pathwaycom/pathway · error · ValueError

vector column does not belong to the provided table. Pass a…

Error message

vector column {vector._name!r} does not belong to the provided table. Pass a column reference from the same table, e.g. vector=table.{vector._name}.

What it means

The Weaviate output connector requires the `vector` column reference to belong to the same pw.Table instance passed as `table`, since the vectors written must line up row-for-row with the table being indexed. write() compares vector._table to table and raises this ValueError pointing at the correct expression when the reference comes from another table object.

Solutions

Write from the table that actually holds the embedding column and reference it directly: pw.io.weaviate.write(t_embedded, vector=t_embedded.embedding).
Add the embedding column to the table you intend to pass: t = t + embedded.select(embedding=pw.this.embedding) before write().

Example fix

# before
t_emb = t + t.select(embedding=pw.apply(embed_fn, pw.this.text))
pw.io.weaviate.write(t, collection_name="Docs", vector=t_emb.embedding)

# after
pw.io.weaviate.write(t_emb, collection_name="Docs", vector=t_emb.embedding)

Defensive patterns

Strategy: validation

Validate before calling

def check_column_belongs(table, col, arg="vector"):
    if col is not None and col._table is not table:
        raise ValueError(f"{arg} column {col.name!r} is not from the given table")
    return True

Prevention

Compute embeddings with table + table.select(...) style expressions so the resulting object owns the embedding column, then write that object.
Lint for the anti-pattern of passing table_a/table_b.mix mixes: both table and column arguments should come from one variable.

When it happens

Trigger: Calling pw.io.weaviate.write(table_a, ..., vector=table_b.embedding) where table_b is a different table instance — typically the pre-transform table or a side table produced by an embedding step.

Common situations: Computing embeddings on one table (t_embedded = t + t.select(embedding=pw.apply(embed))) and then passing the original t as `table` with vector=t_embedded.embedding; keeping stale references after refactor; joining metadata onto an embedded table and mixing up which object to pass.

Related errors

AI-assisted analysis of pathwaycom/pathway@fa2f74a464 (2026-08-15). Data as JSON: /api/errors/6bdff8ec57cb0c2c. Report an issue: GitHub.

Appendix: source

Thrown at python/pathway/io/weaviate/__init__.py:122

    >>> pw.io.weaviate.write(  # doctest: +SKIP
    ...     table,
    ...     collection_name="Docs",
    ...     primary_key=table.doc_id,
    ...     vector=table.embedding,
    ... )
    >>> pw.run(monitoring_level=pw.MonitoringLevel.NONE)  # doctest: +SKIP
    """
    _check_entitlements("weaviate")

    if primary_key is not None and primary_key._table is not table:
        raise ValueError(
            f"primary_key column {primary_key._name!r} does not belong to the "
            f"provided table. Pass a column reference from the same table, "
            f"e.g. primary_key=table.{primary_key._name}."
        )
    if vector is not None and vector._table is not table:
        raise ValueError(
            f"vector column {vector._name!r} does not belong to the provided "
            f"table. Pass a column reference from the same table, "
            f"e.g. vector=table.{vector._name}."
        )

    pk = primary_key._name if primary_key is not None else None
    vector_field = vector._name if vector is not None else None

    # Weaviate reserves "id" and "vector" as object-level keys and rejects them as
    # property names. The primary key (encoded in the UUID) and the vector column
    # are never sent as properties, so they may freely use these names; any other
    # column that does collides and is reported up front.
    reserved_property_columns = [
        column_name
        for column_name in table.schema.column_names()
        if column_name in ("id", "vector")
        and column_name != pk
        and column_name != vector_field

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