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Copy file name to clipboardExpand all lines: blazor/ai-assistview/ai-integrations/gemini-integration.md
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# Integration of Gemini AI With Blazor AI AssistView component
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The Syncfusion AI AssistView supports integration with [Gemini](https://ai.google.dev/gemini-api/docs/quickstart), enabling advanced conversational AI features in your applications.
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The Syncfusion AI AssistView supports integration with [Gemini](https://ai.google.dev/gemini-api/docs/quickstart), enabling advanced conversational AI features in applications.
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## Prerequisites
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* Google account to generate API key on accessing `Gemini AI`
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* Syncfusion AI AssistView for Blazor `Syncfusion.Blazor.InteractiveChat` installed in your project.
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* Google account to generate an API key for accessing Gemini AI
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* Syncfusion AI AssistView for Blazor package (Syncfusion.Blazor.InteractiveChat) installed in the project
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* Markdig package available in the project for Markdown-to-HTML conversion (required by the sample code)
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## Getting Started with the AI AssistView Component
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Before integrating Gemini AI, ensure that the Syncfusion AI AssistView is correctly rendered in your application:
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Before integrating Gemini AI, ensure that the Syncfusion AI AssistView renders correctly in the application and that prerequisites are met:
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[Blazor Getting Started Guide](../getting-started)
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[Blazor Getting Started Guide](../getting-started)
1. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and sign in with your Google account. If you don’t have one, create a new account.
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1. Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and sign in with a Google account. Create a new account if needed.
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2.Once logged in, click on `Get API Key` from the left-hand menu or the top-right corner of the dashboard.
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2.Select Get API Key from the left menu or the top-right of the dashboard.
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3.Click the `Create API Key` button. You’ll be prompted to either select an existing Google Cloud project or create a new one. Choose the appropriate option and proceed.
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3.Choose Create API Key. Select an existing Google Cloud project or create a new one, then proceed.
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4. After selecting or creating a project, your API key will be generated and displayed. Copy the key and store it securely, as it will only be shown once.
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4. After creating or selecting a project, an API key is generated and displayed. Copy the key and store it securely, as it may be shown only once.
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> `Security Note`: Never commit the API key to version control. Use environment variables or a secret manager for production.
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> Security note: Do not commit API keys to version control. Use environment variables, a secret manager, or a server-side proxy in production.
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## Integration Gemini AI with AI AssistView
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* Add your generated `API Key` at the line
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* Add the generated API key in the following line.
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```bash
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{% endhighlight %}
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{% endtabs %}
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Copy file name to clipboardExpand all lines: blazor/ai-assistview/how-to/integration-with-ai.md
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The Syncfusion<supstyle="font-size:70%">®</sup> AI AssistView component supports integration with the `Microsoft.Extensions.AI` framework, enabling seamless communication with various large language models (LLMs) such as `Azure OpenAI`, `OpenAI`, and more.
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`The Microsoft.Extensions.AI` simplifies integration with different models, requiring minimal configuration changes depending on the provider. The following example demonstrates integration using `Azure OpenAI`.
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`Microsoft.Extensions.AI` simplifies integration with different providers and typically requires only minimal configuration changes based on the selected model. The following example demonstrates integration using `Azure OpenAI`.
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N> The Microsoft AI extension libraries are currently in preview, and breaking changes may occur. Ensure that you use compatible versions to avoid integration issues.
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N> The Microsoft AI extension libraries are currently in preview and may include breaking changes. Use compatible versions of all referenced packages to prevent integration issues.
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### Getting started with AI AssistView
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Before integrating `AI AssistView` with `Microsoft.Extensions.AI`, ensure the SfAIAssistView component is rendered by following the appropriate project guideline:
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Before integrating `AI AssistView` with `Microsoft.Extensions.AI`, ensure the `SfAIAssistView` component is rendered by following the appropriate project guidelines:
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*[Blazor Web App](../getting-started-webapp)
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*[Blazor WASM App](../getting-started)
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### Prerequisites for Microsoft.Extensions.AI integration
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To add the required NuGet packages, use the NuGet package manager in Visual Studio (*Tools → NuGet Package Manager → Manage NuGet Packages for Solution*) search and install the following:
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To add the required NuGet packages, use the NuGet Package Manager in Visual Studio (Tools → NuGet Package Manager → Manage NuGet Packages for Solution), then search for and install the following packages:
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*`Azure.AI.OpenAI`
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*`Azure.Identity`
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### Configure services in Program.cs
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Register the `Azure OpenAI` client and Syncfusion<supstyle="font-size:70%">®</sup> AI AssistView component within the Blazor application.
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Register the `Azure OpenAI` client and the Syncfusion<supstyle="font-size:70%">®</sup> AI AssistView component within the Blazor application.
The Syncfusion<supstyle="font-size:70%">®</sup> `AI AssistView` component is built to seamlessly integrate with external AI services. When the`IChatClient` is registered via `Microsoft.Extensions.AI`, the component automatically uses it to handle user prompts without any additional configuration.
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The Syncfusion<supstyle="font-size:70%">®</sup> AI AssistView component is designed to integrate seamlessly with external AI services. When an`IChatClient` is registered via Microsoft.Extensions.AI, the component automatically uses it to process user prompts without additional component configuration.
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In the following example, the user input is processed using the injected `IChatClient`. The AI model's response is returned in Markdown format which is converted to HTML using the `Markdig` library before rendering in the AI AssistView component.
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In the following example, user input is sent to the injected `IChatClient`. The AI model’s response is returned in Markdown, converted to HTML using the `Markdig` library, and rendered in the AI AssistView component.
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