The filter body is arbitrary client JSON with no schema, so validation
was emergent: any shape the DSL didn't recognize surfaced as an
unhandled 500 from somewhere in SQLAlchemy or psycopg. Fixing individual
shapes doesn't converge — a fuzz over the DSL found five more families
beyond the three already fixed here:
{"AND": [None]} TypeError, non-dict in a logical list
{"AND": [[]]} AttributeError on .items()
{"session_id": {"gte": true}} SQLAlchemy ArgumentError
{"embedding": []} NotImplementedError, no python_type
{"session_id": {"ne": {...}}} execute-time "cannot adapt type 'dict'"
Two generic guards instead:
1. Any operand bound to a non-JSONB column must be a scalar, checked
element-wise for `in`. A dict or list bound to a scalar column
compiles cleanly and only fails in the driver at execute time, so it
has to be rejected during construction. JSONB columns are exempt —
a dict there is a containment match.
2. apply_filter fails closed: FilterError propagates, anything else is
logged with logger.exception (filter shape included) and re-raised as
FilterError. Unknown filter failures become 422s while staying fully
visible as errors rather than being swallowed.
Adds two invariant tests over a generated matrix of filter shapes: every
shape either compiles or raises FilterError, and no non-scalar is ever
bound to a scalar column. Both fail without the guards above. They cover
shapes nobody enumerated, so the next unimagined body fails in CI rather
than in production.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
d9de9b88f8