E9afcf9a 4
datasource file: /Users/neoneye/git/simon_arc_lab/run_tasks_result/20241222_033847_task_to_prompt_o3_format/task_to_prompt.jsonl datasource row: 834 groupname: arcagi dataset_id: ARC-AGI task_id: e9afcf9a 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": "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: You are an expert at solving ARC (Abstraction & reasoning corpus) puzzles --- PROMPT: Find the common rule that maps an input grid to an output grid, given the examples below. Example 1: Input: 3 3 3 3 3 3 9 9 9 9 9 9 Output: 3 9 3 9 3 9 9 3 9 3 9 3 Example 2: Input: 4 4 4 4 4 4 8 8 8 8 8 8 Output: 4 8 4 8 4 8 8 4 8 4 8 4 Below is a test input grid. Predict the corresponding output grid by applying the rule you found. Your final answer should just be the text output grid itself. Input: 6 6 6 6 6 6 2 2 2 2 2 2 --- RESPONSE: Based on the examples provided, I notice that in each case, the input grid consists of two rows with identical elements. The output grid also has two rows, but with a specific pattern: the first row is identical to the first row of the input grid, and the second row is identical to the second row of the input grid, but with the positions of the elements swapped. Applying this rule to the test input grid: Input: 6 6 6 6 6 6 2 2 2 2 2 2 The output grid would be: Output: 6 2 6 2 6 2 2 6 2 6 2 6 --- response byte count: 500 response item count: 144 elapsed: 4.45 seconds expected output: [[6, 2, 6, 2, 6, 2], [2, 6, 2, 6, 2, 6]] predicted output: [[6, 2, 6, 2, 6, 2], [2, 6, 2, 6, 2, 6]] status: correct
when to use it
Community prompt sourced from the open-source GitHub repo neoneye/arc-prompt (Apache-2.0). A "E9afcf9a 4" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
productivitycommunitydeveloper
source
neoneye/arc-prompt · Apache-2.0
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