datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241221_202038/task_to_prompt.jsonl
datasource row: 496
groupname: arcagi
dataset_id: ARC-AGI
task_id: 25ff71a9
test_index: 1
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":[[1,1,1],[0,0,0],[0,0,0]],"output":[[0,0,0],[1,1,1],[0,0,0]]},{"input":[[0,0,0],[1,1,1],[0,0,0]],"output":[[0,0,0],[0,0,0],[1,1,1]]},{"input":[[0,1,0],[1,1,0],[0,0,0]],"output":[[0,0,0],[0,1,0],[1,1,0]]},{"input":[[0,2,2],[0,0,2],[0,0,0]],"output":[[0,0,0],[0,2,2],[0,0,2]]}],"test":[{"input":[[0,0,0],[0,1,0],[0,0,0]]}]}
```

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/output pairs:

* All inputs have a common structure: 3x3 matrices with values ranging from 0 to 2.
* All outputs have a similar structure: 3x3 matrices with values ranging from 0 to 2, but with some elements flipped or mirrored.
* The input and output pairs seem to be related by a simple transformation: flipping the middle row of each matrix.

**Task B**

Based on the identified transformation rule, I'll apply it to the test.input data:

```json
{"input":[[0,0,0],[0,1,0],[0,0,0]]}
```

Flipping the middle row gives us:

```json
{"output":[[0,0,0],[0,0,0],[0,1,0]]}
```

**Task C**

Converting the output data to JSON format:

```json
[[0,0,0],[0,0,0],[0,1,0]]
```

---


number of response items: 210
elapsed: 5.78 seconds

expected output:
[[0, 0, 0], [0, 0, 0], [0, 1, 0]]

predicted output:
[[0, 0, 0], [0, 0, 0], [0, 1, 0]]

status: correct
