Sanitizzare prompt e risposte

Questa pagina descrive in dettaglio come sanificare i prompt e le risposte. Model Armor offre un insieme di filtri per proteggere le tue applicazioni di AI. Model Armor controlla i prompt e le risposte in base ai livelli di confidenza di screening configurati.

Prima di iniziare

Crea un modello seguendo le istruzioni riportate in Creare modelli.

Ottenere le autorizzazioni richieste

Per ottenere le autorizzazioni necessarie per sanificare i prompt e le risposte, chiedi all'amministratore di concederti i seguenti ruoli IAM su Model Armor:

Per ulteriori informazioni sulla concessione dei ruoli, consulta Gestisci l'accesso a progetti, cartelle e organizzazioni.

Potresti anche riuscire a ottenere le autorizzazioni richieste tramite i ruoli personalizzati o altri ruoli predefiniti.

Abilita API

Prima di poter utilizzare Model Armor, devi abilitare le API Model Armor.

Console

  1. Enable the Model Armor API.

    Roles required to enable APIs

    To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

    Enable the API

  2. Seleziona il progetto in cui vuoi attivare Model Armor.

gcloud

Prima di iniziare, segui questi passaggi utilizzando Google Cloud CLI con l'API Model Armor:

  1. In the Google Cloud console, activate Cloud Shell.

    Activate Cloud Shell

    At the bottom of the Google Cloud console, a Cloud Shell session starts and displays a command-line prompt. Cloud Shell is a shell environment with the Google Cloud CLI already installed and with values already set for your current project. It can take a few seconds for the session to initialize.

  2. Esegui questo comando per impostare l'endpoint API per il servizio Model Armor.

    gcloud config set api_endpoint_overrides/modelarmor "https://modelarmor.LOCATION.rep.googleapis.com/"

    Sostituisci LOCATION con la regione in cui vuoi utilizzare Model Armor.

    3. Esegui questo comando per attivare Model Armor.

      gcloud services enable modelarmor.googleapis.com --project=PROJECT_ID

    Sostituisci PROJECT_ID con l'ID del progetto.

    Nel progetto contenente il modello Sensitive Data Protection, concedi il ruolo Utente DLP (roles/dlp.user) e il ruolo Lettore DLP (roles/dlp.reader) all'agente di servizio creato nell'ambito del passaggio di protezione avanzata dei dati sensibili di Crea modelli. Salta questo passaggio se il modello Sensitive Data Protection si trova nello stesso progetto del modello Model Armor.

    gcloud projects add-iam-policy-binding SDP_PROJECT_ID \
    --member=serviceAccount:service-PROJECT_NUMBER@gcp-sa-modelarmor.iam.gserviceaccount.com --role=roles/dlp.user

gcloud projects add-iam-policy-binding SDP_PROJECT_ID \
    --member=serviceAccount:service-PROJECT_NUMBER@gcp-sa-modelarmor.iam.gserviceaccount.com --role=roles/dlp.reader

    Sostituisci quanto segue:

    • SDP_PROJECT_ID: l'ID del progetto a cui appartiene il modello avanzato di Sensitive Data Protection.
    • PROJECT_NUMBER: il numero del progetto a cui appartiene il modello.

    Pulire i prompt

    Sanitizza i prompt per impedire input dannosi e contribuire a garantire che vengano inviati prompt sicuri e appropriati ai tuoi LLM.

    Prompt di testo

    Model Armor sanifica i prompt di testo analizzando il testo e applicando diversi filtri per identificare e mitigare potenziali minacce.

    REST

    Utilizza il seguente comando per sanificare un prompt di testo in Model Armor.

      curl -X POST \
      -d '{"userPromptData":{"text":"[UNSAFE TEXT]"}}' \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $(gcloud auth print-access-token)" \
      "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeUserPrompt"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto per il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Il risultato è la seguente risposta. Tieni presente che MATCH_FOUND rientra nella categoria Contenuti dannosi.

      {
  "sanitizationResult": {
    "filterMatchState": "MATCH_FOUND",
    "invocationResult": "SUCCESS",
    "filterResults": {
      "csam": {
        "csamFilterFilterResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "NO_MATCH_FOUND"
        }
      },
      "malicious_uris": {
        "maliciousUriFilterResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "NO_MATCH_FOUND"
        }
      },
      "rai": {
        "raiFilterResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "MATCH_FOUND",
          "raiFilterTypeResults": {
            "sexually_explicit": {
              "matchState": "NO_MATCH_FOUND"
            },
            "hate_speech": {
              "matchState": "NO_MATCH_FOUND"
            },
            "harassment": {
              "matchState": "NO_MATCH_FOUND"
            },
            "dangerous": {
              "matchState": "MATCH_FOUND"
            }
          }
        }
      },
      "pi_and_jailbreak": {
        "piAndJailbreakFilterResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "MATCH_FOUND"
        }
      },
      "sdp": {
        "sdpFilterResult": {
          "inspectResult": {
            "executionState": "EXECUTION_SUCCESS",
            "matchState": "NO_MATCH_FOUND"
          }
        }
      }
    }
  }
  }

    Vai

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Go e installare l'SDK Model Armor Go.

    
import (
	"context"
	"fmt"
	"io"

	modelarmor "cloud.google.com/go/modelarmor/apiv1"
	modelarmorpb "cloud.google.com/go/modelarmor/apiv1/modelarmorpb"
	"google.golang.org/api/option"
)

// sanitizeUserPrompt sanitizes a user prompt based on the project, location, and template settings.
//
// w io.Writer: The writer to use for logging.
// projectID string: The ID of the project.
// locationID string: The ID of the location.
// templateID string: The ID of the template.
// userPrompt string: The user prompt to sanitize.
func sanitizeUserPrompt(w io.Writer, projectID, locationID, templateID, userPrompt string) error {
	ctx := context.Background()

	//Create options for Model Armor client.
	opts := option.WithEndpoint(fmt.Sprintf("modelarmor.%s.rep.googleapis.com:443", locationID))

	// Create the Model Armor client.
	client, err := modelarmor.NewClient(ctx, opts)
	if err != nil {
		return fmt.Errorf("failed to create client for location %s: %w", locationID, err)
	}
	defer client.Close()

	// Initialize request argument(s)
	userPromptData := &modelarmorpb.DataItem{
		DataItem: &modelarmorpb.DataItem_Text{
			Text: userPrompt,
		},
	}

	// Prepare request for sanitizing user prompt.
	req := &modelarmorpb.SanitizeUserPromptRequest{
		Name:           fmt.Sprintf("projects/%s/locations/%s/templates/%s", projectID, locationID, templateID),
		UserPromptData: userPromptData,
	}

	// Sanitize the user prompt.
	response, err := client.SanitizeUserPrompt(ctx, req)
	if err != nil {
		return fmt.Errorf("failed to sanitize user prompt for template %s: %w", templateID, err)
	}

	// Sanitization Result.
	fmt.Fprintf(w, "Sanitization Result: %v\n", response)

	return nil
}

    Java

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Java e installare l'SDK Java Model Armor.

    
import com.google.cloud.modelarmor.v1.DataItem;
import com.google.cloud.modelarmor.v1.ModelArmorClient;
import com.google.cloud.modelarmor.v1.ModelArmorSettings;
import com.google.cloud.modelarmor.v1.SanitizeUserPromptRequest;
import com.google.cloud.modelarmor.v1.SanitizeUserPromptResponse;
import com.google.cloud.modelarmor.v1.TemplateName;
import com.google.protobuf.util.JsonFormat;
import java.io.IOException;

public class SanitizeUserPrompt {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.

    // Specify the Google Project ID.
    String projectId = "your-project-id";
    // Specify the location ID. For example, us-central1.
    String locationId = "your-location-id";
    // Specify the template ID.
    String templateId = "your-template-id";
    // Specify the user prompt.
    String userPrompt = "Unsafe user prompt";

    sanitizeUserPrompt(projectId, locationId, templateId, userPrompt);
  }

  public static SanitizeUserPromptResponse sanitizeUserPrompt(String projectId, String locationId,
      String templateId, String userPrompt) throws IOException {

    // Endpoint to call the Model Armor server.
    String apiEndpoint = String.format("modelarmor.%s.rep.googleapis.com:443", locationId);
    ModelArmorSettings modelArmorSettings = ModelArmorSettings.newBuilder()
        .setEndpoint(apiEndpoint)
        .build();

    try (ModelArmorClient client = ModelArmorClient.create(modelArmorSettings)) {
      // Build the resource name of the template.
      String templateName = TemplateName.of(projectId, locationId, templateId).toString();

      // Prepare the request.
      SanitizeUserPromptRequest request = SanitizeUserPromptRequest.newBuilder()
          .setName(templateName)
          .setUserPromptData(DataItem.newBuilder().setText(userPrompt).build())
          .build();

      SanitizeUserPromptResponse response = client.sanitizeUserPrompt(request);
      System.out.println("Result for the provided user prompt: "
          + JsonFormat.printer().print(response.getSanitizationResult()));

      return response;
    }
  }
}

    Node.js

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Node.js e installare l'SDK Node.js di Model Armor.

    /**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = process.env.PROJECT_ID || 'your-project-id';
// const locationId = process.env.LOCATION_ID || 'us-central1';
// const templateId = process.env.TEMPLATE_ID || 'template-id';
// const userPrompt = 'unsafe user prompt';
const {ModelArmorClient} = require('@google-cloud/modelarmor').v1;

const client = new ModelArmorClient({
  apiEndpoint: `modelarmor.${locationId}.rep.googleapis.com`,
});

const request = {
  name: `projects/${projectId}/locations/${locationId}/templates/${templateId}`,
  userPromptData: {
    text: userPrompt,
  },
};

const [response] = await client.sanitizeUserPrompt(request);
console.log(JSON.stringify(response, null, 2));
return response;

    PHP

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo PHP e installare l'SDK PHP Model Armor.

    use Google\Cloud\ModelArmor\V1\Client\ModelArmorClient;
use Google\Cloud\ModelArmor\V1\SanitizeUserPromptRequest;
use Google\Cloud\ModelArmor\V1\DataItem;

/**
 * Sanitizes a user prompt using the specified template.
 *
 * @param string $projectId The ID of your Google Cloud Platform project (e.g. 'my-project').
 * @param string $locationId The ID of the location where the template is stored (e.g. 'us-central1').
 * @param string $templateId The ID of the template (e.g. 'my-template').
 * @param string $userPrompt The user prompt to sanitize (e.g. 'my-user-prompt').
 */
function sanitize_user_prompt(
    string $projectId,
    string $locationId,
    string $templateId,
    string $userPrompt
): void {
    $options = ['apiEndpoint' => "modelarmor.$locationId.rep.googleapis.com"];
    $client = new ModelArmorClient($options);

    $userPromptRequest = (new SanitizeUserPromptRequest())
        ->setName("projects/$projectId/locations/$locationId/templates/$templateId")
        ->setUserPromptData((new DataItem())->setText($userPrompt));

    $response = $client->sanitizeUserPrompt($userPromptRequest);

    printf('Result for Sanitize User Prompt: %s' . PHP_EOL, $response->serializeToJsonString());
}

    Python

    Per eseguire questo codice, configura un ambiente di sviluppo Python e installa l'SDK Python di Model Armor.

    
from google.api_core.client_options import ClientOptions
from google.cloud import modelarmor_v1

# TODO(Developer): Uncomment these variables.
# project_id = "YOUR_PROJECT_ID"
# location_id = "us-central1"
# template_id = "template_id"
# user_prompt = "Prompt entered by the user"

# Create the Model Armor client.
client = modelarmor_v1.ModelArmorClient(
    transport="rest",
    client_options=ClientOptions(
        api_endpoint=f"modelarmor.{location_id}.rep.googleapis.com"
    ),
)

# Initialize request argument(s).
user_prompt_data = modelarmor_v1.DataItem(text=user_prompt)

# Prepare request for sanitizing the defined prompt.
request = modelarmor_v1.SanitizeUserPromptRequest(
    name=f"projects/{project_id}/locations/{location_id}/templates/{template_id}",
    user_prompt_data=user_prompt_data,
)

# Sanitize the user prompt.
response = client.sanitize_user_prompt(request=request)

# Sanitization Result.
print(response)

    Il risultato è la seguente risposta.

      sanitization_result {
    filter_match_state: MATCH_FOUND
    filter_results {
      key: "rai"
      value {
        rai_filter_result {
          execution_state: EXECUTION_SUCCESS
          match_state: MATCH_FOUND
          rai_filter_type_results {
            key: "dangerous"
            value {
              confidence_level: HIGH
              match_state: MATCH_FOUND
            }
          }
        }
      }
    }
    filter_results {
      key: "pi_and_jailbreak"
      value {
        pi_and_jailbreak_filter_result {
          execution_state: EXECUTION_SUCCESS
          match_state: MATCH_FOUND
          confidence_level: HIGH
        }
      }
    }
    filter_results {
      key: "malicious_uris"
      value {
        malicious_uri_filter_result {
          execution_state: EXECUTION_SUCCESS
          match_state: NO_MATCH_FOUND
        }
      }
    }
    filter_results {
      key: "csam"
      value {
        csam_filter_filter_result {
          execution_state: EXECUTION_SUCCESS
          match_state: NO_MATCH_FOUND
        }
      }
    }
    invocation_result: SUCCESS
  }

    Sanitizzare i prompt di testo con il rilevamento multilingue attivato

    Abilita il rilevamento multilingue su base per richiesta impostando il flag enableMultiLanguageDetection su true per ogni singola richiesta. Se vuoi, puoi specificare la lingua di origine per ottenere risultati più precisi. Se la lingua di origine non è specificata, viene rilevata automaticamente per fornire il supporto multilingue.

    Utilizza il seguente comando per sanificare un prompt di testo in Model Armor con il rilevamento multilingue abilitato a livello di richiesta.

    curl -X POST \
    -d  '{"userPromptData":{"text":"[UNSAFE TEXT]"}, "multiLanguageDetectionMetadata": { "enableMultiLanguageDetection": true , "sourceLanguage": "jp"}}' \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
       "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeUserPrompt"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto per il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Prompt basati su file

    Per sanificare un prompt archiviato in un file, fornisci i contenuti del file in formato base64. Model Armor non rileva automaticamente il tipo di file. Devi impostare esplicitamente il campo byteDataType per indicare il formato del file. Se il campo non è presente o non è specificato, la richiesta non va a buon fine. I valori possibili di byteDataType sono PLAINTEXT_UTF8, PDF, WORD_DOCUMENT, EXCEL_DOCUMENT, POWERPOINT_DOCUMENT, TXT e CSV.

    REST 

      curl -X POST \
      -d "$(jq -n \
      --arg data "$(base64 -w 0 -i sample.pdf)" \
      '{userPromptData: {byteItem: {byteDataType: "FILE_TYPE", byteData: $data}}}')" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $(gcloud auth print-access-token)" \
      "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeUserPrompt"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.
    • FILE_TYPE: il formato del file di input.

    Vai

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Go e installare l'SDK Model Armor Go.

    
import (
	"context"
	"fmt"
	"io"
	"os"

	modelarmor "cloud.google.com/go/modelarmor/apiv1"
	modelarmorpb "cloud.google.com/go/modelarmor/apiv1/modelarmorpb"
	"google.golang.org/api/option"
)

// screenPDFFile screens a PDF file.
//
// This method screens a PDF file based on the project, location, and template settings.
//
// w io.Writer: The writer to use for logging.
// projectID string: The ID of the project.
// locationID string: The ID of the location.
// templateID string: The ID of the template.
// pdfFilePath string: The path to the PDF file to be screened.
func screenPDFFile(w io.Writer, projectID, locationID, templateID, pdfFilePath string) error {
	ctx := context.Background()

	// Create options for Model Armor client.
	opts := option.WithEndpoint(fmt.Sprintf("modelarmor.%s.rep.googleapis.com:443", locationID))
	// Create the Model Armor client.
	client, err := modelarmor.NewClient(ctx, opts)
	if err != nil {
		return fmt.Errorf("failed to create client: %w", err)
	}
	defer client.Close()

	// Read PDF file content into bytes
	pdfBytes, err := os.ReadFile(pdfFilePath)
	if err != nil {
		return fmt.Errorf("failed to read PDF file: %w", err)
	}

	// Initialize request argument(s)
	userPromptData := &modelarmorpb.DataItem{
		DataItem: &modelarmorpb.DataItem_ByteItem{
			ByteItem: &modelarmorpb.ByteDataItem{
				ByteDataType: modelarmorpb.ByteDataItem_PDF,
				ByteData:     pdfBytes,
			},
		},
	}

	// Prepare request for sanitizing the defined prompt.
	req := &modelarmorpb.SanitizeUserPromptRequest{
		Name:           fmt.Sprintf("projects/%s/locations/%s/templates/%s", projectID, locationID, templateID),
		UserPromptData: userPromptData,
	}

	// Sanitize the user prompt.
	response, err := client.SanitizeUserPrompt(ctx, req)
	if err != nil {
		return fmt.Errorf("failed to sanitize PDF content for template %s: %w", templateID, err)
	}

	// Sanitization Result.
	fmt.Fprintf(w, "PDF screening sanitization result: %v\n", response)

	return nil
}

    Java

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Java e installare l'SDK Java Model Armor.

    
import com.google.cloud.modelarmor.v1.ByteDataItem;
import com.google.cloud.modelarmor.v1.ByteDataItem.ByteItemType;
import com.google.cloud.modelarmor.v1.DataItem;
import com.google.cloud.modelarmor.v1.ModelArmorClient;
import com.google.cloud.modelarmor.v1.ModelArmorSettings;
import com.google.cloud.modelarmor.v1.SanitizeUserPromptRequest;
import com.google.cloud.modelarmor.v1.SanitizeUserPromptResponse;
import com.google.cloud.modelarmor.v1.TemplateName;
import com.google.protobuf.ByteString;
import com.google.protobuf.util.JsonFormat;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;

public class ScreenPdfFile {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.

    // Specify the Google Project ID.
    String projectId = "your-project-id";
    // Specify the location ID. For example, us-central1. 
    String locationId = "your-location-id";
    // Specify the template ID.
    String templateId = "your-template-id";
    // Specify the PDF file path. Replace with your PDF file path.
    String pdfFilePath = "src/main/resources/test_sample.pdf";

    screenPdfFile(projectId, locationId, templateId, pdfFilePath);
  }

  public static SanitizeUserPromptResponse screenPdfFile(String projectId, String locationId,
      String templateId, String pdfFilePath) throws IOException {

    // Endpoint to call the Model Armor server.
    String apiEndpoint = String.format("modelarmor.%s.rep.googleapis.com:443", locationId);
    ModelArmorSettings modelArmorSettings = ModelArmorSettings.newBuilder().setEndpoint(apiEndpoint)
        .build();

    try (ModelArmorClient client = ModelArmorClient.create(modelArmorSettings)) {
      // Build the resource name of the template.
      String name = TemplateName.of(projectId, locationId, templateId).toString();

      // Read the PDF file content and encode it to Base64.
      byte[] fileContent = Files.readAllBytes(Paths.get(pdfFilePath));

      // Prepare the request.
      DataItem userPromptData = DataItem.newBuilder()
          .setByteItem(
            ByteDataItem.newBuilder()
              .setByteDataType(ByteItemType.PDF)
              .setByteData(ByteString.copyFrom(fileContent))
              .build())
          .build();

      SanitizeUserPromptRequest request =
          SanitizeUserPromptRequest.newBuilder()
              .setName(name)
              .setUserPromptData(userPromptData)
              .build();

      // Send the request and get the response.
      SanitizeUserPromptResponse response = client.sanitizeUserPrompt(request);

      // Print the sanitization result.
      System.out.println("Result for the provided PDF file: "
          + JsonFormat.printer().print(response.getSanitizationResult()));

      return response;
    }
  }
}

    Node.js

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Node.js e installare l'SDK Node.js di Model Armor.

    /**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = process.env.PROJECT_ID || 'your-project-id';
// const locationId = process.env.LOCATION_ID || 'us-central1';
// const templateId = process.env.TEMPLATE_ID || 'template-id';
// const pdfContentFilename = 'path/to/file.pdf';

// Imports the Model Armor library
const modelarmor = require('@google-cloud/modelarmor');
const {ModelArmorClient} = modelarmor.v1;
const {protos} = modelarmor;
const ByteItemType =
  protos.google.cloud.modelarmor.v1.ByteDataItem.ByteItemType;

const fs = require('fs');

const pdfContent = fs.readFileSync(pdfContentFilename);
const pdfContentBase64 = pdfContent.toString('base64');

const client = new ModelArmorClient({
  apiEndpoint: `modelarmor.${locationId}.rep.googleapis.com`,
});

const request = {
  name: `projects/${projectId}/locations/${locationId}/templates/${templateId}`,
  userPromptData: {
    byteItem: {
      byteDataType: ByteItemType.PDF,
      byteData: pdfContentBase64,
    },
  },
};

const [response] = await client.sanitizeUserPrompt(request);
console.log(JSON.stringify(response, null, 2));
return response;

    PHP

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo PHP e installare l'SDK PHP Model Armor.

    use Google\Cloud\ModelArmor\V1\Client\ModelArmorClient;
use Google\Cloud\ModelArmor\V1\SanitizeUserPromptRequest;
use Google\Cloud\ModelArmor\V1\ByteDataItem;
use Google\Cloud\ModelArmor\V1\ByteDataItem\ByteItemType;
use Google\Cloud\ModelArmor\V1\DataItem;

/**
 * Screens a PDF file using the ModelArmor service.
 *
 * @param string $projectId The Google Cloud project ID (e.g. 'my-project').
 * @param string $locationId The location ID of the ModelArmor service (e.g. 'us-central1').
 * @param string $templateId The ID of the template to use for the screener (e.g. 'my-template').
 * @param string $filePath The path to the PDF file to screen (e.g. 'path/to/file.pdf').
 */
function screen_pdf_file(
    string $projectId,
    string $locationId,
    string $templateId,
    string $filePath
): void {
    $options = ['apiEndpoint' => "modelarmor.$locationId.rep.googleapis.com"];
    $client = new ModelArmorClient($options);

    // Read the file content and encode it in base64.
    $pdfContent = file_get_contents($filePath);
    $pdfContentBase64 = base64_encode($pdfContent);

    $userPromptRequest = (new SanitizeUserPromptRequest())
        ->setName("projects/$projectId/locations/$locationId/templates/$templateId")
        ->setUserPromptData((new DataItem())
            ->setByteItem((new ByteDataItem())->setByteData($pdfContentBase64)
                ->setByteDataType(ByteItemType::PDF)));

    $response = $client->sanitizeUserPrompt($userPromptRequest);

    printf('Result for Screen PDF File: %s' . PHP_EOL, $response->serializeToJsonString());
}

    Python

    Per eseguire questo codice, configura un ambiente di sviluppo Python e installa l'SDK Python di Model Armor.

    
import base64
from google.api_core.client_options import ClientOptions
from google.cloud import modelarmor_v1

# TODO(Developer): Uncomment these variables.
# project_id = "YOUR_PROJECT_ID"
# location_id = "us-central1"
# template_id = "template_id"
# pdf_content_filename = "path/to/file.pdf"

# Encode the PDF file into base64
with open(pdf_content_filename, "rb") as f:
    pdf_content_base64 = base64.b64encode(f.read())

# Create the Model Armor client.
client = modelarmor_v1.ModelArmorClient(
    transport="rest",
    client_options=ClientOptions(
        api_endpoint=f"modelarmor.{location_id}.rep.googleapis.com"
    ),
)

# Initialize request argument(s).
user_prompt_data = modelarmor_v1.DataItem(
    byte_item=modelarmor_v1.ByteDataItem(
        byte_data_type=modelarmor_v1.ByteDataItem.ByteItemType.PDF,
        byte_data=pdf_content_base64,
    )
)

request = modelarmor_v1.SanitizeUserPromptRequest(
    name=f"projects/{project_id}/locations/{location_id}/templates/{template_id}",
    user_prompt_data=user_prompt_data,
)

# Sanitize the user prompt.
response = client.sanitize_user_prompt(request=request)

# Sanitization Result.
print(response)

    Configurazione di base di Sensitive Data Protection

    Model Armor si integra con la protezione dei dati sensibili per contribuire a prevenire l'esposizione accidentale di informazioni private. Crea un modello con le impostazioni di base di Sensitive Data Protection abilitate. La protezione dei dati sensibili di base ti aiuta a eseguire lo screening di un insieme fisso di infoType di Sensitive Data Protection.

    I seguenti infoType di Sensitive Data Protection vengono scansionati nel prompt per tutte le regioni:

    • CREDIT_CARD_NUMBER: il numero di una carta di credito può contenere da 12 a 19 cifre. Si utilizzano per eseguire transazioni di pagamento a livello globale.
    • FINANCIAL_ACCOUNT_NUMBER: Un numero che si riferisce a un conto finanziario specifico, ad esempio un numero di conto bancario o un numero di conto pensionistico.
    • GCP_CREDENTIALS: Google Cloud credenziali del service account. Credenziali che possono essere utilizzate per l'autenticazione con {api_client_lib_name} e service account.
    • GCP_API_KEY: Google Cloud chiave API. Una stringa criptata utilizzata quando vengono chiamate API Google Cloud che non richiedono l'accesso a dati utente privati.
    • PASSWORD: cancella le password in chiaro nelle configurazioni, nel codice e in altri contenuti testuali.

    I seguenti infoType di Sensitive Data Protection aggiuntivi vengono scansionati nel prompt per le regioni con sede negli Stati Uniti:

    • US_SOCIAL_SECURITY_NUMBER: Il codice SSN (States Social Security) statunitense è un numero di previdenza sociale di 9 cifre rilasciato a cittadini statunitensi, residenti permanenti e residenti temporanei. Questo rilevatore non ricercherà la corrispondenza con numeri composti da soli zeri in uno dei gruppi di cifre (ossia 000-##-####, ###-00-#### o ###-##-0000), con numeri contenenti 666 nel primo gruppo di cifre o con numeri la cui cifra iniziale è 9.
    • US_INDIVIDUAL_TAXPAYER_IDENTIFICATION_NUMBER: un numero di identificazione del contribuente individuale (ITIN) degli Stati Uniti è un tipo di numero di identificazione del contribuente (TIN) emesso dall'Internal Revenue Service (IRS). Si tratta di un numero utilizzato a fini fiscali disponibile solo per alcuni stranieri residenti e non residenti, i loro coniugi e familiari a carico che non possono ottenere un numero di previdenza sociale (SSN).

    Ecco un esempio di configurazione di base di Sensitive Data Protection:

    gcloud 

    gcloud model-armor templates create TEMPLATE_ID \
    --location=LOCATION \
    --project=PROJECT_ID \
    --basic-config-filter-enforcement=enabled

    Sostituisci quanto segue:

    • TEMPLATE_ID: l'ID del modello.
    • LOCATION: la posizione del modello.

    REST 

    export FILTER_CONFIG_SDP_BASIC='{
  "filterConfig": {
    "sdpSettings": {
      "basicConfig": {
        "filterEnforcement": "ENABLED"
      }
    }
  }
}'

curl -X PATCH \
    -d "$FILTER_CONFIG_SDP_BASIC" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID?updateMask=filterConfig.sdpSettings.basicConfig.filterEnforcement"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Vai

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Go e installare l'SDK Model Armor Go.

    
import (
	"context"
	"fmt"
	"io"

	modelarmor "cloud.google.com/go/modelarmor/apiv1"
	modelarmorpb "cloud.google.com/go/modelarmor/apiv1/modelarmorpb"
	"google.golang.org/api/option"
)

// createModelArmorTemplateWithBasicSDP method creates a new Model Armor template with basic SDP settings.
//
// w io.Writer: The writer to use for logging.
// projectID string: The ID of the Google Cloud project.
// locationID string: The ID of the Google Cloud location.
// templateID string: The ID of the template to create.
func createModelArmorTemplateWithBasicSDP(w io.Writer, projectID, locationID, templateID string) error {
	ctx := context.Background()

	// Create options for Model Armor client.
	opts := option.WithEndpoint(fmt.Sprintf("modelarmor.%s.rep.googleapis.com:443", locationID))
	// Create the Model Armor client.
	client, err := modelarmor.NewClient(ctx, opts)
	if err != nil {
		return fmt.Errorf("failed to create client for project %s, location %s: %w", projectID, locationID, err)
	}
	defer client.Close()

	parent := fmt.Sprintf("projects/%s/locations/%s", projectID, locationID)

	// Build the Model Armor template with your preferred filters.
	// For more details on filters, please refer to the following doc:
	// [https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters](https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters)
	template := &modelarmorpb.Template{
		FilterConfig: &modelarmorpb.FilterConfig{
			RaiSettings: &modelarmorpb.RaiFilterSettings{
				RaiFilters: []*modelarmorpb.RaiFilterSettings_RaiFilter{
					{
						FilterType:      modelarmorpb.RaiFilterType_DANGEROUS,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_HARASSMENT,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_MEDIUM_AND_ABOVE,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_HATE_SPEECH,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_SEXUALLY_EXPLICIT,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
				},
			},
			SdpSettings: &modelarmorpb.SdpFilterSettings{
				SdpConfiguration: &modelarmorpb.SdpFilterSettings_BasicConfig{
					BasicConfig: &modelarmorpb.SdpBasicConfig{
						FilterEnforcement: modelarmorpb.SdpBasicConfig_ENABLED,
					},
				},
			},
		},
	}

	// Prepare the request for creating the template.
	req := &modelarmorpb.CreateTemplateRequest{
		Parent:     parent,
		TemplateId: templateID,
		Template:   template,
	}

	// Create the template.
	response, err := client.CreateTemplate(ctx, req)
	if err != nil {
		return fmt.Errorf("failed to create template: %w", err)
	}

	// Print the new template name using fmt.Fprintf with the io.Writer.
	fmt.Fprintf(w, "Created Template with basic SDP: %s\n", response.Name)

	return err
}

    Java

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Java e installare l'SDK Java Model Armor.

    
import com.google.cloud.modelarmor.v1.CreateTemplateRequest;
import com.google.cloud.modelarmor.v1.FilterConfig;
import com.google.cloud.modelarmor.v1.LocationName;
import com.google.cloud.modelarmor.v1.ModelArmorClient;
import com.google.cloud.modelarmor.v1.ModelArmorSettings;
import com.google.cloud.modelarmor.v1.SdpBasicConfig;
import com.google.cloud.modelarmor.v1.SdpBasicConfig.SdpBasicConfigEnforcement;
import com.google.cloud.modelarmor.v1.SdpFilterSettings;
import com.google.cloud.modelarmor.v1.Template;
import java.io.IOException;

public class CreateTemplateWithBasicSdp {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.

    // Specify the Google Project ID.
    String projectId = "your-project-id";
    // Specify the location ID. For example, us-central1. 
    String locationId = "your-location-id";
    // Specify the template ID.
    String templateId = "your-template-id";

    createTemplateWithBasicSdp(projectId, locationId, templateId);
  }

  public static Template createTemplateWithBasicSdp(
      String projectId, String locationId, String templateId) throws IOException {

    // Construct the API endpoint URL.
    String apiEndpoint = String.format("modelarmor.%s.rep.googleapis.com:443", locationId);
    ModelArmorSettings modelArmorSettings = ModelArmorSettings.newBuilder().setEndpoint(apiEndpoint)
        .build();

    // Initialize the client that will be used to send requests. This client
    // only needs to be created once, and can be reused for multiple requests.
    try (ModelArmorClient client = ModelArmorClient.create(modelArmorSettings)) {
      String parent = LocationName.of(projectId, locationId).toString();

      // Build the Model Armor template with your preferred filters.
      // For more details on filters, please refer to the following doc:
      // https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters

      // Configure Basic SDP Filter.
      SdpBasicConfig basicSdpConfig = SdpBasicConfig.newBuilder()
          .setFilterEnforcement(SdpBasicConfigEnforcement.ENABLED)
          .build();

      SdpFilterSettings sdpSettings = SdpFilterSettings.newBuilder()
          .setBasicConfig(basicSdpConfig)
          .build();

      FilterConfig modelArmorFilter = FilterConfig.newBuilder()
          .setSdpSettings(sdpSettings)
          .build();

      Template template = Template.newBuilder()
          .setFilterConfig(modelArmorFilter)
          .build();

      CreateTemplateRequest request = CreateTemplateRequest.newBuilder()
          .setParent(parent)
          .setTemplateId(templateId)
          .setTemplate(template)
          .build();

      Template createdTemplate = client.createTemplate(request);
      System.out.println("Created template with basic SDP filter: " + createdTemplate.getName());

      return createdTemplate;
    }
  }
}

    Node.js

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Node.js e installare l'SDK Node.js di Model Armor.

    /**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'your-project-id';
// const locationId = 'us-central1';
// const templateId = 'template-id';

const parent = `projects/${projectId}/locations/${locationId}`;

// Imports the Model Armor library
const modelarmor = require('@google-cloud/modelarmor');
const {ModelArmorClient} = modelarmor.v1;
const {protos} = modelarmor;

const RaiFilterType = protos.google.cloud.modelarmor.v1.RaiFilterType;
const DetectionConfidenceLevel =
  protos.google.cloud.modelarmor.v1.DetectionConfidenceLevel;
const SdpBasicConfigEnforcement =
  protos.google.cloud.modelarmor.v1.SdpBasicConfig.SdpBasicConfigEnforcement;

// Instantiates a client
const client = new ModelArmorClient({
  apiEndpoint: `modelarmor.${locationId}.rep.googleapis.com`,
});

// Configuration for the template with basic SDP settings
const templateConfig = {
  filterConfig: {
    raiSettings: {
      raiFilters: [
        {
          filterType: RaiFilterType.DANGEROUS,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
        {
          filterType: RaiFilterType.HARASSMENT,
          confidenceLevel: DetectionConfidenceLevel.MEDIUM_AND_ABOVE,
        },
        {
          filterType: RaiFilterType.HATE_SPEECH,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
        {
          filterType: RaiFilterType.SEXUALLY_EXPLICIT,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
      ],
    },
    sdpSettings: {
      basicConfig: {
        filterEnforcement: SdpBasicConfigEnforcement.ENABLED,
      },
    },
  },
};

// Construct request
const request = {
  parent,
  templateId,
  template: templateConfig,
};

const [response] = await client.createTemplate(request);
return response;

    PHP

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo PHP e installare l'SDK PHP Model Armor.

    use Google\Cloud\ModelArmor\V1\Client\ModelArmorClient;
use Google\Cloud\ModelArmor\V1\SdpBasicConfig\SdpBasicConfigEnforcement;
use Google\Cloud\ModelArmor\V1\SdpBasicConfig;
use Google\Cloud\ModelArmor\V1\SdpFilterSettings;
use Google\Cloud\ModelArmor\V1\FilterConfig;
use Google\Cloud\ModelArmor\V1\CreateTemplateRequest;
use Google\Cloud\ModelArmor\V1\Template;

/**
 * Create a Model Armor template with Basic SDP Filter.
 *
 * @param string $projectId The ID of the project (e.g. 'my-project').
 * @param string $locationId The ID of the location (e.g. 'us-central1').
 * @param string $templateId The ID of the template (e.g. 'my-template').
 */
function create_template_with_basic_sdp(string $projectId, string $locationId, string $templateId): void
{
    $options = ['apiEndpoint' => "modelarmor.$locationId.rep.googleapis.com"];
    $client = new ModelArmorClient($options);
    $parent = $client->locationName($projectId, $locationId);

    // Build the Model Armor template with your preferred filters.
    // For more details on filters, please refer to the following doc:
    // https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters

    // Configure Basic SDP Filter.
    $sdpBasicConfig = (new SdpBasicConfig())->setFilterEnforcement(SdpBasicConfigEnforcement::ENABLED);
    $sdpSettings = (new SdpFilterSettings())->setBasicConfig($sdpBasicConfig);

    $templateFilterConfig = (new FilterConfig())
        ->setSdpSettings($sdpSettings);

    $template = (new Template())->setFilterConfig($templateFilterConfig);

    $request = (new CreateTemplateRequest())
        ->setParent($parent)
        ->setTemplateId($templateId)
        ->setTemplate($template);

    $response = $client->createTemplate($request);

    printf('Template created: %s' . PHP_EOL, $response->getName());
}

    Python

    Per eseguire questo codice, configura un ambiente di sviluppo Python e installa l'SDK Python di Model Armor.

    
from google.api_core.client_options import ClientOptions
from google.cloud import modelarmor_v1

# TODO(Developer): Uncomment these variables.
# project_id = "YOUR_PROJECT_ID"
# location_id = "us-central1"
# template_id = "template_id"

# Create the Model Armor client.
client = modelarmor_v1.ModelArmorClient(
    client_options=ClientOptions(
        api_endpoint=f"modelarmor.{location_id}.rep.googleapis.com"
    )
)

parent = f"projects/{project_id}/locations/{location_id}"

# Build the Model Armor template with your preferred filters.
# For more details on filters, please refer to the following doc:
# https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters
template = modelarmor_v1.Template(
    filter_config=modelarmor_v1.FilterConfig(
        rai_settings=modelarmor_v1.RaiFilterSettings(
            rai_filters=[
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.DANGEROUS,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.HARASSMENT,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.MEDIUM_AND_ABOVE,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.HATE_SPEECH,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.SEXUALLY_EXPLICIT,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
            ]
        ),
        sdp_settings=modelarmor_v1.SdpFilterSettings(
            basic_config=modelarmor_v1.SdpBasicConfig(
                filter_enforcement=modelarmor_v1.SdpBasicConfig.SdpBasicConfigEnforcement.ENABLED
            )
        ),
    ),
)

# Prepare the request for creating the template.
create_template = modelarmor_v1.CreateTemplateRequest(
    parent=parent, template_id=template_id, template=template
)

# Create the template.
response = client.create_template(request=create_template)

# Print the new template name.
print(f"Created template: {response.name}")

    Utilizza il modello creato per esaminare i tuoi prompt. Ecco un esempio:

    curl -X POST \
    -d '{"userPromptData":{"text":"can you remember my ITIN : ###-##-####"}}' \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeUserPrompt"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Questo esempio restituisce la seguente risposta:

    {
  "sanitizationResult": {
      "filterMatchState": "MATCH_FOUND",
      "invocationResult": "SUCCESS",
      "filterResults": [
        {
          "csamFilterFilterResult": {
            "executionState": "EXECUTION_SUCCESS",
            "matchState": "NO_MATCH_FOUND"
          }
        },
        {
      "sdpFilterResult": {
        "inspectResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "MATCH_FOUND",
          "findings": [
            {
              "infoType": "US_INDIVIDUAL_TAXPAYER_IDENTIFICATION_NUMBER",
              "likelihood": "LIKELY",
              "location": {
                "byteRange": {
                  "start": "26",
                  "end": "37"
                },
                "codepointRange": {
                  "start": "26",
                  "end": "37"
                }
              }
            }
          ]
        }
       }
      }
    ]
  }
}

    Configurazione avanzata di Sensitive Data Protection

    Model Armor filtra i prompt e le risposte del modello LLM utilizzando l'impostazione di configurazione avanzata di Sensitive Data Protection. In questo modo puoi utilizzare le funzionalità di Sensitive Data Protection oltre agli infoType offerti nell'impostazione di base di Sensitive Data Protection.

    Per utilizzare il filtro avanzato di Sensitive Data Protection in Model Armor, i modelli di Sensitive Data Protection devono trovarsi nella stessa posizione cloud del modello Model Armor.

    gcloud 

    gcloud model-armor templates create TEMPLATE_ID \
    --location=LOCATION \
    --advanced-config-inspect-template="path/to/template" \

    Sostituisci quanto segue:

    • TEMPLATE_ID: l'ID del modello.
    • LOCATION: la posizione del modello.

    REST 

      export FILTER_CONFIG_SDP_ADV='{
    "filterConfig": {
      "sdpSettings": {
        "advancedConfig": {
          "deidentifyTemplate": "projects/PROJECT_ID/locations/LOCATION/deidentifyTemplates/deidentify-ip-address",
          "inspectTemplate": "projects/PROJECT_ID/locations/LOCATION/inspectTemplates/inspect-ip-address"
        }
      }
    }
  }'

 curl -X POST \
     -d "$FILTER_CONFIG_SDP_ADV" \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
       "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID?updateMask=filterConfig.sdpSettings.advancedConfig"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Questo esempio restituisce la seguente risposta:

    {
  "name": "projects/PROJECT_ID/locations/LOCATION/templates/all-filters-test",
  "createTime": "2024-12-16T17:08:19.626693819Z",
  "updateTime": "2024-12-16T17:08:19.626693819Z",
   "filterConfig": {
      "sdpSettings": {
        "advancedConfig": {
          "deidentifyTemplate":  "projects/PROJECT_ID/locations/LOCATION/deidentifyTemplates/deidentify-ip-address",
          "inspectTemplate": "projects/PROJECT_ID/locations/LOCATION/inspectTemplates/inspect-ip-address"
        }
      }
    }
}

    Vai

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Go e installare l'SDK Model Armor Go.

    
import (
	"context"
	"fmt"
	"io"

	modelarmor "cloud.google.com/go/modelarmor/apiv1"
	modelarmorpb "cloud.google.com/go/modelarmor/apiv1/modelarmorpb"
	"google.golang.org/api/option"
)

// createModelArmorTemplateWithAdvancedSDP method creates a
// new Model Armor template with advanced SDP settings,
// including inspect and deidentify templates.
//
// w io.Writer: The writer to use for logging.
// projectID string: The ID of the Google Cloud project.
// locationID string: The ID of the Google Cloud location.
// templateID string: The ID of the template to create.
// inspectTemplate string: The ID of the inspect template to use.
// deidentifyTemplate string: The ID of the deidentify template to use.
func createModelArmorTemplateWithAdvancedSDP(w io.Writer, projectID, locationID, templateID, inspectTemplate, deidentifyTemplate string) error {
	ctx := context.Background()

	// Create options for Model Armor client.
	opts := option.WithEndpoint(fmt.Sprintf("modelarmor.%s.rep.googleapis.com:443", locationID))
	// Create the Model Armor client.
	client, err := modelarmor.NewClient(ctx, opts)
	if err != nil {
		return fmt.Errorf("failed to create client for project %s, location %s: %w", projectID, locationID, err)
	}
	defer client.Close()

	parent := fmt.Sprintf("projects/%s/locations/%s", projectID, locationID)

	// Build the Model Armor template with your preferred filters.
	template := &modelarmorpb.Template{
		FilterConfig: &modelarmorpb.FilterConfig{
			RaiSettings: &modelarmorpb.RaiFilterSettings{
				RaiFilters: []*modelarmorpb.RaiFilterSettings_RaiFilter{
					{
						FilterType:      modelarmorpb.RaiFilterType_DANGEROUS,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_HARASSMENT,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_MEDIUM_AND_ABOVE,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_HATE_SPEECH,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
					{
						FilterType:      modelarmorpb.RaiFilterType_SEXUALLY_EXPLICIT,
						ConfidenceLevel: modelarmorpb.DetectionConfidenceLevel_HIGH,
					},
				},
			},
			SdpSettings: &modelarmorpb.SdpFilterSettings{
				SdpConfiguration: &modelarmorpb.SdpFilterSettings_AdvancedConfig{
					AdvancedConfig: &modelarmorpb.SdpAdvancedConfig{
						InspectTemplate:    inspectTemplate,
						DeidentifyTemplate: deidentifyTemplate,
					},
				},
			},
		},
	}

	// Prepare the request for creating the template.
	req := &modelarmorpb.CreateTemplateRequest{
		Parent:     parent,
		TemplateId: templateID,
		Template:   template,
	}

	// Create the template.
	response, err := client.CreateTemplate(ctx, req)
	if err != nil {
		return fmt.Errorf("failed to create template: %w", err)
	}

	// Print the new template name using fmt.Fprint with the io.Writer.
	fmt.Fprintf(w, "Created Template with advanced SDP: %s\n", response.Name)

	return err
}

    Java

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Java e installare l'SDK Java Model Armor.

    
import com.google.cloud.modelarmor.v1.CreateTemplateRequest;
import com.google.cloud.modelarmor.v1.FilterConfig;
import com.google.cloud.modelarmor.v1.LocationName;
import com.google.cloud.modelarmor.v1.ModelArmorClient;
import com.google.cloud.modelarmor.v1.ModelArmorSettings;
import com.google.cloud.modelarmor.v1.SdpAdvancedConfig;
import com.google.cloud.modelarmor.v1.SdpFilterSettings;
import com.google.cloud.modelarmor.v1.Template;
import com.google.privacy.dlp.v2.DeidentifyTemplateName;
import com.google.privacy.dlp.v2.InspectTemplateName;
import java.io.IOException;

public class CreateTemplateWithAdvancedSdp {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.

    // Specify the Google Project ID.
    String projectId = "your-project-id";
    // Specify the location ID. For example, us-central1.
    String locationId = "your-location-id";
    // Specify the template ID.
    String templateId = "your-template-id";
    // Specify the Inspect template ID.
    String inspectTemplateId = "your-inspect-template-id";
    // Specify the Deidentify template ID.
    String deidentifyTemplateId = "your-deidentify-template-id";

    createTemplateWithAdvancedSdp(projectId, locationId, templateId, inspectTemplateId,
        deidentifyTemplateId);
  }

  public static Template createTemplateWithAdvancedSdp(String projectId, String locationId,
      String templateId, String inspectTemplateId, String deidentifyTemplateId) throws IOException {

    // Construct the API endpoint URL.
    String apiEndpoint = String.format("modelarmor.%s.rep.googleapis.com:443", locationId);
    ModelArmorSettings modelArmorSettings = ModelArmorSettings.newBuilder().setEndpoint(apiEndpoint)
        .build();

    // Initialize the client that will be used to send requests. This client
    // only needs to be created once, and can be reused for multiple requests.
    try (ModelArmorClient client = ModelArmorClient.create(modelArmorSettings)) {
      String parent = LocationName.of(projectId, locationId).toString();

      String inspectTemplateName = InspectTemplateName
          .ofProjectLocationInspectTemplateName(projectId, locationId, inspectTemplateId)
          .toString();

      String deidentifyTemplateName = DeidentifyTemplateName
          .ofProjectLocationDeidentifyTemplateName(projectId, locationId, deidentifyTemplateId)
          .toString();

      // Build the Model Armor template with Advanced SDP Filter.

      // Note: If you specify only Inspect template, Model Armor reports the filter matches if
      // sensitive data is detected. If you specify Inspect template and De-identify template, Model
      // Armor returns the de-identified sensitive data and sanitized version of prompts or
      // responses in the deidentifyResult.data.text field of the finding.
      SdpAdvancedConfig advancedSdpConfig =
          SdpAdvancedConfig.newBuilder()
              .setInspectTemplate(inspectTemplateName)
              .setDeidentifyTemplate(deidentifyTemplateName)
              .build();

      SdpFilterSettings sdpSettings = SdpFilterSettings.newBuilder()
          .setAdvancedConfig(advancedSdpConfig).build();

      FilterConfig modelArmorFilter = FilterConfig.newBuilder().setSdpSettings(sdpSettings).build();

      Template template = Template.newBuilder().setFilterConfig(modelArmorFilter).build();

      CreateTemplateRequest request = CreateTemplateRequest.newBuilder()
          .setParent(parent)
          .setTemplateId(templateId)
          .setTemplate(template)
          .build();

      Template createdTemplate = client.createTemplate(request);
      System.out.println("Created template with Advanced SDP filter: " + createdTemplate.getName());

      return createdTemplate;
    }
  }
}

    Node.js

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Node.js e installare l'SDK Node.js di Model Armor.

    /**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'your-project-id';
// const locationId = 'us-central1';
// const templateId = 'template-id';
// const inspectTemplate = `projects/${projectId}/locations/${locationId}/inspectTemplates/inspect-template-id`;
// const deidentifyTemplate = `projects/${projectId}/locations/${locationId}/deidentifyTemplates/deidentify-template-id`;

const parent = `projects/${projectId}/locations/${locationId}`;

// Imports the Model Armor library
const modelarmor = require('@google-cloud/modelarmor');
const {ModelArmorClient} = modelarmor.v1;
const {protos} = modelarmor;

const RaiFilterType = protos.google.cloud.modelarmor.v1.RaiFilterType;
const DetectionConfidenceLevel =
  protos.google.cloud.modelarmor.v1.DetectionConfidenceLevel;

// Instantiates a client
const client = new ModelArmorClient({
  apiEndpoint: `modelarmor.${locationId}.rep.googleapis.com`,
});

// Configuration for the template with advanced SDP settings
const templateConfig = {
  filterConfig: {
    raiSettings: {
      raiFilters: [
        {
          filterType: RaiFilterType.DANGEROUS,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
        {
          filterType: RaiFilterType.HARASSMENT,
          confidenceLevel: DetectionConfidenceLevel.MEDIUM_AND_ABOVE,
        },
        {
          filterType: RaiFilterType.HATE_SPEECH,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
        {
          filterType: RaiFilterType.SEXUALLY_EXPLICIT,
          confidenceLevel: DetectionConfidenceLevel.HIGH,
        },
      ],
    },
    sdpSettings: {
      advancedConfig: {
        inspectTemplate: inspectTemplate,
        deidentifyTemplate: deidentifyTemplate,
      },
    },
  },
};

// Construct request
const request = {
  parent,
  templateId,
  template: templateConfig,
};

// Create the template
const [response] = await client.createTemplate(request);
return response;

    PHP

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo PHP e installare l'SDK PHP Model Armor.

    use Google\Cloud\ModelArmor\V1\Client\ModelArmorClient;
use Google\Cloud\ModelArmor\V1\SdpAdvancedConfig;
use Google\Cloud\ModelArmor\V1\Template;
use Google\Cloud\ModelArmor\V1\FilterConfig;
use Google\Cloud\ModelArmor\V1\CreateTemplateRequest;
use Google\Cloud\ModelArmor\V1\SdpFilterSettings;

/**
 * Create a Model Armor template with an Advanced SDP Filter.
 *
 * @param string $projectId The ID of the project (e.g. 'my-project').
 * @param string $locationId The ID of the location (e.g. 'us-central1').
 * @param string $templateId The ID of the template (e.g. 'my-template').
 * @param string $inspectTemplate The resource name of the inspect template.
          (e.g. 'organizations/{organization}/inspectTemplates/{inspect_template}')
 * @param string $deidentifyTemplate The resource name of the de-identify template.
          (e.g. 'organizations/{organization}/deidentifyTemplates/{deidentify_template}')
 */
function create_template_with_advanced_sdp(
    string $projectId,
    string $locationId,
    string $templateId,
    string $inspectTemplate,
    string $deidentifyTemplate
): void {
    $options = ['apiEndpoint' => "modelarmor.$locationId.rep.googleapis.com"];
    $client = new ModelArmorClient($options);
    $parent = $client->locationName($projectId, $locationId);

    // Build the Model Armor template with Advanced SDP Filter.

    // Note: If you specify only Inspect template, Model Armor reports the filter matches if
    // sensitive data is detected. If you specify Inspect template and De-identify template, Model
    // Armor returns the de-identified sensitive data and sanitized version of prompts or
    // responses in the deidentifyResult.data.text field of the finding.
    $sdpAdvancedConfig = (new SdpAdvancedConfig())
        ->setInspectTemplate($inspectTemplate)
        ->setDeidentifyTemplate($deidentifyTemplate);

    $sdpSettings = (new SdpFilterSettings())->setAdvancedConfig($sdpAdvancedConfig);

    $templateFilterConfig = (new FilterConfig())
        ->setSdpSettings($sdpSettings);

    $template = (new Template())->setFilterConfig($templateFilterConfig);

    $request = (new CreateTemplateRequest())
        ->setParent($parent)
        ->setTemplateId($templateId)
        ->setTemplate($template);

    $response = $client->createTemplate($request);

    printf('Template created: %s' . PHP_EOL, $response->getName());
}

    Python

    Per eseguire questo codice, configura un ambiente di sviluppo Python e installa l'SDK Python di Model Armor.

    
from google.api_core.client_options import ClientOptions
from google.cloud import modelarmor_v1

# TODO(Developer): Uncomment these variables.
# project_id = "YOUR_PROJECT_ID"
# location_id = "us-central1"
# template_id = "template_id"
# inspect_template = f"projects/{project_id}/inspectTemplates/{inspect_template_id}"
# deidentify_template = f"projects/{project_id}/deidentifyTemplates/{deidentify_template_id}"

# Create the Model Armor client.
client = modelarmor_v1.ModelArmorClient(
    transport="rest",
    client_options=ClientOptions(
        api_endpoint=f"modelarmor.{location_id}.rep.googleapis.com"
    ),
)

parent = f"projects/{project_id}/locations/{location_id}"

# Build the Model Armor template with your preferred filters.
# For more details on filters, please refer to the following doc:
# https://cloud.google.com/security-command-center/docs/key-concepts-model-armor#ma-filters
template = modelarmor_v1.Template(
    filter_config=modelarmor_v1.FilterConfig(
        rai_settings=modelarmor_v1.RaiFilterSettings(
            rai_filters=[
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.DANGEROUS,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.HARASSMENT,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.MEDIUM_AND_ABOVE,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.HATE_SPEECH,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
                modelarmor_v1.RaiFilterSettings.RaiFilter(
                    filter_type=modelarmor_v1.RaiFilterType.SEXUALLY_EXPLICIT,
                    confidence_level=modelarmor_v1.DetectionConfidenceLevel.HIGH,
                ),
            ]
        ),
        sdp_settings=modelarmor_v1.SdpFilterSettings(
            advanced_config=modelarmor_v1.SdpAdvancedConfig(
                inspect_template=inspect_template,
                deidentify_template=deidentify_template,
            )
        ),
    ),
)

# Prepare the request for creating the template.
create_template = modelarmor_v1.CreateTemplateRequest(
    parent=parent, template_id=template_id, template=template
)

# Create the template.
response = client.create_template(request=create_template)

# Print the new template name.
print(f"Created template: {response.name}")

    Utilizza il modello creato per esaminare i tuoi prompt. Ecco un esempio:

    curl -X POST \
    -d '{"userPromptData":{"text":"is there anything malicious running on 1.1.1.1?"}}' \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
        "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeUserPrompt"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Questo esempio restituisce la seguente risposta:

    {
  "sanitizationResult": {
    "filterMatchState": "MATCH_FOUND",
    "invocationResult": "SUCCESS",
      "filterResults": [
      {
        "csamFilterFilterResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "NO_MATCH_FOUND"
        }
      },
      {
      "sdpFilterResult": {
        "deidentifyResult": {
          "executionState": "EXECUTION_SUCCESS",
          "matchState": "MATCH_FOUND",
          "data": {
            "text": "is there anything malicious running on [IP_ADDRESS]?"
          },
            "transformedBytes": "7",
            "infoTypes": ["IP_ADDRESS"]
        }
      }
      }
      ]
  }
}

    Sanificare la risposta del modello

    A volte gli LLM possono generare risposte dannose. Per ridurre i rischi associati all'utilizzo di LLM nelle tue applicazioni, è importante sanificare le loro risposte.

    Ecco un esempio di comando per sanificare una risposta del modello in Model Armor.

    REST 

     curl -X POST \
     -d '{"text":"IP address of the current network is ##.##.##.##"}' \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
         "https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeModelResponse"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.

    • TEMPLATE_ID: l'ID del modello.

      Questo esempio restituisce la seguente risposta:

      {
"sanitizationResult": {
"filterMatchState": "MATCH_FOUND",
"invocationResult": "SUCCESS",
  "filterResults": {
    "rai": {
      "raiFilterResult": {
        "executionState": "EXECUTION_SUCCESS",
        "matchState": "MATCH_FOUND",
        "raiFilterTypeResults": {
    "dangerous": {
      "confidenceLevel": "MEDIUM_AND_ABOVE",
      "matchState": "MATCH_FOUND"
    },
    "sexually_explicit": {
      "matchState": "NO_MATCH_FOUND"
    },
    "hate_speech": {
      "matchState": "NO_MATCH_FOUND"
    },
    "harassment": {
      "matchState": "NO_MATCH_FOUND"
    }
  }
}
},
"pi_and_jailbreak": {
"piAndJailbreakFilterResult": {
  "executionState": "EXECUTION_SUCCESS",
  "matchState": "NO_MATCH_FOUND"
  }
},
"csam": {
"csamFilterFilterResult": {
  "executionState": "EXECUTION_SUCCESS",
  "matchState": "NO_MATCH_FOUND"
}
},
"malicious_uris": {
"maliciousUriFilterResult": {
  "executionState": "EXECUTION_SUCCESS",
  "matchState": "NO_MATCH_FOUND"
}
},
}
}
}

    Vai

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Go e installare l'SDK Model Armor Go.

    
import (
	"context"
	"fmt"
	"io"

	modelarmor "cloud.google.com/go/modelarmor/apiv1"
	modelarmorpb "cloud.google.com/go/modelarmor/apiv1/modelarmorpb"
	"google.golang.org/api/option"
)

// sanitizeModelResponse method sanitizes a model
// response based on the project, location, and template settings.
//
// w io.Writer: The writer to use for logging.
// projectID string: The ID of the project.
// locationID string: The ID of the location.
// templateID string: The ID of the template.
// modelResponse string: The model response to sanitize.
func sanitizeModelResponse(w io.Writer, projectID, locationID, templateID, modelResponse string) error {
	ctx := context.Background()

	// Create options for Model Armor client.
	opts := option.WithEndpoint(fmt.Sprintf("modelarmor.%s.rep.googleapis.com:443", locationID))
	// Create the Model Armor client.
	client, err := modelarmor.NewClient(ctx, opts)
	if err != nil {
		return fmt.Errorf("failed to create client for location %s: %w", locationID, err)
	}
	defer client.Close()

	// Initialize request argument(s)
	modelResponseData := &modelarmorpb.DataItem{
		DataItem: &modelarmorpb.DataItem_Text{
			Text: modelResponse,
		},
	}

	// Prepare request for sanitizing model response.
	req := &modelarmorpb.SanitizeModelResponseRequest{
		Name:              fmt.Sprintf("projects/%s/locations/%s/templates/%s", projectID, locationID, templateID),
		ModelResponseData: modelResponseData,
	}

	// Sanitize the model response.
	response, err := client.SanitizeModelResponse(ctx, req)
	if err != nil {
		return fmt.Errorf("failed to sanitize model response with user prompt for template %s: %w", templateID, err)
	}

	// Sanitization Result.
	fmt.Fprintf(w, "Sanitization Result: %v\n", response)

	return nil
}

    Java

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Java e installare l'SDK Java Model Armor.

    
import com.google.cloud.modelarmor.v1.DataItem;
import com.google.cloud.modelarmor.v1.ModelArmorClient;
import com.google.cloud.modelarmor.v1.ModelArmorSettings;
import com.google.cloud.modelarmor.v1.SanitizeModelResponseRequest;
import com.google.cloud.modelarmor.v1.SanitizeModelResponseResponse;
import com.google.cloud.modelarmor.v1.TemplateName;
import com.google.protobuf.util.JsonFormat;
import java.io.IOException;

public class SanitizeModelResponse {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.

    // Specify the Google Project ID.
    String projectId = "your-project-id";
    // Specify the location ID. For example, us-central1. 
    String locationId = "your-location-id";
    // Specify the template ID.
    String templateId = "your-template-id";
    // Specify the model response.
    String modelResponse = "Unsanitized model output";

    sanitizeModelResponse(projectId, locationId, templateId, modelResponse);
  }

  public static SanitizeModelResponseResponse sanitizeModelResponse(String projectId,
      String locationId, String templateId, String modelResponse) throws IOException {

    // Endpoint to call the Model Armor server.
    String apiEndpoint = String.format("modelarmor.%s.rep.googleapis.com:443", locationId);
    ModelArmorSettings modelArmorSettings = ModelArmorSettings.newBuilder().setEndpoint(apiEndpoint)
        .build();

    try (ModelArmorClient client = ModelArmorClient.create(modelArmorSettings)) {
      // Build the resource name of the template.
      String name = TemplateName.of(projectId, locationId, templateId).toString();

      // Prepare the request.
      SanitizeModelResponseRequest request = 
          SanitizeModelResponseRequest.newBuilder()
            .setName(name)
            .setModelResponseData(
              DataItem.newBuilder().setText(modelResponse)
              .build())
            .build();

      SanitizeModelResponseResponse response = client.sanitizeModelResponse(request);
      System.out.println("Result for the provided model response: "
          + JsonFormat.printer().print(response.getSanitizationResult()));

      return response;
    }
  }
}

    Node.js

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo Node.js e installare l'SDK Node.js di Model Armor.

    /**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = process.env.PROJECT_ID || 'your-project-id';
// const locationId = process.env.LOCATION_ID || 'us-central1';
// const templateId = process.env.TEMPLATE_ID || 'template-id';
// const modelResponse = 'unsanitized model output';
const {ModelArmorClient} = require('@google-cloud/modelarmor').v1;

const client = new ModelArmorClient({
  apiEndpoint: `modelarmor.${locationId}.rep.googleapis.com`,
});

const request = {
  name: `projects/${projectId}/locations/${locationId}/templates/${templateId}`,
  modelResponseData: {
    text: modelResponse,
  },
};

const [response] = await client.sanitizeModelResponse(request);
console.log(JSON.stringify(response, null, 2));

    PHP

    Per eseguire questo codice, devi innanzitutto configurare un ambiente di sviluppo PHP e installare l'SDK PHP Model Armor.

    use Google\Cloud\ModelArmor\V1\Client\ModelArmorClient;
use Google\Cloud\ModelArmor\V1\SanitizeModelResponseRequest;
use Google\Cloud\ModelArmor\V1\DataItem;

/**
 * Sanitizes a model response using the specified template.
 *
 * @param string $projectId The ID of your Google Cloud Platform project (e.g. 'my-project').
 * @param string $locationId The ID of the location where the template is stored (e.g. 'us-central1').
 * @param string $templateId The ID of the template (e.g. 'my-template').
 * @param string $modelResponse The model response to sanitize (e.g. 'my-model-response').
 */
function sanitize_model_response(
    string $projectId,
    string $locationId,
    string $templateId,
    string $modelResponse
): void {
    $options = ['apiEndpoint' => "modelarmor.$locationId.rep.googleapis.com"];
    $client = new ModelArmorClient($options);

    $modelResponseRequest = (new SanitizeModelResponseRequest())
        ->setName("projects/$projectId/locations/$locationId/templates/$templateId")
        ->setModelResponseData((new DataItem())->setText($modelResponse));

    $response = $client->sanitizeModelResponse($modelResponseRequest);

    printf('Result for Model Response Sanitization: %s' . PHP_EOL, $response->serializeToJsonString());
}

    Python

    Per eseguire questo codice, configura un ambiente di sviluppo Python e installa l'SDK Python di Model Armor.

    
from google.api_core.client_options import ClientOptions
from google.cloud import modelarmor_v1

# TODO(Developer): Uncomment these variables.
# project_id = "YOUR_PROJECT_ID"
# location_id = "us-central1"
# template_id = "template_id"
# model_response = "The model response data to sanitize"

# Create the Model Armor client.
client = modelarmor_v1.ModelArmorClient(
    client_options=ClientOptions(
        api_endpoint=f"modelarmor.{location_id}.rep.googleapis.com"
    )
)

# Initialize request argument(s)
model_response_data = modelarmor_v1.DataItem(text=model_response)

# Prepare request for sanitizing model response.
request = modelarmor_v1.SanitizeModelResponseRequest(
    name=f"projects/{project_id}/locations/{location_id}/templates/{template_id}",
    model_response_data=model_response_data,
)

# Sanitize the model response.
response = client.sanitize_model_response(request=request)

# Sanitization Result.
print(response)

    Sanifica la risposta del modello con il rilevamento multilingue attivato

    Attiva il rilevamento multilingue in base alla richiesta impostando il flag enableMultiLanguageDetection su true per ogni risposta individuale. Se vuoi, puoi specificare la lingua di origine per risultati più precisi. Se la lingua di origine non è specificata, viene rilevata automaticamente per fornire il supporto multilingue.

    curl -X POST \
-d  '{"userPromptData":{"text":"[UNSAFE TEXT]"}, "multiLanguageDetectionMetadata": { "enableMultiLanguageDetection": true , "sourceLanguage": "jp"}}' \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
"https://modelarmor.LOCATION.rep.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/templates/TEMPLATE_ID:sanitizeModelResponse"

    Sostituisci quanto segue:

    • PROJECT_ID: l'ID del progetto a cui appartiene il modello.
    • LOCATION: la posizione del modello.
    • TEMPLATE_ID: l'ID del modello.

    Passaggi successivi