import requests
url = "https://api.parallel.ai/v1alpha/monitors"
payload = {
"query": "Extract recent news about AI",
"frequency": "1d"
}
headers = {
"x-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-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({query: 'Extract recent news about AI', frequency: '1d'})
};
fetch('https://api.parallel.ai/v1alpha/monitors', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));HttpResponse<String> response = Unirest.post("https://api.parallel.ai/v1alpha/monitors")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"query\": \"Extract recent news about AI\",\n \"frequency\": \"1d\"\n}")
.asString();curl --request POST \
--url https://api.parallel.ai/v1alpha/monitors \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"query": "Extract recent news about AI",
"frequency": "1d"
}
'{
"monitor_id": "monitor_b0079f70195e4258a3b982c1b6d8bd3a",
"query": "Extract recent news about AI",
"status": "active",
"frequency": "1d",
"metadata": {
"key": "value"
},
"webhook": {
"url": "https://example.com/webhook",
"event_types": [
"monitor.event.detected"
]
},
"created_at": "2025-04-23T20:21:48.037943Z"
}{
"type": "error",
"error": {
"ref_id": "fcb2b4f3-c75e-4186-87bc-caa1a8381331",
"message": "Unauthorized: invalid or missing credentials"
}
}{
"type": "error",
"error": {
"ref_id": "fcb2b4f3-c75e-4186-87bc-caa1a8381331",
"message": "Unprocessable content: request validation error"
}
}Create Monitor
Create a web monitor.
Creates a monitor that periodically runs the specified query over the web at the specified cadence (hourly, daily, weekly, or every two weeks). The monitor runs once at creation and then continues according to the specified frequency.
Updates will be sent to the webhook if provided. Use the executions endpoint
to retrieve execution history for a monitor.
import requests
url = "https://api.parallel.ai/v1alpha/monitors"
payload = {
"query": "Extract recent news about AI",
"frequency": "1d"
}
headers = {
"x-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-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({query: 'Extract recent news about AI', frequency: '1d'})
};
fetch('https://api.parallel.ai/v1alpha/monitors', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));HttpResponse<String> response = Unirest.post("https://api.parallel.ai/v1alpha/monitors")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"query\": \"Extract recent news about AI\",\n \"frequency\": \"1d\"\n}")
.asString();curl --request POST \
--url https://api.parallel.ai/v1alpha/monitors \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"query": "Extract recent news about AI",
"frequency": "1d"
}
'{
"monitor_id": "monitor_b0079f70195e4258a3b982c1b6d8bd3a",
"query": "Extract recent news about AI",
"status": "active",
"frequency": "1d",
"metadata": {
"key": "value"
},
"webhook": {
"url": "https://example.com/webhook",
"event_types": [
"monitor.event.detected"
]
},
"created_at": "2025-04-23T20:21:48.037943Z"
}{
"type": "error",
"error": {
"ref_id": "fcb2b4f3-c75e-4186-87bc-caa1a8381331",
"message": "Unauthorized: invalid or missing credentials"
}
}{
"type": "error",
"error": {
"ref_id": "fcb2b4f3-c75e-4186-87bc-caa1a8381331",
"message": "Unprocessable content: request validation error"
}
}Authorizations
Body
- V0CreateMonitorRequest
- DeprecatedCreateMonitorRequest
Request to create a monitor.
Search query to monitor for material changes.
"Extract recent news about AI"
Frequency of the monitor. Format: '' where unit is 'h' (hours), 'd' (days), or 'w' (weeks). Must be between 1h and 30d (inclusive).
"1d"
"1w"
"1h"
"2w"
Webhook to receive notifications about the monitor's execution.
Show child attributes
Show child attributes
User-provided metadata stored with the monitor. Returned in webhook notifications and GET requests, enabling you to map responses to corresponding objects in your application.
Show child attributes
Show child attributes
{
"slack_thread_id": "1234567890.123456",
"user_id": "U123ABC"
}
Output schema for the monitor event.
Show child attributes
Show child attributes
If true, the first execution includes historical events matching the query. Subsequent executions return only new events since the previous run.
Source policy governing included and excluded domains and domain/path prefixes in web search results.
Show child attributes
Show child attributes
{
"include_domains": [
"wikipedia.org",
"docs.python.org/3",
".edu"
]
}
Response
Successful Response
Response object for a monitor, including its status, cadence and metadata.
ID of the monitor.
The query being monitored.
"Recent news about LLM models."
Status of the monitor.
active, canceled "active"
"canceled"
Frequency of the monitor. Format: '' where unit is 'h' (hours), 'd' (days), or 'w' (weeks). Must be between 1h and 30d (inclusive).
"1d"
"1w"
"1h"
"2w"
Timestamp of the creation of the monitor.
"2025-01-15T10:30:00Z"
Deprecated: use 'frequency' field instead.
daily, weekly, hourly, every_two_weeks "daily"
User-provided metadata stored with the monitor. Returned in webhook notifications and GET requests, enabling you to map responses to corresponding objects in your application.
Show child attributes
Show child attributes
{
"slack_thread_id": "1234567890.123456",
"user_id": "U123ABC"
}
Webhook configuration for the monitor.
Show child attributes
Show child attributes
Output schema for the monitor event.
Show child attributes
Show child attributes
Source policy governing included and excluded domains and domain/path prefixes in web search results.
Show child attributes
Show child attributes
{
"include_domains": [
"wikipedia.org",
"docs.python.org/3",
".edu"
]
}
Timestamp of the last run for the monitor.
"2025-01-15T10:30:00Z"
If true, the first execution includes historical events matching the query. Subsequent executions return only new events since the previous run.