datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241221_202038/task_to_prompt.jsonl
datasource row: 595
groupname: arcagi
dataset_id: ARC-AGI
task_id: 662c240a
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": "qwen2.5-coder: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":[[8,9,8],[9,8,8],[8,8,8],[2,2,1],[2,2,1],[1,1,2],[4,4,4],[4,4,3],[3,3,3]],"output":[[4,4,4],[4,4,3],[3,3,3]]},{"input":[[1,5,5],[5,1,1],[5,1,1],[3,3,3],[3,6,3],[3,6,6],[7,7,7],[7,2,2],[7,2,2]],"output":[[3,3,3],[3,6,3],[3,6,6]]},{"input":[[2,2,2],[2,2,3],[2,3,3],[5,7,7],[7,5,5],[7,5,5],[8,8,1],[1,8,1],[1,8,1]],"output":[[8,8,1],[1,8,1],[1,8,1]]},{"input":[[8,8,4],[4,4,4],[4,4,8],[1,1,3],[1,3,3],[3,3,1],[6,2,2],[2,2,2],[2,2,6]],"output":[[8,8,4],[4,4,4],[4,4,8]]}],"test":[{"input":[[5,4,4],[4,5,4],[4,5,4],[3,3,2],[3,3,2],[2,2,3],[1,1,1],[1,8,8],[1,8,8]]}]}
```

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: Identifying Patterns and Transformation Rules

#### Commonalities in Inputs:
- All inputs are 9x9 grids.
- Each grid contains a mix of numbers from 1 to 8.

#### Commonalities in Outputs:
- All outputs are also 9x9 grids.
- The output grids contain fewer elements compared to the input grids, typically removing rows or columns with uniform values.

#### Input/Output Relationship:
- Rows or columns with uniform values (e.g., [4, 4, 4]) are removed from the output.
- Non-uniform rows/columns are retained in the output.

### Task B: Solving the Puzzle

Given the transformation rules identified, we can solve the test case:

```json
{"input":[[5,4,4],[4,5,4],[4,5,4],[3,3,2],[3,3,2],[2,2,3],[1,1,1],[1,8,8],[1,8,8]],"output":[[5,4,4],[4,5,4],[4,5,4]]}
```

- The first three rows are uniform (all 4s), so they are removed.
- The next two rows ([3,3,2],[3,3,2]) are non-uniform, so they remain.
- The last three rows ([2,2,3],[1,1,1],[1,8,8],[1,8,8]) contain uniform and non-uniform elements. Uniform rows ([1,1,1]) are removed, and non-uniform rows ([2,2,3],[1,8,8],[1,8,8]) remain.

Thus, the output should be:

```json
[[5,4,4],[4,5,4],[4,5,4]]
```

### Task C: Converting `test.output` to JSON Format

The `test.output` data is already in JSON format. Here it is again for completeness:

```json
[[5,4,4],[4,5,4],[4,5,4]]
```

---


response text byte count: 1342
number of response items: 445
elapsed: 15.10 seconds

expected output:
[[5, 4, 4], [4, 5, 4], [4, 5, 4]]

predicted output:
[[5, 4, 4], [4, 5, 4], [4, 5, 4]]

status: correct
