SAP HANA Cloud
先決條件
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您需要一個 SAP HANA Cloud 向量引擎帳戶 - 請參閱 SAP HANA Cloud 向量引擎 - 佈建試用帳戶 指南以建立試用帳戶。
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如果需要,EmbeddingModel 的 API 金鑰,用於產生向量儲存庫儲存的嵌入。
自動配置
Spring AI 為 SAP Hana 向量儲存庫提供 Spring Boot 自動配置。若要啟用它,請將以下依賴項新增至您的專案 Maven pom.xml
檔案
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-hanadb-store-spring-boot-starter</artifactId>
</dependency>
或您的 Gradle build.gradle
建置檔案。
dependencies {
implementation 'org.springframework.ai:spring-ai-hanadb-store-spring-boot-starter'
}
請參閱 依賴項管理 章節,將 Spring AI BOM 新增至您的建置檔案。 |
請查看 向量儲存庫的配置參數 列表,以了解預設值和配置選項。
請參閱 儲存庫 章節,將 Milestone 和/或 Snapshot 儲存庫新增至您的建置檔案。 |
此外,您還需要一個已配置的 EmbeddingModel
bean。請參閱 EmbeddingModel 章節以取得更多資訊。
HanaCloudVectorStore 屬性
您可以在 Spring Boot 配置中使用以下屬性來自訂 SAP Hana 向量儲存庫。它使用 spring.datasource.
屬性來配置 Hana 資料來源,並使用 spring.ai.vectorstore.hanadb.
屬性來配置 Hana 向量儲存庫。
屬性 | 描述 | 預設值 |
---|---|---|
|
驅動程式類別名稱 |
com.sap.db.jdbc.Driver |
|
Hana 資料來源 URL |
- |
|
Hana 資料來源使用者名稱 |
- |
|
Hana 資料來源密碼 |
- |
|
待辦事項 |
- |
|
待辦事項 |
- |
|
是否初始化必要的結構描述 |
|
建立範例 RAG 應用程式
展示如何設定一個專案,使用 SAP Hana Cloud 作為向量資料庫,並利用 OpenAI 實作 RAG 模式
-
在 SAP Hana DB 中建立名為
CRICKET_WORLD_CUP
的資料表
CREATE TABLE CRICKET_WORLD_CUP ( _ID VARCHAR2(255) PRIMARY KEY, CONTENT CLOB, EMBEDDING REAL_VECTOR(1536) )
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在您的
pom.xml
中新增以下依賴項
您可以將屬性 spring-ai-version
設定為 <spring-ai-version>1.0.0-SNAPSHOT</spring-ai-version>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${spring-ai-version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-pdf-document-reader</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-hanadb-store-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.30</version>
<scope>provided</scope>
</dependency>
-
在
application.properties
檔案中新增以下屬性
spring.ai.openai.api-key=${OPENAI_API_KEY} spring.ai.openai.embedding.options.model=text-embedding-ada-002 spring.datasource.driver-class-name=com.sap.db.jdbc.Driver spring.datasource.url=${HANA_DATASOURCE_URL} spring.datasource.username=${HANA_DATASOURCE_USERNAME} spring.datasource.password=${HANA_DATASOURCE_PASSWORD} spring.ai.vectorstore.hanadb.tableName=CRICKET_WORLD_CUP spring.ai.vectorstore.hanadb.topK=3
建立名為 CricketWorldCup
的 Entity
類別,該類別繼承自 HanaVectorEntity
package com.interviewpedia.spring.ai.hana;
import jakarta.persistence.Column;
import jakarta.persistence.Entity;
import jakarta.persistence.Table;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.extern.jackson.Jacksonized;
import org.springframework.ai.vectorstore.HanaVectorEntity;
@Entity
@Table(name = "CRICKET_WORLD_CUP")
@Data
@Jacksonized
@NoArgsConstructor
public class CricketWorldCup extends HanaVectorEntity {
@Column(name = "content")
private String content;
}
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建立名為
CricketWorldCupRepository
的Repository
,該 Repository 實作HanaVectorRepository
介面
package com.interviewpedia.spring.ai.hana;
import jakarta.persistence.EntityManager;
import jakarta.persistence.PersistenceContext;
import jakarta.transaction.Transactional;
import org.springframework.ai.vectorstore.HanaVectorRepository;
import org.springframework.stereotype.Repository;
import java.util.List;
@Repository
public class CricketWorldCupRepository implements HanaVectorRepository<CricketWorldCup> {
@PersistenceContext
private EntityManager entityManager;
@Override
@Transactional
public void save(String tableName, String id, String embedding, String content) {
String sql = String.format("""
INSERT INTO %s (_ID, EMBEDDING, CONTENT)
VALUES(:_id, TO_REAL_VECTOR(:embedding), :content)
""", tableName);
this.entityManager.createNativeQuery(sql)
.setParameter("_id", id)
.setParameter("embedding", embedding)
.setParameter("content", content)
.executeUpdate();
}
@Override
@Transactional
public int deleteEmbeddingsById(String tableName, List<String> idList) {
String sql = String.format("""
DELETE FROM %s WHERE _ID IN (:ids)
""", tableName);
return this.entityManager.createNativeQuery(sql)
.setParameter("ids", idList)
.executeUpdate();
}
@Override
@Transactional
public int deleteAllEmbeddings(String tableName) {
String sql = String.format("""
DELETE FROM %s
""", tableName);
return this.entityManager.createNativeQuery(sql).executeUpdate();
}
@Override
public List<CricketWorldCup> cosineSimilaritySearch(String tableName, int topK, String queryEmbedding) {
String sql = String.format("""
SELECT TOP :topK * FROM %s
ORDER BY COSINE_SIMILARITY(EMBEDDING, TO_REAL_VECTOR(:queryEmbedding)) DESC
""", tableName);
return this.entityManager.createNativeQuery(sql, CricketWorldCup.class)
.setParameter("topK", topK)
.setParameter("queryEmbedding", queryEmbedding)
.getResultList();
}
}
-
現在,建立一個 REST Controller 類別
CricketWorldCupHanaController
,並自動注入ChatModel
和VectorStore
作為依賴項。在這個 controller 類別中,建立以下 REST 端點-
/ai/hana-vector-store/cricket-world-cup/purge-embeddings
- 從向量儲存庫清除所有嵌入 -
/ai/hana-vector-store/cricket-world-cup/upload
- 上傳 Cricket_World_Cup.pdf,使其資料作為嵌入儲存在 SAP Hana Cloud 向量資料庫中 -
/ai/hana-vector-store/cricket-world-cup
- 使用 SAP Hana DB 中的 Cosine_Similarity 實作RAG
-
package com.interviewpedia.spring.ai.hana;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.chat.prompt.SystemPromptTemplate;
import org.springframework.ai.document.Document;
import org.springframework.ai.reader.pdf.PagePdfDocumentReader;
import org.springframework.ai.transformer.splitter.TokenTextSplitter;
import org.springframework.ai.vectorstore.HanaCloudVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.core.io.Resource;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import org.springframework.web.multipart.MultipartFile;
import java.io.IOException;
import java.util.List;
import java.util.Map;
import java.util.function.Function;
import java.util.function.Supplier;
import java.util.stream.Collectors;
@RestController
@Slf4j
public class CricketWorldCupHanaController {
private final VectorStore hanaCloudVectorStore;
private final ChatModel chatModel;
@Autowired
public CricketWorldCupHanaController(ChatModel chatModel, VectorStore hanaCloudVectorStore) {
this.chatModel = chatModel;
this.hanaCloudVectorStore = hanaCloudVectorStore;
}
@PostMapping("/ai/hana-vector-store/cricket-world-cup/purge-embeddings")
public ResponseEntity<String> purgeEmbeddings() {
int deleteCount = ((HanaCloudVectorStore) this.hanaCloudVectorStore).purgeEmbeddings();
log.info("{} embeddings purged from CRICKET_WORLD_CUP table in Hana DB", deleteCount);
return ResponseEntity.ok().body(String.format("%d embeddings purged from CRICKET_WORLD_CUP table in Hana DB", deleteCount));
}
@PostMapping("/ai/hana-vector-store/cricket-world-cup/upload")
public ResponseEntity<String> handleFileUpload(@RequestParam("pdf") MultipartFile file) throws IOException {
Resource pdf = file.getResource();
Supplier<List<Document>> reader = new PagePdfDocumentReader(pdf);
Function<List<Document>, List<Document>> splitter = new TokenTextSplitter();
List<Document> documents = splitter.apply(reader.get());
log.info("{} documents created from pdf file: {}", documents.size(), pdf.getFilename());
this.hanaCloudVectorStore.accept(documents);
return ResponseEntity.ok().body(String.format("%d documents created from pdf file: %s",
documents.size(), pdf.getFilename()));
}
@GetMapping("/ai/hana-vector-store/cricket-world-cup")
public Map<String, String> hanaVectorStoreSearch(@RequestParam(value = "message") String message) {
var documents = this.hanaCloudVectorStore.similaritySearch(message);
var inlined = documents.stream().map(Document::getContent).collect(Collectors.joining(System.lineSeparator()));
var similarDocsMessage = new SystemPromptTemplate("Based on the following: {documents}")
.createMessage(Map.of("documents", inlined));
var userMessage = new UserMessage(message);
Prompt prompt = new Prompt(List.of(similarDocsMessage, userMessage));
String generation = this.chatModel.call(prompt).getResult().getOutput().getContent();
log.info("Generation: {}", generation);
return Map.of("generation", generation);
}
}
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使用來自維基百科的上下文 PDF 檔案

使用我們在上一步建立的檔案上傳 REST 端點上傳此 PDF 檔案。