import os
from dataframer import Dataframer

client = Dataframer(
    api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
)
evaluation = client.dataframer.evaluations.create(
    run_id="a98715da-921d-4326-bbf8-208f8bcc2956",
)
print(evaluation.id)

curl https://df-api.dataframer.ai/api/dataframer/evaluations/ \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $DATAFRAMER_API_KEY" \
    -d '{
          "run_id": "a98715da-921d-4326-bbf8-208f8bcc2956"
        }'

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "run_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "status": "PENDING",
  "distribution_analysis": [
    {
      "property_name": "<string>",
      "total_samples": 123,
      "requested_distributions": {
        "positive": 40,
        "negative": 30,
        "neutral": 30
      },
      "expected_distributions": {
        "positive": 42,
        "negative": 30,
        "neutral": 28
      },
      "evaluated_distributions": {
        "positive": 45,
        "negative": 28,
        "neutral": 27
      },
      "total_samples_analyzed": 123
    }
  ],
  "sample_classifications": [
    {
      "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "evaluation_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "sample_identifier": "<string>",
      "classifications": {
        "sentiment": "positive",
        "topic": "technology",
        "length": "medium"
      },
      "created_at": "2023-11-07T05:31:56Z"
    }
  ],
  "completed_at": "2023-11-07T05:31:56Z",
  "error_message": "<string>",
  "created_by_email": "<string>",
  "created_at": "2023-11-07T05:31:56Z"
}

{
  "run_id": [
    "This field is required."
  ],
  "evaluation_model": [
    "Unsupported evaluation model: invalid-model"
  ],
  "error": "Can only evaluate completed runs"
}