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Add Neo4j examples after community migration (#155)
Add Neo4j examples after community migration - Neo4jEmbeddingStore configuration examples - Neo4jText2CypherRetriever example - Spring Boot example
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‎neo4j-example/pom.xml

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<groupId>dev.langchain4j</groupId>
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<artifactId>neo4j-example</artifactId>
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<version>1.0.0-beta4</version>
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<parent>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-parent</artifactId>
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<version>3.2.5</version>
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<relativePath/>
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</parent>
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<properties>
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<maven.compiler.source>17</maven.compiler.source>
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<maven.compiler.target>17</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<java.version>17</java.version>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.springframework.boot</groupId>
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<artifactId>spring-boot-starter-web</artifactId>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-spring-boot-starter</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-community-neo4j</artifactId>
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<version>1.0.0-beta3</version>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-community-neo4j-spring-boot-starter</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-community-neo4j-retriever</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
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<version>1.0.0-beta4</version>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.testcontainers</groupId>
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<artifactId>neo4j</artifactId>
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<version>1.19.6</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-open-ai</artifactId>
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<version>1.0.0-rc1</version>
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</dependency>
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</dependencies>
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‎neo4j-example/src/main/java/Neo4jContentRetrieverExample.java

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import dev.langchain4j.community.rag.content.retriever.neo4j.Neo4jGraph;
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import dev.langchain4j.community.rag.content.retriever.neo4j.Neo4jText2CypherRetriever;
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import dev.langchain4j.model.openai.OpenAiChatModel;
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import dev.langchain4j.rag.content.Content;
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import dev.langchain4j.rag.query.Query;
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import org.neo4j.driver.AuthTokens;
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import org.neo4j.driver.Driver;
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import org.neo4j.driver.GraphDatabase;
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import org.neo4j.driver.Session;
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import org.testcontainers.containers.Neo4jContainer;
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import java.util.List;
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import static dev.langchain4j.internal.Utils.getOrDefault;
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import static dev.langchain4j.model.openai.OpenAiChatModelName.GPT_4_O_MINI;
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public class Neo4jContentRetrieverExample {
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// You can use "demo" api key for demonstration purposes.
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// You can get your own OpenAI API key here: https://platform.openai.com/account/api-keys
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public static final String OPENAI_API_KEY = getOrDefault(System.getenv("OPENAI_API_KEY"), "demo");
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public static final String OPENAI_BASE_URL = getOrDefault(System.getenv("OPENAI_BASE_URL"), "http://langchain4j.dev/demo/openai/v1");
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public static void main(String[] args) {
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final OpenAiChatModel chatLanguageModel = OpenAiChatModel.builder()
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.apiKey(OPENAI_API_KEY)
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.baseUrl(OPENAI_BASE_URL)
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.modelName(GPT_4_O_MINI)
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.build();
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try (Neo4jContainer<?> neo4jContainer = new Neo4jContainer<>("neo4j:5.26")
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.withoutAuthentication()
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.withLabsPlugins("apoc")) {
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neo4jContainer.start();
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try (Driver driver = GraphDatabase.driver(neo4jContainer.getBoltUrl(), AuthTokens.none())) {
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try (Neo4jGraph graph = Neo4jGraph.builder().driver(driver).build()) {
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try (Session session = driver.session()) {
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session.run("CREATE (book:Book {title: 'Dune'})<-[:WROTE]-(author:Person {name: 'Frank Herbert'})");
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}
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// The refreshSchema is needed only if we execute write operation after the `Neo4jGraph` instance,
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// in this case `CREATE (book:Book...`
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// If CREATE (and in general write operations to the db) are performed externally before Neo4jGraph.builder(),
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// the refreshSchema() is not needed
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graph.refreshSchema();
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Neo4jText2CypherRetriever retriever = Neo4jText2CypherRetriever.builder()
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.graph(graph)
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.chatModel(chatLanguageModel)
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.build();
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Query query = new Query("Who is the author of the book 'Dune'?");
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List<Content> contents = retriever.retrieve(query);
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System.out.println(contents.get(0).textSegment().text()); // "Frank Herbert"
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}
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}
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}
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}
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}

‎neo4j-example/src/main/java/Neo4jEmbeddingStoreExample.java

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import dev.langchain4j.community.store.embedding.neo4j.Neo4jEmbeddingStore;
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import dev.langchain4j.data.document.Metadata;
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import dev.langchain4j.data.embedding.Embedding;
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import dev.langchain4j.data.segment.TextSegment;
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import dev.langchain4j.model.embedding.onnx.allminilml6v2.AllMiniLmL6V2EmbeddingModel;
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public class Neo4jEmbeddingStoreExample {
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private static EmbeddingStore<TextSegment> minimalEmbedding;
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private static final EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
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public static void main(String[] args) {
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try (Neo4jContainer<?> neo4j = new Neo4jContainer<>("neo4j:5")) {
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try (Neo4jContainer<?> neo4j = new Neo4jContainer<>("neo4j:5.26")) {
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neo4j.start();
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minimalEmbedding = Neo4jEmbeddingStore.builder()
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.withBasicAuth(neo4j.getBoltUrl(), "neo4j", neo4j.getAdminPassword())
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.dimension(embeddingModel.dimension())
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.build();
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EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
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EmbeddingStore<TextSegment> embeddingStore = Neo4jEmbeddingStore.builder()
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searchEmbeddingsWithSingleMaxResult(minimalEmbedding);
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searchEmbeddingsWithAddAllAndSingleMaxResult();
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searchEmbeddingsWithAddAllWithMetadataMaxResultsAndMinScore();
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// custom embeddingStore
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Neo4jEmbeddingStore customEmbeddingStore = Neo4jEmbeddingStore.builder()
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.withBasicAuth(neo4j.getBoltUrl(), "neo4j", neo4j.getAdminPassword())
2334
.dimension(embeddingModel.dimension())
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.indexName("customidx")
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.label("CustomLabel")
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.embeddingProperty("customProp")
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.idProperty("customId")
39+
.textProperty("customText")
2440
.build();
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searchEmbeddingsWithSingleMaxResult(customEmbeddingStore);
42+
}
43+
}
2544

26-
TextSegment segment1 = TextSegment.from("I like football.");
27-
Embedding embedding1 = embeddingModel.embed(segment1).content();
28-
embeddingStore.add(embedding1, segment1);
45+
private static void searchEmbeddingsWithSingleMaxResult(EmbeddingStore<TextSegment> minimalEmbedding) {
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47+
TextSegment segment1 = TextSegment.from("I like football.");
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Embedding embedding1 = embeddingModel.embed(segment1).content();
49+
minimalEmbedding.add(embedding1, segment1);
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30-
TextSegment segment2 = TextSegment.from("The weather is good today.");
31-
Embedding embedding2 = embeddingModel.embed(segment2).content();
32-
embeddingStore.add(embedding2, segment2);
51+
TextSegment segment2 = TextSegment.from("The weather is good today.");
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Embedding embedding2 = embeddingModel.embed(segment2).content();
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minimalEmbedding.add(embedding2, segment2);
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34-
Embedding queryEmbedding = embeddingModel.embed("What is your favourite sport?").content();
35-
EmbeddingSearchRequest embeddingSearchRequest = EmbeddingSearchRequest.builder()
36-
.queryEmbedding(queryEmbedding)
37-
.maxResults(1)
38-
.build();
39-
List<EmbeddingMatch<TextSegment>> matches = embeddingStore.search(embeddingSearchRequest).matches();
40-
EmbeddingMatch<TextSegment> embeddingMatch = matches.get(0);
55+
Embedding queryEmbedding = embeddingModel.embed("What is your favourite sport?").content();
56+
final EmbeddingSearchRequest request = EmbeddingSearchRequest.builder()
57+
.queryEmbedding(queryEmbedding)
58+
.maxResults(1)
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.build();
60+
List<EmbeddingMatch<TextSegment>> relevant = minimalEmbedding.search(request).matches();
61+
EmbeddingMatch<TextSegment> embeddingMatch = relevant.get(0);
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42-
System.out.println(embeddingMatch.score()); // 0.8144289255142212
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System.out.println(embeddingMatch.embedded().text()); // I like football.
44-
}
63+
System.out.println(embeddingMatch.score()); // 0.8144289255142212
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System.out.println(embeddingMatch.embedded().text()); // I like football.
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}
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67+
private static void searchEmbeddingsWithAddAllAndSingleMaxResult() {
68+
69+
TextSegment segment1 = TextSegment.from("I like football.");
70+
Embedding embedding1 = embeddingModel.embed(segment1).content();
71+
72+
TextSegment segment2 = TextSegment.from("The weather is good today.");
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Embedding embedding2 = embeddingModel.embed(segment2).content();
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75+
TextSegment segment3 = TextSegment.from("I like basketball.");
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Embedding embedding3 = embeddingModel.embed(segment3).content();
77+
minimalEmbedding.addAll(
78+
List.of(embedding1, embedding2, embedding3),
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List.of(segment1, segment2, segment3)
80+
);
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82+
Embedding queryEmbedding = embeddingModel.embed("What are your favourites sport?").content();
83+
final EmbeddingSearchRequest request = EmbeddingSearchRequest.builder()
84+
.queryEmbedding(queryEmbedding)
85+
.maxResults(1)
86+
.build();
87+
List<EmbeddingMatch<TextSegment>> relevant = minimalEmbedding.search(request).matches();
88+
89+
relevant.forEach(match -> {
90+
System.out.println(match.score()); // 0.8144289255142212
91+
System.out.println(match.embedded().text()); // I like football. || I like basketball.
92+
});
93+
94+
}
95+
96+
private static void searchEmbeddingsWithAddAllWithMetadataMaxResultsAndMinScore() {
97+
98+
TextSegment segment1 = TextSegment.from("I like football.", Metadata.from("test-key-1", "test-value-1"));
99+
Embedding embedding1 = embeddingModel.embed(segment1).content();
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101+
TextSegment segment2 = TextSegment.from("The weather is good today.", Metadata.from("test-key-2", "test-value-2"));
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Embedding embedding2 = embeddingModel.embed(segment2).content();
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104+
TextSegment segment3 = TextSegment.from("I like basketball.", Metadata.from("test-key-3", "test-value-3"));
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Embedding embedding3 = embeddingModel.embed(segment3).content();
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minimalEmbedding.addAll(
107+
List.of(embedding1, embedding2, embedding3),
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List.of(segment1, segment2, segment3)
109+
);
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Embedding queryEmbedding = embeddingModel.embed("What are your favourite sports?").content();
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final EmbeddingSearchRequest request = EmbeddingSearchRequest.builder()
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.queryEmbedding(queryEmbedding)
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.maxResults(2)
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.minScore(0.15)
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.build();
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List<EmbeddingMatch<TextSegment>> relevant = minimalEmbedding.search(request).matches();
118+
relevant.forEach(match -> {
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System.out.println(match.score()); // 0.8144289255142212
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System.out.println(match.embedded().text()); // I like football. || I like basketball.
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});
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}
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}

‎neo4j-example/src/main/java/com/example/demo/EmbeddingController.java

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package com.example.demo;
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import dev.langchain4j.data.embedding.Embedding;
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import dev.langchain4j.data.segment.TextSegment;
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import dev.langchain4j.model.embedding.EmbeddingModel;
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import dev.langchain4j.store.embedding.EmbeddingStore;
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import dev.langchain4j.store.embedding.EmbeddingSearchRequest;
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import org.springframework.web.bind.annotation.*;
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import java.util.List;
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12+
@RestController
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@RequestMapping("/api/embeddings")
14+
public class EmbeddingController {
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16+
private final EmbeddingStore<TextSegment> store;
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private final EmbeddingModel model;
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public EmbeddingController(EmbeddingStore<TextSegment> store, EmbeddingModel model) {
20+
this.store = store;
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this.model = model;
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}
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24+
@PostMapping("/add")
25+
public String add(@RequestBody String text) {
26+
TextSegment segment = TextSegment.from(text);
27+
Embedding embedding = model.embed(text).content();
28+
return store.add(embedding, segment);
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}
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@PostMapping("/search")
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public List<String> search(@RequestBody String query) {
33+
Embedding queryEmbedding = model.embed(query).content();
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EmbeddingSearchRequest request = EmbeddingSearchRequest.builder()
35+
.queryEmbedding(queryEmbedding)
36+
.maxResults(5)
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.build();
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return store.search(request).matches()
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.stream()
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.map(i -> i.embedded().text()).toList();
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}
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}

‎neo4j-example/src/main/java/com/example/demo/SpringBootExample.java

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package com.example.demo;
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import dev.langchain4j.model.embedding.onnx.allminilml6v2.AllMiniLmL6V2EmbeddingModel;
4+
import org.springframework.boot.SpringApplication;
5+
import org.springframework.boot.autoconfigure.SpringBootApplication;
6+
import org.springframework.context.annotation.Bean;
7+
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/**
9+
* NOTE:
10+
* This example assumes we have a Neo4j instance with Bolt URI bolt://localhost:7687, username 'neo4j' and password 'pass1234'
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* as specified in the application.properties.
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* If needed, change the properties values to address a running instance.
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*
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* To add an embedding
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* curl -X POST localhost:8083/api/embeddings/add -H "Content-Type: text/plain" -d "embeddingTest"
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*
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* To search embeddings
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* curl -X POST localhost:8083/api/embeddings/search -H "Content-Type: text/plain" -d "querySearchTest"
19+
*/
20+
@SpringBootApplication
21+
public class SpringBootExample {
22+
23+
public static void main(String[] args) {
24+
SpringApplication.run(SpringBootExample.class, args);
25+
}
26+
27+
@Bean
28+
public AllMiniLmL6V2EmbeddingModel embeddingModel() {
29+
return new AllMiniLmL6V2EmbeddingModel();
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}
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}

‎neo4j-example/src/main/resources/application.properties

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spring.application.name=LangChain4j Spring Boot Example
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server.port=8083
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langchain4j.community.neo4j.auth.uri=bolt://localhost:7687
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langchain4j.community.neo4j.auth.user=neo4j
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langchain4j.community.neo4j.auth.password=pass1234
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langchain4j.community.neo4j.label=CustomLabel
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langchain4j.community.neo4j.dimension=384

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