datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241222_033847_task_to_prompt_o3_format/task_to_prompt.jsonl
datasource row: 701
groupname: arcagi
dataset_id: ARC-AGI
task_id: a416b8f3
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 concise

---

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

Example 1:

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

Example 2:

Input:
3 0 0
2 3 0
2 1 8
0 1 0
Output:
3 0 0 3 0 0
2 3 0 2 3 0
2 1 8 2 1 8
0 1 0 0 1 0

Example 3:

Input:
5 2 3 0
2 5 3 0
5 2 8 8
0 0 6 0
Output:
5 2 3 0 5 2 3 0
2 5 3 0 2 5 3 0
5 2 8 8 5 2 8 8
0 0 6 0 0 0 6 0

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:
4 0 0 0
4 5 0 0
0 5 6 0
6 6 1 0
0 0 0 1


---

RESPONSE:
Based on the examples provided, it appears that the common rule is to duplicate each row of the input grid.

Applying this rule to the test input grid:

Input:
4 0 0 0
4 5 0 0
0 5 6 0
6 6 1 0
0 0 0 1

Output:
4 0 0 0 4 0 0 0
4 5 0 0 4 5 0 0
0 5 6 0 0 5 6 0
6 6 1 0 6 6 1 0
0 0 0 1 0 0 0 1

---


response byte count: 288
response item count: 156
elapsed: 5.00 seconds

expected output:
[[4, 0, 0, 0, 4, 0, 0, 0], [4, 5, 0, 0, 4, 5, 0, 0], [0, 5, 6, 0, 0, 5, 6, 0], [6, 6, 1, 0, 6, 6, 1, 0], [0, 0, 0, 1, 0, 0, 0, 1]]

predicted output:
[[4, 0, 0, 0, 4, 0, 0, 0], [4, 5, 0, 0, 4, 5, 0, 0], [0, 5, 6, 0, 0, 5, 6, 0], [6, 6, 1, 0, 6, 6, 1, 0], [0, 0, 0, 1, 0, 0, 0, 1]]

status: correct
