RyanCodrai/turbovec · error · NotImplementedError

filter condition {condition!r} not supported by TurboQuantVe

Error message

filter condition {condition!r} not supported by TurboQuantVectorStore

What it means

_filters_match only implements AND, OR, and NOT condition types from LlamaIndex's MetadataFilters. Any other FilterCondition (e.g. custom or newly added enum values) hits the fallthrough NotImplementedError.

Source

Thrown at turbovec-python/python/turbovec/llama_index.py:712

            if isinstance(f, MetadataFilters):
                # Deliberate superset of the reference: SimpleVectorStore's
                # build_metadata_filter_fn raises ValueError on nested
                # MetadataFilters groups; turbovec recurses and evaluates
                # them. Per-operator semantics still match the reference
                # (see _single_filter_match).
                results.append(cls._filters_match(metadata, f))
            else:
                results.append(cls._single_filter_match(metadata, f))
        if condition == FilterCondition.AND:
            return all(results) if results else True
        if condition == FilterCondition.OR:
            return any(results) if results else True
        if _CONDITION_NOT is not None and condition == _CONDITION_NOT:
            # Reference semantics (`build_metadata_filter_fn`,
            # `utils.py:187-189`): NOT matches when none of the inner
            # filters match. Empty inner list trivially satisfies NOT.
            return not any(results)
        raise NotImplementedError(
            f"filter condition {condition!r} not supported by TurboQuantVectorStore"
        )

    @staticmethod
    def _single_filter_match(metadata: dict[str, Any], f: MetadataFilter) -> bool:
        # Semantics mirror SimpleVectorStore's _build_metadata_filter_fn
        # (llama_index/core/vector_stores/simple.py) so that filtered
        # results agree with the in-tree reference store.
        op = f.operator
        target = f.value
        value = metadata.get(f.key)

        # IS_EMPTY is the only operator that treats a missing key as a hit.
        if op == FilterOperator.IS_EMPTY:
            return value is None or value == "" or value == []

        # Missing key: no value to compare, so every operator declines —
        # EXCEPT the negative ones. "this node's colour is not red" is

View on GitHub (pinned to ccab9f325e)

Solutions

1. Rewrite the filter using MetadataFilters(condition=FilterCondition.AND/OR/NOT)
2. Simplify to a single flat filter list (implicit AND)
3. Check supported conditions before building filters

Example fix

// before
filters = MetadataFilters(filters=[...], condition=FilterCondition.PIPE)
// after
filters = MetadataFilters(filters=[...], condition=FilterCondition.AND)

from llama_index.core.vector_stores.types import FilterCondition
assert filters.condition in (FilterCondition.AND, FilterCondition.OR, FilterCondition.NOT)

try:
    results = store.query(q)
except NotImplementedError as e:
    if "filter condition" in str(e):
        q.filters = MetadataFilters(filters=q.filters.filters, condition=FilterCondition.AND)
        results = store.query(q)
    else:
        raise

When it happens

Trigger: Passing VectorStoreQuery(filters=MetadataFilters(condition=<unsupported>)) to delete_nodes, get_nodes, or query where condition is not AND/OR/NOT.

Common situations: Upgrading llama_index-core introduces a new FilterCondition and code passes it through; copy-pasted filter code using an exotic condition.

Related errors

• filter operator {op!r} not supported by TurboQuantVectorStor
• TurboQuantVectorStore.get(text_id) cannot return the origina
• TurboQuantVectorStore does not support query mode {query.mod
• duplicate node_id {dup!r} appears multiple times in the inpu
• Both metadata value and filter value must be strings for the

AI-assisted analysis of RyanCodrai/turbovec@ccab9f325e (2026-09-06). Data as JSON: /api/errors/1af7a9a610a02a8c. Report an issue: GitHub.