datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241221_202038/task_to_prompt.jsonl
datasource row: 763
groupname: arcagi
dataset_id: ARC-AGI
task_id: c8f0f002
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":[[1,8,8,7,7,8],[1,1,7,7,1,8],[7,1,1,7,7,8]],"output":[[1,8,8,5,5,8],[1,1,5,5,1,8],[5,1,1,5,5,8]]},{"input":[[7,7,7,1],[1,8,1,7],[7,1,1,7]],"output":[[5,5,5,1],[1,8,1,5],[5,1,1,5]]},{"input":[[1,8,1,7,1],[7,8,8,1,1],[7,1,8,8,7]],"output":[[1,8,1,5,1],[5,8,8,1,1],[5,1,8,8,5]]}],"test":[{"input":[[1,7,7,1,7],[8,1,7,7,7],[8,7,1,7,8]]}]}
```

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**

After analyzing the input and output pairs:

* All inputs have a common pattern: each row is a sequence of numbers with a specific length (6).
* All outputs have a common pattern: each row is a sequence of numbers with a specific length (6), where each number is either 1, 5, or 8.
* The input and output pairs have a common structure: they are both sequences of rows, where each row is a sequence of numbers.

**Transformation**

The transformation from input to output appears to be a simple substitution:

* Replace all occurrences of 7 with 5.

**Verification**

Let's verify that this transformation rule works on all input/output pairs:

1. Input: [[1,8,8,7,7,8]], Output: [[1,8,8,5,5,8]]. Replacing 7 with 5 matches the output.
2. Input: [[7,7,7,1]], Output: [[5,5,5,1]]. Replacing 7 with 5 matches the output.
3. Input: [[1,8,1,7,1],[7,8,8,1,1],[7,1,8,8,7]], Output: [[1,8,1,5,1],[5,8,8,1,1],[5,1,8,8,5]]. Replacing 7 with 5 matches the output.

**Task B**

The transformation rule is to replace all occurrences of 7 with 5. Applying this rule to the test input:

Input: [[1,7,7,1,7],[8,1,7,7,7],[8,7,1,7,8]]

Output: [[1,5,5,1,5],[8,1,5,5,5],[8,5,1,5,8]]

**Task C**

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

```json
[[1,5,5,1,5],[8,1,5,5,5],[8,5,1,5,8]]
```

---


number of response items: 443
elapsed: 12.55 seconds

expected output:
[[1, 5, 5, 1, 5], [8, 1, 5, 5, 5], [8, 5, 1, 5, 8]]

predicted output:
[[1, 5, 5, 1, 5], [8, 1, 5, 5, 5], [8, 5, 1, 5, 8]]

status: correct
