datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241222_033847_task_to_prompt_o3_format/task_to_prompt.jsonl
datasource row: 589
groupname: arcagi
dataset_id: ARC-AGI
task_id: 6150a2bd
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

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

Example 1:

Input:
3 3 8
3 7 0
5 0 0
Output:
0 0 5
0 7 3
8 3 3

Example 2:

Input:
5 5 2
1 0 0
0 0 0
Output:
0 0 0
0 0 1
2 5 5

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:
6 3 5
6 8 0
4 0 0


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RESPONSE:
After examining the examples, I noticed that the output grid is obtained by rotating the input grid clockwise and then reversing each row.

Here's how it works:

Example 1:

Input: 
3 3 8
3 7 0
5 0 0

Output:
0 0 5 (reversed row)
0 7 3 (reversed row)
8 3 3 (rotated clockwise)

Example 2:

Input: 
5 5 2
1 0 0
0 0 0

Output:
0 0 0 (reversed row)
0 0 1 (reversed row)
2 5 5 (rotated clockwise)

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

Input: 
6 3 5
6 8 0
4 0 0

Output:
0 0 4 (reversed row)
0 8 6 (reversed row)
5 3 6 (rotated clockwise)

So, the predicted output grid is:

0 0 4
0 8 6
5 3 6

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response byte count: 601
response item count: 237
elapsed: 6.41 seconds

expected output:
[[0, 0, 4], [0, 8, 6], [5, 3, 6]]

predicted output:
[[0, 0, 4], [0, 8, 6], [5, 3, 6]]

status: correct
