# For DeepEval / LangSmith integrations, prefer the dedicated helpers:
#   decimalai.push_deepeval_results(trace_id=..., results=...)
#   decimalai.push_langsmith_scores(trace_id=..., feedback=...)
# Generic custom scores:
import decimalai

decimalai.push_custom_scores(
    api_key="dai_sk_...",
    trace_id="trc_abc123",
    source="my-pipeline",
    scores=[
        {"name": "correctness", "score": 0.9},
        {"name": "faithfulness", "score": 0.85},
    ],
)

{
  "trace_id": "trc_abc123",
  "source": "deepeval",
  "scores_stored": 2,
  "scores": [
    {
      "id": "es_001",
      "name": "correctness",
      "score": 0.9,
      "passed": true,
      "source": "deepeval",
      "category": "quality"
    },
    {
      "id": "es_002",
      "name": "faithfulness",
      "score": 0.85,
      "passed": true,
      "source": "deepeval",
      "category": "quality"
    }
  ]
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}