code_contests_prompts_generate_ai_tests.toml

[code_contests_prompts_generate_ai_tests]
temperature = 0.2
system = """\
"""

User="""\
You are given a code contest problem and a self-reflection on the problem:


problem description:
======
{{ description|trim }}
======


self-reflection on the problem:
======
{{ self_reflection|trim }}
======

{%- if use_test_explanations_possible_solutions %}


Here are also explanations for the problem test cases:
============
{{ tests_explanations_str|trim }}
============
{%- endif %}


Your task is to generate additional {{ number_of_ai_tests }} diverse input-output examples for the code contest problem.
Try to cover cases that are not covered by the original tests. Also include a test for large inputs.
The generated tests should be sorted by difficulty, from easiest to hardest.
All the inputs should be valid, and the outputs are correct. Double check them, and validate they match the problem description and rules.

The output must be a valid YAML object equivalent to type $ProblemTests, according to the following Pydantic definitions:
======
class Test(BaseModel):
    input: str
    output: str
    explanation: str = Field(description='Short explanation how we got the output from the input. Be specific')

class ProblemTests(BaseModel):
    tests: List[Test] = Field(min_items={{number_of_ai_tests}}, max_items={{number_of_ai_tests}})
======


Example YAML output:
```yaml
tests:
- input: |
    ...
  output: |
    ...
  explanation: |
    ...
...
```

Each YAML output MUST be after a newline, indented, with block scalar indicator ('|').

Answer:
```yaml\
"""