上传备份

pom.xml

@@ -52,7 +52,6 @@
             <artifactId>hutool-all</artifactId>
             <version>5.8.24</version>
         </dependency>
-
         <dependency>
             <groupId>dev.langchain4j</groupId>
             <artifactId>langchain4j-core</artifactId>
@@ -65,24 +64,25 @@
         </dependency>
         <dependency>
             <groupId>dev.langchain4j</groupId>
-            <artifactId>langchain4j</artifactId>
+            <artifactId>langchain4j-ollama</artifactId>
             <version>${langchain4j.version}</version>
         </dependency>
         <dependency>
             <groupId>dev.langchain4j</groupId>
-            <artifactId>langchain4j-ollama</artifactId>
+            <artifactId>langchain4j-easy-rag</artifactId>
             <version>${langchain4j.version}</version>
         </dependency>
         <dependency>
             <groupId>dev.langchain4j</groupId>
-            <artifactId>langchain4j-easy-rag</artifactId>
+            <artifactId>langchain4j-embeddings</artifactId>
             <version>${langchain4j.version}</version>
         </dependency>
         <dependency>
             <groupId>dev.langchain4j</groupId>
-            <artifactId>langchain4j-embeddings</artifactId>
+            <artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
             <version>${langchain4j.version}</version>
         </dependency>
+
         <dependency>
             <groupId>dev.langchain4j</groupId>
             <artifactId>langchain4j-chroma</artifactId>
@@ -94,5 +94,21 @@
             <artifactId>langchain4j-milvus</artifactId>
             <version>${langchain4j.version}</version>
         </dependency>
+
+        <!-- 嵌入向量库 -->
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-qdrant</artifactId>
+            <version>1.0.0-beta2</version>
+        </dependency>
     </dependencies>
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j</artifactId>
+                <version>${langchain4j.version}</version>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
 </project>

src/main/java/xyz/wbsite/ai/Naive_RAG_Example.java

@@ -48,7 +48,7 @@ public class Naive_RAG_Example {
         //此存储将用于在每次与LLM交互时搜索相关细分市场。
         //为简单起见，此示例使用内存中的嵌入存储，但您可以从任何支持的存储中进行选择。
         //Langchain4j目前支持超过15个流行的嵌入商店。
-        EmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
+        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
         embeddingStore.addAll(embeddings, segments);
 
         // 我们还可以使用EmbeddingStoreIngestor将上面的手动步骤隐藏在更简单的API后面。

src/main/java/xyz/wbsite/ai/Qdrant_Embedding_Example.java

@@ -0,0 +1,30 @@
+package xyz.wbsite.ai;
+
+import dev.langchain4j.data.embedding.Embedding;
+import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.model.embedding.EmbeddingModel;
+import dev.langchain4j.model.embedding.onnx.allminilml6v2.AllMiniLmL6V2EmbeddingModel;
+import dev.langchain4j.store.embedding.EmbeddingStore;
+import dev.langchain4j.store.embedding.qdrant.QdrantEmbeddingStore;
+
+import static dev.langchain4j.internal.Utils.randomUUID;
+
+/**
+ * 语义相似度比较
+ */
+public class Qdrant_Embedding_Example {
+
+    public static void main(String[] args) {
+        EmbeddingStore<TextSegment> embeddingStore =
+                QdrantEmbeddingStore.builder()
+                        .host("127.0.0.1")
+                        .port(6334)
+                        .collectionName("langchain4j-" + randomUUID())
+                        .build();
+
+        EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
+        TextSegment segment1 = TextSegment.from("I've been to France twice.");
+        Embedding embedding1 = embeddingModel.embed(segment1).content();
+        embeddingStore.add(embedding1, segment1);
+    }
+}