|
|
package xyz.wbsite.ai;
|
|
|
|
|
|
import dev.langchain4j.data.document.*;
|
|
|
import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
|
|
|
import dev.langchain4j.data.document.parser.TextDocumentParser;
|
|
|
import dev.langchain4j.data.segment.TextSegment;
|
|
|
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
|
|
|
import dev.langchain4j.model.chat.ChatLanguageModel;
|
|
|
import dev.langchain4j.model.ollama.OllamaChatModel;
|
|
|
import dev.langchain4j.model.openai.OpenAiChatModel;
|
|
|
import dev.langchain4j.rag.content.Content;
|
|
|
import dev.langchain4j.rag.content.retriever.EmbeddingStoreContentRetriever;
|
|
|
import dev.langchain4j.rag.query.Query;
|
|
|
import dev.langchain4j.service.AiServices;
|
|
|
import dev.langchain4j.service.SystemMessage;
|
|
|
import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
|
|
|
import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
|
|
|
|
|
|
import java.io.IOException;
|
|
|
import java.io.InputStream;
|
|
|
import java.util.List;
|
|
|
|
|
|
public class RagTest {
|
|
|
|
|
|
public static void main(String[] args) {
|
|
|
|
|
|
List<Document> documents = FileSystemDocumentLoader.loadDocuments("D:\\wbSource\\starter-ai\\src\\main\\resources");
|
|
|
InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
|
|
|
EmbeddingStoreIngestor.ingest(documents, embeddingStore);
|
|
|
|
|
|
EmbeddingStoreContentRetriever embeddingStoreContentRetriever = EmbeddingStoreContentRetriever.from(embeddingStore);
|
|
|
|
|
|
List<Content> retrieve = embeddingStoreContentRetriever.retrieve(new Query("java中会存在内存泄漏吗，请简单描述"));
|
|
|
|
|
|
System.out.println();
|
|
|
|
|
|
// ChatLanguageModel model = OllamaChatModel.builder()
|
|
|
// .baseUrl("http://36.138.207.178:11434")
|
|
|
// .modelName("deepseek-r1:32B")
|
|
|
// .build();
|
|
|
//
|
|
|
// Assistant assistant = AiServices.create(Assistant.class,model);
|
|
|
// .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
|
|
|
// .contentRetriever(EmbeddingStoreContentRetriever.from(embeddingStore))
|
|
|
// .build();
|
|
|
//
|
|
|
// String chat = assistant.chat("java中会存在内存泄漏吗，请简单描述。");
|
|
|
// System.out.println(chat);
|
|
|
}
|
|
|
|
|
|
|
|
|
interface Assistant {
|
|
|
|
|
|
// @SystemMessage("请扮演一名小学生,根据输入的文章题目写一篇100字以内的作文")
|
|
|
String chat(String userMessage);
|
|
|
}
|
|
|
|
|
|
}
|
