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GET
https://api.keywordsai.co
/
api
/
logs
/
{log_id}
/
scores
import requests

url = "https://api.keywordsai.co/api/logs/{log_id}/scores/"
api_key = "YOUR_KEY" # Replace with your actual Keywords AI API key
headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

response = requests.get(url, headers=headers)
print(response.json())

{
  "count": 2,
  "next": null,
  "previous": null,
  "results": [
    {
      "id": "eval_result_unique_id_1",
      "created_at": "2024-01-15T10:30:00Z",
      "type": "llm",
      "environment": "test",
      "numerical_value": 4.5,
      "string_value": "Good quality",
      "boolean_value": true,
      "categorical_value": ["excellent"],
      "is_passed": false,
      "cost": 0.0,
      "evaluator_id": null,
      "evaluator_slug": "quality_evaluator",
      "log_id": "log_unique_id",
      "dataset_id": null
    }
  ]
}
Retrieves all scores associated with a specific log. 
import requests

url = "https://api.keywordsai.co/api/logs/{log_id}/scores/"
api_key = "YOUR_KEY" # Replace with your actual Keywords AI API key
headers = {
    "Authorization": f"Bearer {api_key}",
    "Content-Type": "application/json"
}

response = requests.get(url, headers=headers)
print(response.json())

{
  "count": 2,
  "next": null,
  "previous": null,
  "results": [
    {
      "id": "eval_result_unique_id_1",
      "created_at": "2024-01-15T10:30:00Z",
      "type": "llm",
      "environment": "test",
      "numerical_value": 4.5,
      "string_value": "Good quality",
      "boolean_value": true,
      "categorical_value": ["excellent"],
      "is_passed": false,
      "cost": 0.0,
      "evaluator_id": null,
      "evaluator_slug": "quality_evaluator",
      "log_id": "log_unique_id",
      "dataset_id": null
    }
  ]
}

​
Score Enrichment in Logs

When you retrieve log details, scores are automatically included in the response under a scores field with enriched information including evaluator names and score values.

​
Score Summary Aggregations

Aggregated score summaries (average scores for numerical evaluators, true/false counts for boolean evaluators) are available in:
  • Logs Summary: GET/POST /api/request-logs/summary/
  • Experiment Logs Summary: GET/POST /evaluations/experiments//logs/summary/
  • Dataset Logs Summary: GET/POST /api/datasets//logs/summary/
Score summaries show:
  • Numerical/Percentage evaluators: Average score (1-5 scale or 0-100%)
  • Boolean evaluators: True count and false count
See the Logs Summary endpoint for complete details on the score summary format.