Live Monitoring

You can use the REST API to start an EVAL activity that generates model output for the missed time range. The activity status can be tracked within Activity view on the Falkonry UI.

Note

This is a recommended option, if you do not want to disrupt or restart live monitoring for an entity in order to set the retroactive time option to generate model output on the historical time range.

The API requires live model ID, common model ID (i.e. M[0]), entity name and time range for which model output needs to be generated. Use the Live Context API</apis/fetch_output> to get the common model ID and use the Falkonry UI to get the live model ID of the relevant assessment. Then use the below Flows API to start generating model output for the historical time range.

Request Payload

{
"flowType": "EVAL",
"datastream": "zzzzzzzzzzzzzzz",
"assessment": "yyyyyyyyyyyyyyy",
"model": "mmmmmmmmmmmmmm",
"name": "Model output run-1",
"spec": {
"commonModelId": "ccccccccccccccc",
"segments": [
{
"entities": ["<entity_name_1>", "<entity_name_2>"],
"timeRange": {
"startTime": "0000000000000000", // in nanoseconds
"endTime": "0000000000000000" // in nanoseconds
}
}
],
"forLive": true,
"withEpisodes": true
}
}

Example curl request

curl --location --request POST 'https://app3.falkonry.ai/api/1.2/accounts/xxxxxxxxxxxxxxx/flows' \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data-raw '{
      "flowType": "EVAL", 
      "datastream": "zzzzzzzzzzzzzzz",
      "assessment": "yyyyyyyyyyyyyyy", 
      "model": "mmmmmmmmmmmmmm", 
      "name": "Model output run-1", 
      "spec": {
          "commonModelId": "ccccccccccccccc", 
          "segments": [{
              "entities": ["<entity_name>"], 
              "timeRange": {
                  "startTime": "0000000000000000", // in nanoseconds
                  "endTime": "0000000000000000" // in nanoseconds 
                      }}],
      "forLive": true, 
      "withEpisodes": true } }'

Example with python

import requests 
URL = 'https://app3.falkonry.ai/api/1.2/accounts/xxxxxxxxxxxxxxx/flows'
TOKEN = '<token>' 
HEADERS = {'Authorization': f'Bearer {TOKEN}'} 
PAYLOAD = { "flowType": "EVAL", 
              "datastream":"zzzzzzzzzzzzzzz", 
              "assessment": "yyyyyyyyyyyyyyy", 
              "model": "mmmmmmmmmmmmmm", 
              "name": "Model output run-1", 
              "spec": {
                  "commonModelId": "ccccccccccccccc", 
                  "segments": [ {
                          "entities": ["<entity_name>"], 
                          "timeRange": { "startTime": "0000000000000000", # in nanoseconds 
                          "endTime": "00000000000000000" # in nanoseconds 
                              }}], 
              "forLive": true,
              "withEpisodes": true}}

response = requests.post(URL, headers=HEADERS, data=PAYLOAD)
print(response.json())

Example response

{
  "id": "1124191510837645312",
  "type": "entities.flow",
  "flowType": "EVAL",
  "status": "CREATED",
  "name": "Model output run-1",
  "datastream": "zzzzzzzzzzzzzzz",
  "assessment": "yyyyyyyyyyyyyyy",
  "model": "mmmmmmmmmmmmmm",
  "spec": {
    "isBatch": false,
    "datastreamStats": {},
    "model": "mmmmmmmmmmmmmm",
    "commonModelId": "ccccccccccccccc",
    "segments": [
      {
        "entities": [
          "machine-1"
        ],
        "timeRange": {
          "startTime": "1684843200000000000",
          "endTime": "1687521600000000000"
        }
      }
    ],
    "assessmentRate": 2000000000,
    "config": {},
    "inputList": [],
    "withEpisodes": true,
    "forEpisode": false,
    "tolerateNoData": false,
    "forLive": true
  },
  "createTime": 1688098542651,
  "updateTime": 1688098542651,
  "createdBy": "1013056801100267520",
  "updatedBy": "1013056801100267520",
  "archived": false,
  "links": []
}