SAP AI Core Provider for Vercel AI SDK

A community provider for SAP AI Core that integrates seamlessly with the Vercel AI SDK. Built on top of the official @sap-ai-sdk/orchestration package, this provider enables you to use SAP's enterprise-grade AI models through the familiar Vercel AI SDK interface.

⚠️ Breaking Changes in v2.0

Version 2.0 is a complete rewrite using the official SAP AI SDK. Key changes:

• Authentication: Now uses AICORE_SERVICE_KEY environment variable (SAP AI SDK standard)
• Provider creation: Now synchronous - createSAPAIProvider() instead of await createSAPAIProvider()
• No more serviceKey option: Authentication is handled automatically by the SAP AI SDK
• New helper functions: Use buildDpiMaskingProvider(), buildAzureContentSafetyFilter() etc. from the SDK

Table of Contents

• Features
• Quick Start
• Installation
• Authentication
• Basic Usage
• Supported Models
• Advanced Features
• Configuration Options
• Error Handling
• Examples
• Migration from v1
• Contributing
• License

Features

• 🔐 Automatic Authentication - Uses SAP AI SDK's built-in credential handling
• 🎯 Tool Calling Support - Full function calling capabilities
• 🖼️ Multi-modal Input - Support for text and image inputs
• 📡 Streaming Support - Real-time text generation
• 🔒 Data Masking - Built-in SAP DPI integration for privacy
• 🛡️ Content Filtering - Azure Content Safety and Llama Guard support
• 🔧 TypeScript Support - Full type safety and IntelliSense
• 🎨 Multiple Models - Support for GPT-4, Claude, Gemini, Nova, and more

Quick Start

npm install @mymediset/sap-ai-provider ai

import { createSAPAIProvider } from "@mymediset/sap-ai-provider";
import { generateText } from "ai";

// Create provider (authentication via AICORE_SERVICE_KEY env var)
const provider = createSAPAIProvider();

// Generate text with gpt-4o
const result = await generateText({
  model: provider("gpt-4o"),
  prompt: "Explain quantum computing in simple terms.",
});

console.log(result.text);

Installation

Requirements: Node.js 18+ and Vercel AI SDK 6.0+

npm install @mymediset/sap-ai-provider ai

Or with other package managers:

# Yarn
yarn add @mymediset/sap-ai-provider ai

# pnpm
pnpm add @mymediset/sap-ai-provider ai

Authentication

The SAP AI SDK handles authentication automatically. You need to provide credentials in one of these ways:

On SAP BTP (Recommended)

When running on SAP BTP, bind an AI Core service instance to your application. The SDK will automatically detect the service binding from VCAP_SERVICES.

Local Development

Set the AICORE_SERVICE_KEY environment variable with your service key JSON:

# .env
AICORE_SERVICE_KEY='{"serviceurls":{"AI_API_URL":"https://..."},"clientid":"...","clientsecret":"...","url":"..."}'

Get your service key from SAP BTP:

1. Go to your SAP BTP Cockpit
2. Navigate to your AI Core instance
3. Create a service key
4. Copy the JSON and set it as the environment variable

Basic Usage

Text Generation

import { createSAPAIProvider } from "@mymediset/sap-ai-provider";
import { generateText } from "ai";

const provider = createSAPAIProvider();

const result = await generateText({
  model: provider("gpt-4o"),
  prompt: "Write a short story about a robot learning to paint.",
});

console.log(result.text);

Chat Conversations

import { generateText } from "ai";

const result = await generateText({
  model: provider("anthropic--claude-3.5-sonnet"),
  messages: [
    { role: "system", content: "You are a helpful coding assistant." },
    {
      role: "user",
      content: "How do I implement binary search in TypeScript?",
    },
  ],
});

Streaming Responses

import { streamText } from "ai";

const result = streamText({
  model: provider("gpt-4o"),
  prompt: "Explain machine learning concepts.",
});

for await (const delta of result.textStream) {
  process.stdout.write(delta);
}

Model Configuration

const model = provider("gpt-4o", {
  modelParams: {
    temperature: 0.3,
    maxTokens: 2000,
    topP: 0.9,
  },
});

const result = await generateText({
  model,
  prompt: "Write a technical blog post about TypeScript.",
});

Supported Models

Azure OpenAI Models

• gpt-4o, gpt-4o-mini
• gpt-4.1, gpt-4.1-mini, gpt-4.1-nano
• o1, o3, o3-mini, o4-mini

Google Vertex AI Models

• gemini-2.0-flash, gemini-2.0-flash-lite
• gemini-2.5-flash, gemini-2.5-pro

AWS Bedrock Models

• anthropic--claude-3-haiku, anthropic--claude-3-sonnet, anthropic--claude-3-opus
• anthropic--claude-3.5-sonnet, anthropic--claude-3.7-sonnet
• anthropic--claude-4-sonnet, anthropic--claude-4-opus
• amazon--nova-pro, amazon--nova-lite, amazon--nova-micro, amazon--nova-premier

AI Core Open Source Models

• mistralai--mistral-large-instruct, mistralai--mistral-medium-instruct, mistralai--mistral-small-instruct
• cohere--command-a-reasoning

Model availability depends on your SAP AI Core subscription and region.

Advanced Features

Tool Calling

import { generateText, tool } from "ai";
import { z } from "zod";

const weatherSchema = z.object({
  location: z.string(),
});

const weatherTool = tool({
  description: "Get weather for a location",
  inputSchema: weatherSchema,
  execute: (args: z.infer<typeof weatherSchema>) => {
    const { location } = args;
    return `Weather in ${location}: sunny, 72°F`;
  },
});

const result = await generateText({
  model: provider("gpt-4o"),
  prompt: "What's the weather in Tokyo?",
  tools: { getWeather: weatherTool },
  maxSteps: 3,
});

console.log(result.text);

Multi-modal Input (Images)

const result = await generateText({
  model: provider("gpt-4o"),
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "What do you see in this image?" },
        { type: "image", image: new URL("https://example.com/image.jpg") },
      ],
    },
  ],
});

Data Masking (SAP DPI)

Use SAP's Data Privacy Integration to mask sensitive data:

import {
  createSAPAIProvider,
  buildDpiMaskingProvider,
} from "@mymediset/sap-ai-provider";

const dpiConfig = buildDpiMaskingProvider({
  method: "anonymization",
  entities: [
    "profile-email",
    "profile-person",
    {
      type: "profile-phone",
      replacement_strategy: { method: "constant", value: "REDACTED" },
    },
  ],
});

const provider = createSAPAIProvider({
  defaultSettings: {
    masking: {
      masking_providers: [dpiConfig],
    },
  },
});

const result = await generateText({
  model: provider("gpt-4o"),
  prompt: "Email [email protected] about the meeting.",
});

Content Filtering

import {
  createSAPAIProvider,
  buildAzureContentSafetyFilter,
} from "@mymediset/sap-ai-provider";

const provider = createSAPAIProvider({
  defaultSettings: {
    filtering: {
      input: {
        filters: [
          buildAzureContentSafetyFilter("input", {
            hate: "ALLOW_SAFE",
            violence: "ALLOW_SAFE_LOW_MEDIUM",
          }),
        ],
      },
    },
  },
});

Configuration Options

Provider Settings

interface SAPAIProviderSettings {
  resourceGroup?: string; // SAP AI Core resource group (default: 'default')
  deploymentId?: string; // Specific deployment ID (auto-resolved if not set)
  destination?: HttpDestinationOrFetchOptions; // Custom destination
  defaultSettings?: SAPAISettings; // Default settings for all models
}

Model Settings

interface SAPAISettings {
  modelVersion?: string; // Model version (default: 'latest')
  modelParams?: {
    maxTokens?: number; // Maximum tokens to generate
    temperature?: number; // Sampling temperature (0-2)
    topP?: number; // Nucleus sampling (0-1)
    frequencyPenalty?: number; // Frequency penalty (-2 to 2)
    presencePenalty?: number; // Presence penalty (-2 to 2)
    n?: number; // Number of completions
    parallel_tool_calls?: boolean; // Enable parallel tool calls
  };
  masking?: MaskingModule; // Data masking configuration
  filtering?: FilteringModule; // Content filtering configuration
}

Error Handling

import { SAPAIError } from "@mymediset/sap-ai-provider";

try {
  const result = await generateText({
    model: provider("gpt-4o"),
    prompt: "Hello world",
  });
} catch (error) {
  if (error instanceof SAPAIError) {
    console.error("Code:", error.code);
    console.error("Location:", error.location);
    console.error("Request ID:", error.requestId);
  }
}

Examples

Check out the examples directory for complete working examples:

• Simple Chat Completion
• Tool Calling
• Image Recognition
• Text Generation
• Data Masking
• Streaming

Migration from v1

Authentication

Before (v1):

const provider = await createSAPAIProvider({
  serviceKey: process.env.SAP_AI_SERVICE_KEY,
});

After (v2):

// Set AICORE_SERVICE_KEY env var instead
const provider = createSAPAIProvider();

Masking Configuration

Before (v1):

const dpiMasking = {
  type: "sap_data_privacy_integration",
  method: "anonymization",
  entities: [{ type: "profile-email" }],
};

After (v2):

import { buildDpiMaskingProvider } from "@mymediset/sap-ai-provider";

const dpiMasking = buildDpiMaskingProvider({
  method: "anonymization",
  entities: ["profile-email"],
});

Provider is now synchronous

Before (v1):

const provider = await createSAPAIProvider({ serviceKey });

After (v2):

const provider = createSAPAIProvider();

Important Note

Third-Party Provider: This SAP AI Core provider (@mymediset/sap-ai-provider) is developed and maintained by mymediset, not by SAP SE. While it uses the official SAP AI SDK and integrates with SAP AI Core services, it is not an official SAP product.

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

Apache License 2.0 - see LICENSE for details.

Support

• 📖 Documentation
• 🐛 Issue Tracker

Related

• Vercel AI SDK - The AI SDK this provider extends
• SAP AI SDK - Official SAP Cloud SDK for AI
• SAP AI Core Documentation - Official SAP AI Core docs