datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241222_033847_task_to_prompt_o3_format/task_to_prompt.jsonl
datasource row: 780
groupname: arcagi
dataset_id: ARC-AGI
task_id: d10ecb37
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:
Be brief and clear in your responses

---

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

Example 1:

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

Example 2:

Input:
2 4 2 2 5 2 4 5
2 5 5 4 4 2 2 2
4 5 5 2 2 2 2 4
2 2 4 2 5 4 2 5
2 4 2 2 5 2 4 5
2 5 5 4 4 2 2 2
4 5 5 2 2 2 2 4
2 2 4 2 5 4 2 5
Output:
2 4
2 5

Example 3:

Input:
3 2 1 3 4 1
1 4 4 2 2 3
1 3 3 2 2 4
4 2 1 4 3 1
4 1 2 4 3 2
2 3 3 1 1 4
2 4 4 1 1 3
3 1 2 3 4 2
3 2 1 3 4 1
1 4 4 2 2 3
1 3 3 2 2 4
4 2 1 4 3 1
Output:
3 2
1 4

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:
9 6 2 9 9 2 6 9
2 9 9 6 6 9 9 2
6 9 9 2 2 9 9 6
9 2 6 9 9 6 2 9


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RESPONSE:
Based on the examples, it appears that the common rule is to take the first and last elements of each row in the input grid as the corresponding elements in the output grid.

Applying this rule to the test input grid:

Input:
9 6 2 9 9 2 6 9
2 9 9 6 6 9 9 2
6 9 9 2 2 9 9 6
9 2 6 9 9 6 2 9
9 6 2 9 9 2 6 9

The output grid would be:

9 6
2 9

---


response byte count: 341
response item count: 141
elapsed: 3.77 seconds

expected output:
[[9, 6], [2, 9]]

predicted output:
[[9, 6], [2, 9]]

status: correct
