(improvement)[build] Use Spotless to customize the code formatting (#1750)

2025-12-11 20:25:12 +00:00 · 2024-10-04 00:05:04 +08:00
parent 44d1cde34f
commit 71a9954be5
521 changed files with 7811 additions and 13046 deletions
--- a/common/src/main/java/dev/langchain4j/model/openai/OpenAiChatModel.java
+++ b/common/src/main/java/dev/langchain4j/model/openai/OpenAiChatModel.java
@@ -60,8 +60,8 @@ import static java.util.Collections.singletonList;

 /**
 * Represents an OpenAI language model with a chat completion interface, such as gpt-3.5-turbo and
- * gpt-4. You can find description of parameters <a
- * href="https://platform.openai.com/docs/api-reference/chat/create">here</a>.
+ * gpt-4. You can find description of parameters
+ * <a href="https://platform.openai.com/docs/api-reference/chat/create">here</a>.
 */
@Slf4j
 public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
@@ -88,32 +88,13 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
    private final List<ChatModelListener> listeners;

    @Builder
-    public OpenAiChatModel(
-            String baseUrl,
-            String apiKey,
-            String organizationId,
-            String modelName,
-            Double temperature,
-            Double topP,
-            List<String> stop,
-            Integer maxTokens,
-            Double presencePenalty,
-            Double frequencyPenalty,
-            Map<String, Integer> logitBias,
-            String responseFormat,
-            Boolean strictJsonSchema,
-            Integer seed,
-            String user,
-            Boolean strictTools,
-            Boolean parallelToolCalls,
-            Duration timeout,
-            Integer maxRetries,
-            Proxy proxy,
-            Boolean logRequests,
-            Boolean logResponses,
-            Tokenizer tokenizer,
-            Map<String, String> customHeaders,
-            List<ChatModelListener> listeners) {
+    public OpenAiChatModel(String baseUrl, String apiKey, String organizationId, String modelName,
+            Double temperature, Double topP, List<String> stop, Integer maxTokens,
+            Double presencePenalty, Double frequencyPenalty, Map<String, Integer> logitBias,
+            String responseFormat, Boolean strictJsonSchema, Integer seed, String user,
+            Boolean strictTools, Boolean parallelToolCalls, Duration timeout, Integer maxRetries,
+            Proxy proxy, Boolean logRequests, Boolean logResponses, Tokenizer tokenizer,
+            Map<String, String> customHeaders, List<ChatModelListener> listeners) {

        baseUrl = getOrDefault(baseUrl, OPENAI_URL);
        if (OPENAI_DEMO_API_KEY.equals(apiKey)) {
@@ -123,21 +104,11 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {

        timeout = getOrDefault(timeout, ofSeconds(60));

-        this.client =
-                OpenAiClient.builder()
-                        .openAiApiKey(apiKey)
-                        .baseUrl(baseUrl)
-                        .organizationId(organizationId)
-                        .callTimeout(timeout)
-                        .connectTimeout(timeout)
-                        .readTimeout(timeout)
-                        .writeTimeout(timeout)
-                        .proxy(proxy)
-                        .logRequests(logRequests)
-                        .logResponses(logResponses)
-                        .userAgent(DEFAULT_USER_AGENT)
-                        .customHeaders(customHeaders)
-                        .build();
+        this.client = OpenAiClient.builder().openAiApiKey(apiKey).baseUrl(baseUrl)
+                .organizationId(organizationId).callTimeout(timeout).connectTimeout(timeout)
+                .readTimeout(timeout).writeTimeout(timeout).proxy(proxy).logRequests(logRequests)
+                .logResponses(logResponses).userAgent(DEFAULT_USER_AGENT)
+                .customHeaders(customHeaders).build();
        this.modelName = getOrDefault(modelName, GPT_3_5_TURBO);
        this.temperature = getOrDefault(temperature, 0.7);
        this.topP = topP;
@@ -146,14 +117,10 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
        this.presencePenalty = presencePenalty;
        this.frequencyPenalty = frequencyPenalty;
        this.logitBias = logitBias;
-        this.responseFormat =
-                responseFormat == null
-                        ? null
-                        : ResponseFormat.builder()
-                                .type(
-                                        ResponseFormatType.valueOf(
-                                                responseFormat.toUpperCase(Locale.ROOT)))
-                                .build();
+        this.responseFormat = responseFormat == null ? null
+                : ResponseFormat.builder()
+                        .type(ResponseFormatType.valueOf(responseFormat.toUpperCase(Locale.ROOT)))
+                        .build();
        this.strictJsonSchema = getOrDefault(strictJsonSchema, false);
        this.seed = seed;
        this.user = user;
@@ -183,61 +150,44 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
    }

    @Override
-    public Response<AiMessage> generate(
-            List<ChatMessage> messages, List<ToolSpecification> toolSpecifications) {
+    public Response<AiMessage> generate(List<ChatMessage> messages,
+            List<ToolSpecification> toolSpecifications) {
        return generate(messages, toolSpecifications, null, this.responseFormat);
    }

    @Override
-    public Response<AiMessage> generate(
-            List<ChatMessage> messages, ToolSpecification toolSpecification) {
-        return generate(
-                messages, singletonList(toolSpecification), toolSpecification, this.responseFormat);
+    public Response<AiMessage> generate(List<ChatMessage> messages,
+            ToolSpecification toolSpecification) {
+        return generate(messages, singletonList(toolSpecification), toolSpecification,
+                this.responseFormat);
    }

    @Override
    public ChatResponse chat(ChatRequest request) {
        Response<AiMessage> response =
-                generate(
-                        request.messages(),
-                        request.toolSpecifications(),
-                        null,
+                generate(request.messages(), request.toolSpecifications(), null,
                        getOrDefault(
                                toOpenAiResponseFormat(request.responseFormat(), strictJsonSchema),
                                this.responseFormat));
-        return ChatResponse.builder()
-                .aiMessage(response.content())
-                .tokenUsage(response.tokenUsage())
-                .finishReason(response.finishReason())
-                .build();
+        return ChatResponse.builder().aiMessage(response.content())
+                .tokenUsage(response.tokenUsage()).finishReason(response.finishReason()).build();
    }

-    private Response<AiMessage> generate(
-            List<ChatMessage> messages,
-            List<ToolSpecification> toolSpecifications,
-            ToolSpecification toolThatMustBeExecuted,
+    private Response<AiMessage> generate(List<ChatMessage> messages,
+            List<ToolSpecification> toolSpecifications, ToolSpecification toolThatMustBeExecuted,
            ResponseFormat responseFormat) {

-        if (responseFormat != null
-                && responseFormat.type() == JSON_SCHEMA
+        if (responseFormat != null && responseFormat.type() == JSON_SCHEMA
                && responseFormat.jsonSchema() == null) {
            responseFormat = null;
        }

-        ChatCompletionRequest.Builder requestBuilder =
-                ChatCompletionRequest.builder()
-                        .model(modelName)
-                        .messages(toOpenAiMessages(messages))
-                        .topP(topP)
-                        .stop(stop)
-                        .maxTokens(maxTokens)
-                        .presencePenalty(presencePenalty)
-                        .frequencyPenalty(frequencyPenalty)
-                        .logitBias(logitBias)
-                        .responseFormat(responseFormat)
-                        .seed(seed)
-                        .user(user)
-                        .parallelToolCalls(parallelToolCalls);
+        ChatCompletionRequest.Builder requestBuilder = ChatCompletionRequest.builder()
+                .model(modelName).messages(toOpenAiMessages(messages)).topP(topP).stop(stop)
+                .maxTokens(maxTokens).presencePenalty(presencePenalty)
+                .frequencyPenalty(frequencyPenalty).logitBias(logitBias)
+                .responseFormat(responseFormat).seed(seed).user(user)
+                .parallelToolCalls(parallelToolCalls);

        if (!(baseUrl.contains(ZHIPU))) {
            requestBuilder.temperature(temperature);
@@ -257,40 +207,33 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
        Map<Object, Object> attributes = new ConcurrentHashMap<>();
        ChatModelRequestContext requestContext =
                new ChatModelRequestContext(modelListenerRequest, attributes);
-        listeners.forEach(
-                listener -> {
-                    try {
-                        listener.onRequest(requestContext);
-                    } catch (Exception e) {
-                        log.warn("Exception while calling model listener", e);
-                    }
-                });
+        listeners.forEach(listener -> {
+            try {
+                listener.onRequest(requestContext);
+            } catch (Exception e) {
+                log.warn("Exception while calling model listener", e);
+            }
+        });

        try {
            ChatCompletionResponse chatCompletionResponse =
                    withRetry(() -> client.chatCompletion(request).execute(), maxRetries);

-            Response<AiMessage> response =
-                    Response.from(
-                            aiMessageFrom(chatCompletionResponse),
-                            tokenUsageFrom(chatCompletionResponse.usage()),
-                            finishReasonFrom(
-                                    chatCompletionResponse.choices().get(0).finishReason()));
+            Response<AiMessage> response = Response.from(aiMessageFrom(chatCompletionResponse),
+                    tokenUsageFrom(chatCompletionResponse.usage()),
+                    finishReasonFrom(chatCompletionResponse.choices().get(0).finishReason()));

-            ChatModelResponse modelListenerResponse =
-                    createModelListenerResponse(
-                            chatCompletionResponse.id(), chatCompletionResponse.model(), response);
-            ChatModelResponseContext responseContext =
-                    new ChatModelResponseContext(
-                            modelListenerResponse, modelListenerRequest, attributes);
-            listeners.forEach(
-                    listener -> {
-                        try {
-                            listener.onResponse(responseContext);
-                        } catch (Exception e) {
-                            log.warn("Exception while calling model listener", e);
-                        }
-                    });
+            ChatModelResponse modelListenerResponse = createModelListenerResponse(
+                    chatCompletionResponse.id(), chatCompletionResponse.model(), response);
+            ChatModelResponseContext responseContext = new ChatModelResponseContext(
+                    modelListenerResponse, modelListenerRequest, attributes);
+            listeners.forEach(listener -> {
+                try {
+                    listener.onResponse(responseContext);
+                } catch (Exception e) {
+                    log.warn("Exception while calling model listener", e);
+                }
+            });

            return response;
        } catch (RuntimeException e) {
@@ -305,14 +248,13 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
            ChatModelErrorContext errorContext =
                    new ChatModelErrorContext(error, modelListenerRequest, null, attributes);

-            listeners.forEach(
-                    listener -> {
-                        try {
-                            listener.onError(errorContext);
-                        } catch (Exception e2) {
-                            log.warn("Exception while calling model listener", e2);
-                        }
-                    });
+            listeners.forEach(listener -> {
+                try {
+                    listener.onError(errorContext);
+                } catch (Exception e2) {
+                    log.warn("Exception while calling model listener", e2);
+                }
+            });

            throw e;
        }
@@ -328,8 +270,8 @@ public class OpenAiChatModel implements ChatLanguageModel, TokenCountEstimator {
    }

    public static OpenAiChatModelBuilder builder() {
-        for (OpenAiChatModelBuilderFactory factory :
-                loadFactories(OpenAiChatModelBuilderFactory.class)) {
+        for (OpenAiChatModelBuilderFactory factory : loadFactories(
+                OpenAiChatModelBuilderFactory.class)) {
            return factory.get();
        }
        return new OpenAiChatModelBuilder();