Google Gemini Provider

The Google Gemini provider integrates Reveal SDK AI with Google Cloud's Vertex AI platform, enabling access to Google's Gemini family of models.

Installation

Install the Google provider NuGet package:

dotnet add package Reveal.Sdk.AI.Google

Configuration

Basic Setup

Add the Google Gemini provider in your Program.cs:

using Reveal.Sdk;
using Reveal.Sdk.AI;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddControllers().AddReveal();

builder.Services.AddRevealAI()
    .AddGoogle(options =>
    {
        options.ProjectId = "your-gcp-project-id";
        options.CredentialsPath = "/path/to/credentials.json";
    });

var app = builder.Build();
app.MapControllers();
app.Run();

Using appsettings.json

The provider automatically binds to the RevealAI:Google configuration section:

appsettings.json

{
  "RevealAI": {
    "Google": {
      "ProjectId": "your-gcp-project-id",
      "CredentialsPath": "/path/to/credentials.json",
      "Location": "us-central1",
      "Model": "gemini-2.5-pro"
    }
  }
}

With configuration binding, no code options are needed:

builder.Services.AddRevealAI()
    .AddGoogle();

Options

Property	Type	Default	Description
ProjectId	string	""	Required. Your Google Cloud project ID.
CredentialsPath	string	""	Path to the Google Cloud credentials JSON file.
Location	string	"us-central1"	The Google Cloud region for the model.
Publisher	string	"google"	The model publisher.
Model	string	"gemini-2.5-pro"	The Gemini model to use.
Temperature	float	0	Controls randomness (0.0 to 2.0). Lower values are more deterministic.
MaxTokens	int	32768	Maximum number of tokens to generate in the response.
TopP	float	1	Nucleus sampling parameter (0.0 to 1.0).
TopK	float	32	Top-K sampling parameter. Controls the number of top tokens considered.

Google Cloud Prerequisites

Before using the Google Gemini provider, you need:

1. A Google Cloud project with billing enabled
2. The Vertex AI API enabled in your project
3. A service account with the Vertex AI User role
4. A credentials JSON file for the service account

Setting Up Credentials

1. Go to the Google Cloud Console
2. Navigate to IAM & Admin > Service Accounts
3. Create a new service account or select an existing one
4. Grant the Vertex AI User role
5. Create a key in JSON format and download it
6. Set the CredentialsPath option to the path of the downloaded JSON file

The provider sets the GOOGLE_APPLICATION_CREDENTIALS environment variable automatically based on the CredentialsPath option.

Available Models

Model	Description
gemini-2.5-pro	Most capable Gemini model (default)
gemini-2.5-flash	Fast and efficient for most tasks
gemini-2.0-flash	Previous generation fast model

builder.Services.AddRevealAI()
    .AddGoogle(options =>
    {
        options.ProjectId = "your-project-id";
        options.CredentialsPath = "/path/to/credentials.json";
        options.Model = "gemini-2.5-flash";
        options.Location = "us-east1";
    });

Regions

The Location option determines which Google Cloud region processes your requests. Common options include:

• us-central1 (default)
• us-east1
• europe-west1
• asia-northeast1
• global

Choose a region close to your application for lower latency.

Never Commit Credentials

Never commit Google Cloud credentials JSON files to source control. Store them securely and reference the path through environment variables or User Secrets.