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| license: apache-2.0
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| ---
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| # AssertAI
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| A fine-tuned SLM to generate deterministic Python unit test plans in strict JSON. It's designed to act as a test-case planner, rather than a full code generator.
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| Base model: **Llama3.2**.
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| ### What it does
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| Given a function signature + docstring/spec, Assert-AI outputs:
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| - a compact list of 2–5 high-signal unit tests
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| - each test includes args, kwargs, and either an expected value (expect) or expected exception (error)
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| ### Output format
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| Assert-AI outputs only this JSON object (no extra keys, no markdown):
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| ```json
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| {
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| "fn": "safe_divide",
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| "tests": [
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| { "name": "divides_when_nonzero", "args": [19, -3], "kwargs": {"default": 0.0}, "expect": -6.333333333333333 },
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| { "name": "returns_default_on_zero", "args": [19, 0.0], "kwargs": {"default": 1.5}, "expect": 1.5 }
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| ]
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| }
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| ```
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| ### Example User Input
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| ```text
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| Function spec:
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| def clamp(n: int, lo: int, hi: int) -> int:
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| \"\"\"Return n bounded between lo and hi inclusive. Precondition: lo <= hi.\"\"\"
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| ```
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| ### Author
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| **Author:** Sai Teja Erukude
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| **Role:** Developer & Maintainer |
