adding detailed tests for chat.

Author: Vaijanath Rao

src/test/java/de/kherud/llama/LlamaChatModelTest.java

@@ -8,22 +8,20 @@
 import org.junit.Test;
 import org.junit.Assert;
 
-
 public class LlamaChatModelTest {
-	
+
 	private static LlamaModel model;
-	
+
 	@BeforeClass
 	public static void setup() {
-//		LlamaModel.setLogger(LogFormat.TEXT, (level, msg) -> System.out.println(level + ": " + msg));
 		model = new LlamaModel(
-				new ModelParameters()
+					new ModelParameters()
 						.setCtxSize(128)
 						.setModel("models/codellama-7b.Q2_K.gguf")
-						//.setModelUrl("https://huggingface.co/TheBloke/CodeLlama-7B-GGUF/resolve/main/codellama-7b.Q2_K.gguf")
 						.setGpuLayers(43)
-						.enableEmbedding().enableLogTimestamps().enableLogPrefix()
-		);
+						.enableLogTimestamps()
+						.enableLogPrefix()
+				);
 	}
 
 	@AfterClass
@@ -32,42 +30,91 @@ public static void tearDown() {
 			model.close();
 		}
 	}
+
+	@Test
+	public void testMultiTurnChat() {
+	    List<Pair<String, String>> userMessages = new ArrayList<>();
+	    userMessages.add(new Pair<>("user", "Recommend a good ML book."));
+	    
+	    InferenceParameters params = new InferenceParameters("")
+	            .setMessages("You are a Book Recommendation System", userMessages)
+	            .setTemperature(0.7f)
+	            .setNPredict(50);
+
+	    String response1 = model.completeChat(params);
+	    Assert.assertNotNull(response1);
+	    
+	    userMessages.add(new Pair<>("assistant", response1));
+	    userMessages.add(new Pair<>("user", "How does it compare to 'Hands-on ML'?"));
+
+	    params.setMessages("Book", userMessages);
+	    String response2 = model.completeChat(params);
+
+	    Assert.assertNotNull(response2);
+	    Assert.assertNotEquals(response1, response2);
+	}
 
 	@Test
-	public void testChat() {
-		List<Pair<String, String>> userMessages = new ArrayList<>();
-        userMessages.add(new Pair<>("user", "What is the best book for machine learning?"));
-        
-        InferenceParameters params = new InferenceParameters("A book recommendation system.")
-				.setMessages("Book", userMessages)
-				.setTemperature(0.0f)
-				.setStopStrings("\"\"\"")
-				.setNPredict(10)
-				.setSeed(42);
-        
-        String assistantResponse = model.completeChat(params);
-        
-        Assert.assertNotNull(assistantResponse);
-        
-        Assert.assertEquals(params.get("prompt"), "\"<|im_start|>system\\nBook<|im_end|>\\n<|im_start|>user\\nWhat is the best book for machine learning?<|im_end|>\\n<|im_start|>assistant\\n\"");
-        
-        userMessages.add(new Pair<>("assistant", assistantResponse));
-        userMessages.add(new Pair<>("user", "that is great book for machine learning?, what about linear algebra"));
-        
-        params = new InferenceParameters("A book recommendation system.")
-				.setMessages("Book", userMessages)
-				.setTemperature(0.0f)
-				.setStopStrings("\"\"\"")
-				.setNPredict(10)
-				.setSeed(42);
-        
-        
-        assistantResponse = model.completeChat(params);
-        Assert.assertNotNull(assistantResponse);
-        
-        Assert.assertEquals(params.get("prompt"), "\"<|im_start|>system\\nBook<|im_end|>\\n<|im_start|>user\\nWhat is the best book for machine learning?<|im_end|>\\n<|im_start|>assistant\\nWhat is the best book for machine learning?<<|im_end|>\\n<|im_start|>user\\nthat is great book for machine learning?, what about linear algebra<|im_end|>\\n<|im_start|>assistant\\n\"");
-        
-        
+	public void testEmptyInput() {
+	    List<Pair<String, String>> userMessages = new ArrayList<>();
+	    userMessages.add(new Pair<>("user", ""));
+
+	    InferenceParameters params = new InferenceParameters("A book recommendation system.")
+	            .setMessages("Book", userMessages)
+	            .setTemperature(0.5f)
+	            .setNPredict(20);
+
+	    String response = model.completeChat(params);
+	    Assert.assertNotNull(response);
+	    Assert.assertFalse(response.isEmpty());
+	}
+	
+	@Test
+	public void testStopString() {
+	    List<Pair<String, String>> userMessages = new ArrayList<>();
+	    userMessages.add(new Pair<>("user", "Tell me about AI ethics."));
+
+	    InferenceParameters params = new InferenceParameters("A book recommendation system.")
+	            .setMessages("AI", userMessages)
+	            .setStopStrings("\"\"\"") // Ensures stopping at proper place
+	            .setTemperature(0.7f)
+	            .setNPredict(50);
+
+	    String response = model.completeChat(params);
+	    Assert.assertNotNull(response);
+	    Assert.assertFalse(response.contains("\"\"\""));
+	}
+	
+	@Test
+	public void testFixedSeed() {
+	    List<Pair<String, String>> userMessages = new ArrayList<>();
+	    userMessages.add(new Pair<>("user", "What is reinforcement learning?"));
+
+	    InferenceParameters params = new InferenceParameters("AI Chatbot.")
+	            .setMessages("AI", userMessages)
+	            .setTemperature(0.7f)
+	            .setSeed(42) // Fixed seed for reproducibility
+	            .setNPredict(50);
+
+	    String response1 = model.completeChat(params);
+	    String response2 = model.completeChat(params);
+
+	    Assert.assertEquals(response1, response2); // Responses should be identical
+	}
+	
+	@Test
+	public void testNonEnglishInput() {
+	    List<Pair<String, String>> userMessages = new ArrayList<>();
+	    userMessages.add(new Pair<>("user", "Quel est le meilleur livre sur l'apprentissage automatique ?"));
+
+	    InferenceParameters params = new InferenceParameters("A book recommendation system.")
+	            .setMessages("Book", userMessages)
+	            .setTemperature(0.7f)
+	            .setNPredict(50);
+
+	    String response = model.completeChat(params);
+	    Assert.assertNotNull(response);
+	    Assert.assertTrue(response.length() > 5); // Ensure some response is generated
 	}
 
 }