datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241221_202038/task_to_prompt.jsonl
datasource row: 701
groupname: arcagi
dataset_id: ARC-AGI
task_id: a416b8f3
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":[[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]]},{"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]]},{"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]]}],"test":[{"input":[[4,0,0,0],[4,5,0,0],[0,5,6,0],[6,6,1,0],[0,0,0,1]]}]}
```

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: 2D arrays with 3 columns.
* All outputs have a common structure: 2D arrays with 4-6 columns (depending on the input).
* The number of rows in both input and output is always equal.

**Transformation Identification**

The transformation from input to output appears to be adding a new column to the right, which contains a copy of the first column of the input. This can be verified by comparing each input/output pair:

* In the first example, the first column `[0,5,0]` is copied to the fourth position in the output.
* In the second example, the first column `[3,0,0]` is copied to the fourth position in the output.
* In the third example, the first column `[5,2,3,0]` is copied to the fifth position in the output.

**Task B**

To solve this ARC puzzle, we can apply the identified transformation rule to each input:

```json
{"train":[{"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]]},{"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]]},{"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]]}],"test":[{"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]]}]}
```

**Task C**

The `test.output` data in JSON format is:

```json
[[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]]
```

---


number of response items: 702
elapsed: 19.56 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
