a987e0305a
- Introduce FactCheckingEvaluator class for LLM response validation - Implement evaluation logic using ChatClient for fact-checking - Add comprehensive JavaDoc explaining the evaluator's purpose and usage - Reference Bespoke-Minicheck model for efficient implementation options - Include links to Ollama blog post and MiniCheck research paper - Distinguish from 'closed book' scenario testing in documentation This new evaluator enables detection and reduction of hallucinations in LLM outputs by checking claims against provided context. It provides a foundation for implementing advanced fact-checking methodologies in Spring AI applications. See https://ollama.com/blog/reduce-hallucinations-with-bespoke-minicheck
66 lines
3.0 KiB
Plaintext
66 lines
3.0 KiB
Plaintext
diff --git a/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatModel.java b/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatModel.java
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index c6d689e6..6168ea55 100644
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--- a/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatModel.java
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+++ b/models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatModel.java
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@@ -211,13 +211,18 @@ public class OllamaChatModel extends AbstractToolCallSupport implements ChatMode
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Flux<ChatResponse> chatResponse = ollamaResponse.map(chunk -> {
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String content = (chunk.message() != null) ? chunk.message().content() : "";
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- List<AssistantMessage.ToolCall> toolCalls = chunk.message().toolCalls() == null ? List.of()
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- : chunk.message()
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- .toolCalls()
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- .stream()
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- .map(toolCall -> new AssistantMessage.ToolCall("", "function", toolCall.function().name(),
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- ModelOptionsUtils.toJsonString(toolCall.function().arguments())))
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- .toList();
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+
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+ List<AssistantMessage.ToolCall> toolCalls = List.of();
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+
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+ // Added null checks to prevent NPE when accessing tool calls
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+ if (chunk.message() != null && chunk.message().toolCalls() != null) {
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+ toolCalls = chunk.message()
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+ .toolCalls()
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+ .stream()
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+ .map(toolCall -> new AssistantMessage.ToolCall("", "function", toolCall.function().name(),
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+ ModelOptionsUtils.toJsonString(toolCall.function().arguments())))
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+ .toList();
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+ }
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var assistantMessage = new AssistantMessage(content, Map.of(), toolCalls);
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diff --git a/models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelMultimodalIT.java b/models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelMultimodalIT.java
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index f58552f8..4dffc7d2 100644
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--- a/models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelMultimodalIT.java
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+++ b/models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelMultimodalIT.java
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@@ -40,6 +40,7 @@ import java.io.IOException;
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import java.util.List;
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import static org.assertj.core.api.Assertions.assertThat;
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+import static org.junit.Assert.assertThrows;
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@SpringBootTest
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@Testcontainers
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@@ -67,6 +68,18 @@ class OllamaChatModelMultimodalIT extends BaseOllamaIT {
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@Autowired
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private OllamaChatModel chatModel;
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+ @Test
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+ void unsupportedMediaType() throws IOException {
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+
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+ var imageData = new ClassPathResource("/norway.webp");
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+
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+ var userMessage = new UserMessage("Explain what do you see on this picture?",
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+ List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
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+
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+ assertThrows(RuntimeException.class, () -> chatModel.call(new Prompt(List.of(userMessage))));
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+
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+ }
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+
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@Test
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void multiModalityTest() throws IOException {
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diff --git a/models/spring-ai-ollama/src/test/resources/norway.webp b/models/spring-ai-ollama/src/test/resources/norway.webp
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new file mode 100644
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index 00000000..0da983e2
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Binary files /dev/null and b/models/spring-ai-ollama/src/test/resources/norway.webp differ
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