---
license: apache-2.0
---

# AssertAI

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.

Base model: **Llama3.2**.

### What it does
Given a function signature + docstring/spec, Assert-AI outputs:

- a compact list of 2–5 high-signal unit tests
- each test includes args, kwargs, and either an expected value (expect) or expected exception (error)


### Output format
Assert-AI outputs only this JSON object (no extra keys, no markdown):

```json
{
  "fn": "safe_divide",
  "tests": [
    { "name": "divides_when_nonzero", "args": [19, -3], "kwargs": {"default": 0.0}, "expect": -6.333333333333333 },
    { "name": "returns_default_on_zero", "args": [19, 0.0], "kwargs": {"default": 1.5}, "expect": 1.5 }
  ]
}

```

### Example User Input
```text
Function spec:
def clamp(n: int, lo: int, hi: int) -> int:
  \"\"\"Return n bounded between lo and hi inclusive. Precondition: lo <= hi.\"\"\"
```

### Author

**Author:** Sai Teja Erukude  
**Role:** Developer & Maintainer