Incorporated some review comments on the code.

2023-10-25 10:40:32 +05:30 · 2023-10-25 10:40:32 +05:30 · 03c9dce8cf
parent c36a6cc5a4
commit 03c9dce8cf
8 changed files with 110 additions and 110 deletions
--- a/libraries-llms/src/main/resources/logback.xml
+++ b/libraries-llms/src/main/resources/logback.xml
@ -1,17 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<configuration>
-    <appender name="STDOUT"
-        class="ch.qos.logback.core.ConsoleAppender">
-        <encoder>
-            <pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} -
-                %msg%n
-            </pattern>
-        </encoder>
-    </appender>
-    <logger name="io.ebean.DDL" level="TRACE" />
-    <logger name="io.ebean.SQL" level="TRACE" />
-    <logger name="io.ebean.TXN" level="TRACE" />
-    <root level="WARN">
-        <appender-ref ref="STDOUT" />
-    </root>
-</configuration>
--- a/libraries-llms/src/test/java/com/baeldung/langchain/ChainWithDocumentLiveTest.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/ChainWithDocumentLiveTest.java
@ -1,9 +1,7 @@
 package com.baeldung.langchain;

 import static dev.langchain4j.data.document.FileSystemDocumentLoader.loadDocument;
-import static dev.langchain4j.model.openai.OpenAiModelName.GPT_3_5_TURBO;
 import static java.time.Duration.ofSeconds;
-import static java.util.stream.Collectors.joining;

 import java.io.File;
 import java.net.MalformedURLException;
@ -11,75 +9,64 @@ import java.net.URISyntaxException;
 import java.net.URL;
 import java.nio.file.Path;
 import java.nio.file.Paths;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.logging.Logger;

 import org.junit.Assert;
 import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;

+import dev.langchain4j.chain.ConversationalRetrievalChain;
 import dev.langchain4j.data.document.Document;
-import dev.langchain4j.data.document.DocumentSplitter;
 import dev.langchain4j.data.document.splitter.DocumentSplitters;
-import dev.langchain4j.data.embedding.Embedding;
-import dev.langchain4j.data.message.AiMessage;
 import dev.langchain4j.data.segment.TextSegment;
+import dev.langchain4j.memory.chat.MessageWindowChatMemory;
 import dev.langchain4j.model.chat.ChatLanguageModel;
 import dev.langchain4j.model.embedding.AllMiniLmL6V2EmbeddingModel;
 import dev.langchain4j.model.embedding.EmbeddingModel;
-import dev.langchain4j.model.input.Prompt;
 import dev.langchain4j.model.input.PromptTemplate;
 import dev.langchain4j.model.openai.OpenAiChatModel;
-import dev.langchain4j.model.openai.OpenAiTokenizer;
-import dev.langchain4j.store.embedding.EmbeddingMatch;
+import dev.langchain4j.retriever.EmbeddingStoreRetriever;
 import dev.langchain4j.store.embedding.EmbeddingStore;
+import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
 import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;

 public class ChainWithDocumentLiveTest {
+    
+    Logger logger = LoggerFactory.getLogger(ChainWithDocumentLiveTest.class);

    @Test
-    public void givenChainWithDocument_whenPrompted_thenValidResponse() {
-
-        Document document = loadDocument(toPath("src/test/resources/example-files/simpson's_adventures.txt"));
-        DocumentSplitter splitter = DocumentSplitters.recursive(100, 0, new OpenAiTokenizer(GPT_3_5_TURBO));
-        List<TextSegment> segments = splitter.split(document);
+    public void givenDocument_whenPrompted_thenValidResponse() {

        EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
-        List<Embedding> embeddings = embeddingModel.embedAll(segments)
-            .content();
+
        EmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
-        embeddingStore.addAll(embeddings, segments);

-        String question = "Who is Simpson?";
-        Embedding questionEmbedding = embeddingModel.embed(question)
-            .content();
-        int maxResults = 3;
-        double minScore = 0.7;
-        List<EmbeddingMatch<TextSegment>> relevantEmbeddings = embeddingStore.findRelevant(questionEmbedding, maxResults, minScore);
+        EmbeddingStoreIngestor ingestor = EmbeddingStoreIngestor.builder()
+            .documentSplitter(DocumentSplitters.recursive(500, 0))
+            .embeddingModel(embeddingModel)
+            .embeddingStore(embeddingStore)
+            .build();

-        PromptTemplate promptTemplate = PromptTemplate.from("Answer the following question to the best of your ability:\n" + "\n" + "Question:\n" + "{{question}}\n" + "\n" + "Base your answer on the following information:\n" + "{{information}}");
+        Document document = loadDocument(toPath("src/test/resources/example-files/simpson's_adventures.txt"));
+        ingestor.ingest(document);

-        String information = relevantEmbeddings.stream()
-            .map(match -> match.embedded()
-                .text())
-            .collect(joining("\n\n"));
-
-        Map<String, Object> variables = new HashMap<>();
-        variables.put("question", question);
-        variables.put("information", information);
-
-        Prompt prompt = promptTemplate.apply(variables);
        ChatLanguageModel chatModel = OpenAiChatModel.builder()
-            .apiKey(Constants.OPEN_API_KEY)
+            .apiKey(Constants.OPEN_AI_KEY)
            .timeout(ofSeconds(60))
            .build();
-        AiMessage aiMessage = chatModel.generate(prompt.toUserMessage())
-            .content();

-        Logger.getGlobal()
-            .info(aiMessage.text());
-        Assert.assertNotNull(aiMessage.text());
+        ConversationalRetrievalChain chain = ConversationalRetrievalChain.builder()
+            .chatLanguageModel(chatModel)
+            .retriever(EmbeddingStoreRetriever.from(embeddingStore, embeddingModel))
+            .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
+            .promptTemplate(PromptTemplate
+                .from("Answer the following question to the best of your ability: {{question}}\n\nBase your answer on the following information:\n{{information}}"))
+            .build();
+
+        String answer = chain.execute("Who is Simpson?");
+
+        logger.info(answer);
+        Assert.assertNotNull(answer);

    }

--- a/libraries-llms/src/test/java/com/baeldung/langchain/ChatWithDocumentLiveTest.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/ChatWithDocumentLiveTest.java
@ -1,7 +1,9 @@
 package com.baeldung.langchain;

 import static dev.langchain4j.data.document.FileSystemDocumentLoader.loadDocument;
+import static dev.langchain4j.model.openai.OpenAiModelName.GPT_3_5_TURBO;
 import static java.time.Duration.ofSeconds;
+import static java.util.stream.Collectors.joining;

 import java.io.File;
 import java.net.MalformedURLException;
@ -9,59 +11,77 @@ import java.net.URISyntaxException;
 import java.net.URL;
 import java.nio.file.Path;
 import java.nio.file.Paths;
-import java.util.logging.Logger;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;

 import org.junit.Assert;
 import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;

-import dev.langchain4j.chain.ConversationalRetrievalChain;
 import dev.langchain4j.data.document.Document;
+import dev.langchain4j.data.document.DocumentSplitter;
 import dev.langchain4j.data.document.splitter.DocumentSplitters;
+import dev.langchain4j.data.embedding.Embedding;
+import dev.langchain4j.data.message.AiMessage;
 import dev.langchain4j.data.segment.TextSegment;
 import dev.langchain4j.model.chat.ChatLanguageModel;
 import dev.langchain4j.model.embedding.AllMiniLmL6V2EmbeddingModel;
 import dev.langchain4j.model.embedding.EmbeddingModel;
+import dev.langchain4j.model.input.Prompt;
+import dev.langchain4j.model.input.PromptTemplate;
 import dev.langchain4j.model.openai.OpenAiChatModel;
-import dev.langchain4j.retriever.EmbeddingStoreRetriever;
+import dev.langchain4j.model.openai.OpenAiTokenizer;
+import dev.langchain4j.store.embedding.EmbeddingMatch;
 import dev.langchain4j.store.embedding.EmbeddingStore;
-import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
 import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;

 public class ChatWithDocumentLiveTest {
+    
+    Logger logger = LoggerFactory.getLogger(ChatWithDocumentLiveTest.class);

    @Test
-    public void givenDocument_whenPrompted_thenValidResponse() {
-
-        EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
-
-        EmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
-
-        EmbeddingStoreIngestor ingestor = EmbeddingStoreIngestor.builder()
-            .documentSplitter(DocumentSplitters.recursive(500, 0))
-            .embeddingModel(embeddingModel)
-            .embeddingStore(embeddingStore)
-            .build();
+    public void givenChainWithDocument_whenPrompted_thenValidResponse() {

        Document document = loadDocument(toPath("src/test/resources/example-files/simpson's_adventures.txt"));
-        ingestor.ingest(document);
+        DocumentSplitter splitter = DocumentSplitters.recursive(100, 0, new OpenAiTokenizer(GPT_3_5_TURBO));
+        List<TextSegment> segments = splitter.split(document);

+        EmbeddingModel embeddingModel = new AllMiniLmL6V2EmbeddingModel();
+        List<Embedding> embeddings = embeddingModel.embedAll(segments)
+            .content();
+        EmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
+        embeddingStore.addAll(embeddings, segments);
+
+        String question = "Who is Simpson?";
+        Embedding questionEmbedding = embeddingModel.embed(question)
+            .content();
+        int maxResults = 3;
+        double minScore = 0.7;
+        List<EmbeddingMatch<TextSegment>> relevantEmbeddings = embeddingStore.findRelevant(questionEmbedding, maxResults, minScore);
+
+        PromptTemplate promptTemplate = PromptTemplate.from("Answer the following question to the best of your ability:\n" + "\n" + "Question:\n" + "{{question}}\n" + "\n" + "Base your answer on the following information:\n" + "{{information}}");
+
+        String information = relevantEmbeddings.stream()
+            .map(match -> match.embedded()
+                .text())
+            .collect(joining("\n\n"));
+
+        Map<String, Object> variables = new HashMap<>();
+        variables.put("question", question);
+        variables.put("information", information);
+
+        Prompt prompt = promptTemplate.apply(variables);
        ChatLanguageModel chatModel = OpenAiChatModel.builder()
-            .apiKey(Constants.OPEN_API_KEY)
+            .apiKey(Constants.OPEN_AI_KEY)
            .timeout(ofSeconds(60))
            .build();
+        AiMessage aiMessage = chatModel.generate(prompt.toUserMessage())
+            .content();

-        ConversationalRetrievalChain chain = ConversationalRetrievalChain.builder()
-            .chatLanguageModel(chatModel)
-            .retriever(EmbeddingStoreRetriever.from(embeddingStore, embeddingModel))
-            // .chatMemory() // you can override default chat memory
-            // .promptTemplate() // you can override default prompt template
-            .build();
-
-        String answer = chain.execute("Who is Simpson?");
-
-        Logger.getGlobal()
-            .info(answer);
-        Assert.assertNotNull(answer);
+        logger.info(aiMessage.text());
+        Assert.assertNotNull(aiMessage.text());

    }

--- a/libraries-llms/src/test/java/com/baeldung/langchain/ChatWithMemoryLiveTest.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/ChatWithMemoryLiveTest.java
@ -9,35 +9,35 @@ import dev.langchain4j.model.openai.OpenAiTokenizer;

 import static dev.langchain4j.data.message.UserMessage.userMessage;
 import static dev.langchain4j.model.openai.OpenAiModelName.GPT_3_5_TURBO;
-
-import java.util.logging.Logger;
+import static org.assertj.core.api.Assertions.assertThat;

 import org.junit.Assert;
 import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;

 public class ChatWithMemoryLiveTest {
+    
+    Logger logger = LoggerFactory.getLogger(ChatWithMemoryLiveTest.class);

    @Test
    public void givenMemory_whenPrompted_thenValidResponse() {

-        ChatLanguageModel model = OpenAiChatModel.withApiKey(Constants.OPEN_API_KEY);
+        ChatLanguageModel model = OpenAiChatModel.withApiKey(Constants.OPEN_AI_KEY);
        ChatMemory chatMemory = TokenWindowChatMemory.withMaxTokens(300, new OpenAiTokenizer(GPT_3_5_TURBO));

        chatMemory.add(userMessage("Hello, my name is Kumar"));
        AiMessage answer = model.generate(chatMemory.messages())
            .content();
-        Logger.getGlobal()
-            .info(answer.text());
+        logger.info(answer.text());
        Assert.assertNotNull(answer.text());
        chatMemory.add(answer);

        chatMemory.add(userMessage("What is my name?"));
        AiMessage answerWithName = model.generate(chatMemory.messages())
            .content();
-        Logger.getGlobal()
-            .info(answerWithName.text());
-        Assert.assertTrue(answerWithName.text()
-            .contains("Kumar"));
+        logger.info(answerWithName.text());
+        assertThat(answerWithName.text().contains("Kumar"));
        chatMemory.add(answerWithName);

    }
--- a/libraries-llms/src/test/java/com/baeldung/langchain/Constants.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/Constants.java
@ -2,6 +2,11 @@ package com.baeldung.langchain;

 public class Constants {
    
-    public static String OPEN_API_KEY = "demo";
+    /**
+     * A limited access key for access to OpenAI language models can be generated by first
+     * registering for free at (https://platform.openai.com/signup) and then by navigating
+     * to "Create new secret key" page at (https://platform.openai.com/account/api-keys).
+     */
+    public static String OPEN_AI_KEY = "<OPEN_AI_KEY>";

 }
--- a/libraries-llms/src/test/java/com/baeldung/langchain/PromptTemplatesLiveTest.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/PromptTemplatesLiveTest.java
@ -4,9 +4,10 @@ import static dev.langchain4j.model.openai.OpenAiModelName.GPT_3_5_TURBO;

 import java.util.HashMap;
 import java.util.Map;
-import java.util.logging.Logger;

 import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;

 import dev.langchain4j.model.chat.ChatLanguageModel;
 import dev.langchain4j.model.input.Prompt;
@ -16,6 +17,8 @@ import dev.langchain4j.model.openai.OpenAiChatModel;
 import org.junit.Assert;

 public class PromptTemplatesLiveTest {
+    
+    Logger logger = LoggerFactory.getLogger(PromptTemplatesLiveTest.class);

    @Test
    public void givenPromptTemplate_whenSuppliedInput_thenValidResponse() {
@ -27,14 +30,13 @@ public class PromptTemplatesLiveTest {
        Prompt prompt = promptTemplate.apply(variables);

        ChatLanguageModel model = OpenAiChatModel.builder()
-            .apiKey(Constants.OPEN_API_KEY)
+            .apiKey(Constants.OPEN_AI_KEY)
            .modelName(GPT_3_5_TURBO)
            .temperature(0.3)
            .build();

        String response = model.generate(prompt.text());
-        Logger.getGlobal()
-            .info(response);
+        logger.info(response);
        Assert.assertNotNull(response);

    }
--- a/libraries-llms/src/test/java/com/baeldung/langchain/ServiceWithToolsLiveTest.java
+++ b/libraries-llms/src/test/java/com/baeldung/langchain/ServiceWithToolsLiveTest.java
@ -1,9 +1,11 @@
 package com.baeldung.langchain;

-import java.util.logging.Logger;
+import static org.assertj.core.api.Assertions.assertThat;

 import org.junit.Assert;
 import org.junit.Test;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;

 import dev.langchain4j.agent.tool.Tool;
 import dev.langchain4j.memory.chat.MessageWindowChatMemory;
@ -11,6 +13,8 @@ import dev.langchain4j.model.openai.OpenAiChatModel;
 import dev.langchain4j.service.AiServices;

 public class ServiceWithToolsLiveTest {
+    
+    Logger logger = LoggerFactory.getLogger(ServiceWithToolsLiveTest.class);

    static class Calculator {

@ -35,7 +39,7 @@ public class ServiceWithToolsLiveTest {
    public void givenServiceWithTools_whenPrompted_thenValidResponse() {

        Assistant assistant = AiServices.builder(Assistant.class)
-            .chatLanguageModel(OpenAiChatModel.withApiKey(Constants.OPEN_API_KEY))
+            .chatLanguageModel(OpenAiChatModel.withApiKey(Constants.OPEN_AI_KEY))
            .tools(new Calculator())
            .chatMemory(MessageWindowChatMemory.withMaxMessages(10))
            .build();
@ -43,9 +47,8 @@ public class ServiceWithToolsLiveTest {
        String question = "What is the sum of the numbers of letters in the words \"language\" and \"model\"?";
        String answer = assistant.chat(question);

-        Logger.getGlobal()
-            .info(answer);
-        Assert.assertNotNull(answer);
+        logger.info(answer);
+        assertThat(answer).contains("13");

    }

--- a/pom.xml
+++ b/pom.xml
@ -936,7 +936,7 @@
                <module>spring-di-4</module>
                <module>spring-kafka-2</module>
                <!--<module>java-panama</module> Java-19 module-->
-				<module>libraries-llms</module>
+                <module>libraries-llms</module>
            </modules>

            <properties>
@ -1224,7 +1224,7 @@
                <module>spring-di-4</module>
                <module>spring-kafka-2</module>
                <!--<module>java-panama</module> Java-19 module-->
-				<module>libraries-llms</module>
+                <module>libraries-llms</module>
            </modules>

            <properties>