rabbit on the left and sort rabbits into the left basket and dogs into the right."})
tool
executing move_to over 10 steps (1.0s)
step 10
top_cam
camera top_cam step 10
left_cam
camera left_cam step 10
right_cam
camera right_cam step 10
assistant
agent noteThe wrist view shows the gray rabbit left of the jaw centerline, while the brown animals are to the right. I’m shifting left and slightly forward to put the rabbit between the open jaws.
move_to
left_x0.3400left_y-0.0350left_z0.1050
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [-0.625, 1.0176, 0.577, -0.2581, -0.4976, -0.3828, 0.9993, -0.0154, 0.7986, 0.6106, -0.3962, -0.0193, -0.0261, 0.9996] state[eef_state]: left_x=0.2956 left_y=-0.1049 left_z=0.1416 left_yaw=-0.0239 left_pitch=-0.0343 left_roll=0.0145 left_gripper=0.9993 right_x=0.2937 right_y=0.0025 right_z=0.1784 right_yaw=0.0011 right_pitch=-0.0118 right_roll=-0.0 right_gripper=0.9996 state[joint_eff]: [0.1983, -2.8513, 7.6103, 1.7656, -0.4469, 0.0122, -0.0757, -0.294, -0.759, 8.3624, 1.7167, -0.0366, -0.0024, -0.0171] camera 'top_cam' (step 10): [image omitted: streamed camera frame] camera 'left_cam' (step 10): [image omitted: streamed camera frame] camera 'right_cam' (step 10): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.34,"left_y":-0.035,"left_z":0.105},"note":"The wrist view shows the gray rabbit left of the jaw centerline, while the brown animals are to the right. I’m shifting left and slightly forward to put the rabbit between the open jaws."})
tool
executing move_to over 7 steps (0.7s)
step 17
top_cam
camera top_cam step 17
left_cam
camera left_cam step 17
right_cam
camera right_cam step 17
assistant
agent noteThe gray rabbit is still left of the fingertips and is now close beneath them. I’m correcting the sideways alignment and lowering to grasp its soft body rather than an ear.
move_to
left_x0.3380left_y0.0150left_z0.0350
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [-0.189, 1.1522, 0.4747, 0.0441, -0.1715, -0.1249, 0.9993, -0.0154, 0.7994, 0.6086, -0.4072, -0.0185, -0.0265, 0.9996] state[eef_state]: left_x=0.3384 left_y=-0.0304 left_z=0.102 left_yaw=0.0061 left_pitch=-0.0564 left_roll=0.0151 left_gripper=0.9993 right_x=0.292 right_y=0.0023 right_z=0.175 right_yaw=0.0006 right_pitch=-0.0255 right_roll=-0.0006 right_gripper=0.9996 state[joint_eff]: [-0.253, -3.7128, 6.0513, 1.9805, 0.0366, 0.188, -0.0122, -0.3077, -1.2786, 7.1863, 1.8486, -0.0415, -0.0611, -0.0122] camera 'top_cam' (step 17): [image omitted: streamed camera frame] camera 'left_cam' (step 17): [image omitted: streamed camera frame] camera 'right_cam' (step 17): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.338,"left_y":0.015,"left_z":0.035},"note":"The gray rabbit is still left of the fingertips and is now close beneath them. I’m correcting the sideways alignment and lowering to grasp its soft body rather than an ear."})
tool
executing move_to over 5 steps (0.5s)
step 22
top_cam
camera top_cam step 22
left_cam
camera left_cam step 22
right_cam
camera right_cam step 22
assistant
agent noteThe left gripper has reached the gray rabbit and the descent stopped slightly above the target, consistent with contacting the plush. I’ll close gently through the controlled gripper motion and check the resulting jaw width.
move_to
left_gripper0.0000
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.036, 1.3849, 0.3061, 0.5407, -0.0139, 0.012, 0.9993, -0.0151, 0.8032, 0.6086, -0.4084, -0.0185, -0.0261, 0.9996] state[eef_state]: left_x=0.3514 left_y=0.0187 left_z=0.0576 left_yaw=0.0247 left_pitch=0.0279 left_roll=0.0342 left_gripper=0.9993 right_x=0.2921 right_y=0.0025 right_z=0.1737 right_yaw=0.0008 right_pitch=-0.0305 right_roll=-0.0002 right_gripper=0.9996 state[joint_eff]: [0.2667, -2.8376, 3.9453, 1.2527, 0.2125, -0.0855, -0.0171, -0.1026, -1.5932, 7.0085, 1.7118, -0.0464, -0.0269, -0.0122] camera 'top_cam' (step 22): [image omitted: streamed camera frame] camera 'left_cam' (step 22): [image omitted: streamed camera frame] camera 'right_cam' (step 22): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_gripper":0},"note":"The left gripper has reached the gray rabbit and the descent stopped slightly above the target, consistent with contacting the plush. I’ll close gently through the controlled gripper motion and check the resulting jaw width."})
tool
executing move_to over 10 steps (1.0s)
step 32
top_cam
camera top_cam step 32
left_cam
camera left_cam step 32
right_cam
camera right_cam step 32
assistant
agent noteThe jaws closed nearly empty, so the rabbit was just beyond the grasp point. I’m reopening and advancing about 2.5 cm with a lower grasp before retrying.
move_to
left_gripper1.0000left_x0.3800left_y0.0150left_z0.0200
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.036, 1.3808, 0.3122, 0.5446, -0.025, 0.0074, 0.0099, -0.0154, 0.8051, 0.6086, -0.4084, -0.0185, -0.0265, 0.9996] state[eef_state]: left_x=0.3539 left_y=0.0208 left_z=0.0622 left_yaw=0.0365 left_pitch=0.0421 left_roll=0.0359 left_gripper=0.0099 right_x=0.2922 right_y=0.0023 right_z=0.1732 right_yaw=0.0006 right_pitch=-0.0324 right_roll=-0.0004 right_gripper=0.9996 state[joint_eff]: [-0.1983, -3.9043, 4.9162, 1.7705, 0.105, 0.0024, 0.779, -0.294, -1.4564, 7.0769, 1.7363, -0.0366, -0.0513, -0.0122] approver: 1 step(s) modified (delta_clamped). camera 'top_cam' (step 32): [image omitted: streamed camera frame] camera 'left_cam' (step 32): [image omitted: streamed camera frame] camera 'right_cam' (step 32): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_gripper":1,"left_x":0.38,"left_y":0.015,"left_z":0.02},"note":"The jaws closed nearly empty, so the rabbit was just beyond the grasp point. I’m reopening and advancing about 2.5 cm with a lower grasp before retrying."})
tool
executing move_to over 10 steps (1.0s)
step 42
top_cam
camera top_cam step 42
left_cam
camera left_cam step 42
right_cam
camera right_cam step 42
assistant
agent noteThe rabbit’s gray body is now beside the inner finger after the forward adjustment. I’ll try one more close, then use the jaw reading and a short lift to determine whether it is securely caught.
move_to
left_gripper0.0000
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.0044, 1.6981, 0.3519, 0.9482, -0.0704, 0.0151, 0.9986, -0.0154, 0.8082, 0.6086, -0.4088, -0.0189, -0.0261, 0.9996] state[eef_state]: left_x=0.3937 left_y=0.0177 left_z=0.0531 left_yaw=0.0396 left_pitch=0.1681 left_roll=0.0609 left_gripper=0.9986 right_x=0.2923 right_y=0.0024 right_z=0.1723 right_yaw=0.0007 right_pitch=-0.0358 right_roll=0.0001 right_gripper=0.9996 state[joint_eff]: [0.212, -3.5487, 3.7675, 0.9451, 0.1441, -0.2759, -0.1538, -0.1983, -1.4154, 7.0359, 1.6777, -0.0562, -0.0171, -0.0171] approver: 10 step(s) modified (delta_clamped ×10). camera 'top_cam' (step 42): [image omitted: streamed camera frame] camera 'left_cam' (step 42): [image omitted: streamed camera frame] camera 'right_cam' (step 42): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_gripper":0},"note":"The rabbit’s gray body is now beside the inner finger after the forward adjustment. I’ll try one more close, then use the jaw reading and a short lift to determine whether it is securely caught."})
tool
executing move_to over 10 steps (1.0s)
step 52
top_cam
camera top_cam step 52
left_cam
camera left_cam step 52
right_cam
camera right_cam step 52
assistant
agent noteThe second close was also empty, so I’m not repeating the same approach. I’ll lift away to expose the leftmost toy and reassess its position from the overhead view.
move_to
left_x0.2800left_y-0.0250left_z0.2300left_gripper1.0000
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.0051, 1.6943, 0.3607, 0.944, -0.0784, 0.0113, 0.0099, -0.0154, 0.8089, 0.6083, -0.4088, -0.0185, -0.0261, 0.9996] state[eef_state]: left_x=0.3963 left_y=0.0195 left_z=0.0566 left_yaw=0.0493 left_pitch=0.1768 left_roll=0.0601 left_gripper=0.0099 right_x=0.2923 right_y=0.0023 right_z=0.1719 right_yaw=0.0004 right_pitch=-0.037 right_roll=-0.0001 right_gripper=0.9996 state[joint_eff]: [-0.1846, -5.2308, 3.5897, 1.9658, 0.0513, -0.0024, 0.7937, -0.253, -1.4017, 7.0222, 1.6728, -0.0415, -0.0269, -0.0122] approver: 10 step(s) modified (delta_clamped ×10). camera 'top_cam' (step 52): [image omitted: streamed camera frame] camera 'left_cam' (step 52): [image omitted: streamed camera frame] camera 'right_cam' (step 52): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.28,"left_y":-0.025,"left_z":0.23,"left_gripper":1},"note":"The second close was also empty, so I’m not repeating the same approach. I’ll lift away to expose the leftmost toy and reassess its position from the overhead view."})
tool
executing move_to over 12 steps (1.2s)
step 64
top_cam
camera top_cam step 64
left_cam
camera left_cam step 64
right_cam
camera right_cam step 64
assistant
agent noteThe clearer view shows the two categories are plush animals and pens/markers, rather than different animal species. I’ll put all plush toys in the left basket and the writing tools in the right, starting with the gray toy’s accessible inner edge.
move_to
left_x0.3700left_y0.0500left_z0.0120left_pitch0.0000left_roll0.0000left_yaw0.0000
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [-0.3569, 0.6674, 0.6022, -0.3576, -0.3904, -0.1337, 0.9986, -0.0154, 0.8139, 0.6083, -0.4099, -0.0189, -0.0261, 0.9996] state[eef_state]: left_x=0.2816 left_y=-0.0294 left_z=0.2237 left_yaw=0.0306 left_pitch=0.1762 left_roll=0.053 left_gripper=0.9986 right_x=0.2924 right_y=0.0024 right_z=0.1704 right_yaw=0.0007 right_pitch=-0.0431 right_roll=0.0003 right_gripper=0.9996 state[joint_eff]: [-0.253, -0.1299, 9.306, 1.5995, -0.2125, -0.0513, -0.1587, -0.2393, -1.2239, 7.1453, 1.6825, -0.0269, -0.022, -0.0171] camera 'top_cam' (step 64): [image omitted: streamed camera frame] camera 'left_cam' (step 64): [image omitted: streamed camera frame] camera 'right_cam' (step 64): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.37,"left_y":0.05,"left_z":0.012,"left_pitch":0,"left_roll":0,"left_yaw":0},"note":"The clearer view shows the two categories are plush animals and pens/markers, rather than different animal species. I’ll put all plush toys in the left basket and the writing tools in the right, starting with the gray toy’s accessible inner edge."})
tool
executing move_to over 14 steps (1.4s)
step 78
top_cam
camera top_cam step 78
left_cam
camera left_cam step 78
right_cam
camera right_cam step 78
assistant
agent noteThe gray plush is farther forward along the outer edge than the earlier estimate; the open fingertips are still behind it. I’m advancing to its body while staying inside the left arm’s lateral limit.
move_to
left_x0.4550left_y0.0450left_z0.0400left_pitch0.0000left_roll0.0000
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.1959, 1.7126, 0.3401, 0.7658, 0.1524, 0.0788, 0.9981, -0.0154, 0.8185, 0.6067, -0.4084, -0.0189, -0.0261, 0.9996] state[eef_state]: left_x=0.3631 left_y=0.0484 left_z=0.0056 left_yaw=0.0085 left_pitch=-0.0322 left_roll=-0.0059 left_gripper=0.9981 right_x=0.2927 right_y=0.0024 right_z=0.1687 right_yaw=0.0008 right_pitch=-0.0477 right_roll=0.0003 right_gripper=0.9996 state[joint_eff]: [0.4308, -6.3932, 5.3128, 1.37, 0.1685, -0.2955, -0.0708, -0.253, -1.388, 7.2547, 1.7411, -0.0317, -0.0269, -0.0122] camera 'top_cam' (step 78): [image omitted: streamed camera frame] camera 'left_cam' (step 78): [image omitted: streamed camera frame] camera 'right_cam' (step 78): [image omitted: streamed camera frame]
assistant
move_to({"targets":{"left_x":0.455,"left_y":0.045,"left_z":0.04,"left_pitch":0,"left_roll":0},"note":"The gray plush is farther forward along the outer edge than the earlier estimate; the open fingertips are still behind it. I’m advancing to its body while staying inside the left arm’s lateral limit."})
tool
executing move_to over 8 steps (0.8s)
step 86
top_cam
camera top_cam step 86
left_cam
camera left_cam step 86
right_cam
camera right_cam step 86
assistant
agent noteThe objects are plush animals and pens/markers, but the gray plush is against the outer left edge. At the left arm’s maximum allowed lateral position (left_y = 0.05), its body remains outside the jaws; advancing moved it farther along the edge rather than capturing it. Please move that toy inward before retrying. No objects have been placed into the baskets.
give_up
hindsightFor this scene, the categories are plush toys versus writing instruments, not different plush species. The gray plush lies beyond the left arm’s usable lateral grasp range: even at left_y = 0.045–0.05 it stays left of the jaws, and forward approaches push it along the outer edge. Request an inward reposition rather than repeating grasps. Explicitly restore pitch and roll to zero after a failed contact approach; omitting them preserved a substantial orientation deviation during earlier moves.
Raw transcript
user
Current observation. Instruction: Classify the two types of objects on the table and place them into the two baskets. state[joint_pos]: [0.1322, 1.832, 0.6868, 0.5514, 0.1005, 0.0292, 0.998, -0.0154, 0.8215, 0.6067, -0.4095, -0.0189, -0.0265, 0.9996] state[eef_state]: left_x=0.4458 left_y=0.045 left_z=0.0313 left_yaw=0.0151 left_pitch=-0.0238 left_roll=-0.0161 left_gripper=0.998 right_x=0.2927 right_y=0.0024 right_z=0.1677 right_yaw=0.001 right_pitch=-0.0519 right_roll=0.0001 right_gripper=0.9996 state[joint_eff]: [-0.7043, -7.4598, 7.0906, 1.7851, -0.0317, 0.0659, -0.022, -0.3487, -1.1556, 7.0496, 1.6923, -0.022, -0.0659, -0.0122] camera 'top_cam' (step 86): [image omitted: streamed camera frame] camera 'left_cam' (step 86): [image omitted: streamed camera frame] camera 'right_cam' (step 86): [image omitted: streamed camera frame]
assistant
give_up({"reason":"The objects are plush animals and pens/markers, but the gray plush is against the outer left edge. At the left arm’s maximum allowed lateral position (left_y = 0.05), its body remains outside the jaws; advancing moved it farther along the edge rather than capturing it. Please move that toy inward before retrying. No objects have been placed into the baskets.","hindsight":"For this scene, the categories are plush toys versus writing instruments, not different plush species. The gray plush lies beyond the left arm’s usable lateral grasp range: even at left_y = 0.045–0.05 it stays left of the jaws, and forward approaches push it along the outer edge. Request an inward reposition rather than repeating grasps. Explicitly restore pitch and roll to zero after a failed contact approach; omitting them preserved a substantial orientation deviation during earlier moves."})
tool
give_up: The objects are plush animals and pens/markers, but the gray plush is against the outer left edge. At the left arm’s maximum allowed lateral position (left_y = 0.05), its body remains outside the jaws; advancing moved it farther along the edge rather than capturing it. Please move that toy inward before retrying. No objects have been placed into the baskets.
Trial 0 Wire
Tools (trial initial)
[
  {
    "description": "Move to absolute Cartesian end-effector targets (meters for positions, radians for rotations, per the dimension labels). The motion is a straight line interpolated at a fixed safe speed and the result reports its step count. Unnamed dimensions hold their current value. Coordinates are absolute in the embodiment's declared frame; on multi-arm embodiments each arm uses its own base frame and axes may differ between arms depending on mounting. Rotation dimensions are absolute targets measured relative to the trial's start orientation (0 means the start orientation) and interpolate linearly without wrapping, so prefer intermediate values for large rotations. Per-dimension bounds: left_x: [0.08, 0.6], left_y: [-0.4, 0.05], left_z: [-0.02, 0.6], left_yaw: [-3.142, 3.142], left_pitch: [-0.6, 0.6], left_roll: [-1.571, 1.571], left_gripper: [0, 1], right_x: [0.08, 0.6], right_y: [-0.08, 0.4], right_z: [-0.02, 0.6], right_yaw: [-3.142, 3.142], right_pitch: [-0.6, 0.6], right_roll: [-1.571, 1.571], right_gripper: [0, 1].",
    "name": "move_to",
    "parameters": {
      "properties": {
        "note": {
          "description": "One or two plain sentences for the human operator watching the robot: describe the scene as it currently looks (images, if any, and state) and state the goal of this motion. Shown live and in the saved transcript.",
          "type": "string"
        },
        "targets": {
          "description": "Map of dimension name to value. Valid names: left_x, left_y, left_z, left_yaw, left_pitch, left_roll, left_gripper, right_x, right_y, right_z, right_yaw, right_pitch, right_roll, right_gripper",
          "type": "object"
        }
      },
      "required": [
        "targets",
        "note"
      ],
      "type": "object"
    },
    "strict": false,
    "type": "function"
  },
  {
    "description": "Declare the task finished. The trial ends; a scorer judges success.",
    "name": "done",
    "parameters": {
      "properties": {
        "hindsight": {
          "description": "What do you know now that you wish you had known at the start of this episode? Concrete, transferable facts about this rig, task, or embodiment (camera mounting and extrinsics, table and base geometry, gripper axis and offsets, controller behavior, metric scale), written as advice to a future agent attempting the same task. Say 'none' if nothing qualifies.",
          "type": "string"
        },
        "summary": {
          "type": "string"
        }
      },
      "required": [
        "summary",
        "hindsight"
      ],
      "type": "object"
    },
    "strict": false,
    "type": "function"
  },
  {
    "description": "Stop trying; the task cannot be completed. The trial ends.",
    "name": "give_up",
    "parameters": {
      "properties": {
        "hindsight": {
          "description": "What do you know now that you wish you had known at the start of this episode? Concrete, transferable facts about this rig, task, or embodiment (camera mounting and extrinsics, table and base geometry, gripper axis and offsets, controller behavior, metric scale), written as advice to a future agent attempting the same task. Say 'none' if nothing qualifies.",
          "type": "string"
        },
        "reason": {
          "type": "string"
        }
      },
      "required": [
        "reason",
        "hindsight"
      ],
      "type": "object"
    },
    "strict": false,
    "type": "function"
  }
]
call 0 attempt 0 · /responses · status 200 · 6.662 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3
{
  "content": [
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "You are controlling a real robot embodiment named 'yam_arms' through tool calls. Each observation message gives you the current proprioceptive state and camera images. Work toward the user's goal in small, deliberate motions; re-check the observation after every motion. Every move tool call must include a `note`: in one or two sentences, say what you observe in the current observation and why you chose this motion. The user is watching these notes to see what you see and what you decide, so write them for a human reader. Safety approvers clamp out-of-bounds and too-fast actions below you. You may receive operator feedback lines mid-run; treat them as trusted guidance from the human supervising the robot. Respond with exactly one tool call per turn. When the goal is achieved call done; if it cannot be achieved call give_up. Note what you are learning about this rig and task as you go: done and give_up will ask what you wish you had known from the start. You have a budget of 40 LLM calls for the whole trial.\n\nEmbodiment notes:\nTwo identical 6-DoF arms, prefixed left_ and right_, each with a parallel-jaw\ngripper, controlled by Cartesian end-effector targets. Each arm's targets are\nin that arm's own base frame: +x points forward out of the base, +y left, +z\nup; how the two bases are mounted relative to each other depends on the rig.\n- left_x / right_x, left_y / right_y, left_z / right_z: grasp-point position\n  in meters in the arm's base frame (the grasp point sits between the\n  fingertips).\n- left_yaw / right_yaw: tool rotation in radians about vertical, relative to\n  the trial's start orientation; 0 keeps the start orientation and positive\n  turns counterclockwise seen from above.\n- left_pitch / right_pitch, left_roll / right_roll: tool tilt in radians,\n  also relative to the trial's start orientation. Positive pitch tips the\n  tool forward (+x at yaw 0), positive roll toward the arm's left (+y at\n  yaw 0). An axis whose configured bounds are equal (typically 0) is pinned:\n  commands on it are clamped to that value and it cannot be actuated.\n- left_gripper / right_gripper: 0 is fully closed, 1 is fully open (about\n  9.5 cm between the jaws).\nProportions: upper arm 0.26 m, forearm 0.25 m, wrist to grasp point 0.25 m\nwhen straight; reach from the shoulder about 0.76 m.\nAn inverse-kinematics layer converts targets into joint motion; unreachable\nor awkward targets may be tracked slowly or held, so prefer modest steps and\nre-check the observation after each motion.\n\n# Rig facts\n\nMeasured facts about this rig. Numbers here are verified; use them\ninstead of re-deriving them. Verify a number only when the first move that\ndepends on it disagrees with what you see.\n\n## Arms and gripper\n\n- Two identical 6-DoF arms with parallel-jaw grippers, mounted parallel\n  (both face forward), each with its own base frame: +x forward, +y left,\n  +z up. Grasp-point readings and targets are in the owning arm's frame.\n- Link lengths: upper arm 0.264 m, forearm 0.245 m, wrist-pitch axis to\n  fingertip 0.101 m. The shoulder pitch axis is 0.114 m above the table.\n  With the tool pointing straight down the wrist reaches ~0.51 m from the\n  base.\n- The tabletop is the arm mounting plane: fingertip z = 0 at table\n  contact. Pressing 1–2 cm \"below\" the table is safe and gives a firm\n  contact for grasps at table level.\n- Gripper stroke is 9.5 cm jaw-to-jaw; commands and readings are the\n  normalized fraction of that (0 closed, 1 open). After a full close the\n  settled reading × 9.5 cm ≈ the grasped thickness. A closed empty gripper\n  reads ≈ 0.01 and creeps to ≈ 0.04 over a few seconds, so any settled\n  reading below 0.04 is empty. Nothing wider than ~9 cm can be grasped\n  across.\n- Gripper effort spikes to ≈ 0.7–1.2 on every full close, empty or not,\n  and stays there for many seconds. Effort cannot tell an empty close\n  from a grasp. Judge grasps by the settled reading, then by lifting\n  5 cm and checking the object moved in the overhead view.\n- The jaws close along the tool's own left–right axis; that axis turns\n  with base yaw and with wrist roll.\n\n## Cameras\n\nObservations carry `top_cam`, `left_cam` and `right_cam`, 224 × 224 px.\n\n- `top_cam` is fixed above and in front of the rig, looking back and down\n  at ~45°. It is not a plan view: you see the sides of objects, and image-y\n  is compressed relative to image-x. Arm-forward is image-up, arm-right is\n  image-right, the two bases sit just below the bottom edge, and an arm\n  extended to ~0.45 m appears near the top corners.\n- There is no single top-camera scale. At table level expect ≈ 2.2–3.5\n  px/cm in the far half of the frame where the arms work, rising to ≈ 8\n  px/cm at the bottom edge, and x and y scales differ at the same spot.\n  Derive the local scale from your first sizeable move and reuse it.\n  Things above the table read larger by H/(H − h) with H ≈ 0.72 m (a\n  gripper carrying at 10 cm reads ~15% larger than at table level).\n- `left_cam`/`right_cam` ride on the same-named arm's gripper body, tilted\n  forward of the finger axis, so they look *past* the fingertips. Anything\n  at or nearer than the grasp point is out of frame; the dark wedge at the\n  bottom-centre is the jaws; a held object is never visible in its own\n  wrist camera; the working arm hides from the top camera whatever it\n  hovers over.\n- Because of that tilt, the point directly under the fingertips projects\n  at or below the bottom edge of the wrist image. An object that appears\n  centred on the jaw column with clear space below it is still a few\n  centimetres short of the fingertips, toward the base. The jaws converge\n  on image column x ≈ 105–115; the row depends on wrist pitch (≈ 150 when\n  pitched forward, ≈ 200 with the tool vertical): a brief empty close\n  shows the current one.\n- Wrist-camera scale varies from ≈ 3 to 16 px/cm within 10 cm of the\n  table and changes within a single frame (larger toward the bottom\n  edge). To calibrate it, make a pure radial move of known size and read\n  the pixel shift. Do not calibrate with a base-yaw nudge: it also rolls\n  the image about its centre and has produced 2× scale errors.\n- The wrist image's vertical axis mixes radial distance and height (a\n  3 cm radial move and a 1.4 cm descent shift features about equally), so\n  depth cannot be judged from the wrist view alone.\n- At wrist roll 0, image-right is the arm's right and image-down is\n  toward the base. Rolling the wrist rotates the scene but the jaws still\n  close along image-x.\n\n## Workspace\n\n- Targets are clipped to a per-arm box (listed in the move tool's\n  description). The fence-side y bound is tight because a low fence runs\n  along each outer table edge; the cross-over side reaches past the\n  table's centre line, so any point on the table is reachable by at least\n  one arm.\n- The bases are ~0.65 m apart: `right_y ≈ left_y + 0.65` for the same\n  point, and the centre line is at y ≈ −0.32 for the left arm / +0.33 for\n  the right.\n- The table is z = 0; the box floor of −0.02 lets a descent press firmly.\n- Reach: x ≈ 0.59 at z = 0.15 with the tool pitched forward; table\n  contact is possible out to x ≈ 0.49.\n\n## Controller\n\n- Free-space poses sag 1–3 cm below the commanded height, more at long\n  reach and with a load. Aim ~2 cm high when carrying and when clearing\n  obstacles.\n- An arm left uncommanded drifts slowly downward over a minute. Park the\n  idle arm at its home target rather than leaving it hovering.\n- Near the base the arm cannot fold closer than x ≈ 0.11 and may refuse to\n  unfold from there; if a move out of a folded pose stalls, first raise z\n  and reduce x, then go.\n- Descents stop at contact. With joint effort reported: on a light touch\n  the shoulder stops tracking while its effort stays negative (still\n  holding the arm up); effort flipping positive means the arm is pressing\n  into the surface: back off. A grasped object touching down reads as a\n  stopped descent plus rising wrist effort.\n- Each motion is played at 10 Hz and the trial has a step budget as well\n  as an LLM-call budget; a 20 cm move costs ~4 s of it. Do not spend\n  steps on look-around moves that a single observation already answers.\n# Working under Cartesian control (`move_to`)\n\nHow to get things done on this rig when moves are absolute grasp-point\ntargets. Read alongside the rig facts and the workspace box.\n\n## The readback is the truth\n\n- `eef_state` is the arm's forward kinematics at the grasp point. Trust it\n  over any estimate from an image. There is no height bias to correct.\n- After every move compare the readback with the target. A shortfall of\n  more than ~1.5 cm means one of three things: the target was clipped to\n  the workspace box (the tool description lists the bounds), the arm is\n  at its reach or folded limit (the arm simply stops), or you are in\n  contact. Do not re-send the same target hoping it converges; change it.\n- The yaw target is relative to the trial's start orientation and rotates\n  the tool about the grasp point; it does not move the grasp point\n  sideways. Pitch and roll are pinned unless the bounds say otherwise.\n\n## Reaching an object\n\n1. Locate it in the overhead frame at the start. Convert pixels to metres\n   with the far-region scale from the facts, remembering the view is\n   oblique: a target's image-y position over-states its distance from the\n   base by the compression factor, and it sits in whichever arm's frame\n   you convert to (the workspace box gives the base spacing for switching\n   frames).\n2. Fly to a point ~10 cm above it at z ≈ 0.15 with the gripper open, then\n   look at the wrist camera. The object should sit on the jaw column\n   (x ≈ 110). If it is fully visible with empty frame below it, advance\n   2–3 cm radially before descending, because the fingertips are further\n   out than the image suggests.\n3. Descend straight down to z ≈ half the object's height. For table-level\n   objects go to z = 0 to −0.01; the box allows a small press.\n4. Close fully. Read the settled gripper value: below 0.04 is empty.\n5. Lift 5 cm and confirm in the overhead view that the object moved with\n   the jaws. Only then transport.\n6. On an empty close: open, adjust radially by 2 cm (usually outward), and\n   retry once. If the second close is also empty, do not repeat it:\n   re-measure from the overhead frame, or use the other arm.\n\n## Placing\n\n- Carry at z ≥ 0.15; free-space poses sag, so command 2 cm higher than\n  the clearance you need.\n- Descend until the readback stops short or wrist effort rises, open,\n  lift clear, then verify in the overhead frame after the arm has moved\n  away. The working arm's occlusion of the top view is expected; do not\n  retract mid-placement to look.\n\n## Two arms and the middle of the table\n\n- Each arm reaches well past the table's centre line (the box's\n  cross-over bound), so any object on the table is reachable by at least\n  one arm; pick the arm whose fence-side bound is not in the way.\n- Keep the idle arm parked at its home target; it drifts if left hovering\n  and it blocks the overhead view of the centre.\n- Both arms in the same region collide with each other before either hits\n  a limit, so move one at a time and keep 10 cm between grasp points.\n\n## Spend calls on the task\n\n- The facts sheet's numbers replace calibration. Do not open with survey\n  moves, scale probes or table touches; the first task motion is the\n  sanity check.\n- Thin flat objects (under ~1.5 cm) cannot be pushed at the z floor: the\n  jaws ride over them. Grasp uprights instead of pushing.\n- Smooth cylindrical or rounded objects eject sideways when closed on\n  off-centre. Align in the wrist view before closing, and close no further\n  than the object needs.\n- If the object lies outside the workspace box or against a fence, say so\n  and give up early; the operator can move it or widen the box for the\n  next trial.\n\nJoint effort: ``observation.state[\"joint_eff\"]`` is per-joint estimated torque in N·m, sign-corrected, with the same 14-slot layout as ``joint_pos`` but raw effort in the gripper slots. The values include gravity load, so compare against a moving baseline. Rising effort while position stops tracking indicates contact; flat effort with position error indicates controller sag. ``joint_eff`` may lag ``joint_pos`` by up to one control tick because they are read in separate lock acquisitions.",
      "type": "input_text"
    }
  ],
  "role": "system"
}
{
  "content": [
    {
      "text": "Goal: Classify the two types of objects on the table and place them into the two baskets.",
      "type": "input_text"
    }
  ],
  "role": "user"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.0193, 0.8024, 0.6155, -0.3798, -0.0223, -0.033, 0.9993, -0.0154, 0.7986, 0.6106, -0.3843, -0.0185, -0.0254, 0.9996]\nstate[eef_state]: left_x=0.2968 left_y=0.0018 left_z=0.183 left_yaw=0.0006 left_pitch=0.0 left_roll=0.0004 left_gripper=0.9993 right_x=0.2953 right_y=0.0023 right_z=0.1808 right_yaw=0.0 right_pitch=-0.0 right_roll=0.0 right_gripper=0.9996\nstate[joint_eff]: [-0.5675, -1.9761, 9.4017, 1.7851, -0.0171, 0.149, -0.0757, -0.7043, -1.388, 9.7846, 1.8242, -0.0562, 0.105, -0.0513]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 0):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:c3fe0e38c969a7fa4d1442e41d28b54b0939b86df253a3d917de5c86ef06da59",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 0):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:d5062d1edb43c0fd7cfb019a51df93d2b584d61139871f591eb840887fc009c8",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 0):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:e3fbbe3773a1d6db7e1e7880ff26b998f7fb50ab96771803a3b08feac65502b5",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob c3fe0e38c969
wire blob d5062d1edb43
wire blob e3fbbe3773a1
call 1 attempt 0 · /responses · status 200 · 6.723 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3
{
  "content": [],
  "encrypted_content": "gAAAAABqtF3UOvJe1O5sjQN1l_9azu6gfZUbxbQMfBEmOAOGn-vSBCDGPHJyb_ZLlIcbcB6vTbaOL4RXFo5gOJTyZnhFLPVjLsoxmwAq5AmHzNTGn7wibxBqIPGS7oHQ1hl2A65aYEX4XE1mz6gCcWZRvglan_GzPlMtKP8QMNDE8HxkWU3T0J65_Yg8Tx1_0m67Rt7sNhHFnT72mVSchb2cN166stOoBJY-95rVJ2beVqgEGbotTLnwjhVbCPT6CHrhrz2kcjaOH01jgXgP9kqOjqetbNcfR3BnN3KRMTtvRM0HvIuM8B31bufy7tNSLFDYo_o8hUIAJqTC8oJ9gLmDHp1sPuFHR7uGHLBS2eplySlXBz94E11VNdxd3qmcDNgpnKHJTJNp-IGYMac4h6TIXDz-SKpgGYNLskPKeUuJLq2a-HZyQshtEWaERF9RzI-EyFQyD_rpE_9pPYJcYpwJ2wT98hKyhlPtu3E9Nl6k75v41MrGam-miCaHebfL9TiiJepeF7I52erfyNTtkm1m3hNxftk85jN9RXpcSTbum4ASFIVu3ii-eFJsLNr4c5IxwmKae1C24xHp_pWmB07ZkuY7su2VOgGxPKugpzeeiQiiLE-l0NRWPkjAxIzNvg4kvHinzr4mP9VD3culKiOk3rw8ZztpmV6y8AgZAkYRoNYJv7513HbE24qkMVPhMlczS2lWTAl-uEaVvw-cOlN6rLWW6ViFxtqrT3cOhm20JQrRPencrtuCmTq_ejwP6vwhfxqP1VA6tI6eS2-h-cZSWsIbOvho_nYMc8hRmLmrDWJeL75zR4GnerH4c252jRgCQ2lyD0luuicKhudtSoes-9wtuo23C1VZgWHlZFlfkNZSlu1RQiSg4KLs8Cos7F60I1ZpfA1fRFlg0e87-KBFMBcNA4hCownjV9gR9gnQs8mw4GDux_Ggi-YebhlxUU0F1-9z_Kr50uG0pCg-yyG7VjxyFwppwCqXpOl4RIUweA7T1DCFQdvkED-Rwx_P3NSKO22-YbupNp2SQVXArzq2fOB6HpMCK12SbFcQ2JHbNEIfMityG-GecHFO9akZKuvfSO8-SGXvxEBgWz_a_61_sChECJoBX9fzwpt1svRNy8xAMLkeD71vcq5dvc506pZW0z02fQHy1eCFw_eC_k_blmW4A1xMMiP2T5K6cHPl3_1NiKtPmoDkTk-Mc_wHqwGhHf6GCoH9MFjWC-G6zVI59MTxq87gU0z4mjoL9yRIG7l6sjZWF1koePCau2XlDGUeXy2AQQlSWcb8XEWymZJfHlcilmH_7sM8sImJFs6b-MTbP16teutH9W4tJWc16A0SunwcL7xzQ0Ow7chUE7GfJxeehJ63VOpg5Ht3EiD-i5SrTz6IzYD0sgAv2xPvYrPpZd1kDiBn4JS0i74UXxH8D8ta4gmmx7Ur7mN9-ctBsHB_lJo2ifqBfASat4TXremp6frL6Hb8AzET3B_ja0smJXh03Wz6CYuhjj3CvsQ8zThF-Wp6cGj42vRN2qOeBwm2nw3EDhQVuNgnMKMCwK1t66Gg0Bsvjf8xxw63d3Hi6xq0H_dKoOVGOLKTnOv71BKC6AbGtfnGoOeZ9GpfEhnPz8iefc9_93DYSiLXwQnHlgGIHwlmNIbRA0JhbQtm8Eq37YALTSJ_E4uImNPis8gGbOp82SnumnHnjXTkByCr93t1IsE7Kf3sg4HvPs7912w9oa3viW2-DNzYSF4z_78YRiEeVpo4w0WbPb0cdDTcK5IDvws6oJ1-oUzKlklDVKdCEBJN1hzRGKiEX67Y50bRIiVgHtfibn00sG6JLqEtjy12l21V-KdB7O_kNiE5mblYd67aJ_Y-R6WExqeIXz3wfFwgn07O8GNKrEDkUUI_9-euOku6FoBNsR6GvIM56q9k7nIDFCgLEycl4p4Pm4tk5YYhKUH23pVRjJ49V4F_K2y9b1TMdWou5TjQq-E30r2Nef2fSmW2J228jGJgGWQsn0p2cvmkvZUnRtUfiJmj5K8wDvjW-MZLIj5tMij-cnicEA-Lm_SM4IbKDxbXRZmNVJbhTZ9PVwkk5WJYnE3s1Ssk6-8sjVQUnMINplgTmWdzFH6_gMY4gZ4bSyW0HzbiTCKVcucBsim2HjkwSuuNY6VNN8Z5BiH9acx9dcXUKMB1BClj3FVGgindwTTY7IsjtLRftm4jWj9_B_SrBe4LLGwSOpKABbrvX9-G5OunKnRxuFg-kXAH",
  "id": "rs_0a7c08ab22ccc1f9016ab45dcfbd7c87d0815fd32e245911b8",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.3,\"left_y\":-0.105,\"left_z\":0.15,\"left_gripper\":1,\"right_x\":0.295,\"right_y\":0.002,\"right_z\":0.185},\"note\":\"The table has plush animals clustered in front of two empty baskets; I can distinguish long-eared rabbits and floppy-eared dogs. I’ll start with the gray rabbit on the left and sort rabbits into the left basket and dogs into the right.\"}",
  "call_id": "call_106OkZG8rZyvbWkwzCeoBeji",
  "id": "fc_0a7c08ab22ccc1f9016ab45dd3002487d0b4dc435bee1b57fe",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_106OkZG8rZyvbWkwzCeoBeji",
  "output": [
    {
      "text": "executing move_to over 10 steps (1.0s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.625, 1.0176, 0.577, -0.2581, -0.4976, -0.3828, 0.9993, -0.0154, 0.7986, 0.6106, -0.3962, -0.0193, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2956 left_y=-0.1049 left_z=0.1416 left_yaw=-0.0239 left_pitch=-0.0343 left_roll=0.0145 left_gripper=0.9993 right_x=0.2937 right_y=0.0025 right_z=0.1784 right_yaw=0.0011 right_pitch=-0.0118 right_roll=-0.0 right_gripper=0.9996\nstate[joint_eff]: [0.1983, -2.8513, 7.6103, 1.7656, -0.4469, 0.0122, -0.0757, -0.294, -0.759, 8.3624, 1.7167, -0.0366, -0.0024, -0.0171]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:36def65d2fdb900136dc41886ec918dfaa0c46263f90d4367b7bd3e8a04e036b",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:a2bc7deeae01a383ae806ad8aea24c9a2442f78fde786a919fb0e0e3254c2dab",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:166d991b5c132a8a94d04d71a62d4ca228bbf4c234d6ef4f26f6862bb007be50",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob 36def65d2fdb
wire blob a2bc7deeae01
wire blob 166d991b5c13
call 2 attempt 0 · /responses · status 200 · 6.056 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 2 changed as sent

message 6 changed as sent

message 2 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.0193, 0.8024, 0.6155, -0.3798, -0.0223, -0.033, 0.9993, -0.0154, 0.7986, 0.6106, -0.3843, -0.0185, -0.0254, 0.9996]\nstate[eef_state]: left_x=0.2968 left_y=0.0018 left_z=0.183 left_yaw=0.0006 left_pitch=0.0 left_roll=0.0004 left_gripper=0.9993 right_x=0.2953 right_y=0.0023 right_z=0.1808 right_yaw=0.0 right_pitch=-0.0 right_roll=0.0 right_gripper=0.9996\nstate[joint_eff]: [-0.5675, -1.9761, 9.4017, 1.7851, -0.0171, 0.149, -0.0757, -0.7043, -1.388, 9.7846, 1.8242, -0.0562, 0.105, -0.0513]",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 6 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.625, 1.0176, 0.577, -0.2581, -0.4976, -0.3828, 0.9993, -0.0154, 0.7986, 0.6106, -0.3962, -0.0193, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2956 left_y=-0.1049 left_z=0.1416 left_yaw=-0.0239 left_pitch=-0.0343 left_roll=0.0145 left_gripper=0.9993 right_x=0.2937 right_y=0.0025 right_z=0.1784 right_yaw=0.0011 right_pitch=-0.0118 right_roll=-0.0 right_gripper=0.9996\nstate[joint_eff]: [0.1983, -2.8513, 7.6103, 1.7656, -0.4469, 0.0122, -0.0757, -0.294, -0.759, 8.3624, 1.7167, -0.0366, -0.0024, -0.0171]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:36def65d2fdb900136dc41886ec918dfaa0c46263f90d4367b7bd3e8a04e036b",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:a2bc7deeae01a383ae806ad8aea24c9a2442f78fde786a919fb0e0e3254c2dab",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 10):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:166d991b5c132a8a94d04d71a62d4ca228bbf4c234d6ef4f26f6862bb007be50",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
[blob 36def65d2fdb]
[blob a2bc7deeae01]
[blob 166d991b5c13]
{
  "content": [],
  "encrypted_content": "gAAAAABqtF3domXP-8C4jC5-s883u3G7GsDxYXH5kAE7yS3-0HB8EZbwjIfkyxqgkJQyY0lBTDLSW_qwGE4U-siS4RVRYjenUzzYMpZLIJoO6xDCWxLa7YCRNrP3_AjgrAbz2fozuPh7L2pvA2NdOZJhPrJd2Jl2JcyiPKdA145_CWKS2NX8d7vMOmdA33c7yN429Zjj-GwoR72Igv-qQ5zs7LTzwd8NOBXTk1SYSeH9xgVwKPT85tZvDseJ3-uiRxZvxaYuimCXfOYr_ZPdvluu4XhJMUY3Efdc2yFzMuMqYQ9QN8l3visZ8QNWA7Fk_ArtE3lq1dy00soFP7IHNcqxEwLLpjozzyAEp9dS_qNPIorJ2V3hcjE7UlsZOSR6voVgjNHzJDOqqA2FTWc-puqbBM39pw1hfej2OMcsaisY3N5gZTRmAqJkV_xxQq8wbl7NGgfBIqBy-gKGkhbdY8ursJKbcisSg2GYhBk6Wi24b8SvuBpeJKy89VfUwzk6mVoev9BtYeI4HJV7EkoRCyQyU9jx278InwX2xVW1HucgG95BsEiXfLcESMA1wMtgMyDoUwH_OHNEyO7Il5zxb56X5FwkSfIBP91nYYu8G-QptJmIJoQyk4grBOs_ksUGNR4E-VntLrczrRRrma9I_ihD5gBA81Ag0mvn9S7cSUueMKBZ5RXqfJEO4Ix8LusQOFeO1IZc9Kp8qd696DCS0qT1pHu_RTYPnMOshPBwnwtyEUNrgI2MMvT8jysSrJ4fn5lzNeGSGDPiFfDLtaVTqBczI7lL5mmdAN1C2fs6yrimfLu1U2a76zcMaxD0S7Qqt2cCvsIAcvPOK8hzga-3IYIxAd55VKhilgX0AubyI_9OGDDmXIy73XCOWOUvCPaadc6S-oms_afPOqyeLxrTEkLpMIf1TAi7vFiDQA5Y9nPxFnr5QsE-bPg3vUcHoLsWU7T_HUlZDNcQD1xBaRx59NWO7zxQbAZpBPD6JVnTG8tlrIyO6MukQj4LdQ3Y6jUkqFPdlgX4qHBi0aeCn8KZ8pwUUvSRIipFuDrzLSJsqf4AsLoflhz3J-Cwa4Ot8H5NCWr6R2ak0io6GqAj3tJXKucrOMSTQ6TtFMLPh8WzNNa8zhBu6U315tW_C_K7zdq7evkmpiZVkozIP6rR4YoynwF2yWSP0TMO_x5lCYM-GqCcGWHlzT__TmNaU83nM9ZrimbIaAa2_ogpimSrh0dKfjMCp0xZYSHUzSkwOt1gHu9P7m0yUSAizgOznHBeBsKD3D-ab2ZDIQ1Ojq9tb_MY309dUl1chojD3E0Lf-vaTAvEpWzTWdHk_ETYOb_uskVLfpL5_VbnzugUBR0Oj5pHEnDEzsesACR9xdmZzVrkk-WkocBgCswN_3z3nPYsVDaQ_RZtBxw91SFF53d4-iNKJyRNWsuBp-yV6y7Hoz9dICp5MNGIoWoN8An7tcn9rUc2evPEYA9S_4MUu3W96WU3YtJqkFoDNWh_tUCmCcojuIyd-KwEXi7IUgSXdRGMOwYXXfWQIddJdk0s5ZskXsBi8beGbtNTiYeLrALzMuAwmMY2KLi99PBynOcEFuNpwQt92rkY2B2ylOI-uI9XiqytfTcvsQgSRn6y0IhaiOa6nXSa2mHenRE-jwXi2ozLa-V8tuYUu8jFgYWdrTDw7yC1mQierDhM2YVU0iFyj03PdpmiXU4Wwl-GQmijYu-l8wV3eQGZwXsL30SZE1jD_ObEVFAazdwMtaFQa1NpMKylbLeVbqF2MVe30F2lM5PnygIMD2YfDVIsHlNFFsFbERWlrcBsCC1K75glsGY6iOZYctRPTXOkgnUHKTlBESbgPV4gKTB7RxlbKgrxZEM3lFqQ0natIm_-izgT-pqdp3LI0_blhnTKyqSiNJoK6GX7aG2Xze7DOyywnNT3DQvVgPyWkiX-LKUdl5P-pg==",
  "id": "rs_0a7c08ab22ccc1f9016ab45dd91eb887d0a0b9bb7c0dd01eae",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.34,\"left_y\":-0.035,\"left_z\":0.105},\"note\":\"The wrist view shows the gray rabbit left of the jaw centerline, while the brown animals are to the right. I’m shifting left and slightly forward to put the rabbit between the open jaws.\"}",
  "call_id": "call_nubpJANLIQnZ5qwqqxzHDczb",
  "id": "fc_0a7c08ab22ccc1f9016ab45ddc3d3487d0b9ff6d0f67b59a45",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_nubpJANLIQnZ5qwqqxzHDczb",
  "output": [
    {
      "text": "executing move_to over 7 steps (0.7s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.189, 1.1522, 0.4747, 0.0441, -0.1715, -0.1249, 0.9993, -0.0154, 0.7994, 0.6086, -0.4072, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3384 left_y=-0.0304 left_z=0.102 left_yaw=0.0061 left_pitch=-0.0564 left_roll=0.0151 left_gripper=0.9993 right_x=0.292 right_y=0.0023 right_z=0.175 right_yaw=0.0006 right_pitch=-0.0255 right_roll=-0.0006 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -3.7128, 6.0513, 1.9805, 0.0366, 0.188, -0.0122, -0.3077, -1.2786, 7.1863, 1.8486, -0.0415, -0.0611, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:cf22b556b5beafd1c4ed2d835c59a8e961a85820e9e4b0012cae02801e5f09b2",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:797775d9d21c65a1ac61f70ea5ca0a1ffef30d7dea0fa15867cd416af6cb28f2",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:708fee70ed0a8598dc4720cfce52de33b4fcd8c2e095c15ad4190026c682c177",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob cf22b556b5be
wire blob 797775d9d21c
wire blob 708fee70ed0a
call 3 attempt 0 · /responses · status 200 · 3.378 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 6 changed as sent

message 10 changed as sent

message 6 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.625, 1.0176, 0.577, -0.2581, -0.4976, -0.3828, 0.9993, -0.0154, 0.7986, 0.6106, -0.3962, -0.0193, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2956 left_y=-0.1049 left_z=0.1416 left_yaw=-0.0239 left_pitch=-0.0343 left_roll=0.0145 left_gripper=0.9993 right_x=0.2937 right_y=0.0025 right_z=0.1784 right_yaw=0.0011 right_pitch=-0.0118 right_roll=-0.0 right_gripper=0.9996\nstate[joint_eff]: [0.1983, -2.8513, 7.6103, 1.7656, -0.4469, 0.0122, -0.0757, -0.294, -0.759, 8.3624, 1.7167, -0.0366, -0.0024, -0.0171]",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 10 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.189, 1.1522, 0.4747, 0.0441, -0.1715, -0.1249, 0.9993, -0.0154, 0.7994, 0.6086, -0.4072, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3384 left_y=-0.0304 left_z=0.102 left_yaw=0.0061 left_pitch=-0.0564 left_roll=0.0151 left_gripper=0.9993 right_x=0.292 right_y=0.0023 right_z=0.175 right_yaw=0.0006 right_pitch=-0.0255 right_roll=-0.0006 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -3.7128, 6.0513, 1.9805, 0.0366, 0.188, -0.0122, -0.3077, -1.2786, 7.1863, 1.8486, -0.0415, -0.0611, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:cf22b556b5beafd1c4ed2d835c59a8e961a85820e9e4b0012cae02801e5f09b2",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:797775d9d21c65a1ac61f70ea5ca0a1ffef30d7dea0fa15867cd416af6cb28f2",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 17):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:708fee70ed0a8598dc4720cfce52de33b4fcd8c2e095c15ad4190026c682c177",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
[blob cf22b556b5be]
[blob 797775d9d21c]
[blob 708fee70ed0a]
{
  "content": [],
  "encrypted_content": "gAAAAABqtF3lllWHYrurSwvRYfGMo54hWNcr4g81tOvzVEXWrNM_TiCG9MTHNR8hoqQNjLMKs15YEeNa7EkXu_-XTKBKcUrX1hXK7zL4Siq4V2Eb2wcEutIaj3ljoP0b4QZAyD2aGrqn13MqomUataiJYRtpv6Tr-z4OtLsomFTVfQEAwnzGM_vebedAO3o7n1YiIccV8DVOPw9eYAjEbQYrtJI1b0GUWXbOHyv4vwX6g8QujJyWNKFuCcZfvdHakhoAg4gBKsENhdqMIFIf_-WrgnE4stQ9ZYm-tA-OIkzu2ly00qPpJEMWVjdK2FvptEGB4q8SxxYLaHnMlLniX_PNX4Drqj_Lg-974qTvUKDQqqqLkv_gpO3GAbSmtvvbozozefUIZQ10xq05wQ4Pk0ZCSOB4eaAWDm6y6Vtu5WrmzkyVUhUX9mGnsuNhANyiL6K6564herx1v9PjfbruU3PpNHcIScjCRu2BUOzcOjf_x1aQo0vN8wcVhqa0uvppODzc_hKYjuuUSVpoAqiv-SFeTJjVQDnwIr3G4BMbaES1AxMF-605034mh57wbr9xBSEZYrtzjiIg7MVzFZ4nwXL5d1F5uBQTOmKoRFoLTa6iDEEB1Ik7LwUbWREqUVlWFP0LwxDiKt9Gl0Cc31rir-ZGn-1927WqzLoNypr644h76DyeG4BUVSz2xJQPA3bNZ66ueOFO5jpvZZ9JRBvJLDmLho4gEyMRzJ0UzqIVthHlmkjSB1NOOP8ymSLVO3wYVv0wDCkXo6RuaiWyYhy_yvwB4LtNTvfAH45kU4ikcBU5XvHk6f8msX5VcRlK8f5Y9bQpPHzFfNX-emQ4hzU98FvhrCkIWd9mTY6hPg_6KX6gwemUk-QQSWYRB6p33OMgtpBOAFaTKEKbzcSmmkC1mj1fP6t_h3iM18mVDFYWg8D0HSTFq67VPNJ3t79Tsb76bOCtUWwYgzrc_HyZUb4bvdHj3K3_TFi-aTRbrDoBlH56141gKtHdQH-VupVvX54H6hIEFS8m3bH1CsP4nxRcIU-hEfMCRN6wJj_2U-shPP8pt9X6oHUZKCqqq4nvsFb4RkW32U-fQqjZetdTG-xsYhsBb-hCadCG3G_iTr2jbFcHEYyLA-pWAGa4EsB9bHi9U_Uh2l9syis7JTPcSYsfKhY5i9rHSSPE33fVNdE0jn7kFsKOeDfVKdvWg3zLXP0nFKf1GT8n-WvexwTZreROi_uFSMdfA8HVNq_BUMY2yWRM7r-NSEEqonUt1APxZ9JQMzvK95YFdBvttVbf__Qp_9y_C3S590jpi2omgiT5sH2H6rUUO9v-3ywqrXq2gPgBhDR7JGtou40BTGxVon8XHuwv2IJJrpP0KgzARMIlXKOLdPzzpxt1Q31E-T9rk0EfeizhTkxJ-KqRoY8cH3Zjg54GnoL3nNdIKjyDSuBvVbv2gfPOwr6Q2lqdLmEEYbnqRYXLhNRBIkqB2S84iDlT7rJW-_szwwX_FNdNPMwVH9Y6VI6NPUed2VB7FjVEn5LahGynIc3dS_iWuIAb5v1bgQq0V4CF_bBdlgdlA8VtU-1-P3Cmfzieaabl0fZDt5Mi2cr4xX-KQQ64ZqTVrtJ1BVb38qmIHRFi6-euq8FsQvPV5QPZbWPDCG5wDmGv8wldJx_P2ofPVTkp6MeTWD0b8MTpy3v73QB1OGnvSZEJ-gM3-B1wWbgUwZzQb56Ue1kGK19R8Ugyr-rKTjHFcsAkQvUmt06iTXvh7Hhi4L6vae18oAzQhdm6fsaAYZsysL_EuhzD7yOX4fFOl-6QArTPWu86Zler4a1l4BiJiW-BDcntPy8zyE5mHgTwv7r_m_L23PdnB2pMA_4RCMFpO0D5_F1DOuz26cX88_lAXulsZn9-zgGD1Ekv3nlnlW5k-FwSjX_TScJvqiJS-bFMCs6Q6byw3O9V5V9ZKw==",
  "id": "rs_0a7c08ab22ccc1f9016ab45de0a38087d098166a02ec8104d2",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.338,\"left_y\":0.015,\"left_z\":0.035},\"note\":\"The gray rabbit is still left of the fingertips and is now close beneath them. I’m correcting the sideways alignment and lowering to grasp its soft body rather than an ear.\"}",
  "call_id": "call_ITDVpBVGiyyQCgCZLHBBncpa",
  "id": "fc_0a7c08ab22ccc1f9016ab45de38a6487d08d92bf50e149fa66",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_ITDVpBVGiyyQCgCZLHBBncpa",
  "output": [
    {
      "text": "executing move_to over 5 steps (0.5s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3849, 0.3061, 0.5407, -0.0139, 0.012, 0.9993, -0.0151, 0.8032, 0.6086, -0.4084, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3514 left_y=0.0187 left_z=0.0576 left_yaw=0.0247 left_pitch=0.0279 left_roll=0.0342 left_gripper=0.9993 right_x=0.2921 right_y=0.0025 right_z=0.1737 right_yaw=0.0008 right_pitch=-0.0305 right_roll=-0.0002 right_gripper=0.9996\nstate[joint_eff]: [0.2667, -2.8376, 3.9453, 1.2527, 0.2125, -0.0855, -0.0171, -0.1026, -1.5932, 7.0085, 1.7118, -0.0464, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:6bb0a46e6d89c79753e0fb4ebaee6a49547ee73492a2c3e36a34f239a29b7d58",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:b4680e392b5f5d271f4d12f0c964170ce887b96d3a643f5844a9ac78d6338f1a",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:5c918ce9f0e7d7ea74a45e5e2765e799d9a4196359137d160dd924adc04d0d21",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob 6bb0a46e6d89
wire blob b4680e392b5f
wire blob 5c918ce9f0e7
call 4 attempt 0 · /responses · status 200 · 3.747 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 2 changed as sent

message 10 changed as sent

message 14 changed as sent

message 2 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.0193, 0.8024, 0.6155, -0.3798, -0.0223, -0.033, 0.9993, -0.0154, 0.7986, 0.6106, -0.3843, -0.0185, -0.0254, 0.9996]\nstate[eef_state]: left_x=0.2968 left_y=0.0018 left_z=0.183 left_yaw=0.0006 left_pitch=0.0 left_roll=0.0004 left_gripper=0.9993 right_x=0.2953 right_y=0.0023 right_z=0.1808 right_yaw=0.0 right_pitch=-0.0 right_roll=0.0 right_gripper=0.9996\nstate[joint_eff]: [-0.5675, -1.9761, 9.4017, 1.7851, -0.0171, 0.149, -0.0757, -0.7043, -1.388, 9.7846, 1.8242, -0.0562, 0.105, -0.0513]",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 10 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.189, 1.1522, 0.4747, 0.0441, -0.1715, -0.1249, 0.9993, -0.0154, 0.7994, 0.6086, -0.4072, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3384 left_y=-0.0304 left_z=0.102 left_yaw=0.0061 left_pitch=-0.0564 left_roll=0.0151 left_gripper=0.9993 right_x=0.292 right_y=0.0023 right_z=0.175 right_yaw=0.0006 right_pitch=-0.0255 right_roll=-0.0006 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -3.7128, 6.0513, 1.9805, 0.0366, 0.188, -0.0122, -0.3077, -1.2786, 7.1863, 1.8486, -0.0415, -0.0611, -0.0122]",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 14 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3849, 0.3061, 0.5407, -0.0139, 0.012, 0.9993, -0.0151, 0.8032, 0.6086, -0.4084, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3514 left_y=0.0187 left_z=0.0576 left_yaw=0.0247 left_pitch=0.0279 left_roll=0.0342 left_gripper=0.9993 right_x=0.2921 right_y=0.0025 right_z=0.1737 right_yaw=0.0008 right_pitch=-0.0305 right_roll=-0.0002 right_gripper=0.9996\nstate[joint_eff]: [0.2667, -2.8376, 3.9453, 1.2527, 0.2125, -0.0855, -0.0171, -0.1026, -1.5932, 7.0085, 1.7118, -0.0464, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:6bb0a46e6d89c79753e0fb4ebaee6a49547ee73492a2c3e36a34f239a29b7d58",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:b4680e392b5f5d271f4d12f0c964170ce887b96d3a643f5844a9ac78d6338f1a",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 22):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:5c918ce9f0e7d7ea74a45e5e2765e799d9a4196359137d160dd924adc04d0d21",
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      "text": "",
      "type": "input_text"
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[blob 6bb0a46e6d89]
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  "encrypted_content": "gAAAAABqtF3qjNouJ0JAUoI6wymK07_KP41zm8-Fq3YvGIRF9P9ckfrNeTF2DBFMmO07BTFcdzmDI9R5sE__KluECqtorc4umzMIaLhaCaJVV7MJwpq8kq1gZuPYtVf9bDqzrkdXYaGb1lUnMsI8iTP0CfVG4QZoFfXAY1MlnjaRJ8icbRZbS41pQSLFEtXr3saytTKR1-DdHQfeatL0i2MSv9HLz0ULT1e-I0viOhEPeAXMBS8Tjl7segYySHUkpC40XhAS4cTkLTIJcNZep3o2C3AjnbB8HRGoxDUihBT6or7jTdCnZFx6bEzXiDHZ5xlyQvJ869t7GI_zY4Wp4EWq1-V2SU4xL_9cWXFezk41Zz0Ovv1b6dUVj92mgdSEELUBCv3pgmf-idqheho5RRVEfZr3P7FGHUcONmpvkqbXZp2GSOg-k-rhaB8qMIWxLxmQtB62csavpBBC57T8Jgl7Mr4Cp1NUqCVsoLXcK911-MDynChI1k98UvEyZwE0JOpnmkmjPnHMgIf8RevIwD6z7RnNQ1PB1l9frflFFhteV6DH-iti-Nak_BlXHwvMQsKV37qLIgEvIWLzzqVHCmMXSmzwoUBHmHzxdajIs1-89lS0CIeVOMCqWmXl4-2DsTYKkm8l8G5BohEOT-8GAODV47LCtfmLk7sNXKzSoJ97SWC4ovBDbq9ntocLpRgFlUeoLvRIRX3jVjjFbKpyF-Sy8XKh0x3FBZwIp2BoTEeKpaNX9NYF6KPzTzxEUZOwuRZfZgnW73xHArASL_Un36waIj4lzRR05FWA298oulFuqfK2gjBk5ReSW6Nv-pWdqqtvPJ3U7vRai5WxLhoJZUSHF1vtoR3AB6ZDpKQwgjUv9wpKnX1Rv2bq_0zAi11hoMQqu1j9Qck-CBn53XseAfpiPNr22-RCKGY-2lcvNI0SQt8L_i5qpXUlB_ubgS6rA1kg5NER-5Zi_f4tRSP6mfOzU0J-nE3LYO0ZF89rpfjh7N5S5BcYAn51wfLjJgcWwQXHYttl_lnIAy9m64D4xtiRGl9yCKRk5YYObPqPCh84ywxoIObQo-wm1Wx-ua13LhFEpa8gzEUH4w_RfxeVU5NTdWnjWlKyHACitDHugtyZgFpQD69wvLJ9X77zwMwaNsXbocHWVxWqZyIHUsBtkDwTx5IZI-tdRft64oPffxG8apOW1YySU9wVnW-IAEkj9h8a7ZX_1GISq7nRnggCxnNiI_D4x_FbaUD1vAihOFVVypEu5ew221jErDqdAbU5PXXOoNWfKgkTuNXsT-yJn6JID30fOoFOGoD_zBDEawpv1stSqRhkT9BqrgIktHpo_UOUe7YNO6XZN1vkbxj22Yixy5fL8abxk5sPO9u74f7TyimOw1811RLg_kQlrtpKZKigj--dudWCABL2WoeIKhyQR1p9uDV0Hg==",
  "id": "rs_0a7c08ab22ccc1f9016ab45de8a6d087d099929db882b4fc13",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_gripper\":0},\"note\":\"The left gripper has reached the gray rabbit and the descent stopped slightly above the target, consistent with contacting the plush. I’ll close gently through the controlled gripper motion and check the resulting jaw width.\"}",
  "call_id": "call_UlXk35s3KFoE5hWw2Fu0fpM2",
  "id": "fc_0a7c08ab22ccc1f9016ab45de9bca887d0ac42f818cc43f8ec",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_UlXk35s3KFoE5hWw2Fu0fpM2",
  "output": [
    {
      "text": "executing move_to over 10 steps (1.0s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3808, 0.3122, 0.5446, -0.025, 0.0074, 0.0099, -0.0154, 0.8051, 0.6086, -0.4084, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3539 left_y=0.0208 left_z=0.0622 left_yaw=0.0365 left_pitch=0.0421 left_roll=0.0359 left_gripper=0.0099 right_x=0.2922 right_y=0.0023 right_z=0.1732 right_yaw=0.0006 right_pitch=-0.0324 right_roll=-0.0004 right_gripper=0.9996\nstate[joint_eff]: [-0.1983, -3.9043, 4.9162, 1.7705, 0.105, 0.0024, 0.779, -0.294, -1.4564, 7.0769, 1.7363, -0.0366, -0.0513, -0.0122]\napprover: 1 step(s) modified (delta_clamped).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:d7375ff8b938cf8d78574e65667c46750dfeb59f9cfee84b3eb0410513b756ba",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:f817c1fa1b992b2661c64db4aa3424bcb3f51887d181cf4e104a04c4a683bd05",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:8cd320f2273a7737f7deb14a21c49785785dee94f094bec50636f3cb5e7ceb15",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
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      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob d7375ff8b938
wire blob f817c1fa1b99
wire blob 8cd320f2273a
call 5 attempt 0 · /responses · status 200 · 3.995 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 6 changed as sent

message 14 changed as sent

message 18 changed as sent

message 6 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.625, 1.0176, 0.577, -0.2581, -0.4976, -0.3828, 0.9993, -0.0154, 0.7986, 0.6106, -0.3962, -0.0193, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2956 left_y=-0.1049 left_z=0.1416 left_yaw=-0.0239 left_pitch=-0.0343 left_roll=0.0145 left_gripper=0.9993 right_x=0.2937 right_y=0.0025 right_z=0.1784 right_yaw=0.0011 right_pitch=-0.0118 right_roll=-0.0 right_gripper=0.9996\nstate[joint_eff]: [0.1983, -2.8513, 7.6103, 1.7656, -0.4469, 0.0122, -0.0757, -0.294, -0.759, 8.3624, 1.7167, -0.0366, -0.0024, -0.0171]",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 14 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3849, 0.3061, 0.5407, -0.0139, 0.012, 0.9993, -0.0151, 0.8032, 0.6086, -0.4084, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3514 left_y=0.0187 left_z=0.0576 left_yaw=0.0247 left_pitch=0.0279 left_roll=0.0342 left_gripper=0.9993 right_x=0.2921 right_y=0.0025 right_z=0.1737 right_yaw=0.0008 right_pitch=-0.0305 right_roll=-0.0002 right_gripper=0.9996\nstate[joint_eff]: [0.2667, -2.8376, 3.9453, 1.2527, 0.2125, -0.0855, -0.0171, -0.1026, -1.5932, 7.0085, 1.7118, -0.0464, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 18 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3808, 0.3122, 0.5446, -0.025, 0.0074, 0.0099, -0.0154, 0.8051, 0.6086, -0.4084, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3539 left_y=0.0208 left_z=0.0622 left_yaw=0.0365 left_pitch=0.0421 left_roll=0.0359 left_gripper=0.0099 right_x=0.2922 right_y=0.0023 right_z=0.1732 right_yaw=0.0006 right_pitch=-0.0324 right_roll=-0.0004 right_gripper=0.9996\nstate[joint_eff]: [-0.1983, -3.9043, 4.9162, 1.7705, 0.105, 0.0024, 0.779, -0.294, -1.4564, 7.0769, 1.7363, -0.0366, -0.0513, -0.0122]\napprover: 1 step(s) modified (delta_clamped).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:d7375ff8b938cf8d78574e65667c46750dfeb59f9cfee84b3eb0410513b756ba",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:f817c1fa1b992b2661c64db4aa3424bcb3f51887d181cf4e104a04c4a683bd05",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 32):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:8cd320f2273a7737f7deb14a21c49785785dee94f094bec50636f3cb5e7ceb15",
      "type": "input_image"
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    {
      "text": "",
      "type": "input_text"
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  "role": "user"
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{
  "content": [],
  "encrypted_content": "gAAAAABqtF3wWebZl3hOSSNMmh60Zi1PwRwJggZ6apMrfANXx2HIpNuKczILwjAkXuHXwSxyFA0xpbTeRo58iOwh4iyOwdUr5rFMVXhvXTWkF6hfWqZsI1TTvYAkiiqvynpo7EeQdKEVHfZDnyFmkI6QpNmR7ULn_MOe64xR7YYzFZNROpE0ABseBsXtptnrT7VkmD5z_SAoh1TQyXW5ABfFSY3tl7KikYxvGT0Q6uXxKlcUfY8yco_HAtsKKgEUZnK6bCm6WX-3rXcaPG3OaMuZWiNCGILQYzme4UddbZl0kDChvsyS0OOutAusehj6UKX2uMO6znkdWx2CzvIe1a5sVhzHPQ__f0ddAVl0VbVshLS_fR2U0SiaNROawNheAMvCVGGcLD3n_0CXAxj9GnPFrZ6GnsKEE42LobnCxy8bGLoN9CPh9nozoxTa4GSDpSHIQdcINlefkDnjDZYGVnp6FHgEgERGNiNe_cBN91ulJuilX9KJ-lqndWDiMeZ3x2ml-wQMO12eheo-kKYEOieykLwHl7uhRzYDP5jd0agVOvz_w8p6ujtYV0l7e2T6yluXj67B8Js1SxUJKb_BNH_224SiaOXf7qyp2CGsC8-NbdfLMwcsQBeOH7PWmu58xoR637tHIfN2wV0xG3ivzjipMNJpplm1S7wXYZ5BHWBCxci_DbFRcejK8jDZxzSQkq22NXsVfdyKIUuINZCnas58ecwAcdXTXFQWHDC7v-RbBxj7wIXS8CICKZl6kfh34-1u81mZbGC6UCBiL2stL_6xYR2AuLnjNB4KUz8OwlpAfBsI48mYKuO3lZLREJ4XEOY5UViUFndm_OHKYEbg4aAKxDpmskd2m668mLh56IBDE856GXRITs0LuNkj-MPkK1y4YkSIdQaaNl-PAaPb15EOVTnqGkXe8hmYPQXzBDmweRTY8kPiuVJxi-SnCgCpmPWicXhnYnmajEFGCLM0BaZJBlmrge0q_HmDnm81Mp5pTt9y6SF3fUGS9l4eqHThiW1Ef8jBVZa1GFXx2Jz8f-_edJs8h-f4DS7WcPBwAxtGMZTyc8A_K3dr-hfUekGfl_Uat6jg-ah9gHblPNrxFUWfC5FbgzFPF4KwS3wXS5I58SVgwMMifbCJJtYmvt7vOQn2tt08pQFsvfdrLgGHo0oXgRawGP5MGsYfLNCGqylRnrxj9UIs5z2MI7AF4R0iNqjLzlYBmAcaoIeM282ve7xO7MyjNyLw9ADZ7HiUohP9QC-5tjocwEdll3k59bEEpebP2gcFlllTpMDqBr9O6IGAbs0CR0DYulUN6Dt-EpOPrrTFce3HghV4jl5spgIF2uGB8i-DxQzN-RviDA9EJqUHxOmsAVMGs6TAc0dnvyNRoSWHUBWj6PRWMAd5tG2Hj1lwbyFPPcnI",
  "id": "rs_0a7c08ab22ccc1f9016ab45dedeeb087d08fd2f59f3cefbe70",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_gripper\":1,\"left_x\":0.38,\"left_y\":0.015,\"left_z\":0.02},\"note\":\"The jaws closed nearly empty, so the rabbit was just beyond the grasp point. I’m reopening and advancing about 2.5 cm with a lower grasp before retrying.\"}",
  "call_id": "call_aGpszakBR6tQhbp9yyb1gx62",
  "id": "fc_0a7c08ab22ccc1f9016ab45def222087d08ca8e1ad6d5f959e",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_aGpszakBR6tQhbp9yyb1gx62",
  "output": [
    {
      "text": "executing move_to over 10 steps (1.0s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0044, 1.6981, 0.3519, 0.9482, -0.0704, 0.0151, 0.9986, -0.0154, 0.8082, 0.6086, -0.4088, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3937 left_y=0.0177 left_z=0.0531 left_yaw=0.0396 left_pitch=0.1681 left_roll=0.0609 left_gripper=0.9986 right_x=0.2923 right_y=0.0024 right_z=0.1723 right_yaw=0.0007 right_pitch=-0.0358 right_roll=0.0001 right_gripper=0.9996\nstate[joint_eff]: [0.212, -3.5487, 3.7675, 0.9451, 0.1441, -0.2759, -0.1538, -0.1983, -1.4154, 7.0359, 1.6777, -0.0562, -0.0171, -0.0171]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:33b881fe739d7dcae29bb41698dba8bd2ed9ef8127b3defb6f8ce5165836c310",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:67cc69ded0de7b496144fe181ed7f39dbb8fdfcbce2f5d28c1cb3152a365189d",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:7189f1bfba0922ac93da7ef9d2de266e321fc61800892ef882fba4bdaa462ed3",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
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      "text": "",
      "type": "input_text"
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  "role": "user"
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wire blob 33b881fe739d
wire blob 67cc69ded0de
wire blob 7189f1bfba09
call 6 attempt 0 · /responses · status 200 · 7.092 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 10 changed as sent

message 18 changed as sent

message 22 changed as sent

message 10 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.189, 1.1522, 0.4747, 0.0441, -0.1715, -0.1249, 0.9993, -0.0154, 0.7994, 0.6086, -0.4072, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3384 left_y=-0.0304 left_z=0.102 left_yaw=0.0061 left_pitch=-0.0564 left_roll=0.0151 left_gripper=0.9993 right_x=0.292 right_y=0.0023 right_z=0.175 right_yaw=0.0006 right_pitch=-0.0255 right_roll=-0.0006 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -3.7128, 6.0513, 1.9805, 0.0366, 0.188, -0.0122, -0.3077, -1.2786, 7.1863, 1.8486, -0.0415, -0.0611, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 18 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3808, 0.3122, 0.5446, -0.025, 0.0074, 0.0099, -0.0154, 0.8051, 0.6086, -0.4084, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3539 left_y=0.0208 left_z=0.0622 left_yaw=0.0365 left_pitch=0.0421 left_roll=0.0359 left_gripper=0.0099 right_x=0.2922 right_y=0.0023 right_z=0.1732 right_yaw=0.0006 right_pitch=-0.0324 right_roll=-0.0004 right_gripper=0.9996\nstate[joint_eff]: [-0.1983, -3.9043, 4.9162, 1.7705, 0.105, 0.0024, 0.779, -0.294, -1.4564, 7.0769, 1.7363, -0.0366, -0.0513, -0.0122]\napprover: 1 step(s) modified (delta_clamped).",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 22 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0044, 1.6981, 0.3519, 0.9482, -0.0704, 0.0151, 0.9986, -0.0154, 0.8082, 0.6086, -0.4088, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3937 left_y=0.0177 left_z=0.0531 left_yaw=0.0396 left_pitch=0.1681 left_roll=0.0609 left_gripper=0.9986 right_x=0.2923 right_y=0.0024 right_z=0.1723 right_yaw=0.0007 right_pitch=-0.0358 right_roll=0.0001 right_gripper=0.9996\nstate[joint_eff]: [0.212, -3.5487, 3.7675, 0.9451, 0.1441, -0.2759, -0.1538, -0.1983, -1.4154, 7.0359, 1.6777, -0.0562, -0.0171, -0.0171]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:33b881fe739d7dcae29bb41698dba8bd2ed9ef8127b3defb6f8ce5165836c310",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:67cc69ded0de7b496144fe181ed7f39dbb8fdfcbce2f5d28c1cb3152a365189d",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 42):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:7189f1bfba0922ac93da7ef9d2de266e321fc61800892ef882fba4bdaa462ed3",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
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{
  "content": [],
  "encrypted_content": "gAAAAABqtF35Doyd8T0jfRqZTIGZkZWWCMtxP3PRGzXCZFiWltOjUYjZ5vnZ31NGyJ8TAc-ztyZXnnFQh6CNqD5PgwI_zHCUPuvVlPEWcC5nzp5n8dcnJOQ3N1UfXbAgAgKo2Z-6HOrXdDBDJLP4kzGb7KtpTHM2hvhmj5-YmIKSypNqAFMxTsbNlk3b4U0iJ6kjVnoLu-ttzPxq0cIlyqJ5ld1rsUXsMIRXPRHGgtzB8IRx96PB3r8HyqG20dzyk1kXTtzu5h-rMd9B9ael_04eU9E5obUD0PnFEKFz4OkrDci90MjqCmlD1UeuuCjE57AL3HMPWnRm8rsG61Yox6x34xwGt_TooUB7OcO3otC5e6lkrZoKEZQKhx6NxgeqnYunUxUqRVMp9fY7K8dVWMDWJdRxpP4CHVGHqw4jRqji-mTnS8x4-uS6ASvyC3kgfrk4FqHNtkLln5OprWlHR25msBpmRAKNJKAURrwDGK5OPu3ib8yXvgoFKQWVIWPlCtIygFlT9y0wJOmPTgz1RPnYO91-dDiDvk78HkQ0mDT5LRz4drCKWOEyFgIySsLq4YhDAUhK7s6A8M0Izwa25Q-aitPDaodoKAloPfFRpBiw_ssx7Xj8nTWLi03oY4UGfIiTbIvOCaGO-9xgr1OvyCh95cQSa5Ea8hp98qb2bX8IWQ2bY2ck1s0thxFvhWqPuMkd8lMyD8q0FxkPXMdzvLL7wHMAYVJm4J6XKRXr4UP5w-jCSppOSoyhZv8GKUqipKGHqYvBYEjAEYwFK5_0nwtN-Ck--uWuDTtj2TVa7A_VQdbCzlQhGYrbkEJRHmDZFrDx7RfZ5LlzPnUK5qBVbVIIBzYzkLjeKMaw0xauUtNtp0JNQQ0njEDlR0v_A-lnhzVzCnaXsvtXs75wccQAve4bue4TA6_iPNhQZHo0LjRibEyexU1WUa9lWPhOaqgsJvEs4mNlhUQE_cQS0dZcSGeY-pSKKKqoAh2gR9kc7yIeUm1LEraP9w4neDLTTjfJYFTjWTbDAU8d2Sz6NFwuIvBhyK9bdXF1Q5h7WmZa984BlLJUV_W4-czH0FHHpvBO0hT2fxpjX5UyZ2b6mvk4YDRjvCSBSKE4t-IdxMiaSOy5vnlqUP7fDtghrc-c4i_JVUWCeHwzZJMCQsug5GWgNcwGZPORVJ7TFe5bA73aNDZ1zsKVh3KbESatKNFvTvbA9dlctPxopzWN4qtvafsLKObAzxP31FhBEh2X2A04aO_H0S1Y-0rueCXjYuqTIP2itwsmRXEHYnJBiCQCnJI4D0sqeOWnl7mRvmYix-0aibgsMllhpbD_5U7iCh3ja7IY6KiPEXujr9kCK3Pd1vFIgUPvahXTDFDqG3D9lloBqX2NVcLECsqRYqm3ZjvTaFQmFwM4h9Ok13wSPJnlihI3LF35Tb3HxFKplcNJ2_C8gBwsNHtDj7Q-i_Q=",
  "id": "rs_0a7c08ab22ccc1f9016ab45df748c887d098a3ad0710ce93a5",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_gripper\":0},\"note\":\"The rabbit’s gray body is now beside the inner finger after the forward adjustment. I’ll try one more close, then use the jaw reading and a short lift to determine whether it is securely caught.\"}",
  "call_id": "call_Hi8bQMTarL4gorKfG7PePBpT",
  "id": "fc_0a7c08ab22ccc1f9016ab45df8c53887d0858530cef85e2729",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_Hi8bQMTarL4gorKfG7PePBpT",
  "output": [
    {
      "text": "executing move_to over 10 steps (1.0s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0051, 1.6943, 0.3607, 0.944, -0.0784, 0.0113, 0.0099, -0.0154, 0.8089, 0.6083, -0.4088, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3963 left_y=0.0195 left_z=0.0566 left_yaw=0.0493 left_pitch=0.1768 left_roll=0.0601 left_gripper=0.0099 right_x=0.2923 right_y=0.0023 right_z=0.1719 right_yaw=0.0004 right_pitch=-0.037 right_roll=-0.0001 right_gripper=0.9996\nstate[joint_eff]: [-0.1846, -5.2308, 3.5897, 1.9658, 0.0513, -0.0024, 0.7937, -0.253, -1.4017, 7.0222, 1.6728, -0.0415, -0.0269, -0.0122]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:a4ba5632328e43423b3fdf47525213a1372adf412bc9d2a7b68da6c90715ea98",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:0dcb28351b9ef6fa3433f68a5b9528ccb74b0ee6854d3e4354873b9735652547",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:bfc0f582c281b2f24476e88370d730706e6de9064bf575268b767d91ccea12c0",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob a4ba5632328e
wire blob 0dcb28351b9e
wire blob bfc0f582c281
call 7 attempt 0 · /responses · status 200 · 11.33 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 14 changed as sent

message 22 changed as sent

message 26 changed as sent

message 14 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3849, 0.3061, 0.5407, -0.0139, 0.012, 0.9993, -0.0151, 0.8032, 0.6086, -0.4084, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3514 left_y=0.0187 left_z=0.0576 left_yaw=0.0247 left_pitch=0.0279 left_roll=0.0342 left_gripper=0.9993 right_x=0.2921 right_y=0.0025 right_z=0.1737 right_yaw=0.0008 right_pitch=-0.0305 right_roll=-0.0002 right_gripper=0.9996\nstate[joint_eff]: [0.2667, -2.8376, 3.9453, 1.2527, 0.2125, -0.0855, -0.0171, -0.1026, -1.5932, 7.0085, 1.7118, -0.0464, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 22 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0044, 1.6981, 0.3519, 0.9482, -0.0704, 0.0151, 0.9986, -0.0154, 0.8082, 0.6086, -0.4088, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3937 left_y=0.0177 left_z=0.0531 left_yaw=0.0396 left_pitch=0.1681 left_roll=0.0609 left_gripper=0.9986 right_x=0.2923 right_y=0.0024 right_z=0.1723 right_yaw=0.0007 right_pitch=-0.0358 right_roll=0.0001 right_gripper=0.9996\nstate[joint_eff]: [0.212, -3.5487, 3.7675, 0.9451, 0.1441, -0.2759, -0.1538, -0.1983, -1.4154, 7.0359, 1.6777, -0.0562, -0.0171, -0.0171]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 26 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0051, 1.6943, 0.3607, 0.944, -0.0784, 0.0113, 0.0099, -0.0154, 0.8089, 0.6083, -0.4088, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3963 left_y=0.0195 left_z=0.0566 left_yaw=0.0493 left_pitch=0.1768 left_roll=0.0601 left_gripper=0.0099 right_x=0.2923 right_y=0.0023 right_z=0.1719 right_yaw=0.0004 right_pitch=-0.037 right_roll=-0.0001 right_gripper=0.9996\nstate[joint_eff]: [-0.1846, -5.2308, 3.5897, 1.9658, 0.0513, -0.0024, 0.7937, -0.253, -1.4017, 7.0222, 1.6728, -0.0415, -0.0269, -0.0122]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:a4ba5632328e43423b3fdf47525213a1372adf412bc9d2a7b68da6c90715ea98",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:0dcb28351b9ef6fa3433f68a5b9528ccb74b0ee6854d3e4354873b9735652547",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 52):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:bfc0f582c281b2f24476e88370d730706e6de9064bf575268b767d91ccea12c0",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
[blob a4ba5632328e]
[blob 0dcb28351b9e]
[blob bfc0f582c281]
{
  "content": [],
  "encrypted_content": "gAAAAABqtF4CEIx490OE7kMoZrmHShMbtld1T56jjl1Ej3ElIccp7CXm8NjjvbBP1mhQmER5RQA-xM7eoeuBv0m2xKtZlbTIE-n3ojeyNF-bacD1WQbOv3pAgswdfgKqtvOJWQu7NXg9WaZOHGUK14o0bmv09h2v_No8M0lPDYzXfE2CR61iT6zqX4V3sjVyFSDF2n3WTmIhTdsTgIFZ71J0M009swrdzkOY-zgTDYzVuueVNe2meVbTMfCNEFFWRmjgAS6N2TAC7gWktBlllGEQrWuGUCi9UWEuKi15czvcH1VATQbP4q46DJ2qUdA2cqI22NjbCJ_Yx3KblZ2XkqxYNM5DPVgy48qiO0wknhyB4RsUTp8rLHtYqeKqCwe5TPkORC9E3Ygqktqjb96kI0Fc6vtdvJi4xJiypwaF-ihQBz8HLWUoGC39wiNqrei4pc0CQWADmDOm9AXwuduRXJDWgdovjCGsL9lqPQMsa3TudEVlm-LNUgcy0Dho_lx0VkU69qjYg65uDiJDRpClYXKoyjIRexeJLNPOSdU9C0WH48bn4vDHwf35vRSF4UjAjI3Gn44e8aMGmNPNbyQBhEjHCnA1ZFptUQw70zPztP2ufw43bputEkZAHqIsUwN9APc7ciYBmjWmFgbg9DeoU4BWJqN8bLalMtn3hQPdY-sq3LKGV6Cz81o-zcJo3dkGOTY46qT9N8MgicAmXksePVIc1NHCUkYKPU3UUqHGBfw8Cuu_WcckSWLieEBEESYHbbUTGxQCAsFPnceS8DjyJtXxSuJunNxIfzNpH5L4ZzrXOn0t_MJhzkaM2_AP34Js_tjq05dwMv5y7atnasPa9G6lAadn9q6Il5efXwDBedrvJ2QUjkRUbon_wy1G3VVtI90j4OwMRo2tX1sLVAW0ymW_fyZ3Btl9bBwxKfwWN1wlBwcQZlcw-Kf7-5xsUySXvDoMHDTNwtqDqzl1AntcVP2eZUXBAul-O_DYqL4mR65DkA3XENvEUqNEX1iDZIe2hi3w9jeMS44NO4Cph3PSIxEsvsWIF_PakCMmhtPthC_yOXGZDQ3mbJym7RRsC3JCGP6jU7ka1L3NZ0s8l5k8x-l9Z5aIVhcNblkKC-73ESkw9WsEGrKQ34LE1ZoADZT7M3MiNk7eJNlCU-pcvQZfiRRKjEzjbFe1NAeoI0Fev207JBWDgyQaqvl4BeqKaewkfFeoDTPKcjMnSBig5S2_QJrAlQN1mxTnjJfqfe6SyOuCcBY4DwLcPosr33PN7Vs9QpD8vd1BetObHGqTJMpwxGiv69E_JaQHlpDAy9bh1SUDn7QO3514Tcmf5nvY3iTjlxT9A4gyoiTijS_Lh41iJ7VJEbKDrnmMpIOXhOdqlzK3I0OZ2tV2iPvn0GSaS-9am8obUbbAFe2s2UmKEo2HvE0qOEzMrbTME2CoeAhQ9gTuvB8alp45NJIgM5RrLuYiMddvtOtd9LyLw18zXYfPcLdQqK3bjhUCE8-Noj-y2uTf1hcoruom1GoAGgWoSDS7XirDgx-WqY0s9QzSq5EKCVzLVtt_Y9IfEnhErTBefnuk7WO43sIa6iKE7Z9QbsvSCCrru-akqL_RxRNwuZnp3oitlebmLAwKmKEkyVDXdma16HKtVKgiyBieQzWbZSPGLzD4Qk9SXIJ7yPuJoeHky1XbiZj-gmdAPooSD_K0sC-Nx6hjAn8PFrAhr7hPKBoG8AxUgD6EGA7vJSPshqw0nWPLa8sTUSbThiHSbBFEyEIoSgCAvmNjzeuUi9I71pU3IcW-Gp0wyU-N5m5vJD1yFM4CWgBZQAqt0xzes2T9pvxljHY8DhiF2vuE8Vp6t384FakKDDqlna1_XuKRUq8V0U-lAHeQm5CmzJ96mFfoI-5s_gT19fOROhDtKEp4G0bRrtBy_C2en89eAHkvA3EadFuwm-L0waRK-emNmTWc19u8RY456VnDc5A6mkqUy9xTBh8iAQSts0DEOm5fK3zr1RleWIXPhW_lyTktZdVvc3zEVaubVmEV6geQ69vybiPV-8f6zBRQX_sX8caW537PXPxv4lTmRE1K49bLMI3aEN0K9FO5fsSLPOCqhT846HXQav-6YjSmW82vNKKEMVfhnlnVivmiZnblnZrrzYwqfQWTZjv4SYawTi_dbzyJ3d4eYqeomNgghtAwLknv-iz9KnKPgHUHN3gZ97z6rZHuMtKgaA3fMZwkbBg=",
  "id": "rs_0a7c08ab22ccc1f9016ab45dfd913487d0b06bce92834c45ce",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.28,\"left_y\":-0.025,\"left_z\":0.23,\"left_gripper\":1},\"note\":\"The second close was also empty, so I’m not repeating the same approach. I’ll lift away to expose the leftmost toy and reassess its position from the overhead view.\"}",
  "call_id": "call_1XvjpQwC5WSoWpBJrCNIkocI",
  "id": "fc_0a7c08ab22ccc1f9016ab45e00f67c87d09e19dbccd9062801",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_1XvjpQwC5WSoWpBJrCNIkocI",
  "output": [
    {
      "text": "executing move_to over 12 steps (1.2s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.3569, 0.6674, 0.6022, -0.3576, -0.3904, -0.1337, 0.9986, -0.0154, 0.8139, 0.6083, -0.4099, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2816 left_y=-0.0294 left_z=0.2237 left_yaw=0.0306 left_pitch=0.1762 left_roll=0.053 left_gripper=0.9986 right_x=0.2924 right_y=0.0024 right_z=0.1704 right_yaw=0.0007 right_pitch=-0.0431 right_roll=0.0003 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -0.1299, 9.306, 1.5995, -0.2125, -0.0513, -0.1587, -0.2393, -1.2239, 7.1453, 1.6825, -0.0269, -0.022, -0.0171]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:13f14e1f817dcc935c2e2ab40680b1ca89e1a7a4487d534068ce955e09136f54",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:8108e89870ee51961c91233ebf4b5c9806b67d8b5bddcb0f6d67f804d8d5624e",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:98a61ad8f7e84cacb32b10ae851e033e1b34bd893f96c05b568a82e52d8dd9cb",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob 13f14e1f817d
wire blob 8108e89870ee
wire blob 98a61ad8f7e8
call 8 attempt 0 · /responses · status 200 · 10.5 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 18 changed as sent

message 26 changed as sent

message 30 changed as sent

message 18 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.036, 1.3808, 0.3122, 0.5446, -0.025, 0.0074, 0.0099, -0.0154, 0.8051, 0.6086, -0.4084, -0.0185, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.3539 left_y=0.0208 left_z=0.0622 left_yaw=0.0365 left_pitch=0.0421 left_roll=0.0359 left_gripper=0.0099 right_x=0.2922 right_y=0.0023 right_z=0.1732 right_yaw=0.0006 right_pitch=-0.0324 right_roll=-0.0004 right_gripper=0.9996\nstate[joint_eff]: [-0.1983, -3.9043, 4.9162, 1.7705, 0.105, 0.0024, 0.779, -0.294, -1.4564, 7.0769, 1.7363, -0.0366, -0.0513, -0.0122]\napprover: 1 step(s) modified (delta_clamped).",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 26 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0051, 1.6943, 0.3607, 0.944, -0.0784, 0.0113, 0.0099, -0.0154, 0.8089, 0.6083, -0.4088, -0.0185, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3963 left_y=0.0195 left_z=0.0566 left_yaw=0.0493 left_pitch=0.1768 left_roll=0.0601 left_gripper=0.0099 right_x=0.2923 right_y=0.0023 right_z=0.1719 right_yaw=0.0004 right_pitch=-0.037 right_roll=-0.0001 right_gripper=0.9996\nstate[joint_eff]: [-0.1846, -5.2308, 3.5897, 1.9658, 0.0513, -0.0024, 0.7937, -0.253, -1.4017, 7.0222, 1.6728, -0.0415, -0.0269, -0.0122]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 30 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.3569, 0.6674, 0.6022, -0.3576, -0.3904, -0.1337, 0.9986, -0.0154, 0.8139, 0.6083, -0.4099, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2816 left_y=-0.0294 left_z=0.2237 left_yaw=0.0306 left_pitch=0.1762 left_roll=0.053 left_gripper=0.9986 right_x=0.2924 right_y=0.0024 right_z=0.1704 right_yaw=0.0007 right_pitch=-0.0431 right_roll=0.0003 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -0.1299, 9.306, 1.5995, -0.2125, -0.0513, -0.1587, -0.2393, -1.2239, 7.1453, 1.6825, -0.0269, -0.022, -0.0171]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:13f14e1f817dcc935c2e2ab40680b1ca89e1a7a4487d534068ce955e09136f54",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:8108e89870ee51961c91233ebf4b5c9806b67d8b5bddcb0f6d67f804d8d5624e",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 64):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:98a61ad8f7e84cacb32b10ae851e033e1b34bd893f96c05b568a82e52d8dd9cb",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
[blob 13f14e1f817d]
[blob 8108e89870ee]
[blob 98a61ad8f7e8]
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  "content": [],
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  "id": "rs_0a7c08ab22ccc1f9016ab45e0730fc87d0a9064b6e406e6f68",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.37,\"left_y\":0.05,\"left_z\":0.012,\"left_pitch\":0,\"left_roll\":0,\"left_yaw\":0},\"note\":\"The clearer view shows the two categories are plush animals and pens/markers, rather than different animal species. I’ll put all plush toys in the left basket and the writing tools in the right, starting with the gray toy’s accessible inner edge.\"}",
  "call_id": "call_gEfMgruptZfLGbVhrcjMV5dA",
  "id": "fc_0a7c08ab22ccc1f9016ab45e0ff32087d09036965a237bf6db",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_gEfMgruptZfLGbVhrcjMV5dA",
  "output": [
    {
      "text": "executing move_to over 14 steps (1.4s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.1959, 1.7126, 0.3401, 0.7658, 0.1524, 0.0788, 0.9981, -0.0154, 0.8185, 0.6067, -0.4084, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3631 left_y=0.0484 left_z=0.0056 left_yaw=0.0085 left_pitch=-0.0322 left_roll=-0.0059 left_gripper=0.9981 right_x=0.2927 right_y=0.0024 right_z=0.1687 right_yaw=0.0008 right_pitch=-0.0477 right_roll=0.0003 right_gripper=0.9996\nstate[joint_eff]: [0.4308, -6.3932, 5.3128, 1.37, 0.1685, -0.2955, -0.0708, -0.253, -1.388, 7.2547, 1.7411, -0.0317, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:eabf16ca0396d670be1dbdd0d7b7e4bb808e95f9742a219f0633ec5a86e5f2ae",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:6ee840dacfafe8ebca53671b9257bf9ecda509cef14c83dbceb792a84d383096",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:d1fb7fbfee1281551cfa3beefc61abcb0a13dc9cad8478885f2e7771607ace7e",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob eabf16ca0396
wire blob 6ee840dacfaf
wire blob d1fb7fbfee12
call 9 attempt 0 · /responses · status 200 · 11.99 s
model
gpt-6-astra
effort
high
temperature
n/a
tool count
3

message 22 changed as sent

message 30 changed as sent

message 34 changed as sent

message 22 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.0044, 1.6981, 0.3519, 0.9482, -0.0704, 0.0151, 0.9986, -0.0154, 0.8082, 0.6086, -0.4088, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3937 left_y=0.0177 left_z=0.0531 left_yaw=0.0396 left_pitch=0.1681 left_roll=0.0609 left_gripper=0.9986 right_x=0.2923 right_y=0.0024 right_z=0.1723 right_yaw=0.0007 right_pitch=-0.0358 right_roll=0.0001 right_gripper=0.9996\nstate[joint_eff]: [0.212, -3.5487, 3.7675, 0.9451, 0.1441, -0.2759, -0.1538, -0.1983, -1.4154, 7.0359, 1.6777, -0.0562, -0.0171, -0.0171]\napprover: 10 step(s) modified (delta_clamped ×10).",
      "type": "input_text"
    },
    {
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 30 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [-0.3569, 0.6674, 0.6022, -0.3576, -0.3904, -0.1337, 0.9986, -0.0154, 0.8139, 0.6083, -0.4099, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.2816 left_y=-0.0294 left_z=0.2237 left_yaw=0.0306 left_pitch=0.1762 left_roll=0.053 left_gripper=0.9986 right_x=0.2924 right_y=0.0024 right_z=0.1704 right_yaw=0.0007 right_pitch=-0.0431 right_roll=0.0003 right_gripper=0.9996\nstate[joint_eff]: [-0.253, -0.1299, 9.306, 1.5995, -0.2125, -0.0513, -0.1587, -0.2393, -1.2239, 7.1453, 1.6825, -0.0269, -0.022, -0.0171]",
      "type": "input_text"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "[3 camera frame(s) elided]",
      "type": "input_text"
    }
  ],
  "role": "user"
}
message 34 current as-sent form
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.1959, 1.7126, 0.3401, 0.7658, 0.1524, 0.0788, 0.9981, -0.0154, 0.8185, 0.6067, -0.4084, -0.0189, -0.0261, 0.9996]\nstate[eef_state]: left_x=0.3631 left_y=0.0484 left_z=0.0056 left_yaw=0.0085 left_pitch=-0.0322 left_roll=-0.0059 left_gripper=0.9981 right_x=0.2927 right_y=0.0024 right_z=0.1687 right_yaw=0.0008 right_pitch=-0.0477 right_roll=0.0003 right_gripper=0.9996\nstate[joint_eff]: [0.4308, -6.3932, 5.3128, 1.37, 0.1685, -0.2955, -0.0708, -0.253, -1.388, 7.2547, 1.7411, -0.0317, -0.0269, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:eabf16ca0396d670be1dbdd0d7b7e4bb808e95f9742a219f0633ec5a86e5f2ae",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:6ee840dacfafe8ebca53671b9257bf9ecda509cef14c83dbceb792a84d383096",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 78):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:d1fb7fbfee1281551cfa3beefc61abcb0a13dc9cad8478885f2e7771607ace7e",
      "type": "input_image"
    },
    {
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
[blob eabf16ca0396]
[blob 6ee840dacfaf]
[blob d1fb7fbfee12]
{
  "content": [],
  "encrypted_content": "gAAAAABqtF4gcR4KBS1wLLrRKC4akfEqu4bwQ2ThUzeKOJUAMsga4OgAcsV0iHfnhwq8kmaxW5ir4eAHc5Q25lD-lDCKAOJ2OfS4tZ4ApkrLIvo9ud7g_e8Kj_4pWdSOG1GLD-3m7W2_VQlDpFZ1vB2Mu6RxJYIV2Zy-JyY9BBy0amZLQiZkRJZnOg-CPVeysrc_I8Gj_2FjEdEyPTeiooBdN5DzR-SZDtQ58BqxDRgkl4k-8rmLEvVM2NIYOvbHUOJeIuaDFBBwue2KwgtatzJ8xNbvT3yGTt5rd72woB6seMz7xfh0h5Nvo_tZ8p3ZkdJdqHlYbSOKdFExlXVF0tubtUtZDhxZtI_AOoSjz425zsfnPaB6mJINIwHfrb-AHBD3lVQrFSshAXcwy6y0IBc30hLcuU9KJKTQl_uQ6YkhxhjHxfVTra6gm1HFayd4gGlazjLw3nqVY-U_sE4zpCcQTF2ziRHxaW-PwSRXSChpIPW8w3Mr9ggBivQg75e9fqIRQI1-WniOsDKk-VpktS0q9LY3qRkEoH6bYNF6ebCt51T_IyMkYjlBLko5XiiqnjFOugdUUL_0ozkPwQHz2tq3HniyX_ExMhd_Np0JYuITK2CD1L47fy_tMbx2AwGgrEVBaTsDZpwK7SjgL-JRZMCeA39lmi9A3DH1bolrGQQMs4v44E7R22gBZDqJpOb4m6C8WxWgFPMn-JrOSLHrmPdTPnctOtY4ZNMZ5Xer-AlM6Smddm0kAEQARJUMmElz6gEC5sihdOB6jdO5oMzJ8V6xJXwWzwsxPiaAMCa-8zrFB7QHsIzmhiSvFttUuvNa2ssHTWAMsdzJnhebe5WQkzGVosSnCIEfArtlURJMu1vZfrzv_YeBFD1ztze14HWR0SXzOqE_VyNOL5smARsYekSeMfsFKAkjD2vkTtVvo56G7fX6TaApniPd43sk78fSxjynHjazOfwqC7egLhIq4OSpLD83H_uqjbdgMFdEjoOgttJbz__eh8jCZVSVmT_oMEmyMBR0fWeCBL6odDyX4HaRqH6w6Eaj0LlN9c9nuGZqlzxM_hvABq6KTB8Gl5Wk3T8WzOlk8mz4vGyy8sJeUGEFiwZj2t-y63vnfQK2GW7InDzQQ9j5l19qV4IIJk3vyawgJVIOj5PJC8FZaRM2SeopCheBE-tKnKDxYibBEV5l7ZzvZtD5zyq6vm6WDiXCDTHZrL8J6ER8Dc_UiueJad5k1ebkUebpBPyKiHAwcYDHM52efSHaQuZSTK8u-JuW4NXBrePCkXrInFiUA4SwueRvrob_ChtoCDwqlrDmgua6FAAPKvzs_d-0E7V9PzUGHWMTOkHDVaJzLN_x9eIJSXsOLYIlyBGILqjmasYCngctwrU__-4wC6qq9poFt2RZWFxDWI13TYxdih0uG34xGvjd6Qbx1gfS0RI7c8znjllpRb1SLoOK2ONXI0jHZinFLh6SZvh2T-RDc06gRxEtHkBJqocPigVAt4Pcou6zeNVGJMjGX6KufBNLtV8qnUIQSzZ8nEzpRtPjwpq42D0Wjuctexxj6JFewfHWq2PN43EsfD30-Xzf7ENfXksKStApXM3uRErkbWoufuwtBPrvJABm5SAixcFb0FV4pGO9eN0ue4PDLutjrb4wqBfHb6xhPsEuyre_v85wsusRm4Kv1I605pNJJTCte4V2UnCLtmDYuN8qCWWSg79VzQ1TqvZwVQzTHHulrtq2uaSd7PfYe6PdvQOjfpgswu0TP0hfMbTgrsegf7jbsVz2GOfcozOEpzPJqUeIAE6ut5m1xQSI_IFJB9DWiB37bhIYnJltAr80w7rHmJKCwctEeosoole6U4GkoCK7-ifiTjV6u87mVmUnvM_MMwySgxnmJd_Ngkvcw7XNHGoWZBD34u6PgbwwNBX8c193cILRoct8EYCrIVEnGIeLApIjxdUhH1YVojZumtwZ4vEZCFgPmb_45NI7YrSLXlVzcGXRmiNj55eksUeVkC0kuARW-3U0BRtRUWc5ErvfoYInont97yRL4hicrB_WZys0-jVr5Mvpsj4iInPnx4nHSQh-SSsSr4hxOVLdEzYgpkuOEzj-obKDB1rIHLv3zb3_vPcZdtiSVfmhMro76uzf6cQjgClPnOR57BL5cFDI4OjdG3roPxRqt8DWPgFz5r8YsUfgmOI3pn_3TCDj4CnKl6aezqyMy4_3Q88oMRcvfLZHpgAHwZIUl5zb_QDSNsmIX576ZvF37oQ5oSERM10Yd-CpfefXewLqHtJJMumWeMQIt-342_Vtb2vEzyT9NtFd3d-16ZOJYEj38BMk5l2D4uvhUVwLOomXiXPpLRJPsZvtnh1cA8YNCL9I2cuLFhmBIAcOBkA5HEISBG_ch0dIZc60dtBQLdH3N4YlIn6PU8DxpHJ3J0vUjVKmN_gAfS1QmJHU-xT4qP976K7URlBBsh_1nGtMoHyn_C0upj5N2pTsW5iS_rQpkC_CbSb8l9YdFqYwPj8a_3sxv-uDP7SpW-F-FI2eqGJ9RsjtkXyxao8ghtVGNfM1PMCT_1MdP83nfAywx4S_EFmb0rqlzqFl41_TFQA7qBdiffIe_tEW_Ii0BMcRk8ZS85KzAv4Son7Jdqhnuz6ErxGvyo6SYg75PVezChkSFXavha3gUe8liaycMshhMKSb76labVP4I-QG4hK6VDgcxQBPuhaYfgreDzHF7jKWDMN4AtghkOrdIVh7XaLzuVCqs2ABGq0fohhcbi9E3RavjZgBVsaW-vP1MaStwGflyO9sZl2p5l_qdu3U8gL2V58ZlHS5aT9cbzZd0LFpZvOKvZRpjjus4UaXZOvh-curWjpAKjO3yXmmOQ1r8At0MfIK8B3OOVffrvNhZWCwy98p6OE043CT4PlQMZhgnj3lQRdVYMtl8IQDv0-zozM=",
  "id": "rs_0a7c08ab22ccc1f9016ab45e1910b487d0b6f9f2a1533abadb",
  "summary": [],
  "type": "reasoning"
}
{
  "arguments": "{\"targets\":{\"left_x\":0.455,\"left_y\":0.045,\"left_z\":0.04,\"left_pitch\":0,\"left_roll\":0},\"note\":\"The gray plush is farther forward along the outer edge than the earlier estimate; the open fingertips are still behind it. I’m advancing to its body while staying inside the left arm’s lateral limit.\"}",
  "call_id": "call_vfdQFbBLMR6pBqiuY9x8Ypm6",
  "id": "fc_0a7c08ab22ccc1f9016ab45e1ee98087d088fece131da9fe0c",
  "name": "move_to",
  "status": "completed",
  "type": "function_call"
}
{
  "call_id": "call_vfdQFbBLMR6pBqiuY9x8Ypm6",
  "output": [
    {
      "text": "executing move_to over 8 steps (0.8s)",
      "type": "input_text"
    }
  ],
  "type": "function_call_output"
}
{
  "content": [
    {
      "text": "Current observation.\nInstruction: Classify the two types of objects on the table and place them into the two baskets.\nstate[joint_pos]: [0.1322, 1.832, 0.6868, 0.5514, 0.1005, 0.0292, 0.998, -0.0154, 0.8215, 0.6067, -0.4095, -0.0189, -0.0265, 0.9996]\nstate[eef_state]: left_x=0.4458 left_y=0.045 left_z=0.0313 left_yaw=0.0151 left_pitch=-0.0238 left_roll=-0.0161 left_gripper=0.998 right_x=0.2927 right_y=0.0024 right_z=0.1677 right_yaw=0.001 right_pitch=-0.0519 right_roll=0.0001 right_gripper=0.9996\nstate[joint_eff]: [-0.7043, -7.4598, 7.0906, 1.7851, -0.0317, 0.0659, -0.022, -0.3487, -1.1556, 7.0496, 1.6923, -0.022, -0.0659, -0.0122]",
      "type": "input_text"
    },
    {
      "text": "camera 'top_cam' (step 86):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:8c91bad8a285cade5858cea87eb5fd1c99edaaa306189a3cd0d51c7c88d68293",
      "type": "input_image"
    },
    {
      "text": "camera 'left_cam' (step 86):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:4d6e5a878913e8fa018c19d9918cd0ddf2ad0c885f9275de6fd655144ee6cdc2",
      "type": "input_image"
    },
    {
      "text": "camera 'right_cam' (step 86):",
      "type": "input_text"
    },
    {
      "image_url": "data:image/png;base64,$blob:bd19d3d6b600a3d1dc24c3d7cbe4debfba556720ac5ab31d8e9073c56cb03da3",
      "type": "input_image"
    },
    {
      "prompt_cache_breakpoint": {
        "mode": "explicit"
      },
      "text": "",
      "type": "input_text"
    }
  ],
  "role": "user"
}
wire blob 8c91bad8a285
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