datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241222_033847_task_to_prompt_o3_format/task_to_prompt.jsonl
datasource row: 173
groupname: arcagi
dataset_id: ARC-AGI
task_id: 66e6c45b
test_index: 0
max_prompt_length: 2000
max_response_length: 1000

LLM:
{"system_prompt": null, "pydantic_program_mode": "default", "base_url": "http://localhost:11434", "model": "llama3.1:latest", "temperature": 0.0, "context_window": 3900, "request_timeout": 120.0, "prompt_key": "prompt", "json_mode": false, "additional_kwargs": {}, "is_function_calling_model": true, "keep_alive": null, "class_name": "Ollama_llm"}

SYSTEM PROMPT:
You solve ARC puzzles by carefully examining patterns in each example. Identify the rules, verify them on all examples, then solve the test input

---

PROMPT:
Find the common rule that maps an input grid to an output grid, given the examples below.

Example 1:

Input:
0 0 0 0
0 3 4 0
0 7 6 0
0 0 0 0
Output:
3 0 0 4
0 0 0 0
0 0 0 0
7 0 0 6

Example 2:

Input:
0 0 0 0
0 5 6 0
0 8 3 0
0 0 0 0
Output:
5 0 0 6
0 0 0 0
0 0 0 0
8 0 0 3

Below is a test input grid. Predict the corresponding output grid by applying the rule you found. Your final answer should just be the text output grid itself.

Input:
0 0 0 0
0 2 3 0
0 4 9 0
0 0 0 0


---

RESPONSE:
Let's analyze the examples to find a common rule that maps an input grid to an output grid.

In both Example 1 and Example 2, we can see that:

* The numbers in the top-left and bottom-right corners of the input grid are always 0.
* The non-zero numbers in the input grid are mirrored across the middle row (second row) of the output grid.
* The positions of the non-zero numbers in the output grid are swapped with respect to their original positions in the input grid.

Based on this observation, we can formulate a rule that maps an input grid to an output grid:

1. Identify the non-zero numbers in the input grid.
2. Mirror these numbers across the middle row (second row) of the output grid.
3. Swap the positions of the mirrored numbers with respect to their original positions in the input grid.

Applying this rule to the test input grid, we get:

Input:
0 0 0 0
0 2 3 0
0 4 9 0
0 0 0 0

Output:
2 0 0 3
0 0 0 0
0 0 0 0
4 0 0 9

---


response byte count: 936
response item count: 255
elapsed: 7.40 seconds

expected output:
[[2, 0, 0, 3], [0, 0, 0, 0], [0, 0, 0, 0], [4, 0, 0, 9]]

predicted output:
[[2, 0, 0, 3], [0, 0, 0, 0], [0, 0, 0, 0], [4, 0, 0, 9]]

status: correct
