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GET
/
confidence-scoring
/
summary
Python (SDK)
from meibelai import Meibelai
import os


with Meibelai(
    api_key_header=os.getenv("MEIBELAI_API_KEY_HEADER", ""),
) as m_client:

    res = m_client.confidence_scoring.get_scoring_jobs_summary(primary="<value>", secondary="<value>")

    # Handle response
    print(res)
{
  "primary_field": "<string>",
  "primary_value": "<string>",
  "secondary_field": "<string>",
  "secondary_value": "<string>",
  "status": "submitted",
  "aggregate_score": 123,
  "module_scores": {},
  "n_jobs_per_module": {},
  "jobs": [
    {
      "job_id": "<string>",
      "agent_identity_context": {
        "customer_id": "<string>",
        "project_id": "<string>",
        "agent_name": "<string>",
        "agent_version": "<string>",
        "agent_execution_id": "<string>",
        "agent_workflow_name": "<string>",
        "agent_workflow_version": "<string>",
        "agent_workflow_execution_id": "<string>",
        "tool_id": "<string>",
        "tool_instance_id": "<string>",
        "tool_execution_id": "<string>"
      },
      "module": "<string>",
      "scoring_config": {
        "module": "<string>",
        "config": {
          "anyof_schema_1_validator": {
            "prompt": "<string>",
            "temperature_max": 0.5,
            "temperature_step": 0.25
          },
          "anyof_schema_2_validator": {
            "nli_model_config": {},
            "n_completions": 5,
            "max_tokens": 8192,
            "temperature": 1,
            "models": [
              "<string>"
            ],
            "n_bootstraps": {
              "anyof_schema_1_validator": 123,
              "anyof_schema_2_validator": "<string>",
              "actual_instance": "<unknown>",
              "any_of_schemas": [
                "int",
                "str"
              ]
            },
            "token_limit": 512,
            "original_completion": "",
            "comparison_completions": [
              "<string>"
            ]
          },
          "anyof_schema_3_validator": {
            "calibration_model": "model_calibration_surya_0.5.0_ocr_confidence_horizontal.pkl",
            "ocr_confidence_scores": [
              123
            ]
          },
          "anyof_schema_4_validator": {
            "model": "gpt-4",
            "remove_stop_words": true,
            "lower_case": true,
            "max_ngrams": 2,
            "n_influencers": 10
          },
          "actual_instance": "<unknown>",
          "any_of_schemas": [
            "TokenConfig",
            "OCRConfig",
            "OCConfig",
            "JudgeConfig"
          ]
        }
      },
      "input_value": "<string>",
      "output_value": "<string>",
      "status": "submitted",
      "score": 123
    }
  ]
}

Documentation Index

Fetch the complete documentation index at: https://docs.meibel.ai/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

Meibel-API-Key
string
header
required

Query Parameters

primary
string
required
secondary
string | null

Response

Successful Response

Aggregated summary of scoring jobs matching one or two AgentIdentityContext filters. With one level (primary only): flat aggregate of all jobs matching primary_field=primary_value. With two levels (primary + secondary): both constraints are applied; primary is the higher level and secondary is the lower level.

primary_field
string
required
primary_value
string
required
secondary_field
string | null
secondary_value
string | null
status
enum<string> | null

ScoringStatus

Available options:
submitted,
in_progress,
completed,
failed
aggregate_score
module_scores
Module Scores · object
n_jobs_per_module
N Jobs Per Module · object
jobs
ScoringJobRecord · object[] | null