HKUDS/Vibe-Trading · error · ValueError

valuations[{index}] must be an object with date and value

Error message

valuations[{index}] must be an object with date and value

What it means

Each element of the valuations array must be a dict (JSON object) containing date and value. Non-dict entries (strings, numbers, nested lists) fail this per-index check before field validation begins.

Source

Thrown at agent/src/tools/cashflow_analytics_tool.py:324

    Args:
        raw: Value supplied for the ``valuations`` parameter.

    Returns:
        Pairs in the order supplied; the library sorts and validates them.

    Raises:
        ValueError: If the array is missing, wrongly shaped, over the size cap,
            or an entry lacks a usable date or value.
    """
    if not isinstance(raw, list) or len(raw) < 2:
        raise ValueError("valuations must be an array of at least two {date, value} objects")
    if len(raw) > _MAX_VALUATIONS:
        raise ValueError(f"valuations may contain at most {_MAX_VALUATIONS} entries")

    pairs: list[tuple[date, float]] = []
    for index, item in enumerate(raw):
        if not isinstance(item, dict):
            raise ValueError(f"valuations[{index}] must be an object with date and value")
        if "date" not in item or "value" not in item:
            raise ValueError(f"valuations[{index}] needs both 'date' and 'value'")
        try:
            value = float(item["value"])
        except (TypeError, ValueError) as exc:
            raise ValueError(f"valuations[{index}].value must be numeric") from exc
        if not math.isfinite(value):
            raise ValueError(f"valuations[{index}].value must be finite")
        pairs.append((item["date"], value))
    return pairs


def _resolve_flows(kwargs: dict[str, Any]) -> CashFlowSeries | None:
    """Build the cash-flow series from inline records or from a file.

    Args:
        kwargs: The tool's raw inputs.

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Map rows to dicts: [{'date': d, 'value': v} for d, v in rows]
2. When iterating a DataFrame, use .to_dict('records')
3. Validate element shape with isinstance(item, dict) before submitting

Example fix

# before
valuations=list(zip(dates, values))  # [(d, v), ...]
# after
valuations=[{'date': d, 'value': v} for d, v in zip(dates, values)]

assert all(isinstance(i, dict) and {'date','value'} <= i.keys() for i in valuations)

def entries_are_objects(v: list) -> bool:
    return all(isinstance(i, dict) for i in v)

try:
    tool.execute(valuations=valuations)
except ValueError as e:
    if 'must be an object' in str(e):
        valuations = [{'date': d, 'value': val} for d, val in v]  # reshape rows

When it happens

Trigger: Calling execute with valuations=['2024-01-01', ...], [[date, value], ...], or mixed arrays where some entries are scalars.

Common situations: Tuple/array-style rows from pandas itertuples or zip; LLM emitting shorthand formats; converting CSVs where each row becomes a list.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

• valuations must be an array of at least two {date, value} ob
• valuations may contain at most {_MAX_VALUATIONS} entries
• invalid alpha_id
• alpha_id not found
• invalid period: {exc}

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/acca776b5d32d12e. Report an issue: GitHub.