tenor

Description:

tenor

Tenor #

















Fetch, Search GIF more easily and customised manner from Tenor #
This library is MIT licensed, which means you can use it anywhere without any consent from justkawal, because we believe in Open-Source #
Table of Contents #

Installing
Usage
Upcoming Features

Lets Get Started #
1. Depend on it #
Add this to your package's pubspec.yaml file:
dependencies:
tenor:
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2. Install it #
You can install packages from the command line:
with pub:
$ pub get
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with Flutter:
$ flutter packages get
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3. Import it #
Now in your Dart code, you can use:
import 'package:tenor/tenor.dart';
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Usage #
Initialize Tenor #
Initialize Tenor library
Tenor tenor = Tenor(apiKey: 'ApiKey', language: TenorLanguage.English);
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Select the Language Codes #
TenorLanguage provides codes for different ISO 639-1 language code
var englishCode = TenorLanguage.English;

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Fetch Trending GIF #
Returns response containing a list of the current global trending GIFs. The trending stream is updated regularly throughout the day.
Important: limit: 1 <= limit <= 50
// Future<TenorResponse?> requestTrendingGIF({
// int limit = 20,
// ContentFilter contentFilter = ContentFilter.off,
// GifSize size = GifSize.all,
// MediaFilter mediaFilter = MediaFilter.minimal,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// fetch trending Gif
TenorResponse? res = await tenor.requestTrendingGIF(limit: 5);
res?.results.forEach((TenorResult tenorResult) {
var title = tenorResult.title;
var media = tenorResult.media;
print('$title: gif : ${media?.gif?.previewUrl?.toString()}');
});
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Search GIF #
Returns response containing a list of the searched Gif from Tenor.
Important: limit: 1 <= limit <= 50
// Future<TenorResponse?> searchGIF(
// String search, {
// int limit = 20,
// ContentFilter contentFilter = ContentFilter.off,
// GifSize size = GifSize.all,
// MediaFilter mediaFilter = MediaFilter.minimal,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// search Gif
TenorResponse? res = await tenor.searchGIF('universe', limit: 5);
res?.results.forEach((TenorResult tenorResult) {
var title = tenorResult.title;
var media = tenorResult.media;
print('$title: gif : ${media?.gif?.previewUrl?.toString()}');
});
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Fetch Random GIF #
Get a randomized list of GIFs for a given search term. This differs from the search function which returns a rank ordered list of GIFs for a given search term.
Important: limit: 1 <= limit <= 50
// Future<TenorResponse?> randomGIF(
// String search, {
// int limit = 20,
// ContentFilter contentFilter = ContentFilter.off,
// GifSize size = GifSize.all,
// MediaFilter mediaFilter = MediaFilter.minimal,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// random Gif
TenorResponse? res = await tenor.randomGIF('universe', limit: 5);
res?.results.forEach((TenorResult tenorResult) {
var title = tenorResult.title;
var media = tenorResult.media;
print('$title: gif : ${media?.gif?.previewUrl?.toString()}');
});
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Search Suggestions #
Search suggestions helps a user narrow their search or discover related search terms to find a more precise GIF. Results are returned in order of what is most likely to drive a share for a given term, based on historic user search and share behavior.
Important: limit: 1 <= limit <= 50
// Future<List<String>> searchSuggestions(
// String search, {
// int limit = 20,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// suggestions
List<String> suggestions = await tenor.searchSuggestions('universe', limit: 5);
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Trending search #
Returns response containing a list of the current trending search terms. The list is updated Hourly by Tenor’s AI.
Important: limit: 1 <= limit <= 50
// Future<List<String>> trendingSearch(
// int limit = 20,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// trending search results
List<String> suggestions = await tenor.trendingSearch(limit: 5);
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Auto complete #
Returns response containing a list of completed search terms given a partial search term. The list is sorted by Tenor’s AI and the number of results will decrease as Tenor’s AI becomes more certain.
Important: limit: 1 <= limit <= 50
// Future<List<String>> autoComplete(
// String search, {
// int limit = 20,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// auto complete results
List<String> autoCompleted = await tenor.autoComplete('un', limit: 5);
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Fetching Categories #
Requests Categories from tenor
// Future<List<TenorCategories?>> requestCategories({
// ContentFilter contentFilter = ContentFilter.off,
// CategoryType categoryType = CategoryType.featured,
// })

Tenor tenor = Tenor(apiKey: 'Tenor Api');

// list of categories
List<TenorCategories?> categories = await tenor.requestCategories();
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Fetching Options #



key
description




limit
eg. limit the number of GIF to be fetched. limit can vary from 1 to 50


contentFilter
(values: off, low, medium, high) specify the content safety filter level. eg. contentFilter: ContentFilter.low


mediaFilter
(values: basic, minimal) Reduce the Number of GIF formats returned in response. minimal- (tinygif, gif, and mp4). basic- (nanomp4, tinygif, tinymp4, gif, mp4, and nanogif) eg. mediaFilter: MediaFilter.minimal


size
GIFs with aspect ratios that fit with in the selected range. values: (all, wide, standard), all - no constraints, wide - 0.42 <= aspect ratio <= 2.36, standard - .56 <= aspect ratio <= 1.78



Fetch Next Set of GIF Response #
fetchNext() is used to get next set of response for the current query
// Future<TenorResponse?> fetchNext({int limit = 20});

// here the fetchNext function is used to call next set of GIF which is sequenced after current response

TenorResponse? firstSetResponse = await tenor. /*.... Functions used to get TenorResponse? ....*/

TenorResponse? nextResult = await firstSetResponse?.fetchNext();

nextResult?.results.forEach((tenorResult) {
var title = tenorResult.title;
var media = tenorResult.media;
print('$title: gif : ${media?.gif?.previewUrl?.toString()}');
});
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Fetching Next Options #



key
description




limit
eg. limit the number of GIF to be fetched. limit can vary from 1 to 50



Donate #

A Mac M1 would be sufficient. 😆
Paypal: https://paypal.me/kawal7415

What's next ? 🤔 #

We are thinking what we should give next after giving all these features. ( Your donation would help me to collect money to buy Mac M1 for faster work. )
If you have any new feature request then go ahead and ping me, I'll integrate it.