[PredictionServiceClient] Bug in embedContent and EmbedContentRequest: Invalid model/endpoint mappings causing INVALID_ARGUMENT or undefined method errors

Start by tracing PredictionServiceClient::embedContent() and EmbedContentRequest through the google.cloud.aiplatform.v1 PredictionService/EmbedContent RPC bindings. Reproduce the model and endpoint cases from the issue, then verify that the request maps successfully and returns an EmbedContentResponse without the oneof, URI-template, or undefined-method errors.

When attempting to use PredictionServiceClient::embedContent() with the newer EmbedContentRequest class, the underlying gRPC bindings fail to resolve the model or endpoint correctly. This makes it impossible to use the native text-embedding endpoints via the official PHP SDK.

Steps to reproduce:
If we try to construct the request by setting the model using setModel():

use Google\Cloud\AIPlatform\V1\Client\PredictionServiceClient;
use Google\Cloud\AIPlatform\V1\EmbedContentRequest;
use Google\Cloud\AIPlatform\V1\Content;
use Google\Cloud\AIPlatform\V1\Part;
 
$client = new PredictionServiceClient([
    'apiEndpoint' => 'us-central1-aiplatform.googleapis.com',
    'credentials' => '/path/to/credentials.json'
]);
 
$content = (new Content())->setParts([(new Part())->setText('Hello world')]);
 
$req = new EmbedContentRequest();
$req->setModel('projects/MY_PROJECT/locations/us-central1/publishers/google/models/text-embedding-004');
$req->setContent($content);
 
$res = $client->embedContent($req);

Actual Result: An ApiException is thrown from the backend:

{
    "message": "Invalid value (oneof), oneof field '_model' is already set. Cannot set 'model'",
    "code": 3,
    "status": "INVALID_ARGUMENT",
    "details": [ ... ]
}

If we try to supply an endpoint via the $optionalArgs to bypass the model binding:

$res = $client->embedContent($req, [
    'endpoint' => 'projects/MY_PROJECT/locations/us-central1/publishers/google/models/text-embedding-004'
]);

Actual Result:

Google\ApiCore\ValidationException: Could not map bindings for google.cloud.aiplatform.v1.PredictionService/EmbedContent to any Uri template.

If we attempt to use setEndpoint() on the request object itself (which is available on PredictRequest but seems to be missing here):

$req->setEndpoint('projects/MY_PROJECT/locations/us-central1/publishers/google/models/text-embedding-004');

Actual Result:

Fatal error: Call to undefined method Google\Cloud\AIPlatform\V1\EmbedContentRequest::setEndpoint()

Expected Result:
The EmbedContentRequest should properly bind the model parameter to the gRPC URI template (e.g. /v1/{model=projects//locations//publishers//models/}:embedContent) without throwing a protobuf oneof conflict (_model vs model), and should successfully return the EmbedContentResponse.

Workaround (for others facing this issue):

Currently, the only way to get embeddings via PHP is to bypass EmbedContentRequest and use the older PredictRequest with raw Protobuf Structs:

$instanceValue = new \Google\Protobuf\Value();
$struct = new \Google\Protobuf\Struct();
$struct->setFields(['content' => (new \Google\Protobuf\Value())->setStringValue('Hello World')]);
$instanceValue->setStructValue($struct);
 
$request = (new PredictRequest())
    ->setEndpoint('projects/MY_PROJECT/locations/us-central1/publishers/google/models/text-embedding-004')
    ->setInstances([$instanceValue]);
 
$response = $client->predict($request);

Environment details:
OS: Linux
PHP version: 8.0+
Package name and version: google/cloud-ai-platform (Tested on versions ^1.13.0 up to 1.60.1)