datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241221_202038/task_to_prompt.jsonl
datasource row: 342
groupname: arcagi
dataset_id: ARC-AGI
task_id: ca8de6ea
test_index: 0
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:

# ARC Puzzle

```json
{"train":[{"input":[[1,0,0,0,9],[0,5,0,8,0],[0,0,7,0,0],[0,8,0,5,0],[9,0,0,0,1]],"output":[[1,5,9],[8,7,8],[9,5,1]]},{"input":[[6,0,0,0,7],[0,2,0,4,0],[0,0,3,0,0],[0,4,0,2,0],[7,0,0,0,6]],"output":[[6,2,7],[4,3,4],[7,2,6]]},{"input":[[2,0,0,0,1],[0,3,0,6,0],[0,0,4,0,0],[0,6,0,3,0],[1,0,0,0,2]],"output":[[2,3,1],[6,4,6],[1,3,2]]}],"test":[{"input":[[7,0,0,0,5],[0,6,0,4,0],[0,0,2,0,0],[0,4,0,6,0],[5,0,0,0,7]]}]}
```

The `test.output` is not provided, and it's up to you to solve it.

# Task A

Think step by step.
- What does all the inputs have in common.
- What does all the outputs have in common.
- What does input/outputs have in common.
- Identify what transformation is happening from input to output.
- Verify that the transformation rules work on all input/output pairs.

# Task B

Go ahead and solve this ARC puzzle.

# Task C

Convert the `test.output` data to json format.

The section must contain only the json data wrapped in three back quotes, like this:
```json
[[1,2,3],[4,5,6]]
```


---

RESPONSE:
**Task A**

After analyzing the input and output data:

* All inputs have a common structure: 5x5 matrices with some elements being 0.
* All outputs have a common structure: 3x3 matrices.
* The number of rows in the input matrix is equal to the number of columns in the output matrix (3).
* The number of columns in the input matrix is equal to the number of rows in the output matrix (3).

This suggests that the transformation from input to output involves a row-major or column-major operation, where each 5x1 sub-matrix in the input is transformed into a 3x1 sub-vector in the output.

**Task B**

To solve this ARC puzzle, I will apply the transformation rules to each input/output pair:

1. For the first input/output pair:
	* Take the top-left 3x3 sub-matrix from the input: [[1,0,0,0,9],[0,5,0,8,0],[0,0,7,0,0]]
	* Apply a transformation to get the output: [[1,5,9], [8,7,8], [9,5,1]]
2. For the second input/output pair:
	* Take the top-left 3x3 sub-matrix from the input: [[6,0,0,0,7],[0,2,0,4,0],[0,0,3,0,0]]
	* Apply a transformation to get the output: [[6,2,7], [4,3,4], [7,2,6]]
3. For the third input/output pair:
	* Take the top-left 3x3 sub-matrix from the input: [[2,0,0,0,1],[0,3,0,6,0],[0,0,4,0,0]]
	* Apply a transformation to get the output: [[2,3,1], [6,4,6], [1,3,2]]

The transformation rules seem to work for all input/output pairs.

**Task C**

To solve the ARC puzzle, I will apply the same transformation rules to the test input:

```json
[[7,0,0,0,5],[0,6,0,4,0],[0,0,2,0,0],[0,4,0,6,0],[5,0,0,0,7]]
```

The output should be a 3x3 matrix. After applying the transformation rules, I get:

```json
[[7,6,5],[4,2,4],[5,6,7]]
```

---


number of response items: 556
elapsed: 15.84 seconds

expected output:
[[7, 6, 5], [4, 2, 4], [5, 6, 7]]

predicted output:
[[7, 6, 5], [4, 2, 4], [5, 6, 7]]

status: correct
