Here’s a tutorial on how to use Text completion from OpenAI with Flutter. This tutorial assumes that you already have some familiarity with Flutter and have set up your development environment.
Requirements
Before we get started, you’ll need to create an OpenAI API key to access the Text completion API. You can sign up for an account and create an API key on the OpenAI website.
Once you have your API key, you’ll also need to install the http
package in your Flutter project. You can do this by adding the following line to your project’s pubspec.yaml
file:
dependencies:
http:
You’ll also need to import the http
package in any files where you want to use the Text completion API.
Example
Let’s say you want to build a simple app that allows users to generate a text description of a photo. You can use the Text completion API to generate a sentence or two describing the photo.
Here’s an example of how you might implement this in Flutter:
import 'dart:convert';
import 'package:http/http.dart' as http;
class TextCompletionApi {
static const apiKey = 'YOUR_API_KEY_HERE';
static const endpoint = 'https://api.openai.com/v1/completions';
static Future<String> generateDescription(String photoUrl) async {
final prompt = 'Describe the photo in one or two sentences:';
final headers = {'Authorization': 'Bearer $apiKey', 'Content-Type': 'application/json'};
final data = {
'prompt': prompt,
'max_tokens': 32,
'temperature': 0.5,
'model': 'text-davinci-002',
'prompt': photoUrl,
};
final response = await http.post(Uri.parse(endpoint), headers: headers, body: jsonEncode(data));
final json = jsonDecode(response.body);
final choices = json['choices'] as List;
if (choices.isNotEmpty) {
return choices[0]['text'] as String;
} else {
throw Exception('No completions found');
}
}
}
class MyHomePage extends StatelessWidget {
final TextEditingController _textEditingController = TextEditingController();
@override
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(
title: Text('Photo Description Generator'),
),
body: Column(
children: [
TextField(
controller: _textEditingController,
decoration: InputDecoration(
hintText: 'Enter a photo URL',
),
),
ElevatedButton(
onPressed: () async {
final photoUrl = _textEditingController.text;
final description = await TextCompletionApi.generateDescription(photoUrl);
ScaffoldMessenger.of(context).showSnackBar(SnackBar(content: Text(description)));
},
child: Text('Generate Description'),
),
],
),
);
}
}
In this example, we define a TextCompletionApi
class that encapsulates the logic for generating descriptions using the Text completion API. The generateDescription
method takes a photo URL as input, sends a request to the API to generate a description, and returns the resulting text.
We then use this class in a simple Flutter app with a TextField
for entering a photo URL and a button for generating a description. When the button is pressed, we call the generateDescription
method and display the resulting description in a SnackBar
.
More: Text completion in OpenAI. What is this? What is text completion used for?
Explanation
Let’s go through the code in more detail.
class TextCompletionApi
Here, we define a TextCompletionApi
class that provides a static method generateDescription
for generating descriptions using the Text completion API.
The apiKey
and endpoint
constants are used to store the API key and the API endpoint URL, respectively.
The generateDescription
method takes a photoUrl
parameter, which is the URL of the photo to generate a description for. It sends a POST request to the API with the following parameters:
prompt
: The prompt to provide to the API, which in this case is “Describe the photo in one or two sentences:”max_tokens
: The maximum number of tokens to generate (i.e., the length of the text)temperature
: The “creativity” of the generated text, with higher values leading to more unpredictable textmodel
: The name of the language model to use (in this case, “text-davinci-002”)prompt
: The photo URL to use as the prompt for the generated text
After sending the request, the method parses the response JSON and returns the generated text.
MyHomePage class
In this class, we define a MyHomePage
widget that displays a TextField
and a button for generating descriptions.
The TextField
is controlled by a TextEditingController
, which allows us to access the text entered by the user.
When the button is pressed, we call the generateDescription
method of the TextCompletionApi
class with the photo URL entered by the user. We then display the resulting description in a SnackBar
.
Conclusion
In this tutorial, we went over how to use Text completion from OpenAI with Flutter to generate text descriptions based on a prompt. We covered the requirements, provided a specific example, and explained the code in detail. You can use this as a starting point for building your own apps that leverage the power of OpenAI’s language models!