HKUDS/Vibe-Trading · error · TypeError

build_comps_artifact: result must be a CompsResult, got {typ

Error message

build_comps_artifact: result must be a CompsResult, got {type(result).__name__}

What it means

build_comps_artifact requires result to be a CompsResult instance, mirroring the DCF variant. Anything else (dict, DCFResult, raw multiples table) raises a TypeError before any hashing happens.

Source

Thrown at agent/src/quantlib/valuation/artifact.py:808

    Args:
        target: The :class:`TargetCompany` passed to ``run_comps``.
        peers: The peer sequence passed to ``run_comps``.
        calendarisation_policy: The ``calendarisation_policy`` the call used.
        result: The :class:`CompsResult` that call produced.
        generated_at: Timezone-aware timestamp of the run, supplied by the
            caller.

    Returns:
        A ``model_name="comps"`` :class:`ModelArtifact`.

    Raises:
        TypeError: If ``generated_at`` is not a ``datetime``, or ``result``
            is not a :class:`CompsResult`.
        ValueError: If ``generated_at`` is timezone-naive.
    """
    generated_at = _require_generated_at(generated_at, "build_comps_artifact")
    if not isinstance(result, CompsResult):
        raise TypeError(
            f"build_comps_artifact: result must be a CompsResult, got {type(result).__name__}"
        )

    canonical_inputs = {
        "config": {"calendarisation_policy": calendarisation_policy},
        "target": target,
        "peers": list(peers),
    }
    hash_leaves: dict[str, str] = {}
    readable_inputs: dict[str, Any] = {}
    _flatten(canonical_inputs, "$", hash_leaves, readable_inputs, None)
    input_hash = _hash_leaves(hash_leaves)

    readable_outputs: dict[str, Any] = {}
    assumptions: list[AssumptionRecord] = []
    _flatten(result, "$", {}, readable_outputs, assumptions)

    return ModelArtifact(

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Pass the CompsResult returned by run_comps(...).
2. Re-export or re-wrap your data into a CompsResult before artifact creation.
3. Check for duplicate/stale CompsResult definitions on the import path.

Example fix

# before
build_comps_artifact(result=peer_table_df, generated_at=ts)
# after
build_comps_artifact(result=run_comps(target, peers), generated_at=ts)

from quantlib.valuation.models import CompsResult
assert isinstance(result, CompsResult), f"expected CompsResult, got {type(result).__name__}"

from quantlib.valuation.models import CompsResult
def is_comps_result(value) -> bool:
    return isinstance(value, CompsResult)

When it happens

Trigger: build_comps_artifact(result=df_of_multiples, ...); passing the output of run_dcf or a plain dict; feeding a dataclass from an older version of the comps module.

Common situations: Model refactor changing run_comps' return type; mixing up build_*_artifact calls when copy-pasting; stale imports shadowing CompsResult.

Understand the failure class

Background: "Wrong argument type", "must be a string", "expected Array or Prism::Scope": TypeError and ArgumentError when a library receives a value of the wrong type — this error's family across 28 libraries.

Related errors

• {model}: generated_at must be a datetime.datetime supplied b
• build_dcf_artifact: result must be a DCFResult, got {type(re
• build_three_statement_artifact: result must be a ThreeStatem
• amount must be numeric, got {self.amount!r}
• metadata must be a mapping, got {type(self.metadata).__name_

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/6e2ee4fecc37c88b. Report an issue: GitHub.