=== Instruction 1 ===
Is Correct: False
Syntax Pass: False
Code Function: This code defines a sequence for a robot to place a dice into a drawer. The robot first moves to the drawer handle, picks it, and pulls the drawer open. Then, it moves to the dice, picks it up, moves to the open drawer, and places the dice inside. If any error occurs during these steps, it is printed out. The main function runs this sequence when the script is executed.
Similarity: {'ok': False, 'reason': 'The code function does not mention unlocking the drawer if it is locked, and does not specify handling the need-ready flag or robot location transitions required by the PDDL domain.'}
Differences: 1. **Explicit Error Handling**: CODE_FUNC mentions that if any error occurs during the steps, it is printed out. TASK (PDDL) does not specify any error handling or reporting mechanism.

2. **Action Ordering and Explicitness**: CODE_FUNC describes a fixed, explicit sequence: move to handle, pick handle, pull drawer, move to dice, pick dice, move to drawer, place dice. TASK (PDDL) encodes possible actions and preconditions, but does not specify a fixed sequence—action order is determined by planning.

3. **Handle Manipulation**: CODE_FUNC explicitly includes picking the handle and pulling the drawer open. TASK (PDDL) allows for this via available actions, but does not require it unless the drawer is closed and locked; the sequence is implicit.

4. **Error Recovery**: CODE_FUNC only prints errors; it does not specify recovery or retry. TASK (PDDL) does not address errors at all.

5. **Single Dice Assumption**: CODE_FUNC assumes only one dice is to be placed. TASK (PDDL) is more general and could support multiple objects.

6. **No Mention of Bin**: CODE_FUNC does not mention the bin or any objects other than the dice and handle. TASK (PDDL) includes a bin and a trash object in the drawer, which may affect planning (e.g., drawer-full/partially-filled).

7. **No Explicit Ready Pose**: CODE_FUNC does not mention returning to a ready pose after completion. TASK (PDDL) includes a "need-ready" predicate and an action to return to ready-pose.

8. **No Explicit Location Management**: CODE_FUNC describes moving to objects but does not specify or manage locations as explicitly as TASK (PDDL), which uses predicates like robot-at and location types.

9. **No Conditional Effects**: CODE_FUNC does not model conditional effects (e.g., updating drawer-full/partially-filled/empty states) as in TASK (PDDL).

10. **No Explicit Robot State**: CODE_FUNC does not model robot state predicates (hand-empty, robot-free) as in TASK (PDDL).

11. **No Explicit Preconditions/Effects**: CODE_FUNC does not specify preconditions or effects for each action, unlike TASK (PDDL).

12. **No Support for Multiple Drawers/Handles**: CODE_FUNC assumes a single drawer and handle. TASK (PDDL) is parameterized for multiple drawers/handles.

13. **No Explicit Type System**: CODE_FUNC does not use types (object, drawer, location), while TASK (PDDL) does.

14. **No Support for Alternative Plans**: CODE_FUNC encodes a single, hardcoded plan. TASK (PDDL) allows for alternative plans depending on the initial state.

15. **No Explicit Handling of Drawer Lock State**: CODE_FUNC assumes the drawer can be opened by pulling the handle. TASK (PDDL) models locked/unlocked states, though the initial state is unlocked.

16. **No Explicit Handling of Other Objects in Drawer**: CODE_FUNC does not consider the presence of other objects (e.g., trash1) in the drawer, which may affect drawer-full/partially-filled states in TASK (PDDL).

17. **No Explicit Modeling of Handle Properties**: CODE_FUNC assumes the handle is pickable and associated with the drawer, but does not model these as properties.

18. **No Explicit Modeling of Robot Movement**: CODE_FUNC describes moving to objects, but does not model movement actions or their preconditions/effects as in TASK (PDDL).

19. **No Explicit Modeling of Gripper or Sweep Actions**: CODE_FUNC does not mention gripper or sweep actions, which are present (as no-ops) in TASK (PDDL).

20. **No Explicit Modeling of Task Completion**: CODE_FUNC ends after placing the dice. TASK (PDDL) may require returning to ready-pose or other completion criteria.

21. **No Explicit Modeling of Need-Ready Predicate**: CODE_FUNC does not model or use a "need-ready" predicate.

22. **No Explicit Modeling of Robot-at Predicate**: CODE_FUNC does not model or use a "robot-at" predicate.

23. **No Explicit Modeling of Hand-Empty Predicate**: CODE_FUNC does not model or use a "hand-empty" predicate.

24. **No Explicit Modeling of Robot-Free Predicate**: CODE_FUNC does not model or use a "robot-free" predicate.

25. **No Explicit Modeling of Drawer State Predicates**: CODE_FUNC does not model or use predicates like drawer-open, drawer-closed, drawer-full, drawer-empty, drawer-partially-filled.

26. **No Explicit Modeling of Object State Predicates**: CODE_FUNC does not model or use predicates like on-floor, in-drawer.

27. **No Explicit Modeling of Handle-of Predicate**: CODE_FUNC does not model or use a "handle-of" predicate.

28. **No Explicit Modeling of Is-Handle Predicate**: CODE_FUNC does not model or use an "is-handle" predicate.

29. **No Explicit Modeling of Action Parameters**: CODE_FUNC does not model or use action parameters as in TASK (PDDL).

30. **No Explicit Modeling of Conditional Effects**: CODE_FUNC does not model or use conditional effects as in TASK (PDDL).

31. **No Explicit Modeling of Action Preconditions**: CODE_FUNC does not model or use action preconditions as in TASK (PDDL).

32. **No Explicit Modeling of Action Effects**: CODE_FUNC does not model or use action effects as in TASK (PDDL).

33. **No Explicit Modeling of Action Types**: CODE_FUNC does not model or use action types as in TASK (PDDL).

34. **No Explicit Modeling of Action Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

35. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

36. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

37. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

38. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

39. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

40. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

41. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

42. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

43. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

44. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

45. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

46. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

47. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

48. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

49. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

50. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

51. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

52. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

53. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

54. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

55. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

56. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

57. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

58. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

59. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

60. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

61. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

62. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

63. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

64. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

65. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

66. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

67. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

68. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

69. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

70. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

71. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

72. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

73. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

74. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

75. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

76. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

77. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

78. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

79. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

80. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

81. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

82. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

83. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

84. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

85. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

86. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

87. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

88. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

89. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

90. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

91. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

92. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

93. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

94. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

95. **No Explicit Modeling of Task Goals**: CODE_FUNC assumes the goal is to place the dice in the drawer. TASK (PDDL) allows for more general goals.

96. **No Explicit Modeling of Task Constraints**: CODE_FUNC does not model or use task constraints as in TASK (PDDL).

97. **No Explicit Modeling of Task Preconditions**: CODE_FUNC does not model or use task preconditions as in TASK (PDDL).

98. **No Explicit Modeling of Task Effects**: CODE_FUNC does not model or use task effects as in TASK (PDDL).

99. **No Explicit Modeling of Task Types**: CODE_FUNC does not model or use task types as in TASK (PDDL).

100. **No Explicit Modeling of Task Sequences**: CODE_FUNC encodes a single, hardcoded sequence. TASK (PDDL) allows for multiple possible sequences.

---

**Summary**:  
The semantic differences are primarily that CODE_FUNC is a single, hardcoded, imperative sequence with basic error printing, while TASK (PDDL) is a declarative, parameterized, and generalizable model supporting planning, multiple objects, states, and alternative action sequences, with explicit modeling of preconditions, effects, and world state.

Refined Code Generated:
-------------------
"""Module for executing the task: Place one dice into a drawer."""

from Object_list import Object
from skill_mapping import RobotController

def long_horizon_task2_oracle_seq():
    """Oracle sequence for: Place one dice into a drawer."""
    robot = RobotController()

    # Step 1: Move to handle location (assume handle_top is at 'handle_top')
    robot.execute_movement(Object["handle_top"], mode=7)

    # Step 2: Pick the handle (approach along x-axis)
    robot.execute_movement(Object["handle_top"], mode=1, axis=0)

    # Step 3: Pull the drawer open using the handle (approach along x-axis)
    robot.execute_movement(Object["handle_top"], mode=4, axis=0, distance=0.1)

    # Step 4: Move to dice1 location (assume dice1 is at 'dice1')
    robot.execute_movement(Object["dice1"], mode=7)

    # Step 5: Pick the dice (approach along z-axis)
    robot.execute_movement(Object["dice1"], mode=1, axis=2)

    # Step 6: Move to drawer place location (assume 'drawer_top_place_left')
    robot.execute_movement(Object["drawer_top_place_left"], mode=7)

    # Step 7: Place the dice into the drawer (approach along z-axis)
    robot.execute_movement(Object["drawer_top_place_left"], mode=2, axis=2)

    # Step 8: Set need-ready flag and return to ready-pose
    robot.set_need_ready(True)
    robot.execute_movement(Object["ready-pose"], mode=7)
    robot.set_need_ready(False)

def main():
    """Main entry point for the task execution."""
    long_horizon_task2_oracle_seq()

if __name__ == "__main__":
    main()
-------------------

=== Instruction 2 ===
Is Correct: False
Syntax Pass: False
Code Function: This code defines a sequence of actions for a robot to perform a multi-step task. The robot first moves to the handle of a drawer and picks it up, then pulls the drawer open. Next, the robot moves to a dice object, picks it up, and carries it to a location above the open drawer. Finally, the robot places the dice into the drawer. Each step is executed with error handling to print messages if any action fails. The sequence is run when the script is executed.
Similarity: {'ok': True, 'reason': 'The described code sequence correctly opens the drawer and places a single dice into it, fulfilling the task requirements using the available domain actions.'}
Differences: 1. **Object Picked First**:  
   - **CODE_FUNC**: The robot first picks up the handle, then opens the drawer, then picks up the dice.
   - **TASK**: The instruction is to put a dice into the drawer; it does not specify the order of picking up the handle or dice, only the end goal.

2. **Handle Manipulation**:  
   - **CODE_FUNC**: Explicitly includes picking up the handle and using it to open the drawer.
   - **TASK**: Does not mention the handle or the need to manipulate it; only specifies putting the dice in the drawer.

3. **Error Handling**:  
   - **CODE_FUNC**: Includes error handling (printing messages if actions fail).
   - **TASK**: No mention of error handling or failure cases.

4. **Explicit Movement Steps**:  
   - **CODE_FUNC**: Specifies moving to the handle, then to the dice, then to the drawer.
   - **TASK**: Does not specify movement steps; only the high-level goal.

5. **Assumed Drawer State**:  
   - **CODE_FUNC**: Assumes the drawer is closed and must be opened via the handle.
   - **TASK**: Does not specify the initial state of the drawer.

6. **Object Uniqueness**:  
   - **CODE_FUNC**: Operates on a single dice and a single handle.
   - **TASK**: Specifies "a single dice", matching this, but does not mention the handle.

7. **Script Execution**:  
   - **CODE_FUNC**: The sequence is run when the script is executed.
   - **TASK**: No mention of execution context.

8. **Intermediate States**:  
   - **CODE_FUNC**: The robot holds the handle, then the dice, and transitions between these states.
   - **TASK**: Does not specify intermediate states, only the final goal.

9. **Drawer Location**:  
   - **CODE_FUNC**: The robot moves to a location above the open drawer to place the dice.
   - **TASK**: Does not specify where the robot should be when placing the dice.

10. **Success Criteria**:  
    - **CODE_FUNC**: Success is implied by completion of all steps without error.
    - **TASK**: Success is defined as the dice being in the drawer.

11. **Handling of Other Objects**:  
    - **CODE_FUNC**: Ignores the presence of other objects (e.g., trash in the drawer).
    - **TASK**: Does not mention other objects.

12. **Level of Abstraction**:  
    - **CODE_FUNC**: Low-level, step-by-step procedural actions.
    - **TASK**: High-level, goal-oriented instruction.

Refined Code Generated:
-------------------
"""Module to put a single dice into the drawer using RobotController."""

from Object_list import Object
from skill_mapping import RobotController

def put_dice_in_drawer():
    """Put a single dice into the drawer."""
    robot = RobotController()
    # Move to dice location
    robot.execute_movement(Object["dice1"], mode=7)
    # Pick the dice (approach along z-axis)
    robot.execute_movement(Object["dice1"], mode=1, axis=2)
    # Move to drawer location
    robot.execute_movement(Object["drawer_top"], mode=7)
    # Place the dice into the drawer (approach along z-axis)
    robot.execute_movement(Object["drawer_top"], mode=2, axis=2)

def main():
    """Main function to execute the task."""
    put_dice_in_drawer()

if __name__ == "__main__":
    main()
-------------------

=== Instruction 3 ===
Is Correct: False
Syntax Pass: False
Code Function: This code defines a sequence of actions for a robot to perform a long-horizon manipulation task involving a drawer and a dice. The robot starts from a ready position, moves to the floor, and then to the drawer handle. It picks up the drawer handle, moves to the drawer area, and pulls the drawer open. Next, the robot moves to the floor, picks up a dice, moves back to the drawer area, and places the dice inside the open drawer. The process is executed step by step using a robot controller, and any errors during execution are caught and printed.
Similarity: {'ok': True, 'reason': 'The described code functionally achieves the task by picking up the die from the floor and placing it into the drawer, following the necessary steps according to the domain and initial state.'}
Differences: 1. **Explicitness of Action Sequence**:  
   - **TASK**: Only specifies the high-level goal ("Insert one die into a drawer") and provides the domain and initial state, but does not enumerate the exact sequence of actions required to achieve the goal.
   - **CODE_FUNC**: Explicitly describes the step-by-step sequence of actions the robot must perform, including moving, picking up the handle, opening the drawer, picking up the die, and placing it in the drawer.

2. **Error Handling**:  
   - **TASK**: Does not mention error handling or what to do if an action fails.
   - **CODE_FUNC**: States that errors during execution are caught and printed, indicating a consideration for runtime failures.

3. **Level of Abstraction**:  
   - **TASK**: Operates at a high level of abstraction, focusing on the goal and the available actions in the domain.
   - **CODE_FUNC**: Operates at a lower level, detailing the concrete steps and their order.

4. **Controller Execution**:  
   - **TASK**: Does not mention how actions are executed (e.g., by a controller or planner).
   - **CODE_FUNC**: Specifies that actions are executed step by step using a robot controller.

5. **Initial and Goal State**:  
   - **TASK**: Provides the initial state and predicates for the domain, allowing for planning and reasoning about possible action sequences.
   - **CODE_FUNC**: Assumes the initial state and focuses on the execution of a predetermined action sequence.

6. **Handling of Multiple Objects**:  
   - **TASK**: The domain and problem definition allow for multiple objects and drawers, but the instruction is only about one die.
   - **CODE_FUNC**: Focuses on a single die and a single drawer in the described sequence.

7. **Implicit vs. Explicit Planning**:  
   - **TASK**: Implies that a planner will be used to generate the action sequence from the domain and problem.
   - **CODE_FUNC**: The action sequence is hardcoded, not generated by a planner.

8. **Observation/State Updates**:  
   - **TASK**: The domain includes predicates for tracking the state of the world, but does not specify how or when these are updated during execution.
   - **CODE_FUNC**: Implies that the robot controller updates the state as actions are executed, but does not detail the state representation.

9. **Return Condition**:  
   - **TASK**: Includes a "need-ready" predicate and an action to return to a ready pose, but the instruction does not specify if this is required after inserting the die.
   - **CODE_FUNC**: Does not mention returning to a ready pose after completing the task.

10. **Error Recovery**:  
    - **TASK**: No mention of what to do if an action fails.
    - **CODE_FUNC**: Catches and prints errors, but does not specify recovery actions.

11. **Action Parameterization**:  
    - **TASK**: Actions are parameterized over objects, drawers, and locations, allowing for generalization.
    - **CODE_FUNC**: The sequence is specific to the named objects and locations in the scenario.

12. **Goal Specification**:  
    - **TASK**: The goal is to have the die in the drawer.
    - **CODE_FUNC**: The goal is achieved by following the described sequence, but the goal state is not explicitly checked or asserted.

---

**Summary**:  
The main semantic differences are that TASK is a high-level, planner-oriented specification with a domain and initial state, while CODE_FUNC is a low-level, controller-oriented, step-by-step execution description with error handling. The former is abstract and general, the latter is concrete and specific.

Refined Code Generated:
-------------------
"""Module for executing the task: Insert one die into a drawer."""
from Object_list import Object
from skill_mapping import RobotController

def long_horizon_task2_oracle_seq():
    """Execute the sequence to insert one die into a drawer."""
    robot = RobotController()
    try:
        # Move to floor (simulate pose update if needed)
        robot.execute_movement(Object["drawer_top_handle"], mode=6)
        robot.execute_movement(pose0=None, pose1=None, mode=7)
        robot.execute_movement(Object["drawer_top_handle"], mode=7)
        # Pick handle_top from floor (axis=0 for handle)
        robot.execute_movement(Object["drawer_top_handle"], mode=1, axis=0)
        # Move to drawer-area
        robot.execute_movement(Object["drawer_top_handle"], mode=7)
        # Pull drawer open using handle_top at drawer-area
        robot.execute_movement(Object["drawer_top_handle"], mode=4, axis=0, distance=0.1)
        # Move to floor to pick dice1
        robot.execute_movement(Object["dice1"], mode=7)
        # Pick dice1 from floor (axis=2 for general object)
        robot.execute_movement(Object["dice1"], mode=1, axis=2)
        # Move to drawer-area to place dice1
        robot.execute_movement(Object["drawer_top_place_left"], mode=7)
        # Place dice1 into drawer_top at drawer-area (axis=2 for general object)
        robot.execute_movement(Object["drawer_top_place_left"], mode=2, axis=2)
    except Exception as error:
        print(f"Error during task execution: {error}")

def main():
    """Main function to execute the long horizon task."""
    long_horizon_task2_oracle_seq()

if __name__ == "__main__":
    main()
-------------------

=== Instruction 4 ===
Is Correct: False
Syntax Pass: False
Code Function: This code defines a sequence of actions for a robot to perform a long-horizon manipulation task. The robot starts from a ready position, moves to the floor, and picks up a dice. It then picks up a drawer handle, moves to the drawer area, and pulls the drawer open. Next, the robot places the dice inside the drawer, pushes the drawer closed, and finally returns to the ready position. Each step is executed through specific movement commands, and any errors during execution are caught and printed.
Similarity: {'ok': True, 'reason': "The described code sequence correctly performs all necessary actions to move the dice from the floor into the drawer, matching the domain's available actions and initial state."}
Differences: 1. **Explicit Handling of Handle**:  
   - *CODE_FUNC* specifies that the robot must pick up the drawer handle and use it to open the drawer.  
   - *TASK* ("Store a dice inside the drawer") does not mention the need to interact with a handle or the drawer's locked/unlocked state.

2. **Drawer State Management**:  
   - *CODE_FUNC* includes explicit actions to open and close the drawer (pull and push actions).  
   - *TASK* only specifies the end goal (dice inside drawer), not the intermediate requirement that the drawer must be open to place the dice, or closed afterward.

3. **Return to Ready Position**:  
   - *CODE_FUNC* ends with the robot returning to the ready position.  
   - *TASK* does not specify any post-condition about the robot's final pose.

4. **Error Handling**:  
   - *CODE_FUNC* mentions catching and printing errors during execution.  
   - *TASK* does not mention error handling.

5. **Action Granularity**:  
   - *CODE_FUNC* breaks down the task into a detailed sequence of primitive actions (move, pick, pull, place, push, etc.).  
   - *TASK* is a high-level instruction without specifying the sequence or granularity of actions.

6. **Assumption of Initial State**:  
   - *CODE_FUNC* assumes the dice and handle are on the floor, the drawer is closed, and the robot is at the ready position, matching the provided observation.  
   - *TASK* does not specify or assume any initial state.

7. **Object Specificity**:  
   - *CODE_FUNC* refers to a specific dice, handle, and drawer.  
   - *TASK* generically refers to "a dice" and "the drawer".

8. **No Mention of Other Objects**:  
   - *CODE_FUNC* does not mention or interact with the trash object already in the drawer.  
   - *TASK* does not specify whether the presence of other objects in the drawer is relevant.

9. **No Mention of Bin**:  
   - *CODE_FUNC* does not use the bin at all.  
   - *TASK* does not mention the bin.

10. **Implicit Preconditions**:  
    - *CODE_FUNC* encodes preconditions such as the robot needing to be at certain locations, hand empty, etc.  
    - *TASK* does not mention any preconditions.

11. **No Mention of Robot State**:  
    - *TASK* does not specify the robot's state (hand, location, etc.) before or after the task.  
    - *CODE_FUNC* manages these states explicitly.

12. **No Mention of Handle Placement After Use**:  
    - *CODE_FUNC* does not specify what happens to the handle after opening the drawer (it is released).  
    - *TASK* does not mention the handle at all.

13. **No Mention of Partial/Full Drawer States**:  
    - *CODE_FUNC* does not explicitly manage the drawer's "partially-filled" or "full" predicates, but these are updated by the PDDL actions.  
    - *TASK* does not mention the drawer's capacity.

14. **No Mention of Location Names**:  
    - *CODE_FUNC* uses specific location names (floor, drawer-area, ready-pose).  
    - *TASK* does not mention locations.

15. **No Mention of Robot Movement**:  
    - *CODE_FUNC* includes explicit movement actions between locations.  
    - *TASK* does not mention movement.

---

**Summary**:  
The semantic differences are that *CODE_FUNC* is a fully grounded, step-by-step, low-level plan that includes all necessary manipulation, movement, and state management actions (including error handling and returning to ready pose), while *TASK* is a high-level, underspecified instruction that omits all such details.

Refined Code Generated:
-------------------
"""Module to store a dice inside the drawer using primitive robot actions."""
from Object_list import Object
from skill_mapping import RobotController

def long_horizon_task2_oracle_seq():
    """Sequence of actions to store dice1 inside drawer_top."""
    robot = RobotController()

    # Move from ready-pose to floor
    robot.execute_movement(Object["dice1"], mode=7)

    # Pick dice1 from floor (axis=2 for general object)
    robot.execute_movement(Object["dice1"], mode=1, axis=2)

    # Pick handle_top from floor (axis=0 for handle)
    robot.execute_movement(Object["handle_top"], mode=1, axis=0)

    # Move from floor to drawer-area
    robot.execute_movement(Object["handle_top"], mode=7)

    # Pull drawer open using handle_top (axis=0 for handle)
    robot.execute_movement(Object["handle_top"], mode=4, axis=0, distance=0.1)

    # Place dice1 into drawer_top (axis=2 for general object)
    robot.execute_movement(Object["drawer_top_place_left"], mode=2, axis=2)

    # Push drawer closed (axis=2 for push, but axis param not used in push in this API)
    robot.execute_movement(Object["handle_top"], mode=3, axis=2, distance=0.1)

def main():
    """Main function to execute the dice storing task."""
    long_horizon_task2_oracle_seq()

if __name__ == "__main__":
    main()
-------------------

=== Instruction 5 ===
Is Correct: False
Syntax Pass: False
Code Function: This code defines a sequence of actions for a robot to perform a specific task. The robot first picks up a drawer handle from the floor, then pulls the drawer open. Next, it picks up a dice from the floor and places it inside the open drawer. After completing these steps, the robot optionally returns to a ready position. If any error occurs during the process, it is caught and printed.
Similarity: {'ok': True, 'reason': 'The described code sequence matches the required steps to drop one dice into any open drawer using the available PDDL actions and initial state.'}
Differences: 1. **Explicit Error Handling**: CODE_FUNC mentions that errors during the process are caught and printed, while TASK does not specify any error handling or reporting.

2. **Optional Return to Ready Position**: CODE_FUNC states that the robot "optionally returns to a ready position" after placing the dice, whereas TASK does not mention returning to a ready position.

3. **Action Sequence Explicitness**: CODE_FUNC explicitly lists the sequence: pick up handle, open drawer, pick up dice, place dice in drawer, (optionally) return to ready. TASK only instructs to "drop one dice into any open drawer" without specifying the intermediate steps or the need to open the drawer if it is closed.

4. **Drawer State Assumption**: TASK assumes the existence of an "open drawer" (i.e., at least one drawer is already open), while CODE_FUNC includes the actions necessary to open a closed drawer (by picking up the handle and pulling).

5. **Error Condition Handling**: CODE_FUNC accounts for the possibility of errors (e.g., if the handle or dice cannot be picked up, or the drawer cannot be opened), while TASK does not address what to do if the action cannot be completed as described.

6. **Scope of Action**: TASK is a high-level instruction focused on the end goal (dice in open drawer), while CODE_FUNC is a low-level procedural description including all necessary sub-steps to achieve the goal given the initial state.

7. **Object Selection**: TASK refers generically to "one dice" and "any open drawer," while CODE_FUNC (in the context of the provided observation) operates on specific objects (dice1, handle_top, drawer_top).

8. **Implicit Preconditions**: TASK presumes the precondition that a dice and an open drawer are available, while CODE_FUNC works from an initial state where the drawer is closed and the handle is on the floor, and thus includes steps to satisfy these preconditions.

9. **No Mention of Other Objects**: TASK does not mention or account for other objects in the drawer (e.g., trash1), while CODE_FUNC, by following the domain and observation, implicitly handles the presence of other objects by not interacting with them.

10. **No Mention of Bin**: TASK does not mention the bin at all, while CODE_FUNC, by following the domain, ensures the dice is placed in the drawer and not in the bin.

11. **No Mention of Robot State**: TASK does not specify the robot's initial or final state (e.g., hand empty, robot-free, at ready-pose), while CODE_FUNC (by implication) manages these states as part of the action sequence.

12. **No Mention of Handle**: TASK does not mention the need to use a handle to open the drawer, while CODE_FUNC explicitly includes picking up and using the handle.

13. **No Mention of Location**: TASK does not specify the robot's location or movement, while CODE_FUNC (by implication) includes moving to the necessary locations to perform each action.

14. **No Mention of Drawer Capacity**: TASK does not mention drawer capacity (full, empty, partially filled), while CODE_FUNC (by following the domain) implicitly handles this via the action preconditions and effects.

15. **No Mention of "Drop" vs. "Place"**: TASK uses the word "drop," which could imply a less precise action, while CODE_FUNC (and the domain) uses "place," which is more controlled.

16. **No Mention of "Any" Drawer**: TASK allows "any open drawer," while CODE_FUNC (given the observation) operates on a specific drawer (drawer_top).

17. **No Mention of Multiple Dice**: TASK refers to "one dice," which could imply there are multiple dice to choose from, while CODE_FUNC operates on a specific dice (dice1).

18. **No Mention of Repetition**: TASK could be interpreted as a one-time action, while CODE_FUNC is a single sequence for one dice, but the structure could be repeated for more dice if present.

19. **No Mention of Conditionality**: TASK does not specify what to do if no open drawer is available, while CODE_FUNC includes the steps to open the drawer if needed.

20. **No Mention of Readiness for Next Task**: TASK does not specify if the robot should be ready for another task after completion, while CODE_FUNC optionally returns the robot to a ready position.

---

**Summary**:  
The main semantic differences are that TASK is a high-level, goal-oriented instruction assuming certain preconditions (open drawer, available dice), while CODE_FUNC is a low-level, step-by-step procedure that includes all necessary actions to achieve the goal from a specific initial state, including error handling, state management, and optional return to ready.

Refined Code Generated:
-------------------
from Object_list import Object
from skill_mapping import RobotController

def long_horizon_task2_oracle_seq():
    """
    Drops one dice into any open drawer.
    Assumes at least one dice is available and at least one drawer is open.
    """
    robot = RobotController()

    # Find an open drawer and a dice
    open_drawer = None
    dice_obj = None

    # Example: Assume Object contains keys for all drawers and dice
    for drawer_key in Object:
        if drawer_key.startswith("drawer") and "open" in drawer_key:
            open_drawer = drawer_key
            break
    if open_drawer is None:
        # Fallback: check for known open drawer
        if "drawer_top" in Object:
            open_drawer = "drawer_top"

    for obj_key in Object:
        if "dice" in obj_key:
            dice_obj = obj_key
            break

    if open_drawer is None or dice_obj is None:
        print("No open drawer or dice found.")
        return

    # Pick up the dice from the floor (assume z-axis)
    robot.execute_movement(Object[dice_obj], mode=1, axis=2)

    # Place the dice into the open drawer (assume z-axis)
    place_key = open_drawer + "_place_left"
    if place_key in Object:
        robot.execute_movement(Object[place_key], mode=2, axis=2)
    else:
        # Fallback: use the drawer object itself
        robot.execute_movement(Object[open_drawer], mode=2, axis=2)

def main():
    long_horizon_task2_oracle_seq()

if __name__ == "__main__":
    main()
-------------------

