chroma-core/chroma · error · ValueError

Expected a 1-dimensional array, got a 0-dimensional array {e

Error message

Expected a 1-dimensional array, got a 0-dimensional array {embedding}

What it means

Each embedding must be a 1-dimensional array. validate_embeddings checks embedding.ndim and raises when it equals 0 — a numpy scalar such as np.array(0.5) or np.float32(0.5), which has no length axis and cannot be a vector.

Source

Thrown at chromadb/api/types.py:1389

def validate_embeddings(embeddings: Embeddings) -> Embeddings:
    """Validates embeddings to ensure it is a list of numpy arrays of ints, or floats"""
    if not isinstance(embeddings, (list, np.ndarray)):
        raise ValueError(
            f"Expected embeddings to be a list, got {type(embeddings).__name__}"
        )
    if len(embeddings) == 0:
        raise ValueError(
            f"Expected embeddings to be a list with at least one item, got {len(embeddings)} embeddings"
        )
    if not all([isinstance(e, np.ndarray) for e in embeddings]):
        raise ValueError(
            "Expected each embedding in the embeddings to be a numpy array, got "
            f"{list(set([type(e).__name__ for e in embeddings]))}"
        )
    for i, embedding in enumerate(embeddings):
        if embedding.ndim == 0:
            raise ValueError(
                f"Expected a 1-dimensional array, got a 0-dimensional array {embedding}"
            )
        if embedding.size == 0:
            raise ValueError(
                f"Expected each embedding in the embeddings to be a 1-dimensional numpy array with at least 1 int/float value. Got a 1-dimensional numpy array with no values at pos {i}"
            )

        if embedding.dtype not in [
            np.float16,
            np.float32,
            np.float64,
            np.int32,
            np.int64,
        ]:
            raise ValueError(
                "Expected each value in the embedding to be a int or float, got an embedding with "
                f"{embedding.dtype} - {embedding}"
            )

View on GitHub (pinned to aecdd12c8a)

Solutions

1. Build vectors as 1-D arrays: np.asarray(values, dtype=np.float32) where values is a flat sequence
2. Fix the reduction: use axis=0/axis=1 correctly, or arr.mean(axis=1) to keep one vector per row
3. Index rows, not cells: use matrix[i] not matrix[i][j]

Example fix

# before
emb = np.array(scores).mean()          # 0-dim scalar
embeddings = [emb]

# after
emb = np.asarray(scores, dtype=np.float32)  # 1-D vector
embeddings = [emb]

import numpy as np

def ensure_1d(embeddings):
    out = []
    for i, e in enumerate(embeddings):
        arr = np.asarray(e)
        if arr.ndim != 1:
            raise ValueError(f"embedding {i} has ndim={arr.ndim}, expected 1")
        out.append(arr)
    return out

import numpy as np

def is_1d_vector(e) -> bool:
    return isinstance(e, np.ndarray) and e.ndim == 1

try:
    validate_embeddings(embeddings)
except ValueError as e:
    if "0-dimensional array" in str(e):
        embeddings = [np.atleast_1d(np.asarray(e, dtype=np.float32)) for e in embeddings]
        validate_embeddings(embeddings)
    else:
        raise

When it happens

Trigger: embeddings=[np.array(0.5)] or [np.float32(x) for x in values] — typically the result of reducing/aggregating per-dimension (e.g. taking mean over the wrong axis) or unrolling a matrix with scalars instead of rows.

Common situations: Averaging embeddings with .mean() without axis=1; indexing arr[i, j] instead of arr[i]; converting a single vector with np.array(value) where value is already a scalar.

Related errors

• Expected each embedding in the embeddings to be a numpy arra
• Expected each embedding in the embeddings to be a 1-dimensio
• Expected each value in the embedding to be a int or float, g
• Expected '${fieldName}' to be an array, but got ${typeof emb
• Expected embeddings to be an array with at least one item

AI-assisted analysis of chroma-core/chroma@aecdd12c8a (2026-08-16). Data as JSON: /api/errors/31a91c2dd06e77f2. Report an issue: GitHub.