3527e732d4
Production-ready Next.js boilerplate with: - Runtime env validation (fail-fast on missing vars) - Feature-gated config (S3, Stripe, email, OAuth) - Docker + Coolify deployment pipeline - PostgreSQL + pgvector, MinIO S3, Better Auth - TypeScript strict mode (no ignoreBuildErrors) - i18n (en/es), AI modules, billing, monitoring Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
122 lines
4.9 KiB
Markdown
122 lines
4.9 KiB
Markdown
---
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title: Google AI
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description: Setup Google Generative AI provider and learn how to use its models like Gemini in the starter kit.
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url: /ai/docs/google
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---
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# Google AI
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The [Google Generative AI](https://ai.google/) provider integrates Google's state-of-the-art models, including the versatile Gemini family, into your applications through the AI SDK.
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## Setup
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<Steps>
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<Step>
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### Generate API Key
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Visit the [Google AI Studio](https://aistudio.google.com/app/apikey) to create your API key. For enterprise applications using Google Cloud, you can alternatively configure authentication via Application Default Credentials or service accounts.
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</Step>
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<Step>
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### Add API Key to Environment
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Add your API key to your project's `.env` file (e.g., in `apps/web`):
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```bash title=".env"
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GOOGLE_GENERATIVE_AI_API_KEY=your-api-key
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```
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If using Google Cloud credentials instead, ensure they're properly configured in your environment.
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</Step>
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<Step>
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### Configure Provider (Optional)
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The starter kit automatically uses the `GOOGLE_GENERATIVE_AI_API_KEY` environment variable. For advanced configurations (such as proxies, custom API versions, or specific headers), you can create a tailored provider instance using `createGoogleGenerativeAI`. See the [AI SDK Google documentation](https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#provider-instance) for comprehensive details.
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</Step>
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</Steps>
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## Features
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<Cards>
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<Card title="Language Models (Gemini)" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#language-models">
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Leverage Google's advanced Gemini models for chat, text generation,
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reasoning, and complex instruction following.
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</Card>
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<Card title="Embedding Models" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#embedding-models">
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Utilize text embedding models to convert text into numerical representations
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for tasks like semantic search, clustering, and RAG.
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</Card>
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<Card title="Vision / File Input" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#file-inputs">
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Analyze and understand various file types (including images and PDFs)
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alongside text prompts, enabling rich multimodal applications with
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comprehensive content understanding.
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</Card>
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<Card title="Tool Usage / Function Calling" href="https://sdk.vercel.ai/docs/concepts/tools">
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Empower models to interact seamlessly with external tools and APIs, allowing
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them to perform real-world actions and retrieve up-to-date information for
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more capable applications.
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</Card>
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<Card title="Safety Settings" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#safety-ratings">
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Configure safety thresholds to control model responses regarding harmful
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content categories. Access safety ratings in the response metadata.
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</Card>
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<Card title="Cached Content" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#cached-content">
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Cache content to optimize context reuse and potentially reduce latency and
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costs for repeated queries with similar context.
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</Card>
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<Card title="Search Grounding" href="https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai#search-grounding">
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(With compatible models) Ground responses in real-time search results,
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dramatically enhancing factual accuracy and providing up-to-date information
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on current topics.
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</Card>
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</Cards>
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## Use Cases
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<Cards>
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<Card title="AI Chatbot">
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Create sophisticated conversational agents powered by Gemini models that can
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engage in natural dialogue and handle complex, multi-step tasks. Experience
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this in our [Chat Demo](/ai/docs/chat).
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</Card>
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<Card title="Content Generation">
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Generate diverse text formats, from creative writing and marketing copy to
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code explanations and summaries.
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</Card>
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<Card title="Multimodal Applications">
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Build applications that seamlessly analyze and understand images, documents,
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and other file types alongside text, creating richer, more contextual user
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experiences.
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</Card>
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<Card title="Semantic Search & RAG">
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Implement powerful search capabilities or sophisticated Retrieval-Augmented
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Generation systems using Google's high-performance embedding models for more
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accurate information retrieval.
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</Card>
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<Card title="Automated Workflows">
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Streamline operations by connecting language models to external tools and
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APIs through function calling, automating complex business processes and
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repetitive tasks with minimal human intervention.
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</Card>
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</Cards>
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## Links
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* [Google AI](https://ai.google/)
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* [Google AI Studio](https://aistudio.google.com/)
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* [Google Generative AI Documentation](https://ai.google.dev/docs)
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* [AI SDK - Google Provider Docs](https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai)
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