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sap-cloud-sdk-ai

@secondsky/sap-skills
3
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SKILL.md

name sap-cloud-sdk-ai
description Integrates SAP Cloud SDK for AI into JavaScript/TypeScript and Java applications. Use when building applications with SAP AI Core, Generative AI Hub, or Orchestration Service. Covers chat completion, embedding, streaming, function calling, content filtering, data masking, document grounding, prompt registry, and LangChain/Spring AI integration. Supports OpenAI GPT-4o, Claude, Gemini, Amazon Nova, and other foundation models via SAP BTP.
license GPL-3.0
metadata [object Object]

SAP Cloud SDK for AI

The official SDK for SAP AI Core, SAP Generative AI Hub, and Orchestration Service.

When to Use This Skill

Use this skill when:

  • Integrating AI/LLM capabilities into SAP BTP applications
  • Building chat completion or embedding features
  • Using GPT-4o, Claude, Gemini, or other models via SAP AI Core
  • Implementing content filtering, data masking, or document grounding
  • Creating agentic workflows with LangChain or Spring AI
  • Managing prompts via Prompt Registry
  • Deploying AI models on SAP AI Core

Table of Contents

Quick Start

Note: This skill uses SAP Cloud SDK for AI v2.2.0+. If you're migrating from v1.x, see V1 to V2 Migration Guide for breaking changes.

JavaScript/TypeScript

npm install @sap-ai-sdk/orchestration@^2
import { OrchestrationClient } from '@sap-ai-sdk/orchestration';

const client = new OrchestrationClient({
  promptTemplating: {
    model: { name: 'gpt-4o' },
    prompt: [{ role: 'user', content: '{{?question}}' }]
  }
});

const response = await client.chatCompletion({
  placeholderValues: { question: 'What is SAP?' }
});
console.log(response.getContent());

Java

<dependency>
  <groupId>com.sap.ai.sdk</groupId>
  <artifactId>orchestration</artifactId>
  <version>${ai-sdk.version}</version>
</dependency>
var client = new OrchestrationClient();
var config = new OrchestrationModuleConfig()
    .withLlmConfig(OrchestrationAiModel.GPT_4O);
var prompt = new OrchestrationPrompt("What is SAP?");
var result = client.chatCompletion(prompt, config);
System.out.println(result.getContent());

Prerequisites

  • Node.js 20+ (JavaScript) or Java 17+ (Java)
  • SAP AI Core service instance (extended or sap-internal plan)
  • Orchestration deployment in AI Core (default resource group has this)

Connection Setup

BTP Runtime (Cloud Foundry/Kyma)

Bind AI Core service instance to your application. SDK auto-detects via VCAP_SERVICES or mounted secrets.

Local Development

Set environment variable:

export AICORE_SERVICE_KEY='{"clientid":"...","clientsecret":"...","url":"...","serviceurls":{"AI_API_URL":"..."}}'

Or use CAP hybrid mode:

# JavaScript
cds bind -2 <AICORE_INSTANCE> && cds-tsx watch --profile hybrid

# Java
cds bind --to aicore --exec mvn spring-boot:run

For detailed connection options, see references/connecting-to-ai-core.md

Available Packages

JavaScript/TypeScript

Package Purpose
@sap-ai-sdk/orchestration Chat completion, filtering, grounding
@sap-ai-sdk/foundation-models Direct model access (OpenAI)
@sap-ai-sdk/langchain LangChain integration
@sap-ai-sdk/ai-api Deployments, artifacts, configurations
@sap-ai-sdk/document-grounding Pipeline, Vector, Retrieval APIs
@sap-ai-sdk/prompt-registry Prompt template management

Java

Artifact Purpose
orchestration Chat completion, filtering, grounding
openai (foundationmodels) Direct OpenAI model access
core Base connectivity
document-grounding Pipeline, Vector, Retrieval APIs
prompt-registry Prompt template management

Supported Models

Recommended

  • OpenAI: gpt-4o, gpt-4o-mini, o1, o3-mini
  • Anthropic (AWS): Claude 3.5 Sonnet, Claude 4
  • Amazon: Nova Pro, Nova Lite, Nova Micro
  • Google: Gemini 2.5 Flash, Gemini 2.0 Flash
  • Mistral: Medium, Large

Deprecated Models (Use Replacements)

Deprecated Use Instead
text-embedding-ada-002 text-embedding-3-small/large
gpt-35-turbo (all variants) gpt-4o-mini
gpt-4-32k gpt-4o
gpt-4 (base) gpt-4o or gpt-4.1
gemini-1.0-pro gemini-2.0-flash
gemini-1.5-pro/flash gemini-2.5-flash
mistralai--mixtral-8x7b mistralai--mistral-small-instruct

Core Features

Chat Completion with Streaming

// JavaScript
const stream = client.stream({
  placeholderValues: { question: 'Explain SAP CAP' }
});

for await (const chunk of stream.toContentStream()) {
  process.stdout.write(chunk);
}
// Java
client.streamChatCompletion(prompt, config)
    .forEach(chunk -> System.out.print(chunk.getDeltaContent()));

Function/Tool Calling

// JavaScript
const tools = [{
  type: 'function',
  function: {
    name: 'get_weather',
    parameters: { type: 'object', properties: { city: { type: 'string' } } }
  }
}];

const response = await client.chatCompletion({
  placeholderValues: { question: 'Weather in Berlin?' }
}, { tools });

const toolCalls = response.getToolCalls();

Content Filtering

// JavaScript
import { buildAzureContentSafetyFilter } from '@sap-ai-sdk/orchestration';

const client = new OrchestrationClient({
  promptTemplating: { model: { name: 'gpt-4o' } },
  filtering: {
    input: buildAzureContentSafetyFilter({ Hate: 'ALLOW_SAFE' }),
    output: buildAzureContentSafetyFilter({ Violence: 'ALLOW_SAFE' })
  }
});

Data Masking

// JavaScript
const client = new OrchestrationClient({
  promptTemplating: { model: { name: 'gpt-4o' } },
  masking: {
    masking_providers: [{
      type: 'sap_data_privacy_integration',
      method: 'anonymization',
      entities: [{ type: 'profile-email' }, { type: 'profile-person' }]
    }]
  }
});

Document Grounding

// JavaScript
const client = new OrchestrationClient({
  promptTemplating: { model: { name: 'gpt-4o' } },
  grounding: {
    grounding_input: ['{{?question}}'],
    grounding_output: ['{{?context}}'],
    data_repositories: [{ type: 'vector', id: 'my-repo-id' }]
  }
});

Response Helpers

JavaScript SDK provides helper methods:

const response = await client.chatCompletion({ placeholderValues });

response.getContent();          // Model output string
response.getTokenUsage();       // { prompt_tokens, completion_tokens, total_tokens }
response.getFinishReason();     // 'stop', 'length', 'tool_calls', etc.
response.getToolCalls();        // Array of function calls
response.getDeltaToolCalls();   // Partial tool calls (streaming)
response.getAllMessages();      // Full message history
response.getAssistantMessage(); // Assistant response only
response.getRefusal();          // Refusal message if blocked

Streaming response methods:

const stream = client.stream({ placeholderValues });
for await (const chunk of stream.toContentStream()) {
  process.stdout.write(chunk);
}
// After stream ends:
stream.getFinishReason();
stream.getTokenUsage();

Advanced Topics

For detailed guidance:

  • Orchestration features: references/orchestration-guide.md
  • Foundation models (direct OpenAI): references/foundation-models-guide.md
  • LangChain integration: references/langchain-guide.md
  • Spring AI integration: references/spring-ai-guide.md
  • AI Core management: references/ai-core-api-guide.md

Bundled Resources

Reference Documentation

  • references/foundation-models-guide.md - Foundation models and pricing
  • references/ai-core-api-guide.md - AI Core service API reference
  • references/orchestration-guide.md - Orchestration service guide
  • references/langchain-guide.md - LangChain.js integration
  • references/spring-ai-guide.md - Spring AI integration
  • references/agentic-workflows.md - Agentic workflow patterns
  • references/connecting-to-ai-core.md - Connection setup guide
  • references/error-handling.md - Error handling patterns
  • references/v1-to-v2-migration.md - V1 to V2 migration guide

Version Information

SDK Current Version Node/Java Requirement
JavaScript 2.2.0+ Node.js 20+
Java 1.13.0 (Core) / 1.12.0 (Latest orchestration) Java 17+ (21 LTS recommended)

Note: Generated model classes (in ...model packages) may change in minor releases but are safe to use.

Common Errors

Error Cause Solution
"Could not find service bindings for 'aicore'" Missing AI Core binding Bind AI Core service or set AICORE_SERVICE_KEY
"Orchestration deployment not found" No deployment in resource group Deploy orchestration in AI Core or use different resource group
Content filter violation Input/output blocked Adjust filter thresholds or modify content
Token limit exceeded Response too long Set max_tokens parameter

Documentation Sources

Keep this skill updated using these sources: