When choosing an AI writing API, you need to examine stability, price, function matching and whether there is a free trial; 2. PHP uses Guzzle to send POST requests and uses json_decode to process the returned JSON data, paying attention to capturing exceptions and error codes; 3. To integrate AI content into the project, you need to establish an audit mechanism and support personalized customization; 4. Cache, asynchronous queue and current limiting technology can be used to optimize performance to avoid bottlenecks due to high concurrency.

The core of PHP calls AI writing auxiliary tools is to use the API interface to allow your PHP program to "conversate" with AI writing tools, thereby realizing functions such as automatic content generation, polishing articles, and improving content output efficiency.

Use API docking to give PHP projects AI writing skills.

How to choose the right AI writing assistive tool API?

Choosing an API is like choosing a partner, it depends on the reliability and matching. First, examine the stability of the API and avoid bugs every few days to affect the user experience. Secondly, look at the price and don’t exceed the budget. More importantly, it depends on whether the functions meet the needs, such as whether they support Chinese and whether they can generate articles of a specific style. I personally prefer those APIs that provide free trial limits. You can try it first before deciding whether to pay.

How does PHP send API requests and process return data?

PHP sends API requests, cURL is a common tool, just like a Swiss army knife, which can do anything. But Guzzle HTTP Client is more elegant, with more concise code, and more in line with the style of modern PHP development. The data returned by the API is usually in JSON format. The json_decode() function can turn it into a PHP array or object to facilitate you to extract information. Pay attention to handling the error codes returned by the API, such as request frequency exceeding the limit, parameter errors, etc., and do fault tolerance to make the program more robust.

 // Use Guzzle HTTP Client
use GuzzleHttp\Client;

$client = new Client();
try {
    $response = $client->post('https://api.example.com/ai-writing', [
        'headers' => [
            'Authorization' => 'Bearer YOUR_API_KEY',
            'Content-Type' => 'application/json',
        ],
        'json' => [
            'prompt' => 'Writing an article about PHP',
            'length' => 500,
        ],
    ]);

    $statusCode = $response->getStatusCode();
    $body = $response->getBody();

    if ($statusCode == 200) {
        $data = json_decode($body, true);
        echo $data['content']; // Output content generated by AI} else {
        echo "API request failed, status code: ". $statusCode;
    }

} catch (\Exception $e) {
    echo "Exception occurred:" . $e->getMessage();
}

How to incorporate AI-generated content into existing PHP projects?

This is the real challenge. It is definitely not possible to throw the content generated by AI to the user directly. You have to review it first to see if there are sensitive words and logical errors. It is possible to consider establishing a content audit mechanism, combining manual audit and machine audit. In addition, the content generated by AI can be customized according to user portraits, such as adjusting the tone and style of the article to make the content more in line with user needs.

How to optimize API calls to avoid performance bottlenecks?

API calls are time-consuming, especially in high concurrency scenarios. You can consider using caching technology to cache the data returned by the API and read it directly from the cache next time to reduce the number of API calls. In addition, you can use an asynchronous task queue to put API calls into the background to execute to avoid blocking the main thread. It can also limit the current flow of API requests to prevent API services from being overwhelmed.

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