Merge branch 'main' into feature/model-client-deepseek

.github/workflows/source-code-format-check.yml

@@ -0,0 +1,25 @@
+name: Source Code Format
+
+on:
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  build:
+    name: Build branch
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout source code
+        uses: actions/checkout@v4
+
+      - name: Set up JDK 17
+        uses: actions/setup-java@v4
+        with:
+          java-version: '17'
+          distribution: 'temurin'
+          cache: 'maven'
+
+      - name: Source code formatting check
+        run: |
+          ./mvnw spring-javaformat:validate

README.md

@@ -8,6 +8,20 @@ Let's make your `@Beans` intelligent!
 
 For further information go to our [Spring AI reference documentation](https://docs.spring.io/spring-ai/reference/).
 
+### Breaking changes
+(15.05.2024)
+On our march to release 1.0 M1 we have made several breaking changes.  Apologies, it is for the best!
+
+Renamed POM artifact names:
+ - spring-ai-qdrant -> spring-ai-qdrant-store
+ - spring-ai-cassandra -> spring-ai-cassandra-store
+ - spring-ai-pinecone -> spring-ai-pinecone-store
+ - spring-ai-redis -> spring-ai-redis-store
+ - spring-ai-qdrant -> spring-ai-qdrant-store
+ - spring-ai-gemfire -> spring-ai-gemfire-store
+ - spring-ai-azure-vector-store-spring-boot-starter -> spring-ai-azure-store-spring-boot-starter
+ - spring-ai-redis-spring-boot-starter -> spring-ai-redis-store-spring-boot-starter
+
 ## Project Links
 
 * [Documentation](https://docs.spring.io/spring-ai/reference/)
@@ -94,6 +108,7 @@ Spring AI supports many AI models.  For an overview see here.  Specific models c
 * Transformers (ONNX)
 * Anthropic Claude3
 * DeepSeek
+* MiniMax
 
 
 **Prompts:** Central to AI model interaction is the Prompt, which provides specific instructions for the AI to act upon.

models/spring-ai-anthropic/src/main/java/org/springframework/ai/anthropic/AnthropicChatClient.java

@@ -450,4 +450,11 @@ protected boolean isToolFunctionCall(ResponseEntity<ChatCompletion> response) {
 		return response.getBody().content().stream().anyMatch(content -> content.type() == MediaContent.Type.TOOL_USE);
 	}
 
+	@Override
+	protected Flux<ResponseEntity<ChatCompletion>> doChatCompletionStream(ChatCompletionRequest request) {
+		// https://docs.anthropic.com/en/docs/tool-use
+		throw new UnsupportedOperationException(
+				"Streaming (stream=true) is not yet supported. We plan to add streaming support in a future beta version.");
+	}
+
 }

models/spring-ai-anthropic/src/main/java/org/springframework/ai/anthropic/api/AnthropicApi.java

@@ -29,6 +29,7 @@
 import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.ai.retry.RetryUtils;
 import org.springframework.http.HttpHeaders;
+import org.springframework.http.HttpStatusCode;
 import org.springframework.http.MediaType;
 import org.springframework.http.ResponseEntity;
 import org.springframework.util.Assert;
@@ -100,7 +101,13 @@ public AnthropicApi(String baseUrl, String anthropicApiKey, String anthropicVers
 			.defaultStatusHandler(responseErrorHandler)
 			.build();
 
-		this.webClient = WebClient.builder().baseUrl(baseUrl).defaultHeaders(jsonContentHeaders).build();
+		this.webClient = WebClient.builder()
+			.baseUrl(baseUrl)
+			.defaultHeaders(jsonContentHeaders)
+			.defaultStatusHandler(HttpStatusCode::isError,
+					resp -> Mono.just(new RuntimeException("Response exception, Status: [" + resp.statusCode()
+							+ "], Body:[" + resp.bodyToMono(java.lang.String.class) + "]")))
+			.build();
 	}
 
 	/**

models/spring-ai-anthropic/src/test/java/org/springframework/ai/anthropic/AnthropicChatClientIT.java

@@ -182,12 +182,12 @@ void beanStreamOutputConverterRecords() {
 	@Test
 	void multiModalityTest() throws IOException {
 
-		byte[] imageData = new ClassPathResource("/test.png").getContentAsByteArray();
+		var imageData = new ClassPathResource("/test.png");
 
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		ChatResponse response = chatClient.call(new Prompt(List.of(userMessage)));
+		var response = chatClient.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");
@@ -205,15 +205,15 @@ void functionCallTest() {
 			.withModel(AnthropicApi.ChatModel.CLAUDE_3_OPUS.getValue())
 			.withFunctionCallbacks(List.of(FunctionCallbackWrapper.builder(new MockWeatherService())
 				.withName("getCurrentWeather")
-				.withDescription("Get the weather in location")
+				.withDescription("Get the weather in location. Return temperature in 36°F or 36°C format.")
 				.build()))
 			.build();
 
 		ChatResponse response = chatClient.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
-		Generation generation = response.getResults().get(0);
+		Generation generation = response.getResult();
 		assertThat(generation.getOutput().getContent()).containsAnyOf("30.0", "30");
 		assertThat(generation.getOutput().getContent()).containsAnyOf("10.0", "10");
 		assertThat(generation.getOutput().getContent()).containsAnyOf("15.0", "15");