Split text on sentences
import requests
url = "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}"
payload = {
"batch": [{ "text": "The itsy bitsy spider climbed up the waterspout.
Down came the rain.
And washed the spider out.
Out came the sun.
And dried up all the rain.
And the itsy bitsy spider climbed up the spout again." }],
"useCaseConfig": { "dataType": "query" },
"modelConfig": { "vectorQuantizationMethod": "max-scale" }
}
headers = {
"Authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)HttpResponse<String> response = Unirest.post("https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}")
.header("Authorization", "<authorization>")
.header("Content-Type", "application/json")
.body("{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}")
.asString();const options = {
method: 'POST',
headers: {Authorization: '<authorization>', 'Content-Type': 'application/json'},
body: JSON.stringify({
batch: [
{
text: 'The itsy bitsy spider climbed up the waterspout.\nDown came the rain.\nAnd washed the spider out.\nOut came the sun.\nAnd dried up all the rain.\nAnd the itsy bitsy spider climbed up the spout again.'
}
],
useCaseConfig: {dataType: 'query'},
modelConfig: {vectorQuantizationMethod: 'max-scale'}
})
};
fetch('https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));require 'uri'
require 'net/http'
url = URI("https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}"
response = http.request(request)
puts response.read_bodypackage main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}"
payload := strings.NewReader("{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "<authorization>")
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))
}<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}",
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([
'batch' => [
[
'text' => 'The itsy bitsy spider climbed up the waterspout.
Down came the rain.
And washed the spider out.
Out came the sun.
And dried up all the rain.
And the itsy bitsy spider climbed up the spout again.'
]
],
'useCaseConfig' => [
'dataType' => 'query'
],
'modelConfig' => [
'vectorQuantizationMethod' => 'max-scale'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: <authorization>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}curl --request POST \
--url https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID} \
--header 'Authorization: <authorization>' \
--header 'Content-Type: application/json' \
--data '
{
"batch": [
{
"text": "The itsy bitsy spider climbed up the waterspout.\nDown came the rain.\nAnd washed the spider out.\nOut came the sun.\nAnd dried up all the rain.\nAnd the itsy bitsy spider climbed up the spout again."
}
],
"useCaseConfig": {
"dataType": "query"
},
"modelConfig": {
"vectorQuantizationMethod": "max-scale"
}
}
'{
"chunkingId": "5886c6f0-5897-44a7-b473-bd531c0ee054",
"status": "SUBMITTED"
}{
"chunkingId": "441eb3be-7de6-470a-8141-e416a15c7db1",
"status": "READY",
"message": "<string>"
}Split text on sentences
The sentence chunker (chunking strategy) splits text on sentences.
POST
/
ai
/
async-chunking
/
sentence
/
{MODEL_ID}
Split text on sentences
import requests
url = "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}"
payload = {
"batch": [{ "text": "The itsy bitsy spider climbed up the waterspout.
Down came the rain.
And washed the spider out.
Out came the sun.
And dried up all the rain.
And the itsy bitsy spider climbed up the spout again." }],
"useCaseConfig": { "dataType": "query" },
"modelConfig": { "vectorQuantizationMethod": "max-scale" }
}
headers = {
"Authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)HttpResponse<String> response = Unirest.post("https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}")
.header("Authorization", "<authorization>")
.header("Content-Type", "application/json")
.body("{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}")
.asString();const options = {
method: 'POST',
headers: {Authorization: '<authorization>', 'Content-Type': 'application/json'},
body: JSON.stringify({
batch: [
{
text: 'The itsy bitsy spider climbed up the waterspout.\nDown came the rain.\nAnd washed the spider out.\nOut came the sun.\nAnd dried up all the rain.\nAnd the itsy bitsy spider climbed up the spout again.'
}
],
useCaseConfig: {dataType: 'query'},
modelConfig: {vectorQuantizationMethod: 'max-scale'}
})
};
fetch('https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));require 'uri'
require 'net/http'
url = URI("https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}"
response = http.request(request)
puts response.read_bodypackage main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}"
payload := strings.NewReader("{\n \"batch\": [\n {\n \"text\": \"The itsy bitsy spider climbed up the waterspout.\\nDown came the rain.\\nAnd washed the spider out.\\nOut came the sun.\\nAnd dried up all the rain.\\nAnd the itsy bitsy spider climbed up the spout again.\"\n }\n ],\n \"useCaseConfig\": {\n \"dataType\": \"query\"\n },\n \"modelConfig\": {\n \"vectorQuantizationMethod\": \"max-scale\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "<authorization>")
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))
}<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID}",
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([
'batch' => [
[
'text' => 'The itsy bitsy spider climbed up the waterspout.
Down came the rain.
And washed the spider out.
Out came the sun.
And dried up all the rain.
And the itsy bitsy spider climbed up the spout again.'
]
],
'useCaseConfig' => [
'dataType' => 'query'
],
'modelConfig' => [
'vectorQuantizationMethod' => 'max-scale'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: <authorization>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}curl --request POST \
--url https://{APPLICATION_ID}.applications.lucidworks.com/ai/async-chunking/sentence/{MODEL_ID} \
--header 'Authorization: <authorization>' \
--header 'Content-Type: application/json' \
--data '
{
"batch": [
{
"text": "The itsy bitsy spider climbed up the waterspout.\nDown came the rain.\nAnd washed the spider out.\nOut came the sun.\nAnd dried up all the rain.\nAnd the itsy bitsy spider climbed up the spout again."
}
],
"useCaseConfig": {
"dataType": "query"
},
"modelConfig": {
"vectorQuantizationMethod": "max-scale"
}
}
'{
"chunkingId": "5886c6f0-5897-44a7-b473-bd531c0ee054",
"status": "SUBMITTED"
}{
"chunkingId": "441eb3be-7de6-470a-8141-e416a15c7db1",
"status": "READY",
"message": "<string>"
}Headers
Body
application/json
Response
OK
This is the response to the POST chunking request submitted for a specific chunker and modelId.
The current status of the request. Allowed values are:
-
SUBMITTED - The POST request was successful and the response has returned the
chunkingIdandstatusthat is used by the GET request. -
ERROR - An error was generated when the GET request was sent.
-
READY - The results associated with the
chunkingIdare available and ready to be retrieved. -
RETRIEVED - The results associated with the
chunkingIdare returned successfully when the GET request was sent.
Example:
"SUBMITTED"
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