OpenAI’s Text Completion API is a tool that helps developers generate text automatically based on a given prompt. The API uses machine learning to analyze and understand the prompt, then generates a completion that is grammatically correct, coherent, and consistent with the context.
Here are some advanced examples of using Text completion with Flutter:
Autocomplete text field with OpenAI
One use case for Text completion in Flutter is to implement an autocomplete text field. In this scenario, you can use OpenAI’s Text completion API to suggest possible completions for a partially typed text. To do this, you can use the Completion endpoint of the OpenAI API, which takes a prompt and returns a list of completions.
Here’s an example of how to implement an autocomplete text field with OpenAI:
import 'package:flutter/material.dart';
import 'package:http/http.dart' as http;
import 'dart:convert';
const openaiApiKey = 'YOUR_API_KEY_HERE';
class AutocompleteTextField extends StatefulWidget {
final Function(String) onSelected;
AutocompleteTextField({required this.onSelected});
@override
_AutocompleteTextFieldState createState() => _AutocompleteTextFieldState();
}
class _AutocompleteTextFieldState extends State<AutocompleteTextField> {
final TextEditingController _controller = TextEditingController();
List<String> _suggestions = [];
@override
Widget build(BuildContext context) {
return TextField(
controller: _controller,
onChanged: _onTextChanged,
decoration: InputDecoration(
hintText: 'Type something',
),
keyboardType: TextInputType.text,
textCapitalization: TextCapitalization.sentences,
);
}
void _onTextChanged(String text) async {
if (text.isEmpty) {
setState(() {
_suggestions.clear();
});
return;
}
final response = await http.post(
Uri.parse('https://api.openai.com/v1/completions'),
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer $openaiApiKey'
},
body: jsonEncode({
'prompt': '$text\n',
'max_tokens': 5,
'temperature': 0.5,
'n': 1,
'stop': ['\n']}),
);
if (response.statusCode == 200) {
final data = jsonDecode(response.body);
final completions = data['choices'] as List<dynamic>;
final suggestions = completions.map((c) => c['text']).toList();
setState(() {
_suggestions = suggestions;
});
} else {
setState(() {
_suggestions.clear();
});
}
}
}
In this example, we create a custom TextField widget called AutocompleteTextField that takes a Function(String) callback called onSelected that is called when a suggestion is selected. The AutocompleteTextField widget listens to changes in the text using the onChanged callback, and uses the http package to make a POST request to the OpenAI API’s Completion endpoint to get the suggestions for the current text. The response from the API is then parsed and the suggestions are stored in the _suggestions list, which is used to display the suggestions in a dropdown list below the text field.
Smart Reply feature with OpenAI
Another use case for Text completion in Flutter is to implement a Smart Reply feature. This feature can be used in messaging apps to suggest possible responses based on the incoming message. To implement this feature, you can use OpenAI’s Text completion API to generate possible responses.
Here’s an example of how to implement a Smart Reply feature with OpenAI:
import 'dart:convert';
import 'package:flutter/material.dart';
import 'package:http/http.dart' as http;
class SmartReply extends StatefulWidget {
final String message;
const SmartReply({required this.message, Key? key}) : super(key: key);
@override
_SmartReplyState createState() => _SmartReplyState();
}
class _SmartReplyState extends State<SmartReply> {
String _suggestion = '';
@override
void initState() {
super.initState();
_getSuggestion();
}
void _getSuggestion() async {
final openaiApiKey = 'YOUR_API_KEY';
final response = await http.post(
Uri.parse('https://api.openai.com/v1/completions'),
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer $openaiApiKey'
},
body: jsonEncode({
'prompt': 'Q: ${widget.message}\nA:',
'max_tokens': 10,
'temperature': 0.5,
'n': 1,
'stop': ['\n']
}),
);
if (response.statusCode == 200) {
final data = jsonDecode(response.body);
final completions = data['choices'] as List<dynamic>;
final suggestion = completions[0]['text'] as String;
setState(() {
_suggestion = suggestion;
});
} else {
setState(() {
_suggestion = '';
});
}
}
@override
Widget build(BuildContext context) {
return Text(_suggestion);
}
}
In this example, we define a custom SmartReply widget that takes a String called message as input, which represents the message to which we want to suggest a reply. The SmartReply widget uses the http package to make a POST request to the OpenAI API’s Completion endpoint to generate a suggestion for the message.
The POST request includes several parameters that configure the behavior of the API, such as the max_tokens parameter, which controls the maximum number of tokens in the suggestion, and the temperature parameter, which controls the randomness of the generated text. The stop parameter is set to ['\n'], which tells the API to stop generating text after a newline character is encountered.
Once the API response is received, we parse the response and extract the suggestion from the choices field of the response. The suggestion is then stored in the _suggestion variable and displayed in a Text widget.
More:
- Text completion in OpenAI. What is this? What is text completion used for?
- OpenAI in Flutter: How to use Text completion to create automatic image descriptions?
Overall, these examples demonstrate how you can use OpenAI’s Text completion API to implement advanced features in your Flutter applications, such as autocomplete text fields and smart reply features. With these tools, you can improve the user experience of your applications and provide more intelligent and responsive interfaces.
