Skip to main content
The Schema Verifier goes beyond standard JSON validation. It combines Pydantic structure enforcement with Symbolic Math checks deeply embedded within the schema.

​
How It Works

It validates that:
  1. Structure: The output matches the required JSON keys and types.
  2. Logic: The numeric values inside the JSON are mathematically consistent (e.g., total == sum(items)).

​
Usage

schema = {
    "type": "object",
    "properties": {
        "items": {"type": "array", "items": {"type": "number"}},
        "total": {"type": "number"}
    },
    # QWED Extension: Math Logic
    "qwed:constraints": [
        "total == sum(items)"
    ]
}

response = client.verify_schema(
    obj={"items": [10, 20], "total": 30},
    schema=schema
)
# -> ✅ Verified

response = client.verify_schema(
    obj={"items": [10, 20], "total": 300}, # LLM hallucinations
    schema=schema
)
# -> ❌ MATH ERROR: total (300) != sum(items) (30)

​
Array validation

The Schema Verifier supports standard JSON Schema array keywords including uniqueItems.

​
uniqueItems — fail-closed validation

When a schema sets uniqueItems: true, the verifier checks that every element in the array is distinct. If an element is unhashable or otherwise cannot be compared deterministically (for example, an object containing a Python set), the verifier fails closed — it reports a uniqueness_validation_error issue instead of silently passing. This ensures that unverifiable arrays are never treated as valid. Issue types returned for uniqueItems:
Issue typeMeaning
uniqueness_violationDuplicate items were found in the array
uniqueness_validation_errorUniqueness could not be verified deterministically (fail-closed)
Example — duplicate items: 
schema = {"type": "array", "uniqueItems": True}

result = client.verify_schema(obj=[1, 2, 2, 3], schema=schema)
# -> is_valid: false, issue_type: "uniqueness_violation"
Example — uncheckable items fail closed: 
schema = {"type": "array", "uniqueItems": True}

# Items containing unhashable types cannot be compared deterministically
result = client.verify_schema(obj=[{"bad": {1, 2}}, {"bad": {3, 4}}], schema=schema)
# -> is_valid: false, status: "INVALID"
# -> issue_type: "uniqueness_validation_error"
# -> message: "uniqueItems could not be verified deterministically: ..."
This fail-closed behavior shipped in v5.1.0. See the changelog for the full release notes.

​
When to use

  • Invoice Processing: Ensure line items sum to the total.
  • Financial Reports: Ensure balance sheets balance.
  • Tax Forms: Ensure calculated fields match underlying data.