Create online evals monitors

curl --request POST \
  --url https://evalgate.com/api/online-evals/monitors \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "description": "<string>",
  "evaluationId": 123,
  "configuration": {
    "budget": {
      "maxDailyCostUsd": 123,
      "maxPerCallCostUsd": 123,
      "maxDailyModelCalls": 123,
      "backfillMaxCostUsd": 123,
      "fallbackBehavior": "fail_closed"
    },
    "checks": {
      "maxCostUsd": 123,
      "deterministic": false,
      "maxLatencyMs": 123,
      "scorerVersionIds": [
        123
      ],
      "minimumScore": 123,
      "llmJudge": false
    },
    "environment": "<string>",
    "promptVersionId": 123,
    "datasetVersionId": "<string>",
    "seed": 123,
    "deploymentId": "<string>",
    "policy": {},
    "learning": {
      "generateCandidates": false,
      "autoCreateReview": false,
      "topicAssignment": false,
      "promotionPolicy": "manual"
    },
    "savedViewId": "<string>",
    "alerting": {
      "failureRateThreshold": 123,
      "minimumSeverity": "medium",
      "dedupeWindowMinutes": 123,
      "channels": [
        "review_queue"
      ],
      "activationCostWarningUsd": 123,
      "activationAlertWarningCount": 123
    },
    "evaluatorAction": {
      "action": "release_gate",
      "target": {
        "provider": "<string>",
        "policyHash": "<string>",
        "evaluatorReleaseId": "<string>",
        "measurementRevisionId": "<string>",
        "model": "<string>",
        "taskId": "<string>",
        "sliceId": "<string>",
        "targetScopeHash": "<string>",
        "evaluatorIdentityHash": "<string>",
        "experimentDigest": "<string>",
        "dataScopeHash": "<string>"
      },
      "approvalId": 123
    }
  },
  "matchRules": {
    "environment": "<string>",
    "source": "<string>",
    "status": "<string>",
    "nameContains": "<string>"
  },
  "sampling": {
    "mode": "random",
    "sampleRate": 123,
    "failureOnly": false,
    "maxDailySamples": 123,
    "maxDailyCostUsd": "<string>",
    "severityMultiplier": 123,
    "uncertaintyBoost": 123,
    "adaptiveTargetRate": 123
  },
  "activateImmediately": false
}
'

import requests

url = "https://evalgate.com/api/online-evals/monitors"

payload = {
    "name": "<string>",
    "description": "<string>",
    "evaluationId": 123,
    "configuration": {
        "budget": {
            "maxDailyCostUsd": 123,
            "maxPerCallCostUsd": 123,
            "maxDailyModelCalls": 123,
            "backfillMaxCostUsd": 123,
            "fallbackBehavior": "fail_closed"
        },
        "checks": {
            "maxCostUsd": 123,
            "deterministic": False,
            "maxLatencyMs": 123,
            "scorerVersionIds": [123],
            "minimumScore": 123,
            "llmJudge": False
        },
        "environment": "<string>",
        "promptVersionId": 123,
        "datasetVersionId": "<string>",
        "seed": 123,
        "deploymentId": "<string>",
        "policy": {},
        "learning": {
            "generateCandidates": False,
            "autoCreateReview": False,
            "topicAssignment": False,
            "promotionPolicy": "manual"
        },
        "savedViewId": "<string>",
        "alerting": {
            "failureRateThreshold": 123,
            "minimumSeverity": "medium",
            "dedupeWindowMinutes": 123,
            "channels": ["review_queue"],
            "activationCostWarningUsd": 123,
            "activationAlertWarningCount": 123
        },
        "evaluatorAction": {
            "action": "release_gate",
            "target": {
                "provider": "<string>",
                "policyHash": "<string>",
                "evaluatorReleaseId": "<string>",
                "measurementRevisionId": "<string>",
                "model": "<string>",
                "taskId": "<string>",
                "sliceId": "<string>",
                "targetScopeHash": "<string>",
                "evaluatorIdentityHash": "<string>",
                "experimentDigest": "<string>",
                "dataScopeHash": "<string>"
            },
            "approvalId": 123
        }
    },
    "matchRules": {
        "environment": "<string>",
        "source": "<string>",
        "status": "<string>",
        "nameContains": "<string>"
    },
    "sampling": {
        "mode": "random",
        "sampleRate": 123,
        "failureOnly": False,
        "maxDailySamples": 123,
        "maxDailyCostUsd": "<string>",
        "severityMultiplier": 123,
        "uncertaintyBoost": 123,
        "adaptiveTargetRate": 123
    },
    "activateImmediately": False
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    description: '<string>',
    evaluationId: 123,
    configuration: {
      budget: {
        maxDailyCostUsd: 123,
        maxPerCallCostUsd: 123,
        maxDailyModelCalls: 123,
        backfillMaxCostUsd: 123,
        fallbackBehavior: 'fail_closed'
      },
      checks: {
        maxCostUsd: 123,
        deterministic: false,
        maxLatencyMs: 123,
        scorerVersionIds: [123],
        minimumScore: 123,
        llmJudge: false
      },
      environment: '<string>',
      promptVersionId: 123,
      datasetVersionId: '<string>',
      seed: 123,
      deploymentId: '<string>',
      policy: {},
      learning: {
        generateCandidates: false,
        autoCreateReview: false,
        topicAssignment: false,
        promotionPolicy: 'manual'
      },
      savedViewId: '<string>',
      alerting: {
        failureRateThreshold: 123,
        minimumSeverity: 'medium',
        dedupeWindowMinutes: 123,
        channels: ['review_queue'],
        activationCostWarningUsd: 123,
        activationAlertWarningCount: 123
      },
      evaluatorAction: {
        action: 'release_gate',
        target: {
          provider: '<string>',
          policyHash: '<string>',
          evaluatorReleaseId: '<string>',
          measurementRevisionId: '<string>',
          model: '<string>',
          taskId: '<string>',
          sliceId: '<string>',
          targetScopeHash: '<string>',
          evaluatorIdentityHash: '<string>',
          experimentDigest: '<string>',
          dataScopeHash: '<string>'
        },
        approvalId: 123
      }
    },
    matchRules: {
      environment: '<string>',
      source: '<string>',
      status: '<string>',
      nameContains: '<string>'
    },
    sampling: {
      mode: 'random',
      sampleRate: 123,
      failureOnly: false,
      maxDailySamples: 123,
      maxDailyCostUsd: '<string>',
      severityMultiplier: 123,
      uncertaintyBoost: 123,
      adaptiveTargetRate: 123
    },
    activateImmediately: false
  })
};

fetch('https://evalgate.com/api/online-evals/monitors', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://evalgate.com/api/online-evals/monitors",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => '<string>',
    'description' => '<string>',
    'evaluationId' => 123,
    'configuration' => [
        'budget' => [
                'maxDailyCostUsd' => 123,
                'maxPerCallCostUsd' => 123,
                'maxDailyModelCalls' => 123,
                'backfillMaxCostUsd' => 123,
                'fallbackBehavior' => 'fail_closed'
        ],
        'checks' => [
                'maxCostUsd' => 123,
                'deterministic' => false,
                'maxLatencyMs' => 123,
                'scorerVersionIds' => [
                                123
                ],
                'minimumScore' => 123,
                'llmJudge' => false
        ],
        'environment' => '<string>',
        'promptVersionId' => 123,
        'datasetVersionId' => '<string>',
        'seed' => 123,
        'deploymentId' => '<string>',
        'policy' => [
                
        ],
        'learning' => [
                'generateCandidates' => false,
                'autoCreateReview' => false,
                'topicAssignment' => false,
                'promotionPolicy' => 'manual'
        ],
        'savedViewId' => '<string>',
        'alerting' => [
                'failureRateThreshold' => 123,
                'minimumSeverity' => 'medium',
                'dedupeWindowMinutes' => 123,
                'channels' => [
                                'review_queue'
                ],
                'activationCostWarningUsd' => 123,
                'activationAlertWarningCount' => 123
        ],
        'evaluatorAction' => [
                'action' => 'release_gate',
                'target' => [
                                'provider' => '<string>',
                                'policyHash' => '<string>',
                                'evaluatorReleaseId' => '<string>',
                                'measurementRevisionId' => '<string>',
                                'model' => '<string>',
                                'taskId' => '<string>',
                                'sliceId' => '<string>',
                                'targetScopeHash' => '<string>',
                                'evaluatorIdentityHash' => '<string>',
                                'experimentDigest' => '<string>',
                                'dataScopeHash' => '<string>'
                ],
                'approvalId' => 123
        ]
    ],
    'matchRules' => [
        'environment' => '<string>',
        'source' => '<string>',
        'status' => '<string>',
        'nameContains' => '<string>'
    ],
    'sampling' => [
        'mode' => 'random',
        'sampleRate' => 123,
        'failureOnly' => false,
        'maxDailySamples' => 123,
        'maxDailyCostUsd' => '<string>',
        'severityMultiplier' => 123,
        'uncertaintyBoost' => 123,
        'adaptiveTargetRate' => 123
    ],
    'activateImmediately' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://evalgate.com/api/online-evals/monitors"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"evaluationId\": 123,\n  \"configuration\": {\n    \"budget\": {\n      \"maxDailyCostUsd\": 123,\n      \"maxPerCallCostUsd\": 123,\n      \"maxDailyModelCalls\": 123,\n      \"backfillMaxCostUsd\": 123,\n      \"fallbackBehavior\": \"fail_closed\"\n    },\n    \"checks\": {\n      \"maxCostUsd\": 123,\n      \"deterministic\": false,\n      \"maxLatencyMs\": 123,\n      \"scorerVersionIds\": [\n        123\n      ],\n      \"minimumScore\": 123,\n      \"llmJudge\": false\n    },\n    \"environment\": \"<string>\",\n    \"promptVersionId\": 123,\n    \"datasetVersionId\": \"<string>\",\n    \"seed\": 123,\n    \"deploymentId\": \"<string>\",\n    \"policy\": {},\n    \"learning\": {\n      \"generateCandidates\": false,\n      \"autoCreateReview\": false,\n      \"topicAssignment\": false,\n      \"promotionPolicy\": \"manual\"\n    },\n    \"savedViewId\": \"<string>\",\n    \"alerting\": {\n      \"failureRateThreshold\": 123,\n      \"minimumSeverity\": \"medium\",\n      \"dedupeWindowMinutes\": 123,\n      \"channels\": [\n        \"review_queue\"\n      ],\n      \"activationCostWarningUsd\": 123,\n      \"activationAlertWarningCount\": 123\n    },\n    \"evaluatorAction\": {\n      \"action\": \"release_gate\",\n      \"target\": {\n        \"provider\": \"<string>\",\n        \"policyHash\": \"<string>\",\n        \"evaluatorReleaseId\": \"<string>\",\n        \"measurementRevisionId\": \"<string>\",\n        \"model\": \"<string>\",\n        \"taskId\": \"<string>\",\n        \"sliceId\": \"<string>\",\n        \"targetScopeHash\": \"<string>\",\n        \"evaluatorIdentityHash\": \"<string>\",\n        \"experimentDigest\": \"<string>\",\n        \"dataScopeHash\": \"<string>\"\n      },\n      \"approvalId\": 123\n    }\n  },\n  \"matchRules\": {\n    \"environment\": \"<string>\",\n    \"source\": \"<string>\",\n    \"status\": \"<string>\",\n    \"nameContains\": \"<string>\"\n  },\n  \"sampling\": {\n    \"mode\": \"random\",\n    \"sampleRate\": 123,\n    \"failureOnly\": false,\n    \"maxDailySamples\": 123,\n    \"maxDailyCostUsd\": \"<string>\",\n    \"severityMultiplier\": 123,\n    \"uncertaintyBoost\": 123,\n    \"adaptiveTargetRate\": 123\n  },\n  \"activateImmediately\": false\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://evalgate.com/api/online-evals/monitors")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"evaluationId\": 123,\n  \"configuration\": {\n    \"budget\": {\n      \"maxDailyCostUsd\": 123,\n      \"maxPerCallCostUsd\": 123,\n      \"maxDailyModelCalls\": 123,\n      \"backfillMaxCostUsd\": 123,\n      \"fallbackBehavior\": \"fail_closed\"\n    },\n    \"checks\": {\n      \"maxCostUsd\": 123,\n      \"deterministic\": false,\n      \"maxLatencyMs\": 123,\n      \"scorerVersionIds\": [\n        123\n      ],\n      \"minimumScore\": 123,\n      \"llmJudge\": false\n    },\n    \"environment\": \"<string>\",\n    \"promptVersionId\": 123,\n    \"datasetVersionId\": \"<string>\",\n    \"seed\": 123,\n    \"deploymentId\": \"<string>\",\n    \"policy\": {},\n    \"learning\": {\n      \"generateCandidates\": false,\n      \"autoCreateReview\": false,\n      \"topicAssignment\": false,\n      \"promotionPolicy\": \"manual\"\n    },\n    \"savedViewId\": \"<string>\",\n    \"alerting\": {\n      \"failureRateThreshold\": 123,\n      \"minimumSeverity\": \"medium\",\n      \"dedupeWindowMinutes\": 123,\n      \"channels\": [\n        \"review_queue\"\n      ],\n      \"activationCostWarningUsd\": 123,\n      \"activationAlertWarningCount\": 123\n    },\n    \"evaluatorAction\": {\n      \"action\": \"release_gate\",\n      \"target\": {\n        \"provider\": \"<string>\",\n        \"policyHash\": \"<string>\",\n        \"evaluatorReleaseId\": \"<string>\",\n        \"measurementRevisionId\": \"<string>\",\n        \"model\": \"<string>\",\n        \"taskId\": \"<string>\",\n        \"sliceId\": \"<string>\",\n        \"targetScopeHash\": \"<string>\",\n        \"evaluatorIdentityHash\": \"<string>\",\n        \"experimentDigest\": \"<string>\",\n        \"dataScopeHash\": \"<string>\"\n      },\n      \"approvalId\": 123\n    }\n  },\n  \"matchRules\": {\n    \"environment\": \"<string>\",\n    \"source\": \"<string>\",\n    \"status\": \"<string>\",\n    \"nameContains\": \"<string>\"\n  },\n  \"sampling\": {\n    \"mode\": \"random\",\n    \"sampleRate\": 123,\n    \"failureOnly\": false,\n    \"maxDailySamples\": 123,\n    \"maxDailyCostUsd\": \"<string>\",\n    \"severityMultiplier\": 123,\n    \"uncertaintyBoost\": 123,\n    \"adaptiveTargetRate\": 123\n  },\n  \"activateImmediately\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://evalgate.com/api/online-evals/monitors")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"evaluationId\": 123,\n  \"configuration\": {\n    \"budget\": {\n      \"maxDailyCostUsd\": 123,\n      \"maxPerCallCostUsd\": 123,\n      \"maxDailyModelCalls\": 123,\n      \"backfillMaxCostUsd\": 123,\n      \"fallbackBehavior\": \"fail_closed\"\n    },\n    \"checks\": {\n      \"maxCostUsd\": 123,\n      \"deterministic\": false,\n      \"maxLatencyMs\": 123,\n      \"scorerVersionIds\": [\n        123\n      ],\n      \"minimumScore\": 123,\n      \"llmJudge\": false\n    },\n    \"environment\": \"<string>\",\n    \"promptVersionId\": 123,\n    \"datasetVersionId\": \"<string>\",\n    \"seed\": 123,\n    \"deploymentId\": \"<string>\",\n    \"policy\": {},\n    \"learning\": {\n      \"generateCandidates\": false,\n      \"autoCreateReview\": false,\n      \"topicAssignment\": false,\n      \"promotionPolicy\": \"manual\"\n    },\n    \"savedViewId\": \"<string>\",\n    \"alerting\": {\n      \"failureRateThreshold\": 123,\n      \"minimumSeverity\": \"medium\",\n      \"dedupeWindowMinutes\": 123,\n      \"channels\": [\n        \"review_queue\"\n      ],\n      \"activationCostWarningUsd\": 123,\n      \"activationAlertWarningCount\": 123\n    },\n    \"evaluatorAction\": {\n      \"action\": \"release_gate\",\n      \"target\": {\n        \"provider\": \"<string>\",\n        \"policyHash\": \"<string>\",\n        \"evaluatorReleaseId\": \"<string>\",\n        \"measurementRevisionId\": \"<string>\",\n        \"model\": \"<string>\",\n        \"taskId\": \"<string>\",\n        \"sliceId\": \"<string>\",\n        \"targetScopeHash\": \"<string>\",\n        \"evaluatorIdentityHash\": \"<string>\",\n        \"experimentDigest\": \"<string>\",\n        \"dataScopeHash\": \"<string>\"\n      },\n      \"approvalId\": 123\n    }\n  },\n  \"matchRules\": {\n    \"environment\": \"<string>\",\n    \"source\": \"<string>\",\n    \"status\": \"<string>\",\n    \"nameContains\": \"<string>\"\n  },\n  \"sampling\": {\n    \"mode\": \"random\",\n    \"sampleRate\": 123,\n    \"failureOnly\": false,\n    \"maxDailySamples\": 123,\n    \"maxDailyCostUsd\": \"<string>\",\n    \"severityMultiplier\": 123,\n    \"uncertaintyBoost\": 123,\n    \"adaptiveTargetRate\": 123\n  },\n  \"activateImmediately\": false\n}"

response = http.request(request)
puts response.read_body

{
  "id": 123,
  "name": "<string>",
  "description": "<string>",
  "evaluationId": 123,
  "status": "<string>",
  "matchRules": {
    "environment": "<string>",
    "source": "<string>",
    "status": "<string>",
    "nameContains": "<string>"
  },
  "sampling": {
    "sampleRate": 123,
    "failureOnly": true,
    "maxDailySamples": 123,
    "maxDailyCostUsd": "<string>",
    "policyVersion": 123
  },
  "createdAt": "<string>",
  "updatedAt": "<string>",
  "pausedAt": "<string>",
  "activeVersionId": "<string>",
  "draftVersionId": "<string>"
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "<string>",
    "details": "<unknown>",
    "requestId": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "redaction": {
      "applied": true,
      "fieldCount": 1,
      "secretCount": 1
    }
  }
}