Grouping and ungrouping search results
Grouping and ungrouping refer to the process of organizing the results of a search request in a specific way. The platform allows for grouping based on the unique identifiers of the videos. For example, this is useful when building a user interface, because it allows your users to better understand and navigate the search results. On the other hand, ungrouping presents your search results in a flat list. This is useful if you want to view all of the search results in a simple manner. Note that this feature can only be used with simple queries.
To group or ungroup items in a response, use the group_by
parameter, specifying one of the following values:
video
: The platform will group the matching video clips in the response by video.clip
: The matching video clips in the response will not be grouped.
Note
The
group_by
parameter is optional and its default value isclip
. If omitted, the platform will use the default value. For clarity, the examples in this section always specify thegroup_by
parameter.
For a description of each field in the request and response, see the API Reference> Make any-to-video search requests page.
Prerequisites
- You're familiar with the concepts that are described on the Platform overview page.
- You've already created an index, and the Marengo video understanding engine is enabled for this index.
- You've already uploaded a video, and the platform has finished indexing it.
Examples
Grouping items in a response
The following example code groups the matching video clips in the response by video:
from twelvelabs import TwelveLabs
client = TwelveLabs(api_key="<YOUR_API_KEY>")
search_results = client.search.query(
index_id="<YOUR_INDEX_ID>,
query_text="<YOUR_QUERY>,
options=["visual"],
group_by="video"
)
# Utility function to print a specific page
def print_page(page):
for video in page:
print(f"Video id: {video.id}")
for clip in video.clips:
print(clip)
print(
f"\tscore={clip.score} start={clip.start} end={clip.end} confidence={clip.confidence} metadata={clip.metadata}"
)
print_page(search_results.data)
while True:
try:
print_page(next(search_results))
except StopIteration:
break
import { TwelveLabs, GroupByVideoSearchData } from 'twelvelabs-js';
const client = new TwelveLabs({ apiKey: '<YOUR_API_KEY>'});
let searchResults = await client.search.query({
indexId: '<YOUR_INDEX_ID>'
queryText: '<YOUR_QUERY>',
options: ['visual'],
groupBy: 'video',
});
printPage(searchResults);
while (true) {
const page = await searchResults.next();
if (page === null) break;
else printPage(page);
}
// Utility function to print a specific page
function printPage(searchData) {
(searchData.data as GroupByVideoSearchData[]).forEach((video) => {
console.log(`videoId=${video.id}`);
video.clips?.forEach((clip) => {
console.log(
` score=${clip.score} start=${clip.start} end=${clip.end} confidence=${clip.confidence}`,
);
});
});
}
The output should look similar to the following one:
Video id: 65d60bcf48db9fa780cb415e
score=83.73 start=273.96875 end=289.0625 video_id='65d60bcf48db9fa780cb415e' metadata=[{'type': 'visual'}] confidence='high'
score=83.73 start=273.96875 end=289.0625 confidence=high metadata=[{'type': 'visual'}]
score=83.55 start=397.921875 end=439.84375 video_id='65d60bcf48db9fa780cb415e' metadata=[{'type': 'visual'}] confidence='high'
score=83.55 start=397.921875 end=439.84375 confidence=high metadata=[{'type': 'visual'}]
score=83.46 start=294.5625 end=311.84375 video_id='65d60bcf48db9fa780cb415e' metadata=[{'type': 'visual'}] confidence='high'
Video id: 65d5fbad48db9fa780cb415c
score=83.36 start=342.6875 end=353.140625 video_id='65d5fbad48db9fa780cb415c' metadata=[{'type': 'visual'}] confidence='high' thumbnail_url=None module_confidence=None
score=83.36 start=342.6875 end=353.140625 confidence=high metadata=[{'type': 'visual'}]
score=83.32 start=164.671875 end=200.71875 video_id='65d5fbad48db9fa780cb415c' metadata=[{'type': 'visual'}] confidence='high' thumbnail_url=None module_confidence=None
score=83.32 start=164.671875 end=200.71875 confidence=high metadata=[{'type': 'visual'}]
score=83.31 start=329.96875 end=337.75 video_id='65d5fbad48db9fa780cb415c' metadata=[{'type': 'visual'}] confidence='high' thumbnail_url=None module_confidence=None
score=83.31 start=329.96875 end=337.75 confidence=high metadata=[{'type': 'visual'}]
In this example, note that the data
array contains a list of objects. Each object corresponds to a video that matches your query and is composed of the following key-value pairs:
clips
: An array that groups the information about all the matching video clips in that video.id
: The unique identifier of the video that matched your query.
Ungrouping items in a response
The following example performs a search request, and the matching video clips in the response are not grouped:
from twelvelabs import TwelveLabs
client = TwelveLabs(api_key="<YOUR_API_KEY>")
search_results = client.search.query(
index_id="<YOUR_INDEX_ID>",
query_text= "<YOUR_QUERY>"
options=["visual"],
group_by='clip'
)
# Utility function to print a specific page
def print_page(page):
for clip in page:
print(
f" video_id={clip.video_id} score={clip.score} start={clip.start} end={clip.end} confidence={clip.confidence} metadata={clip.metadata}"
)
print_page(search_results.data)
while True:
try:
print_page(next(search_results))
except StopIteration:
break
import { TwelveLabs, SearchData } from 'twelvelabs-js';
const client = new TwelveLabs({ apiKey: '<YOUR_API_KEY>'});
let searchResults = await client.search.query({
indexId: '<YOUR_INDEX_ID>'
queryText: '<YOUR_QUERY>',
options: ['visual'],
group_by='clip',
});
printPage(searchResults.data);
while (true) {
const page = await searchResults.next();
if (page === null) break;
else printPage(page);
}
// Utility function to print a specific page
function printPage(searchData) {
(searchData as SearchData[]).forEach((clip) => {
console.log(
`video_id= ${clip.videoId} score=${clip.score} start=${clip.start} end=${clip.end} confidence=${clip.confidence} metadata=${JSON.stringify(clip.metadata)}`,
);
});
}
The output should look similar to the following one:
video_id=65d6131c48db9fa780cb415f score=52.04 start=4.5625 end=14.8125 confidence=low metadata=[{'type': 'visual'}]
video_id=65d6131c48db9fa780cb415f score=50.94 start=20.9375 end=25.09375 confidence=low metadata=[{'type': 'visual'}]
video_id=65d60bcf48db9fa780cb415e score=50.94 start=20.9375 end=25.09375 confidence=low metadata=[{'type': 'visual'}]
Updated 28 days ago