Create job

curl --request POST \
  --url https://ai.data.cloud/api/v1/team/jobs \
  --header 'Content-Type: application/json' \
  --header 'x-pd-api-key: <api-key>' \
  --data '
{
  "datasetId": "cm1gjmg8e0057r3x22v1fdu8m",
  "datasourceIdList": [
    "cm1gjmmoo0001h0x24uk1xgu9"
  ],
  "languageType": "EN",
  "question": "Hello World",
  "sessionId": "5534f591-1520-4e74-b753-b87615b2c57a",
  "stream": false
}
'

import requests

url = "https://ai.data.cloud/api/v1/team/jobs"

payload = {
    "datasetId": "cm1gjmg8e0057r3x22v1fdu8m",
    "datasourceIdList": ["cm1gjmmoo0001h0x24uk1xgu9"],
    "languageType": "EN",
    "question": "Hello World",
    "sessionId": "5534f591-1520-4e74-b753-b87615b2c57a",
    "stream": False
}
headers = {
    "x-pd-api-key": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-pd-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    datasetId: 'cm1gjmg8e0057r3x22v1fdu8m',
    datasourceIdList: ['cm1gjmmoo0001h0x24uk1xgu9'],
    languageType: 'EN',
    question: 'Hello World',
    sessionId: '5534f591-1520-4e74-b753-b87615b2c57a',
    stream: false
  })
};

fetch('https://ai.data.cloud/api/v1/team/jobs', 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://ai.data.cloud/api/v1/team/jobs",
  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([
    'datasetId' => 'cm1gjmg8e0057r3x22v1fdu8m',
    'datasourceIdList' => [
        'cm1gjmmoo0001h0x24uk1xgu9'
    ],
    'languageType' => 'EN',
    'question' => 'Hello World',
    'sessionId' => '5534f591-1520-4e74-b753-b87615b2c57a',
    'stream' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-pd-api-key: <api-key>"
  ],
]);

$response = curl_exec($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://ai.data.cloud/api/v1/team/jobs"

	payload := strings.NewReader("{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}")

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

	req.Header.Add("x-pd-api-key", "<api-key>")
	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://ai.data.cloud/api/v1/team/jobs")
  .header("x-pd-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://ai.data.cloud/api/v1/team/jobs")

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

request = Net::HTTP::Post.new(url)
request["x-pd-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}"

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

{
  "code": 0,
  "data": {
    "jobId": "job-cm3ikdeuj02zk01l1yeuirt77",
    "blocks": [
      {
        "type": "CODE",
        "content": "```python\n\nimport pandas as pd\n\ndef invoke(input_0: pd.DataFrame) -> pd.DataFrame:\n    '''\n    input_0: pd.DataFrame  makeovermonday-a-century-of-global-deaths-from-disasters_decadal-deaths-disasters-type.csv\n    '''\n    # Group by 'Year' and sum the deaths for each type of disaster\n    aggregated_data = input_0.groupby('Year').sum().reset_index()\n    \n    # Select only the columns related to deaths\n    death_columns = [\n        'Deaths - Drought (decadal)', 'Deaths - Flood (decadal)', \n        'Deaths - Earthquake (decadal)', 'Deaths - Extreme weather (decadal)', \n        'Deaths - Extreme temperature (decadal)', 'Deaths - Volcanic activity (decadal)', \n        'Deaths - Wildfire (decadal)', 'Deaths - Glacial lake outburst flood (decadal)', \n        'Deaths - Dry mass movement (decadal)', 'Deaths - Wet mass movement (decadal)', \n        'Deaths - Fog (decadal)'\n    ]\n    \n    # Create a new DataFrame with the aggregated results\n    output = aggregated_data[['Year'] + death_columns]\n    \n    # Rename columns to be more descriptive\n    output.columns = ['Decade'] + [col.replace('Deaths - ', '').replace(' (decadal)', '') for col in death_columns]\n    \n    return output\n\n```",
        "groupId": "33063572-6e88-4912-8e2d-4166bcc8caee",
        "groupName": "Analyze the dataset to observe the trend of deaths caused by different types of natural disasters over the past century. This involves aggregating the data by decade and calculating the total number of deaths for each type of disaster to identify any changes in trends.",
        "stage": "Analyze"
      },
      {
        "type": "TABLE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/e24b6a5f-fdb8-48ca-ae35-dc91ac8e8ef7.csv",
          "name": "trend_data.csv",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "33063572-6e88-4912-8e2d-4166bcc8caee",
        "groupName": "Analyze the dataset to observe the trend of deaths caused by different types of natural disasters over the past century. This involves aggregating the data by decade and calculating the total number of deaths for each type of disaster to identify any changes in trends.",
        "stage": "Analyze"
      },
      {
        "type": "IMAGE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/81b75a33-a223-4954-9680-9f397872c8ad.png",
          "name": "Trend of Deaths from Natural Disasters Over the Century",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "7501680b-5879-441b-bd96-f58b1029ae17",
        "groupName": "Visualize the trend data to show how the number of deaths from different types of natural disasters has changed over the past century. Use line charts to represent the trends for each disaster type, which will help in understanding the impact of measures and technological advancements on reducing deaths.",
        "stage": "Analyze"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n`Analyzing Conclusions` \n\n### 自然灾害死亡人数变化趋势分析\n\n#### 数据分析\n\n",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "TABLE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/e24b6a5f-fdb8-48ca-ae35-dc91ac8e8ef7.csv",
          "name": "trend_data.csv",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n- **Droughts and Floods**: In the early 20th century, droughts and floods caused extremely high death tolls, particularly during the 1920s and 1930s.\n- **Earthquakes and Extreme Weather**: Earthquakes and extreme weather also led to significant death tolls throughout the century, especially in the 1970s and 1990s.\n- **Extreme Temperatures and Volcanic Activity**: These disasters had relatively lower death tolls, but in certain decades, such as the 2000s, deaths caused by extreme temperatures increased.\n\n#### Trend Visualization\n\n",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "IMAGE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/81b75a33-a223-4954-9680-9f397872c8ad.png",
          "name": "Trend of Deaths from Natural Disasters Over the Century",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n- **Overall Trend**: The chart shows that although certain decades experienced spikes in death tolls caused by natural disasters, the overall trend is declining.\n- **Impact of Technology and Measures**: Over time, advancements in technology and the implementation of disaster prevention measures are likely key factors in reducing death tolls.\n\n#### Conclusions and Insights\n- **Technological Advancements**: Modern technological progress, such as improved early warning systems and better construction techniques, may have reduced the fatalities caused by earthquakes and extreme weather.\n- **Disaster Prevention Measures**: The enhancement of disaster prevention measures and emergency response capabilities on a global scale has likely contributed to the decreased fatality rates of natural disasters.",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "SOURCES",
        "content": [
          {
            "source": "makeovermonday-a-century-of-global-deaths-from-disasters_decadal-deaths-disasters-type.csv",
            "datasourceId": "clxin6l9200oo01l1457bolx3",
            "datasetId": "clxin6l8400ok01l1ff2m0s25",
            "fileType": "csv"
          }
        ],
        "groupId": "",
        "groupName": "",
        "stage": "Respond"
      },
      {
        "type": "QUESTIONS",
        "content": [
          "Analyze the trends in death tolls from different types of natural disasters over the past century and explore which disaster types have shown the most significant reduction in fatalities.",
          "Study the technological advancements and measures in responding to natural disasters across different regions globally, and analyze how these differences have influenced changes in death tolls in each region.",
          "Explore how future technological advancements and policy measures could further reduce fatalities caused by natural disasters, and assess their feasibility and potential impacts."
        ],
        "groupId": "-1",
        "stage": "Respond"
      }
    ]
  }
}

{
  "code": 210021,
  "msg": "Job quota exceeded"
}

{
  "code": 1003,
  "msg": "insufficient.authentication"
}

{
  "code": 210020,
  "msg": "Something went wrong during job execution. Please try again."
}

Jobs

Create job

Converses with your data. Ask any question you have about your data and get insights instantly. On Powerdrill, a job refers to a task that Powerdrill performs to generate a response based on your request (e.g., a prompt or other workflows). Powerdrill Enterprise supports two types of jobs: general jobs and data agent jobs. Currently, only general jobs are available, so make sure the x-pd-api-agent-id header is set to GENERAL.

For an in-depth explanation of jobs, see What Is Job?.
To quickly create and execute a job, see Quick Start.

POST

team

jobs

Create job

curl --request POST \
  --url https://ai.data.cloud/api/v1/team/jobs \
  --header 'Content-Type: application/json' \
  --header 'x-pd-api-key: <api-key>' \
  --data '
{
  "datasetId": "cm1gjmg8e0057r3x22v1fdu8m",
  "datasourceIdList": [
    "cm1gjmmoo0001h0x24uk1xgu9"
  ],
  "languageType": "EN",
  "question": "Hello World",
  "sessionId": "5534f591-1520-4e74-b753-b87615b2c57a",
  "stream": false
}
'

import requests

url = "https://ai.data.cloud/api/v1/team/jobs"

payload = {
    "datasetId": "cm1gjmg8e0057r3x22v1fdu8m",
    "datasourceIdList": ["cm1gjmmoo0001h0x24uk1xgu9"],
    "languageType": "EN",
    "question": "Hello World",
    "sessionId": "5534f591-1520-4e74-b753-b87615b2c57a",
    "stream": False
}
headers = {
    "x-pd-api-key": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-pd-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    datasetId: 'cm1gjmg8e0057r3x22v1fdu8m',
    datasourceIdList: ['cm1gjmmoo0001h0x24uk1xgu9'],
    languageType: 'EN',
    question: 'Hello World',
    sessionId: '5534f591-1520-4e74-b753-b87615b2c57a',
    stream: false
  })
};

fetch('https://ai.data.cloud/api/v1/team/jobs', 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://ai.data.cloud/api/v1/team/jobs",
  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([
    'datasetId' => 'cm1gjmg8e0057r3x22v1fdu8m',
    'datasourceIdList' => [
        'cm1gjmmoo0001h0x24uk1xgu9'
    ],
    'languageType' => 'EN',
    'question' => 'Hello World',
    'sessionId' => '5534f591-1520-4e74-b753-b87615b2c57a',
    'stream' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-pd-api-key: <api-key>"
  ],
]);

$response = curl_exec($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://ai.data.cloud/api/v1/team/jobs"

	payload := strings.NewReader("{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}")

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

	req.Header.Add("x-pd-api-key", "<api-key>")
	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://ai.data.cloud/api/v1/team/jobs")
  .header("x-pd-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://ai.data.cloud/api/v1/team/jobs")

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

request = Net::HTTP::Post.new(url)
request["x-pd-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"datasetId\": \"cm1gjmg8e0057r3x22v1fdu8m\",\n  \"datasourceIdList\": [\n    \"cm1gjmmoo0001h0x24uk1xgu9\"\n  ],\n  \"languageType\": \"EN\",\n  \"question\": \"Hello World\",\n  \"sessionId\": \"5534f591-1520-4e74-b753-b87615b2c57a\",\n  \"stream\": false\n}"

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

{
  "code": 0,
  "data": {
    "jobId": "job-cm3ikdeuj02zk01l1yeuirt77",
    "blocks": [
      {
        "type": "CODE",
        "content": "```python\n\nimport pandas as pd\n\ndef invoke(input_0: pd.DataFrame) -> pd.DataFrame:\n    '''\n    input_0: pd.DataFrame  makeovermonday-a-century-of-global-deaths-from-disasters_decadal-deaths-disasters-type.csv\n    '''\n    # Group by 'Year' and sum the deaths for each type of disaster\n    aggregated_data = input_0.groupby('Year').sum().reset_index()\n    \n    # Select only the columns related to deaths\n    death_columns = [\n        'Deaths - Drought (decadal)', 'Deaths - Flood (decadal)', \n        'Deaths - Earthquake (decadal)', 'Deaths - Extreme weather (decadal)', \n        'Deaths - Extreme temperature (decadal)', 'Deaths - Volcanic activity (decadal)', \n        'Deaths - Wildfire (decadal)', 'Deaths - Glacial lake outburst flood (decadal)', \n        'Deaths - Dry mass movement (decadal)', 'Deaths - Wet mass movement (decadal)', \n        'Deaths - Fog (decadal)'\n    ]\n    \n    # Create a new DataFrame with the aggregated results\n    output = aggregated_data[['Year'] + death_columns]\n    \n    # Rename columns to be more descriptive\n    output.columns = ['Decade'] + [col.replace('Deaths - ', '').replace(' (decadal)', '') for col in death_columns]\n    \n    return output\n\n```",
        "groupId": "33063572-6e88-4912-8e2d-4166bcc8caee",
        "groupName": "Analyze the dataset to observe the trend of deaths caused by different types of natural disasters over the past century. This involves aggregating the data by decade and calculating the total number of deaths for each type of disaster to identify any changes in trends.",
        "stage": "Analyze"
      },
      {
        "type": "TABLE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/e24b6a5f-fdb8-48ca-ae35-dc91ac8e8ef7.csv",
          "name": "trend_data.csv",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "33063572-6e88-4912-8e2d-4166bcc8caee",
        "groupName": "Analyze the dataset to observe the trend of deaths caused by different types of natural disasters over the past century. This involves aggregating the data by decade and calculating the total number of deaths for each type of disaster to identify any changes in trends.",
        "stage": "Analyze"
      },
      {
        "type": "IMAGE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/81b75a33-a223-4954-9680-9f397872c8ad.png",
          "name": "Trend of Deaths from Natural Disasters Over the Century",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "7501680b-5879-441b-bd96-f58b1029ae17",
        "groupName": "Visualize the trend data to show how the number of deaths from different types of natural disasters has changed over the past century. Use line charts to represent the trends for each disaster type, which will help in understanding the impact of measures and technological advancements on reducing deaths.",
        "stage": "Analyze"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n`Analyzing Conclusions` \n\n### 自然灾害死亡人数变化趋势分析\n\n#### 数据分析\n\n",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "TABLE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/e24b6a5f-fdb8-48ca-ae35-dc91ac8e8ef7.csv",
          "name": "trend_data.csv",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n- **Droughts and Floods**: In the early 20th century, droughts and floods caused extremely high death tolls, particularly during the 1920s and 1930s.\n- **Earthquakes and Extreme Weather**: Earthquakes and extreme weather also led to significant death tolls throughout the century, especially in the 1970s and 1990s.\n- **Extreme Temperatures and Volcanic Activity**: These disasters had relatively lower death tolls, but in certain decades, such as the 2000s, deaths caused by extreme temperatures increased.\n\n#### Trend Visualization\n\n",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "IMAGE",
        "content": {
          "url": "https://static.powerdrill.ai/tmp_datasource_cache/code_result/cm37bchx106e301l1v9yf67yc/81b75a33-a223-4954-9680-9f397872c8ad.png",
          "name": "Trend of Deaths from Natural Disasters Over the Century",
          "expiredAt": "2024-11-21T09:56:34.290544Z"
        },
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "MESSAGE",
        "content": "\n\n- **Overall Trend**: The chart shows that although certain decades experienced spikes in death tolls caused by natural disasters, the overall trend is declining.\n- **Impact of Technology and Measures**: Over time, advancements in technology and the implementation of disaster prevention measures are likely key factors in reducing death tolls.\n\n#### Conclusions and Insights\n- **Technological Advancements**: Modern technological progress, such as improved early warning systems and better construction techniques, may have reduced the fatalities caused by earthquakes and extreme weather.\n- **Disaster Prevention Measures**: The enhancement of disaster prevention measures and emergency response capabilities on a global scale has likely contributed to the decreased fatality rates of natural disasters.",
        "groupId": "b842aca7-6fd5-4190-85fa-97085e473877",
        "groupName": "Conclusions",
        "stage": "Respond"
      },
      {
        "type": "SOURCES",
        "content": [
          {
            "source": "makeovermonday-a-century-of-global-deaths-from-disasters_decadal-deaths-disasters-type.csv",
            "datasourceId": "clxin6l9200oo01l1457bolx3",
            "datasetId": "clxin6l8400ok01l1ff2m0s25",
            "fileType": "csv"
          }
        ],
        "groupId": "",
        "groupName": "",
        "stage": "Respond"
      },
      {
        "type": "QUESTIONS",
        "content": [
          "Analyze the trends in death tolls from different types of natural disasters over the past century and explore which disaster types have shown the most significant reduction in fatalities.",
          "Study the technological advancements and measures in responding to natural disasters across different regions globally, and analyze how these differences have influenced changes in death tolls in each region.",
          "Explore how future technological advancements and policy measures could further reduce fatalities caused by natural disasters, and assess their feasibility and potential impacts."
        ],
        "groupId": "-1",
        "stage": "Respond"
      }
    ]
  }
}

{
  "code": 210021,
  "msg": "Job quota exceeded"
}

{
  "code": 1003,
  "msg": "insufficient.authentication"
}

{
  "code": 210020,
  "msg": "Something went wrong during job execution. Please try again."
}

The Response section in this topic describes the structure of the response when stream is set to false. For an example of the response when stream is set to true and an explanation of how to interpret the streaming response, refer to Streaming.

Authorizations

x-pd-api-key

string

header

required

Headers

x-pd-external-trace-id

string

The external trace ID. The length ranges from 0 to 128 characters.

Query Parameters

userId

string

required

Your user ID.

How to obtain your user ID: Sign in to Powerdrill Enterprise, click Users in the top navigation bar, and find your user ID in the list of users.

Body

application/json

sessionId

string

required

The session ID.

question

string

required

The question you want Powerdrill to answer.

stream

boolean

default:false

Whether to use stream mode. If set to true, Powerdrill will send real-time updates to the client, delivering continuous data as it becomes available. If set to false, Powerdrill will return the full response only once the entire answer is ready.

If not specified, the default value false will be used.

For details about how to understand streaming responses, see "Content description" in Streaming.

datasetId

string

The ID of the dataset to attach to the session. If not specified, the job will run without being associated with any dataset.

datasourceIdList

string[]

Specifies the IDs of the data sources to use in the conversation, rather than the entire dataset. You can specify up to 1,000 data sources.

languageType

enum<string>

default:AUTO

The language in which the output is generated. Possible values are:

AUTO: adaptive recognition
EN: English
ES: Spanish
AR: Arabic
PT: Portuguese
ID: Indonesian
JA: Japanese
RU: Russian
HI: Hindi
FR: French
DE: German
VI: Vietnamese
TR: Turkish
PL: Polish
IT: Italian
KO: Korean
ZH-CN: Simplified Chinese
ZH-TW: Traditional Chinese

Available options:

AUTO,

EN,

ES,

AR,

PT,

ID,

JA,

RU,

HI,

FR,

DE,

VI,

TR,

PL,

IT,

KO,

ZH-CN,

ZH-TW

jobMode

enum<string>

default:AUTO

Job mode. Possible values are:

AUTO: Powerdrill automatically detects your intent and selects the appropriate job mode from data analysis and information retrieval.
DATA_ANALYTICS: Powerdrill focuses specifically on data analysis.

Available options:

AUTO,

DATA_ANALYTICS

answerConfig

object

Show child attributes

Response

code

integer

required

Status code. 0 indicates that the operation is successful. Otherwise, the operation fails. Possible error codes include:

100112: The modelGroup parameter must be set to its default value.
1003: Authentication failed. Please check if the API key is correct.
210020: An error occurred during job execution. Please try again.
210021: Job quota exceeded. Please review your usage limits.
210022: The question is too long. Please shorten it and try again.
210023: The selected data sources are not yet ready. Only data sources in the Synched state are available for use.
210024: The text is too long for the text-to-speech service. The maximum allowed length is 5000 characters.
210025: Too many data sources selected. You can select up to 1,000 data sources.

data

object

required

Show child attributes

Overview

Developer Guides

Datasets

Data sources

Files

Sessions

Jobs

Create job

Authorizations

Headers

Query Parameters

Body

Response