from mercurymesh.schema import get_ir_schemas, sample_payloads
from mercurymesh.bridge_ir import to_ir_market_signal, to_ir_aggregated_signal
from mercurymesh.adapters.venue_a import VenueAAdapter
from mercurymesh.adapters.venue_b import VenueBAdapter


def test_ir_schemas_present():
    schemas = get_ir_schemas()
    # Basic smoke checks for a few required IR models
    assert "LocalMarketContext" in schemas
    assert "AggregatedSignalIR" in schemas
    assert "PlanDeltaIR" in schemas


def test_sample_payloads_shape():
    samples = sample_payloads()
    assert "LocalMarketContext" in samples
    assert "AggregatedSignalIR" in samples


def test_adapter_to_ir_translation():
    a = VenueAAdapter()
    b = VenueBAdapter()
    msa = a.extract_signal()
    msb = b.extract_signal()

    ira = to_ir_market_signal(msa)
    irb = to_ir_market_signal(msb)
    # Ensure canonical wrapper keys exist
    assert "local_context" in ira
    assert "local_context" in irb

    # Build a simple AggregatedSignal-like dict for translation function
    agg = {
        "venues": [msa.venue_id, msb.venue_id],
        "feature_vector": {**msa.features, **msb.features},
        "privacy_budget_used": 0.05,
        "nonce": "n-1",
        "merkle_proof": None,
    }

    # Convert using the helper; ensure keys are present
    out = to_ir_aggregated_signal(type("Agg", (), agg)())
    assert "aggregated" in out
    assert "feature_vector" in out["aggregated"]