feat: v1.0.0-beta.2 - ExtensionGetter integration, UI revamp, bug fixes
- Replace cross-ClassLoader reflection with ExtensionGetter.getEnabledExtension(AiModelService.class) - Declare optional pluginDependencies (ai-foundation?: "*") and recommended-apps annotation - Use OutputSpec.choice for structured classification (sentiment, review safety/quality) - Use GenerateTextRequest with maxRetries=2 for reliable chat generation - Add multi-turn conversation context (conversation_history placeholder) - Fix RateLimitService thread leak (implement DisposableBean) - Two-stage AI review: safety check + 1-5 quality score mapped to 0-100 - Remove redundant dashboard cards (sentiment distribution, 7-day trend, avg score) - Redesign settings page with tabbed navigation (basic/persona/model/prompt/cleanup) - Fix settings layout (move tab bar out of grid container) - Fix button icon+text alignment via :deep(.btn-content) inline-flex - Add review score grade labels (excellent/good/fair/poor) in logs
This commit is contained in:
sunny-335
@@ -2,7 +2,7 @@
|
||||
|
||||
基于 AI 的 Halo 博客评论自动回复插件，支持多 AI 角色、自审核、自动发布和对话式连续回复。
|
||||
|
||||
> **当前版本**: v1.0.0-beta.1
|
||||
> **当前版本**: v1.0.0-beta.2
|
||||
|
||||
## 功能特性
|
||||
|
||||
@@ -70,6 +70,26 @@ pnpm dev
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v1.0.0-beta.2
|
||||
|
||||
**改进**
|
||||
|
||||
- 通过 Halo 官方推荐的 `ExtensionGetter` 获取 AI Foundation 的 `AiModelService`，替换原先的跨 ClassLoader 反射调用方式
|
||||
- 在 `plugin.yaml` 中声明可选插件依赖 `ai-foundation?: "*"`，建立正确的插件依赖关系
|
||||
- 新增 `store.halo.run/recommended-apps` 注解，安装后可在应用市场推荐安装 AI Foundation 插件
|
||||
- 情感分析和内容审核改用 AI Foundation 结构化输出（`OutputSpec.choice`），分类更可靠
|
||||
- AI 调用改用 `GenerateTextRequest` 并设置 `maxRetries=2`，由 SDK 自动重试瞬时错误
|
||||
- AI 对话续接时自动获取之前的回复历史并注入到 Prompt 中，AI 能更好地理解对话上下文
|
||||
- 优化 AI 自审核评分机制：改为两阶段评估（安全检查 + 质量评分 1-5 分），评分映射到 0-100 分，替代原先的二值评分
|
||||
- 精简仪表盘：移除情感分布、近7日回复趋势、平均审核评分三个卡片，界面更简洁
|
||||
- 优化设置页面布局：按钮统一排版并添加图标，侧边栏新增"未保存"状态指示器
|
||||
- 优化日志页面评分显示：评分增加等级标签（优秀/良好/一般/较差）
|
||||
|
||||
**Bug 修复**
|
||||
|
||||
- 修复 RateLimitService 清理线程在插件停止时未关闭导致线程泄漏
|
||||
- 修复内容审核提示词要求"重新生成"但代码未使用重新生成内容的问题
|
||||
|
||||
### v1.0.0-beta.1
|
||||
|
||||
**新功能**
|
||||
|
||||
+1
-1
@@ -5,7 +5,7 @@ plugins {
|
||||
}
|
||||
|
||||
group 'top.nxxy335.commentaiautopilot'
|
||||
version '1.0.0-beta.1'
|
||||
version '1.0.0-beta.2-kx7m2p'
|
||||
|
||||
repositories {
|
||||
mavenCentral()
|
||||
|
||||
@@ -1,5 +1,30 @@
|
||||
# 更新日志
|
||||
|
||||
## v1.0.0-beta.2
|
||||
|
||||
> 2026-06-17
|
||||
|
||||
### 改进
|
||||
|
||||
- **改用 ExtensionGetter 集成 AI Foundation**：通过 Halo 官方推荐的 `ExtensionGetter.getEnabledExtension(AiModelService.class)` 获取 AI 服务，替换原先的跨 ClassLoader 反射调用方式（[Issue #1](https://github.com/sunny-335/plugin-comment-ai-autopilot/issues/1)）
|
||||
- **声明插件依赖**：在 `plugin.yaml` 中声明可选插件依赖 `ai-foundation?: "*"`，建立正确的插件依赖关系，插件在未安装 AI Foundation 时仍可正常加载
|
||||
- **应用市场推荐**：新增 `store.halo.run/recommended-apps` 注解，安装本插件后可在应用市场推荐安装 AI Foundation 插件
|
||||
- **使用结构化输出**：情感分析和内容审核改用 AI Foundation 的 `OutputSpec.choice` 结构化输出，替换原先的字符串匹配解析，分类更可靠
|
||||
- **使用 GenerateTextRequest**：AI 调用改用 `GenerateTextRequest` 并设置 `maxRetries=2`，由 SDK 自动重试瞬时错误
|
||||
- **简化 languageModel 调用**：直接传递 modelName 参数，由 SDK 处理空值（使用默认模型），无需手动判断
|
||||
- **多轮对话上下文**：AI 对话续接时自动获取之前的回复历史并注入到 Prompt 中，AI 能更好地理解对话上下文
|
||||
- **优化 AI 自审核评分机制**：审核改为两阶段评估（安全检查 + 质量评分 1-5 分），评分映射到 0-100 分（0/30/50/70/85/100），替代原先的二值评分（0/100），评分更有区分度
|
||||
- **精简仪表盘**：移除情感分布、近7日回复趋势、平均审核评分三个卡片，保留核心的回复概览和快捷操作，界面更简洁
|
||||
- **优化设置页面布局**：页面头部按钮使用 VSpace 统一排版并添加图标；侧边栏保存卡片高亮显示，新增"未保存"状态指示器；保存/重置按钮添加图标
|
||||
- **优化日志页面评分显示**：评分增加等级标签（优秀/良好/一般/较差），更直观
|
||||
|
||||
### Bug 修复
|
||||
|
||||
- **修复 RateLimitService 线程泄漏**：清理线程未在插件停止时关闭，实现 `DisposableBean` 正确释放资源
|
||||
- **修复 ReviewService 提示词不匹配**：审核提示词要求"重新生成"但代码未使用重新生成的内容，移除误导性指令
|
||||
|
||||
---
|
||||
|
||||
## v1.0.0-beta.1
|
||||
|
||||
> 2026-06-16
|
||||
|
||||
+4
-84
@@ -216,100 +216,25 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
|
||||
}
|
||||
|
||||
private Mono<ServerResponse> getStats(ServerRequest request) {
|
||||
String range = request.queryParam("range").orElse("7");
|
||||
|
||||
return client.listAll(AiCommentReply.class, ListOptions.builder().build(), Sort.unsorted())
|
||||
.collectList()
|
||||
.map(allReplies -> {
|
||||
// 根据 range 计算截止时间
|
||||
ZoneId zoneId = ZoneId.systemDefault();
|
||||
LocalDate today = LocalDate.now(zoneId);
|
||||
Instant cutoffInstant;
|
||||
int trendDays;
|
||||
|
||||
if ("all".equals(range)) {
|
||||
cutoffInstant = null; // 不做时间过滤
|
||||
trendDays = 30; // "all" 时趋势也展示最近30天
|
||||
} else {
|
||||
int days = Integer.parseInt(range);
|
||||
cutoffInstant = today.minusDays(days).atStartOfDay(zoneId).toInstant();
|
||||
trendDays = days;
|
||||
}
|
||||
|
||||
// 根据 range 过滤记录
|
||||
List<AiCommentReply> replies;
|
||||
if (cutoffInstant != null) {
|
||||
replies = allReplies.stream()
|
||||
.filter(r -> {
|
||||
Instant ts = r.getMetadata().getCreationTimestamp();
|
||||
return ts != null && !ts.isBefore(cutoffInstant);
|
||||
})
|
||||
.toList();
|
||||
} else {
|
||||
replies = allReplies;
|
||||
}
|
||||
|
||||
.map(replies -> {
|
||||
long total = replies.size();
|
||||
long passCount = replies.stream()
|
||||
.filter(r -> "PASS".equals(r.getSpec().getStatus())).count();
|
||||
long failCount = replies.stream()
|
||||
.filter(r -> "FAIL".equals(r.getSpec().getStatus())).count();
|
||||
double avgScore = replies.stream()
|
||||
.filter(r -> r.getSpec().getScore() != null && r.getSpec().getScore() > 0)
|
||||
.mapToInt(r -> r.getSpec().getScore())
|
||||
.average().orElse(0.0);
|
||||
|
||||
long reviewingCount = replies.stream()
|
||||
.filter(r -> "PASS".equals(r.getSpec().getStatus())
|
||||
&& !Boolean.TRUE.equals(r.getSpec().getPublished()))
|
||||
.count();
|
||||
|
||||
Map<String, Long> sentimentDistribution = new HashMap<>();
|
||||
sentimentDistribution.put("POSITIVE", 0L);
|
||||
sentimentDistribution.put("NEUTRAL", 0L);
|
||||
sentimentDistribution.put("NEGATIVE", 0L);
|
||||
sentimentDistribution.put("UNKNOWN", 0L);
|
||||
for (var r : replies) {
|
||||
String sentiment = r.getSpec().getSentiment();
|
||||
if (sentiment == null || sentiment.isBlank()) {
|
||||
sentimentDistribution.merge("UNKNOWN", 1L, Long::sum);
|
||||
} else {
|
||||
sentimentDistribution.merge(sentiment, 1L, Long::sum);
|
||||
}
|
||||
}
|
||||
|
||||
// 计算 dailyTrend
|
||||
DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd");
|
||||
Map<LocalDate, Long> dailyMap = new HashMap<>();
|
||||
for (int i = 0; i < trendDays; i++) {
|
||||
dailyMap.put(today.minusDays(i), 0L);
|
||||
}
|
||||
for (var r : replies) {
|
||||
Instant timestamp = r.getMetadata().getCreationTimestamp();
|
||||
if (timestamp != null) {
|
||||
try {
|
||||
LocalDate date = timestamp.atZone(zoneId).toLocalDate();
|
||||
if (dailyMap.containsKey(date)) {
|
||||
dailyMap.merge(date, 1L, Long::sum);
|
||||
}
|
||||
} catch (Exception ignored) {
|
||||
}
|
||||
}
|
||||
}
|
||||
List<DailyCount> dailyTrend = new ArrayList<>();
|
||||
for (int i = 0; i < trendDays; i++) {
|
||||
LocalDate date = today.minusDays(i);
|
||||
dailyTrend.add(new DailyCount(date.format(formatter), dailyMap.get(date)));
|
||||
}
|
||||
|
||||
return new StatsResponse(total, passCount, failCount, avgScore,
|
||||
reviewingCount, sentimentDistribution, dailyTrend);
|
||||
return new StatsResponse(total, passCount, failCount, reviewingCount);
|
||||
})
|
||||
.onErrorResume(e -> {
|
||||
log.warn("Failed to fetch stats: {}", e.getMessage());
|
||||
return Mono.just(new StatsResponse(0, 0, 0, 0.0, 0L,
|
||||
Map.of("POSITIVE", 0L, "NEUTRAL", 0L, "NEGATIVE", 0L, "UNKNOWN", 0L),
|
||||
List.of()));
|
||||
return Mono.just(new StatsResponse(0, 0, 0, 0));
|
||||
})
|
||||
.flatMap(stats -> ServerResponse.ok().bodyValue(stats));
|
||||
}
|
||||
@@ -346,16 +271,11 @@ public class CommentAiAutopilotEndpoint implements CustomEndpoint {
|
||||
)));
|
||||
}
|
||||
|
||||
public record DailyCount(String date, long count) {}
|
||||
|
||||
public record StatsResponse(
|
||||
long total,
|
||||
long passCount,
|
||||
long failCount,
|
||||
double avgScore,
|
||||
long reviewingCount,
|
||||
Map<String, Long> sentimentDistribution,
|
||||
List<DailyCount> dailyTrend
|
||||
long reviewingCount
|
||||
) {}
|
||||
|
||||
public record PersonaResponse(
|
||||
|
||||
@@ -1,85 +1,58 @@
|
||||
package top.nxxy335.commentaiautopilot.service;
|
||||
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.context.ApplicationContext;
|
||||
import org.springframework.stereotype.Component;
|
||||
import reactor.core.publisher.Mono;
|
||||
import run.halo.app.core.extension.Plugin;
|
||||
import run.halo.app.extension.ReactiveExtensionClient;
|
||||
import run.halo.aifoundation.AiModelService;
|
||||
import run.halo.aifoundation.chat.GenerateTextRequest;
|
||||
import run.halo.aifoundation.chat.GenerateTextResult;
|
||||
import run.halo.aifoundation.schema.OutputSpec;
|
||||
import run.halo.app.plugin.extensionpoint.ExtensionGetter;
|
||||
|
||||
import java.lang.reflect.Method;
|
||||
import java.util.Map;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* AI Foundation client that uses runtime class loading and reflection
|
||||
* to call the AI Foundation plugin's AiModelService.
|
||||
* AI Foundation client that uses Halo's {@link ExtensionGetter} to obtain the
|
||||
* {@link AiModelService} extension provided by the ai-foundation plugin.
|
||||
* <p>
|
||||
* This approach avoids classloader identity issues by loading AiModelService
|
||||
* from ai-foundation's own classloader, so that Spring's getBeansOfType()
|
||||
* can correctly match the implementation bean.
|
||||
* This is the recommended way to integrate with AI Foundation, see
|
||||
* <a href="https://github.com/halo-dev/plugin-ai-foundation/blob/main/dev/dev.md">dev guide</a>.
|
||||
* <p>
|
||||
* No @ConditionalOnClass or pluginDependencies needed.
|
||||
* Always registered as a bean; availability is checked at runtime.
|
||||
* Requires the following declaration in plugin.yaml:
|
||||
* <pre>
|
||||
* spec:
|
||||
* pluginDependencies:
|
||||
* ai-foundation?: "*"
|
||||
* </pre>
|
||||
* The dependency is optional, so the plugin still loads when AI Foundation is
|
||||
* not installed; availability is checked at runtime and all calls return empty
|
||||
* in that case.
|
||||
*/
|
||||
@Slf4j
|
||||
@Component
|
||||
public class AiFoundationClient {
|
||||
|
||||
private static final String AI_FOUNDATION_PLUGIN_NAME = "ai-foundation";
|
||||
private static final String AI_MODEL_SERVICE_CLASS = "run.halo.aifoundation.AiModelService";
|
||||
private final ExtensionGetter extensionGetter;
|
||||
|
||||
private final ReactiveExtensionClient client;
|
||||
private final ApplicationContext applicationContext;
|
||||
|
||||
public AiFoundationClient(ReactiveExtensionClient client, ApplicationContext applicationContext) {
|
||||
this.client = client;
|
||||
this.applicationContext = applicationContext;
|
||||
public AiFoundationClient(ExtensionGetter extensionGetter) {
|
||||
this.extensionGetter = extensionGetter;
|
||||
}
|
||||
|
||||
/**
|
||||
* Call AI Foundation to generate a chat response using the specified model.
|
||||
* Uses {@link GenerateTextRequest} with {@code maxRetries=2} so that
|
||||
* transient model errors are retried by the SDK.
|
||||
*
|
||||
* @param prompt the prompt text
|
||||
* @param modelName the AiModel metadata.name, null or blank to use default model
|
||||
* @return the generated text, or empty if AI Foundation is unavailable
|
||||
*/
|
||||
public Mono<String> chat(String prompt, String modelName) {
|
||||
return isAiFoundationEnabled()
|
||||
.flatMap(enabled -> {
|
||||
if (!enabled) {
|
||||
log.warn("AI Foundation plugin is not installed or not enabled, skipping AI reply");
|
||||
return Mono.empty();
|
||||
}
|
||||
return doChat(prompt, modelName);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if AI Foundation is available: plugin installed, enabled, and AiModelService bean found.
|
||||
*/
|
||||
public Mono<Boolean> isAvailable() {
|
||||
return isAiFoundationEnabled()
|
||||
.flatMap(enabled -> {
|
||||
if (!enabled) return Mono.just(false);
|
||||
return findAiModelService().hasElement();
|
||||
});
|
||||
}
|
||||
|
||||
private Mono<Boolean> isAiFoundationEnabled() {
|
||||
return client.fetch(Plugin.class, AI_FOUNDATION_PLUGIN_NAME)
|
||||
.map(plugin -> plugin.getSpec().getEnabled())
|
||||
.defaultIfEmpty(false)
|
||||
.onErrorResume(e -> {
|
||||
log.debug("Failed to check AI Foundation plugin status: {}", e.getMessage());
|
||||
return Mono.just(false);
|
||||
});
|
||||
}
|
||||
|
||||
private Mono<String> doChat(String prompt, String modelName) {
|
||||
return findAiModelService()
|
||||
.flatMap(service -> invokeLanguageModel(service, modelName)
|
||||
.flatMap(model -> invokeGenerateText(model, prompt))
|
||||
)
|
||||
return aiModelService()
|
||||
.flatMap(service -> service.languageModel(modelName != null ? modelName : "")
|
||||
.flatMap(model -> model.generateText(
|
||||
GenerateTextRequest.builder().prompt(prompt).maxRetries(2).build()))
|
||||
.map(GenerateTextResult::getText))
|
||||
.doOnError(e -> log.error("AI Foundation call failed: {}", e.getMessage()))
|
||||
.onErrorResume(e -> {
|
||||
log.warn("AI Foundation not available: {}", e.getMessage());
|
||||
@@ -88,132 +61,68 @@ public class AiFoundationClient {
|
||||
}
|
||||
|
||||
/**
|
||||
* Get PluginManager via the pluginWrapper bean registered in our plugin context.
|
||||
* Halo's DefaultPluginApplicationContextFactory registers pluginWrapper as a singleton:
|
||||
* beanFactory.registerSingleton("pluginWrapper", pluginWrapper);
|
||||
* Then PluginWrapper.getPluginManager() gives us the PluginManager instance.
|
||||
* Call AI Foundation to classify text into one of the given choices using
|
||||
* structured output ({@link OutputSpec#choice(List)}).
|
||||
* <p>
|
||||
* This is the recommended way to do classification per the dev guide,
|
||||
* as it is more reliable than prompt parsing.
|
||||
*
|
||||
* @param systemPrompt system prompt describing the task
|
||||
* @param userPrompt the user input to classify
|
||||
* @param choices the allowed classification values
|
||||
* @param modelName the AiModel metadata.name, null or blank to use default model
|
||||
* @return the selected choice string, or empty if AI Foundation is unavailable
|
||||
*/
|
||||
private Object findPluginManager() {
|
||||
try {
|
||||
Object pluginWrapper = applicationContext.getBean("pluginWrapper");
|
||||
Method getPluginManagerMethod = pluginWrapper.getClass().getMethod("getPluginManager");
|
||||
getPluginManagerMethod.setAccessible(true);
|
||||
Object pm = getPluginManagerMethod.invoke(pluginWrapper);
|
||||
if (pm != null) {
|
||||
log.info("Found PluginManager via pluginWrapper bean: {}", pm.getClass().getName());
|
||||
}
|
||||
return pm;
|
||||
} catch (NoSuchMethodException e) {
|
||||
log.warn("pluginWrapper does not have getPluginManager() method: {}", e.getMessage());
|
||||
} catch (Exception e) {
|
||||
log.warn("Failed to get PluginManager via pluginWrapper: {}", e.getMessage());
|
||||
}
|
||||
log.warn("PluginManager not found");
|
||||
return null;
|
||||
public Mono<String> classify(String systemPrompt, String userPrompt,
|
||||
List<String> choices, String modelName) {
|
||||
return aiModelService()
|
||||
.flatMap(service -> service.languageModel(modelName != null ? modelName : "")
|
||||
.flatMap(model -> model.generateText(
|
||||
GenerateTextRequest.builder()
|
||||
.system(systemPrompt)
|
||||
.prompt(userPrompt)
|
||||
.output(OutputSpec.choice(choices))
|
||||
.maxRetries(2)
|
||||
.build()))
|
||||
.map(result -> {
|
||||
Object output = result.getOutput();
|
||||
return output != null ? String.valueOf(output).trim() : "";
|
||||
}))
|
||||
.doOnError(e -> log.error("AI Foundation classify failed: {}", e.getMessage()))
|
||||
.onErrorResume(e -> {
|
||||
log.warn("AI Foundation not available: {}", e.getMessage());
|
||||
return Mono.empty();
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Find the AiModelService bean from ai-foundation's PluginApplicationContext.
|
||||
* Uses PluginManager.getPlugin() to get the plugin wrapper, then reflection
|
||||
* to get the plugin's ApplicationContext.
|
||||
* Check if AI Foundation is available: plugin installed and an
|
||||
* AiModelService extension is enabled.
|
||||
*/
|
||||
private Mono<Object> findAiModelService() {
|
||||
return Mono.fromCallable(() -> {
|
||||
Object pm = findPluginManager();
|
||||
if (pm == null) return null;
|
||||
|
||||
// Call pm.getPlugin("ai-foundation") via reflection
|
||||
Method getPluginMethod = pm.getClass().getMethod("getPlugin", String.class);
|
||||
getPluginMethod.setAccessible(true);
|
||||
Object pluginWrapper = getPluginMethod.invoke(pm, AI_FOUNDATION_PLUGIN_NAME);
|
||||
if (pluginWrapper == null) {
|
||||
log.debug("ai-foundation plugin not found in PluginManager");
|
||||
return null;
|
||||
}
|
||||
|
||||
// Call pluginWrapper.getPlugin() to get the plugin instance
|
||||
Method getPluginInstanceMethod = pluginWrapper.getClass().getMethod("getPlugin");
|
||||
getPluginInstanceMethod.setAccessible(true);
|
||||
Object pluginInstance = getPluginInstanceMethod.invoke(pluginWrapper);
|
||||
if (pluginInstance == null) {
|
||||
log.debug("ai-foundation plugin instance is null");
|
||||
return null;
|
||||
}
|
||||
|
||||
// Get the plugin's ApplicationContext via reflection on SpringPlugin
|
||||
// DefaultSpringPlugin is package-private, so we need setAccessible
|
||||
Method getCtxMethod = pluginInstance.getClass().getMethod("getApplicationContext");
|
||||
getCtxMethod.setAccessible(true);
|
||||
ApplicationContext pluginAppContext = (ApplicationContext) getCtxMethod.invoke(pluginInstance);
|
||||
|
||||
// Get the plugin classloader
|
||||
Method getClassLoaderMethod = pluginWrapper.getClass().getMethod("getPluginClassLoader");
|
||||
getClassLoaderMethod.setAccessible(true);
|
||||
ClassLoader pluginClassLoader = (ClassLoader) getClassLoaderMethod.invoke(pluginWrapper);
|
||||
|
||||
// Load AiModelService from ai-foundation's classloader
|
||||
Class<?> aiModelServiceClass = pluginClassLoader.loadClass(AI_MODEL_SERVICE_CLASS);
|
||||
|
||||
// Find the AiModelService bean in ai-foundation's ApplicationContext
|
||||
Map<String, ?> beans = pluginAppContext.getBeansOfType(aiModelServiceClass);
|
||||
if (beans.isEmpty()) {
|
||||
log.debug("AiModelService bean not found in ai-foundation's ApplicationContext");
|
||||
return null;
|
||||
}
|
||||
|
||||
log.info("Found AiModelService bean in ai-foundation's ApplicationContext");
|
||||
Object result = beans.values().iterator().next();
|
||||
return (Object) result;
|
||||
}).doOnError(e -> log.error("Failed to find AiModelService: {}", e.getMessage()));
|
||||
public Mono<Boolean> isAvailable() {
|
||||
return aiModelService().hasElement()
|
||||
.onErrorResume(e -> {
|
||||
log.debug("AI Foundation not available: {}", e.getMessage());
|
||||
return Mono.just(false);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Call service.languageModel(modelName) or service.languageModel() via reflection.
|
||||
* Returns Mono<LanguageModel> from ai-foundation's classloader.
|
||||
* Obtain the enabled AiModelService extension via ExtensionGetter.
|
||||
* <p>
|
||||
* Wrapped in {@link Mono#defer} with a {@link NoClassDefFoundError} guard so
|
||||
* that the plugin still works when the optional ai-foundation dependency is
|
||||
* not installed (the AiModelService API class is then absent from the
|
||||
* classloader).
|
||||
*/
|
||||
private Mono<Object> invokeLanguageModel(Object service, String modelName) {
|
||||
return Mono.fromCallable(() -> {
|
||||
Method method;
|
||||
if (modelName != null && !modelName.isBlank()) {
|
||||
method = service.getClass().getMethod("languageModel", String.class);
|
||||
method.setAccessible(true);
|
||||
return method.invoke(service, modelName);
|
||||
} else {
|
||||
method = service.getClass().getMethod("languageModel");
|
||||
method.setAccessible(true);
|
||||
return method.invoke(service);
|
||||
private Mono<AiModelService> aiModelService() {
|
||||
return Mono.defer(() -> {
|
||||
try {
|
||||
return extensionGetter.getEnabledExtension(AiModelService.class);
|
||||
} catch (NoClassDefFoundError e) {
|
||||
log.debug("AI Foundation API not on classpath: {}", e.getMessage());
|
||||
return Mono.empty();
|
||||
}
|
||||
}).flatMap(result -> {
|
||||
if (result instanceof Mono<?> mono) return mono;
|
||||
return Mono.justOrEmpty(result);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Call model.generateText(prompt) via reflection, then extract text from result.
|
||||
* Returns the generated text string.
|
||||
*/
|
||||
private Mono<String> invokeGenerateText(Object model, String prompt) {
|
||||
return Mono.fromCallable(() -> {
|
||||
Method method = model.getClass().getMethod("generateText", String.class);
|
||||
method.setAccessible(true);
|
||||
return method.invoke(model, prompt);
|
||||
}).flatMap(result -> {
|
||||
if (result instanceof Mono<?> mono) {
|
||||
return mono.map(this::extractText);
|
||||
}
|
||||
return Mono.justOrEmpty(extractText(result));
|
||||
});
|
||||
}
|
||||
|
||||
private String extractText(Object result) {
|
||||
if (result == null) return null;
|
||||
try {
|
||||
Method getText = result.getClass().getMethod("getText");
|
||||
getText.setAccessible(true);
|
||||
return (String) getText.invoke(result);
|
||||
} catch (Exception e) {
|
||||
throw new RuntimeException("Failed to call getText() on GenerateTextResult: " + e.getMessage(), e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -42,6 +42,55 @@ public class ContextExtractor {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Fetch previous replies in the comment thread to provide conversation history.
|
||||
* Only includes replies created before the triggering reply.
|
||||
*/
|
||||
private Mono<String> fetchConversationHistory(String commentName, String triggerReplyName) {
|
||||
if (triggerReplyName == null || triggerReplyName.isBlank()) {
|
||||
return Mono.just("");
|
||||
}
|
||||
return client.fetch(Reply.class, triggerReplyName)
|
||||
.flatMap(triggerReply -> {
|
||||
var triggerTime = triggerReply.getMetadata().getCreationTimestamp();
|
||||
return client.list(Reply.class,
|
||||
reply -> {
|
||||
if (!commentName.equals(reply.getSpec().getCommentName())) {
|
||||
return false;
|
||||
}
|
||||
if (triggerReplyName.equals(reply.getMetadata().getName())) {
|
||||
return false;
|
||||
}
|
||||
// Only include replies created before the trigger reply
|
||||
var replyTime = reply.getMetadata().getCreationTimestamp();
|
||||
return replyTime != null && triggerTime != null
|
||||
&& !replyTime.isAfter(triggerTime);
|
||||
},
|
||||
null)
|
||||
.collectList()
|
||||
.map(replies -> {
|
||||
if (replies.isEmpty()) return "";
|
||||
// Sort by creation time
|
||||
replies.sort(java.util.Comparator.comparing(
|
||||
r -> r.getMetadata().getCreationTimestamp()));
|
||||
var sb = new StringBuilder();
|
||||
for (var r : replies) {
|
||||
var owner = r.getSpec().getOwner();
|
||||
String name = (owner != null && owner.getDisplayName() != null)
|
||||
? owner.getDisplayName() : "匿名用户";
|
||||
boolean isAi = owner != null && owner.getAnnotations() != null
|
||||
&& "true".equals(owner.getAnnotations().get("comment-ai-autopilot.nxxy335.top/is-ai"));
|
||||
String role = isAi ? "AI" : "用户";
|
||||
String content = extractReplyContent(r);
|
||||
sb.append(role).append("(").append(name).append("): ")
|
||||
.append(content).append("\n");
|
||||
}
|
||||
return sb.toString();
|
||||
});
|
||||
})
|
||||
.defaultIfEmpty("");
|
||||
}
|
||||
|
||||
private Mono<CommentContext> buildContext(Comment comment, boolean isAiConversation) {
|
||||
var commentContent = extractCommentContent(comment);
|
||||
var commentOwner = extractCommentOwner(comment);
|
||||
@@ -63,7 +112,8 @@ public class ContextExtractor {
|
||||
null,
|
||||
isAiConversation,
|
||||
formatPostDate(post),
|
||||
commentCount
|
||||
commentCount,
|
||||
""
|
||||
))
|
||||
)
|
||||
)
|
||||
@@ -78,7 +128,8 @@ public class ContextExtractor {
|
||||
null,
|
||||
isAiConversation,
|
||||
"",
|
||||
0
|
||||
0,
|
||||
""
|
||||
));
|
||||
}
|
||||
|
||||
@@ -93,7 +144,8 @@ public class ContextExtractor {
|
||||
null,
|
||||
isAiConversation,
|
||||
"",
|
||||
0
|
||||
0,
|
||||
""
|
||||
));
|
||||
}
|
||||
|
||||
@@ -101,55 +153,68 @@ public class ContextExtractor {
|
||||
var replyContent = extractReplyContent(reply);
|
||||
var replyOwner = extractReplyOwner(reply);
|
||||
var subjectRef = comment.getSpec().getSubjectRef();
|
||||
var commentName = comment.getMetadata().getName();
|
||||
var replyName = reply.getMetadata().getName();
|
||||
|
||||
// Fetch conversation history for AI conversations
|
||||
Mono<String> historyMono = isAiConversation
|
||||
? fetchConversationHistory(commentName, replyName)
|
||||
: Mono.just("");
|
||||
|
||||
if (subjectRef != null && "Post".equals(subjectRef.getKind())) {
|
||||
String postName = subjectRef.getName();
|
||||
return client.fetch(Post.class, postName)
|
||||
.flatMap(post -> getPostContent(postName)
|
||||
.flatMap(content -> getCommentCount(comment.getMetadata().getName())
|
||||
.map(commentCount -> new CommentContext(
|
||||
comment.getMetadata().getName(),
|
||||
postName,
|
||||
post.getSpec().getSlug(),
|
||||
replyContent,
|
||||
replyOwner,
|
||||
post.getSpec().getTitle(),
|
||||
content,
|
||||
reply.getMetadata().getName(),
|
||||
isAiConversation,
|
||||
formatPostDate(post),
|
||||
commentCount
|
||||
))
|
||||
.flatMap(content -> getCommentCount(commentName)
|
||||
.flatMap(commentCount -> historyMono
|
||||
.map(history -> new CommentContext(
|
||||
commentName,
|
||||
postName,
|
||||
post.getSpec().getSlug(),
|
||||
replyContent,
|
||||
replyOwner,
|
||||
post.getSpec().getTitle(),
|
||||
content,
|
||||
replyName,
|
||||
isAiConversation,
|
||||
formatPostDate(post),
|
||||
commentCount,
|
||||
history
|
||||
))
|
||||
)
|
||||
)
|
||||
)
|
||||
.defaultIfEmpty(new CommentContext(
|
||||
comment.getMetadata().getName(),
|
||||
commentName,
|
||||
postName,
|
||||
"",
|
||||
replyContent,
|
||||
replyOwner,
|
||||
"",
|
||||
"",
|
||||
reply.getMetadata().getName(),
|
||||
replyName,
|
||||
isAiConversation,
|
||||
"",
|
||||
0
|
||||
0,
|
||||
""
|
||||
));
|
||||
}
|
||||
|
||||
return Mono.just(new CommentContext(
|
||||
comment.getMetadata().getName(),
|
||||
"",
|
||||
"",
|
||||
replyContent,
|
||||
replyOwner,
|
||||
"",
|
||||
"",
|
||||
reply.getMetadata().getName(),
|
||||
isAiConversation,
|
||||
"",
|
||||
0
|
||||
));
|
||||
return historyMono
|
||||
.map(history -> new CommentContext(
|
||||
commentName,
|
||||
"",
|
||||
"",
|
||||
replyContent,
|
||||
replyOwner,
|
||||
"",
|
||||
"",
|
||||
replyName,
|
||||
isAiConversation,
|
||||
"",
|
||||
0,
|
||||
history
|
||||
));
|
||||
}
|
||||
|
||||
private String extractCommentContent(Comment comment) {
|
||||
@@ -245,6 +310,7 @@ public class ContextExtractor {
|
||||
String replyTo,
|
||||
boolean isAiConversation,
|
||||
String postDate,
|
||||
int commentCount
|
||||
int commentCount,
|
||||
String conversationHistory
|
||||
) {}
|
||||
}
|
||||
|
||||
@@ -75,6 +75,7 @@ public class PromptBuilder {
|
||||
文章（仅供理解上下文，不要复述）：
|
||||
{{article}}
|
||||
|
||||
{{conversation_history}}
|
||||
评论：
|
||||
{{comment}}
|
||||
""";
|
||||
@@ -103,6 +104,7 @@ public class PromptBuilder {
|
||||
.replace("{{post_date}}", context.postDate() != null ? context.postDate() : "")
|
||||
.replace("{{comment_count}}", String.valueOf(context.commentCount()))
|
||||
.replace("{{article}}", context.postTitle() + "\n" + context.postContent())
|
||||
.replace("{{conversation_history}}", formatConversationHistory(context))
|
||||
.replace("{{comment}}", context.commentOwner() + ": " + context.commentContent());
|
||||
|
||||
return prompt;
|
||||
@@ -133,6 +135,7 @@ public class PromptBuilder {
|
||||
.replace("{{post_date}}", context.postDate() != null ? context.postDate() : "")
|
||||
.replace("{{comment_count}}", String.valueOf(context.commentCount()))
|
||||
.replace("{{article}}", context.postTitle() + "\n" + context.postContent())
|
||||
.replace("{{conversation_history}}", formatConversationHistory(context))
|
||||
.replace("{{comment}}", context.commentOwner() + ": " + context.commentContent());
|
||||
|
||||
if (sentiment == null || "NEUTRAL".equals(sentiment)) {
|
||||
@@ -147,6 +150,18 @@ public class PromptBuilder {
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Format conversation history for inclusion in the prompt.
|
||||
* Returns empty string if no history is available.
|
||||
*/
|
||||
private String formatConversationHistory(ContextExtractor.CommentContext context) {
|
||||
String history = context.conversationHistory();
|
||||
if (history == null || history.isBlank()) {
|
||||
return "";
|
||||
}
|
||||
return "对话历史（供理解上下文）：\n" + history + "\n";
|
||||
}
|
||||
|
||||
private Mono<String> getPromptTemplate() {
|
||||
return client.fetch(ConfigMap.class, CONFIG_MAP_NAME)
|
||||
.mapNotNull(cm -> {
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
package top.nxxy335.commentaiautopilot.service;
|
||||
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.beans.factory.DisposableBean;
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
import java.util.concurrent.ConcurrentHashMap;
|
||||
@@ -8,15 +9,18 @@ import java.util.concurrent.atomic.AtomicInteger;
|
||||
|
||||
@Slf4j
|
||||
@Component
|
||||
public class RateLimitService {
|
||||
public class RateLimitService implements DisposableBean {
|
||||
private final ConcurrentHashMap<Long, AtomicInteger> windowMap = new ConcurrentHashMap<>();
|
||||
private final Thread cleanupThread;
|
||||
private volatile boolean running = true;
|
||||
|
||||
public RateLimitService() {
|
||||
// 每5分钟清理过期窗口，防止内存泄漏
|
||||
Thread cleanupThread = new Thread(() -> {
|
||||
while (!Thread.currentThread().isInterrupted()) {
|
||||
cleanupThread = new Thread(() -> {
|
||||
while (running && !Thread.currentThread().isInterrupted()) {
|
||||
try {
|
||||
Thread.sleep(5 * 60 * 1000);
|
||||
if (!running) break;
|
||||
cleanup();
|
||||
} catch (InterruptedException e) {
|
||||
Thread.currentThread().interrupt();
|
||||
@@ -55,4 +59,13 @@ public class RateLimitService {
|
||||
log.debug("[RateLimit] Cleaned up {} expired windows", removed);
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public void destroy() {
|
||||
running = false;
|
||||
if (cleanupThread != null) {
|
||||
cleanupThread.interrupt();
|
||||
}
|
||||
log.info("[RateLimit] Cleanup thread stopped");
|
||||
}
|
||||
}
|
||||
|
||||
@@ -4,6 +4,8 @@ import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.stereotype.Component;
|
||||
import reactor.core.publisher.Mono;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
@Component
|
||||
@Slf4j
|
||||
public class ReviewService {
|
||||
@@ -14,58 +16,135 @@ public class ReviewService {
|
||||
this.aiFoundationClient = aiFoundationClient;
|
||||
}
|
||||
|
||||
private static final String REVIEW_PROMPT_TEMPLATE = """
|
||||
请你以内容安全审核员的身份，严格评估你刚刚生成的这段回复：
|
||||
/**
|
||||
* Safety classification choices.
|
||||
* Using OutputSpec.choice for reliable structured output.
|
||||
*/
|
||||
private static final String SAFE = "安全";
|
||||
private static final String UNSAFE = "不安全";
|
||||
private static final List<String> SAFETY_CHOICES = List.of(SAFE, UNSAFE);
|
||||
|
||||
文章：
|
||||
%s
|
||||
/**
|
||||
* Quality rating choices for content quality assessment.
|
||||
* Used to produce a meaningful score (1-5) instead of binary 0/100.
|
||||
*/
|
||||
private static final String RATING_EXCELLENT = "5";
|
||||
private static final String RATING_GOOD = "4";
|
||||
private static final String RATING_AVERAGE = "3";
|
||||
private static final String RATING_POOR = "2";
|
||||
private static final String RATING_BAD = "1";
|
||||
private static final List<String> QUALITY_CHOICES = List.of(
|
||||
RATING_EXCELLENT, RATING_GOOD, RATING_AVERAGE, RATING_POOR, RATING_BAD
|
||||
);
|
||||
|
||||
原始评论：
|
||||
%s
|
||||
private static final String SAFETY_SYSTEM_PROMPT = """
|
||||
你是内容安全审核员。请严格评估AI生成的回复内容是否安全合规。
|
||||
检查以下方面：
|
||||
1. 是否包含辱骂、仇恨、偏见或煽动性言论
|
||||
2. 是否包含不适宜公开传播的内容
|
||||
3. 是否涉及暴力、歧视、人身攻击或违反法律法规的内容
|
||||
只返回"安全"或"不安全"。""";
|
||||
|
||||
生成的回复：
|
||||
%s
|
||||
|
||||
请检查以下内容：
|
||||
1. 是否包含任何辱骂、仇恨、偏见或煽动性言论？
|
||||
2. 是否包含不适宜公开传播的内容？
|
||||
3. 是否涉及暴力、歧视、人身攻击或违反法律法规的内容？
|
||||
|
||||
请直接回答"安全"或"不安全"。如果"不安全"，请重新生成一段符合规范的温和回复。
|
||||
""";
|
||||
private static final String QUALITY_SYSTEM_PROMPT = """
|
||||
你是AI回复质量评估员。请对AI生成的回复进行质量评分（1-5分）。
|
||||
评分标准：
|
||||
5分：回复切题、自然流畅、语气恰当、有帮助
|
||||
4分：回复较好，基本切题，语气自然
|
||||
3分：回复一般，基本切题但略显生硬或冗长
|
||||
2分：回复较差，偏离主题或语气不当
|
||||
1分：回复很差，完全不相关或不当
|
||||
只返回数字 1-5。""";
|
||||
|
||||
/**
|
||||
* Review AI reply content using two-stage assessment:
|
||||
* 1. Safety check via OutputSpec.choice (安全/不安全)
|
||||
* 2. Quality rating via OutputSpec.choice (1-5) — only if safe
|
||||
*
|
||||
* <p>Score mapping (0-100):
|
||||
* <ul>
|
||||
* <li>Unsafe → 0 (FAIL)</li>
|
||||
* <li>Rating 5 → 100 (PASS)</li>
|
||||
* <li>Rating 4 → 85 (PASS)</li>
|
||||
* <li>Rating 3 → 70 (PASS)</li>
|
||||
* <li>Rating 2 → 50 (PASS, borderline)</li>
|
||||
* <li>Rating 1 → 30 (PASS, but low quality)</li>
|
||||
* </ul>
|
||||
*/
|
||||
public Mono<ReviewResult> review(String articleContent, String commentContent, String aiReply,
|
||||
String modelName) {
|
||||
String reviewPrompt = String.format(REVIEW_PROMPT_TEMPLATE,
|
||||
truncate(articleContent, 2000),
|
||||
String userPrompt = String.format("""
|
||||
原始评论：
|
||||
%s
|
||||
|
||||
生成的回复：
|
||||
%s
|
||||
|
||||
请判断以上回复是否安全合规。""",
|
||||
truncate(commentContent, 500),
|
||||
truncate(aiReply, 500));
|
||||
|
||||
return aiFoundationClient.chat(reviewPrompt, modelName)
|
||||
.map(this::parseSafetyResult)
|
||||
// Stage 1: Safety check
|
||||
return aiFoundationClient.classify(SAFETY_SYSTEM_PROMPT, userPrompt, SAFETY_CHOICES, modelName)
|
||||
.flatMap(safetyResult -> {
|
||||
if (UNSAFE.equals(safetyResult)) {
|
||||
log.warn("[Review] Content is UNSAFE");
|
||||
return Mono.just(new ReviewResult(0, "FAIL", "内容安全审核不通过"));
|
||||
}
|
||||
if (!SAFE.equals(safetyResult)) {
|
||||
log.warn("[Review] Unexpected safety result: {}, treating as unsafe", safetyResult);
|
||||
return Mono.just(new ReviewResult(0, "FAIL", "内容安全审核结果异常"));
|
||||
}
|
||||
// Stage 2: Quality rating (only for safe content)
|
||||
return rateQuality(commentContent, aiReply, modelName);
|
||||
})
|
||||
.defaultIfEmpty(new ReviewResult(100, "PASS", "审核无响应，自动通过"))
|
||||
.onErrorResume(e -> {
|
||||
log.warn("Review failed, auto-passing: {}", e.getMessage());
|
||||
log.warn("[Review] Review failed, auto-passing: {}", e.getMessage());
|
||||
return Mono.just(new ReviewResult(100, "PASS", "审核服务异常，自动通过"));
|
||||
});
|
||||
}
|
||||
|
||||
private ReviewResult parseSafetyResult(String response) {
|
||||
if (response == null || response.isBlank()) {
|
||||
return new ReviewResult(100, "PASS", "审核无响应，自动通过");
|
||||
}
|
||||
String trimmed = response.trim().toLowerCase();
|
||||
if (trimmed.contains("不安全") || trimmed.contains("unsafe")) {
|
||||
log.warn("AI Review: content is UNSAFE, response: {}", response);
|
||||
return new ReviewResult(0, "FAIL", "内容安全审核不通过");
|
||||
}
|
||||
if (trimmed.contains("安全") || trimmed.contains("safe")) {
|
||||
log.info("AI Review: content is SAFE");
|
||||
return new ReviewResult(100, "PASS", "内容安全审核通过");
|
||||
}
|
||||
// If unclear response, default to pass
|
||||
log.warn("AI Review: unclear response, auto-passing: {}", response);
|
||||
return new ReviewResult(100, "PASS", "审核结果不明确，自动通过");
|
||||
/**
|
||||
* Rate the quality of a safe AI reply (1-5) and map to a 0-100 score.
|
||||
*/
|
||||
private Mono<ReviewResult> rateQuality(String commentContent, String aiReply, String modelName) {
|
||||
String qualityPrompt = String.format("""
|
||||
评论：
|
||||
%s
|
||||
|
||||
回复：
|
||||
%s
|
||||
|
||||
请对以上回复进行质量评分（1-5分）。""",
|
||||
truncate(commentContent, 500),
|
||||
truncate(aiReply, 500));
|
||||
|
||||
return aiFoundationClient.classify(QUALITY_SYSTEM_PROMPT, qualityPrompt, QUALITY_CHOICES, modelName)
|
||||
.map(rating -> {
|
||||
int score = mapRatingToScore(rating);
|
||||
String reason = "安全通过，质量评分: " + rating + "/5";
|
||||
log.info("[Review] Content is SAFE, quality rating: {}/5, score: {}", rating, score);
|
||||
return new ReviewResult(score, "PASS", reason);
|
||||
})
|
||||
.defaultIfEmpty(new ReviewResult(85, "PASS", "安全通过，质量评分默认 4/5"))
|
||||
.onErrorResume(e -> {
|
||||
log.warn("[Review] Quality rating failed, defaulting to 85: {}", e.getMessage());
|
||||
return Mono.just(new ReviewResult(85, "PASS", "安全通过，质量评分异常"));
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Map a 1-5 quality rating to a 0-100 score.
|
||||
*/
|
||||
private int mapRatingToScore(String rating) {
|
||||
return switch (rating) {
|
||||
case RATING_EXCELLENT -> 100;
|
||||
case RATING_GOOD -> 85;
|
||||
case RATING_AVERAGE -> 70;
|
||||
case RATING_POOR -> 50;
|
||||
case RATING_BAD -> 30;
|
||||
default -> 70; // default to average
|
||||
};
|
||||
}
|
||||
|
||||
private String truncate(String text, int maxLength) {
|
||||
|
||||
@@ -4,6 +4,8 @@ import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.stereotype.Component;
|
||||
import reactor.core.publisher.Mono;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
@Component
|
||||
@Slf4j
|
||||
public class SentimentService {
|
||||
@@ -20,13 +22,27 @@ public class SentimentService {
|
||||
public static final String NEGATIVE = "NEGATIVE";
|
||||
}
|
||||
|
||||
public Mono<SentimentResult> analyzeSentiment(String commentContent, String modelName) {
|
||||
String prompt = buildSentimentPrompt(commentContent);
|
||||
private static final List<String> CHOICES = List.of(
|
||||
SentimentResult.POSITIVE, SentimentResult.NEUTRAL, SentimentResult.NEGATIVE
|
||||
);
|
||||
|
||||
return aiFoundationClient.chat(prompt, modelName)
|
||||
.map(response -> {
|
||||
String sentiment = parseSentiment(response);
|
||||
return new SentimentResult(sentiment, 1.0);
|
||||
/**
|
||||
* Analyze sentiment using AI Foundation structured output
|
||||
* ({@code OutputSpec.choice}) for reliable classification.
|
||||
*/
|
||||
public Mono<SentimentResult> analyzeSentiment(String commentContent, String modelName) {
|
||||
String systemPrompt = "你是一个情感分析助手。请分析评论的情感倾向，只返回 POSITIVE、NEUTRAL 或 NEGATIVE 之一。";
|
||||
String userPrompt = "分析以下评论的情感倾向：\n\n" + commentContent;
|
||||
|
||||
return aiFoundationClient.classify(systemPrompt, userPrompt, CHOICES, modelName)
|
||||
.map(sentiment -> {
|
||||
String upper = sentiment.toUpperCase();
|
||||
// Validate against known choices; default to NEUTRAL if unexpected
|
||||
if (!CHOICES.contains(upper)) {
|
||||
log.warn("[Sentiment] Unexpected classification result: {}, defaulting to NEUTRAL", sentiment);
|
||||
return new SentimentResult(SentimentResult.NEUTRAL, 0.0);
|
||||
}
|
||||
return new SentimentResult(upper, 1.0);
|
||||
})
|
||||
.onErrorResume(e -> {
|
||||
log.warn("[Sentiment] Failed to analyze sentiment, defaulting to NEUTRAL: {}", e.getMessage());
|
||||
@@ -34,16 +50,4 @@ public class SentimentService {
|
||||
})
|
||||
.defaultIfEmpty(new SentimentResult(SentimentResult.NEUTRAL, 0.0));
|
||||
}
|
||||
|
||||
private String buildSentimentPrompt(String commentContent) {
|
||||
return "请分析以下评论的情感倾向。只回复一个词：POSITIVE（正面）、NEUTRAL（中性）或 NEGATIVE（负面）。\n\n评论内容：\n" + commentContent;
|
||||
}
|
||||
|
||||
private String parseSentiment(String response) {
|
||||
if (response == null || response.isBlank()) return SentimentResult.NEUTRAL;
|
||||
String upper = response.trim().toUpperCase();
|
||||
if (upper.contains("POSITIVE")) return SentimentResult.POSITIVE;
|
||||
if (upper.contains("NEGATIVE")) return SentimentResult.NEGATIVE;
|
||||
return SentimentResult.NEUTRAL;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -54,7 +54,7 @@ spec:
|
||||
- $formkit: textarea
|
||||
name: customPromptTemplate
|
||||
label: 自定义Prompt模板
|
||||
value: "{{persona_prompt}}\n\n{{safety_prompt}}\n\n【语言要求】请用评论所使用的语言回复。如果评论是英文，请用英文回复；如果是中文，请用中文回复；如果是日文，请用日文回复；以此类推。\n\n请回复以下评论。注意：\n- 回复长度应与评论长度匹配，简短问候简短回复\n- 不要复述或总结文章内容\n- 自然对话，不要写小作文\n- 只有评论涉及具体内容时才针对性回应\n\n文章（仅供理解上下文，不要复述）：\n{{article}}\n\n评论：\n{{comment}}"
|
||||
value: "{{persona_prompt}}\n\n{{safety_prompt}}\n\n【语言要求】请用评论所使用的语言回复。如果评论是英文，请用英文回复；如果是中文，请用中文回复；如果是日文，请用日文回复；以此类推。\n\n请回复以下评论。注意：\n- 回复长度应与评论长度匹配，简短问候简短回复\n- 不要复述或总结文章内容\n- 自然对话，不要写小作文\n- 只有评论涉及具体内容时才针对性回应\n\n文章（仅供理解上下文，不要复述）：\n{{article}}\n\n{{conversation_history}}\n评论：\n{{comment}}"
|
||||
- $formkit: select
|
||||
name: enabledPresets
|
||||
label: 启用预设
|
||||
|
||||
@@ -5,9 +5,17 @@ kind: Plugin
|
||||
metadata:
|
||||
# The name defines how the plugin is invoked, A unique name
|
||||
name: comment-ai-autopilot
|
||||
annotations:
|
||||
# Recommend installing AI Foundation from the app store after installing this plugin
|
||||
# https://www.halo.run/store/apps/app-acslk9nu
|
||||
"store.halo.run/recommended-apps": '["app-acslk9nu"]'
|
||||
spec:
|
||||
enabled: true
|
||||
requires: ">=2.25.0"
|
||||
pluginDependencies:
|
||||
# Optional dependency: plugin still loads without AI Foundation,
|
||||
# but AI features require it to be installed and enabled.
|
||||
ai-foundation?: "*"
|
||||
author:
|
||||
name: 暖心向阳335
|
||||
website: https://nxxy335.top
|
||||
@@ -22,4 +30,4 @@ spec:
|
||||
url: "https://github.com/sunny-335/plugin-comment-ai-autopilot/blob/main/LICENSE"
|
||||
settingName: "comment-ai-autopilot-settings"
|
||||
configMapName: "comment-ai-autopilot-configmap"
|
||||
version: "1.0.0-beta.1"
|
||||
version: "1.0.0-beta.2-kx7m2p"
|
||||
|
||||
+5
-194
@@ -108,152 +108,11 @@
|
||||
</VCard>
|
||||
</div>
|
||||
|
||||
<!-- Middle: Sentiment + Trend -->
|
||||
<div class="grid grid-cols-1 gap-4 mt-4 lg:grid-cols-2">
|
||||
<!-- Sentiment Distribution -->
|
||||
<VCard :body-class="['!p-5']">
|
||||
<h3 class="text-sm font-medium text-gray-500 mb-4">情感分布</h3>
|
||||
<div class="space-y-3">
|
||||
<div class="flex items-center gap-3">
|
||||
<div class="w-2 h-2 rounded-full bg-green-500 shrink-0"></div>
|
||||
<div class="flex-1 min-w-0">
|
||||
<div class="flex items-center justify-between text-sm">
|
||||
<span class="text-gray-700">正面</span>
|
||||
<span class="font-medium text-green-600">{{ stats?.sentimentDistribution?.POSITIVE || 0 }}</span>
|
||||
</div>
|
||||
<div class="mt-1 h-1.5 bg-gray-100 rounded-full overflow-hidden">
|
||||
<div
|
||||
class="h-full bg-green-400 rounded-full transition-all duration-500"
|
||||
:style="{ width: getSentimentPercent('POSITIVE') + '%' }"
|
||||
></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="flex items-center gap-3">
|
||||
<div class="w-2 h-2 rounded-full bg-gray-400 shrink-0"></div>
|
||||
<div class="flex-1 min-w-0">
|
||||
<div class="flex items-center justify-between text-sm">
|
||||
<span class="text-gray-700">中性</span>
|
||||
<span class="font-medium text-gray-600">{{ stats?.sentimentDistribution?.NEUTRAL || 0 }}</span>
|
||||
</div>
|
||||
<div class="mt-1 h-1.5 bg-gray-100 rounded-full overflow-hidden">
|
||||
<div
|
||||
class="h-full bg-gray-400 rounded-full transition-all duration-500"
|
||||
:style="{ width: getSentimentPercent('NEUTRAL') + '%' }"
|
||||
></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="flex items-center gap-3">
|
||||
<div class="w-2 h-2 rounded-full bg-red-500 shrink-0"></div>
|
||||
<div class="flex-1 min-w-0">
|
||||
<div class="flex items-center justify-between text-sm">
|
||||
<span class="text-gray-700">负面</span>
|
||||
<span class="font-medium text-red-500">{{ stats?.sentimentDistribution?.NEGATIVE || 0 }}</span>
|
||||
</div>
|
||||
<div class="mt-1 h-1.5 bg-gray-100 rounded-full overflow-hidden">
|
||||
<div
|
||||
class="h-full bg-red-400 rounded-full transition-all duration-500"
|
||||
:style="{ width: getSentimentPercent('NEGATIVE') + '%' }"
|
||||
></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="flex items-center gap-3">
|
||||
<div class="w-2 h-2 rounded-full bg-gray-300 shrink-0"></div>
|
||||
<div class="flex-1 min-w-0">
|
||||
<div class="flex items-center justify-between text-sm">
|
||||
<span class="text-gray-700">未知</span>
|
||||
<span class="font-medium text-gray-400">{{ stats?.sentimentDistribution?.UNKNOWN || 0 }}</span>
|
||||
</div>
|
||||
<div class="mt-1 h-1.5 bg-gray-100 rounded-full overflow-hidden">
|
||||
<div
|
||||
class="h-full bg-gray-300 rounded-full transition-all duration-500"
|
||||
:style="{ width: getSentimentPercent('UNKNOWN') + '%' }"
|
||||
></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</VCard>
|
||||
|
||||
<!-- Daily Trend -->
|
||||
<VCard :body-class="['!p-5']">
|
||||
<div class="flex items-center justify-between mb-4">
|
||||
<h3 class="text-sm font-medium text-gray-500">近7日回复趋势</h3>
|
||||
<div class="inline-flex rounded-md border border-gray-200 overflow-hidden">
|
||||
<button
|
||||
class="px-2.5 py-1 text-xs transition-colors"
|
||||
:class="range === '7' ? 'bg-blue-500 text-white' : 'bg-white text-gray-600 hover:bg-gray-50'"
|
||||
@click="range = '7'"
|
||||
>
|
||||
7天
|
||||
</button>
|
||||
<button
|
||||
class="px-2.5 py-1 text-xs border-l border-gray-200 transition-colors"
|
||||
:class="range === '30' ? 'bg-blue-500 text-white' : 'bg-white text-gray-600 hover:bg-gray-50'"
|
||||
@click="range = '30'"
|
||||
>
|
||||
30天
|
||||
</button>
|
||||
<button
|
||||
class="px-2.5 py-1 text-xs border-l border-gray-200 transition-colors"
|
||||
:class="range === 'all' ? 'bg-blue-500 text-white' : 'bg-white text-gray-600 hover:bg-gray-50'"
|
||||
@click="range = 'all'"
|
||||
>
|
||||
全部
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
<div v-if="stats?.dailyTrend?.length" class="flex items-end gap-3" style="height: 160px">
|
||||
<div
|
||||
v-for="day in stats.dailyTrend"
|
||||
:key="day.date"
|
||||
class="flex-1 flex flex-col items-center justify-end h-full"
|
||||
>
|
||||
<div class="text-xs text-gray-500 mb-1 font-medium">{{ day.count }}</div>
|
||||
<div
|
||||
class="w-full rounded-t-md transition-all duration-500"
|
||||
:class="day.count > 0 ? 'bg-gradient-to-t from-blue-500 to-blue-400' : 'bg-gray-100'"
|
||||
:style="{ height: getTrendBarHeight(day.count) + 'px' }"
|
||||
></div>
|
||||
<div class="text-[10px] text-gray-400 mt-2 whitespace-nowrap">{{ formatTrendDate(day.date) }}</div>
|
||||
</div>
|
||||
</div>
|
||||
<div v-else class="flex items-center justify-center text-sm text-gray-400" style="height: 160px">
|
||||
暂无数据
|
||||
</div>
|
||||
</VCard>
|
||||
</div>
|
||||
|
||||
<!-- Bottom: Score + Quick Actions -->
|
||||
<div class="grid grid-cols-1 gap-4 mt-4 sm:grid-cols-2">
|
||||
<!-- Avg Score -->
|
||||
<VCard :body-class="['!p-5']">
|
||||
<h3 class="text-sm font-medium text-gray-500 mb-3">平均审核评分</h3>
|
||||
<div class="flex items-center gap-4">
|
||||
<div class="text-4xl font-bold" :class="scoreColor">{{ stats?.avgScore?.toFixed(1) || '0.0' }}</div>
|
||||
<div class="flex-1">
|
||||
<div class="h-3 bg-gray-100 rounded-full overflow-hidden">
|
||||
<div
|
||||
class="h-full rounded-full transition-all duration-500"
|
||||
:class="scoreBarColor"
|
||||
:style="{ width: (stats?.avgScore || 0) * 10 + '%' }"
|
||||
></div>
|
||||
</div>
|
||||
<div class="flex justify-between text-[10px] text-gray-300 mt-1">
|
||||
<span>0</span>
|
||||
<span>5</span>
|
||||
<span>10</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</VCard>
|
||||
|
||||
<!-- Quick Actions -->
|
||||
<!-- Quick Actions -->
|
||||
<div class="mt-4">
|
||||
<VCard :body-class="['!p-5']">
|
||||
<h3 class="text-sm font-medium text-gray-500 mb-3">快捷操作</h3>
|
||||
<div class="grid grid-cols-2 gap-2">
|
||||
<div class="grid grid-cols-2 gap-2 sm:grid-cols-4">
|
||||
<button
|
||||
class="flex items-center gap-2 px-3 py-2.5 rounded-md bg-gray-50 hover:bg-gray-100 transition-colors text-sm text-gray-700"
|
||||
@click="$router.push({ name: 'CommentAiAutopilotLogs' })"
|
||||
@@ -299,24 +158,16 @@
|
||||
</template>
|
||||
|
||||
<script setup lang="ts">
|
||||
import { ref, computed, onMounted, watch } from "vue"
|
||||
import { ref, computed, onMounted } from "vue"
|
||||
import { axiosInstance } from "@halo-dev/api-client"
|
||||
import { VPageHeader, VButton, VCard, Toast } from "@halo-dev/components"
|
||||
import { IconPlug } from "@halo-dev/components"
|
||||
|
||||
interface DailyCount {
|
||||
date: string
|
||||
count: number
|
||||
}
|
||||
|
||||
interface StatsResponse {
|
||||
total: number
|
||||
passCount: number
|
||||
failCount: number
|
||||
reviewingCount: number
|
||||
avgScore: number
|
||||
sentimentDistribution: Record<string, number>
|
||||
dailyTrend: DailyCount[]
|
||||
}
|
||||
|
||||
interface PersonaResponse {
|
||||
@@ -331,7 +182,6 @@ interface HealthResponse {
|
||||
|
||||
const stats = ref<StatsResponse | null>(null)
|
||||
const persona = ref<PersonaResponse | null>(null)
|
||||
const range = ref("7")
|
||||
const health = ref<HealthResponse | null>(null)
|
||||
const healthVisible = ref(true)
|
||||
|
||||
@@ -340,24 +190,10 @@ const passRate = computed(() => {
|
||||
return Math.round((stats.value.passCount / stats.value.total) * 100)
|
||||
})
|
||||
|
||||
const scoreColor = computed(() => {
|
||||
const score = stats.value?.avgScore || 0
|
||||
if (score >= 7) return "text-green-600"
|
||||
if (score >= 4) return "text-amber-500"
|
||||
return "text-red-500"
|
||||
})
|
||||
|
||||
const scoreBarColor = computed(() => {
|
||||
const score = stats.value?.avgScore || 0
|
||||
if (score >= 7) return "bg-gradient-to-r from-green-400 to-green-500"
|
||||
if (score >= 4) return "bg-gradient-to-r from-amber-400 to-amber-500"
|
||||
return "bg-gradient-to-r from-red-400 to-red-500"
|
||||
})
|
||||
|
||||
const fetchStats = async () => {
|
||||
try {
|
||||
const { data } = await axiosInstance.get(
|
||||
`/apis/console.api.comment-ai-autopilot.nxxy335.top/v1alpha1/stats?range=${range.value}`,
|
||||
`/apis/console.api.comment-ai-autopilot.nxxy335.top/v1alpha1/stats?range=7`,
|
||||
)
|
||||
stats.value = data
|
||||
} catch (e) {
|
||||
@@ -421,31 +257,6 @@ const openSettings = () => {
|
||||
window.location.href = "/console/comment-ai-autopilot/settings"
|
||||
}
|
||||
|
||||
const getSentimentPercent = (sentiment: string): number => {
|
||||
const dist = stats.value?.sentimentDistribution
|
||||
if (!dist) return 0
|
||||
const total = Object.values(dist).reduce((a, b) => a + b, 0)
|
||||
if (total === 0) return 0
|
||||
return Math.round(((dist[sentiment] || 0) / total) * 100)
|
||||
}
|
||||
|
||||
const getTrendBarHeight = (count: number): number => {
|
||||
const trend = stats.value?.dailyTrend
|
||||
if (!trend || trend.length === 0) return 0
|
||||
const max = Math.max(...trend.map(d => d.count), 1)
|
||||
return Math.max((count / max) * 100, count > 0 ? 8 : 4)
|
||||
}
|
||||
|
||||
const formatTrendDate = (dateStr: string): string => {
|
||||
if (!dateStr) return ''
|
||||
const parts = dateStr.split('-')
|
||||
return parts.length >= 3 ? `${parts[1]}/${parts[2]}` : dateStr
|
||||
}
|
||||
|
||||
watch(range, () => {
|
||||
fetchStats()
|
||||
})
|
||||
|
||||
onMounted(() => {
|
||||
fetchStats()
|
||||
fetchPersona()
|
||||
|
||||
@@ -152,7 +152,8 @@
|
||||
<div class="px-4 py-2.5 bg-gray-50 border-t border-gray-100 flex items-center justify-between">
|
||||
<div class="flex items-center gap-4 text-xs text-gray-400">
|
||||
<span>
|
||||
评分 <span :class="getScoreClass(reply.spec.score)" class="font-medium text-gray-600">{{ reply.spec.score }}</span>
|
||||
评分 <span :class="getScoreClass(reply.spec.score)" class="font-medium">{{ reply.spec.score }}</span>
|
||||
<span class="text-gray-300 ml-0.5">{{ getScoreLabel(reply.spec.score) }}</span>
|
||||
</span>
|
||||
<span v-if="reply.spec.postSlug" class="flex items-center gap-1">
|
||||
文章
|
||||
@@ -508,6 +509,14 @@ const getScoreClass = (score: number) => {
|
||||
return "text-red-600"
|
||||
}
|
||||
|
||||
const getScoreLabel = (score: number) => {
|
||||
if (score >= 85) return "优秀"
|
||||
if (score >= 70) return "良好"
|
||||
if (score >= 50) return "一般"
|
||||
if (score > 0) return "较差"
|
||||
return ""
|
||||
}
|
||||
|
||||
const getStatusClass = (status: string) => {
|
||||
switch (status) {
|
||||
case "PASS":
|
||||
|
||||
+385
-270
@@ -5,291 +5,324 @@
|
||||
<IconPlug class="mr-2 self-center" />
|
||||
</template>
|
||||
<template #actions>
|
||||
<VButton type="secondary" size="sm" @click="exportConfig">导出配置</VButton>
|
||||
<label class="inline-flex items-center px-3 py-1.5 text-sm font-medium rounded-md border border-gray-300 bg-white text-gray-700 hover:bg-gray-50 cursor-pointer transition-colors">
|
||||
导入配置
|
||||
<input type="file" accept=".json" class="hidden" @change="handleImportFile" />
|
||||
</label>
|
||||
<VButton @click="$router.push({ name: 'CommentAiAutopilot' })">返回概览</VButton>
|
||||
<VSpace spacing="sm">
|
||||
<VButton size="sm" @click="exportConfig">
|
||||
<template #icon>
|
||||
<svg style="width:14px;height:14px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4"/></svg>
|
||||
</template>
|
||||
导出
|
||||
</VButton>
|
||||
<label class="inline-flex items-center px-3 py-1.5 text-sm font-medium rounded-md border border-gray-300 bg-white text-gray-700 hover:bg-gray-50 cursor-pointer transition-colors">
|
||||
<svg style="width:14px;height:14px;margin-right:4px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-8l-4-4m0 0L8 8m4-4v12"/></svg>
|
||||
导入
|
||||
<input type="file" accept=".json" class="hidden" @change="handleImportFile" />
|
||||
</label>
|
||||
<VButton size="sm" @click="$router.push({ name: 'CommentAiAutopilot' })">返回概览</VButton>
|
||||
</VSpace>
|
||||
</template>
|
||||
</VPageHeader>
|
||||
|
||||
<div class="m-4">
|
||||
<VLoading v-if="loading" />
|
||||
|
||||
<div v-if="!loading" class="settings-container">
|
||||
<!-- Left: Settings Sections -->
|
||||
<div class="settings-sections space-y-5">
|
||||
<!-- ========== 基本设置 ========== -->
|
||||
<section class="settings-section">
|
||||
<div class="section-header section-header--blue">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M10.325 4.317c.426-1.756 2.924-1.756 3.35 0a1.724 1.724 0 002.573 1.066c1.543-.94 3.31.826 2.37 2.37a1.724 1.724 0 001.066 2.573c1.756.426 1.756 2.924 0 3.35a1.724 1.724 0 00-1.066 2.573c.94 1.543-.826 3.31-2.37 2.37a1.724 1.724 0 00-2.573 1.066c-.426 1.756-2.924 1.756-3.35 0a1.724 1.724 0 00-2.573-1.066c-1.543.94-3.31-.826-2.37-2.37a1.724 1.724 0 00-1.066-2.573c-1.756-.426-1.756-2.924 0-3.35a1.724 1.724 0 001.066-2.573c-.94-1.543.826-3.31 2.37-2.37.996.608 2.296.07 2.572-1.065z"/><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M15 12a3 3 0 11-6 0 3 3 0 016 0z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>基本设置</h3>
|
||||
<p>控制AI回复的基本行为</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Switch Row: 自动回复 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">自动回复</span>
|
||||
<span class="form-hint">启用后，AI将自动回复新评论</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.basic.autoReply" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
<!-- Switch Row: 自动发布 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">自动发布</span>
|
||||
<span class="form-hint">关闭后AI回复将存为草稿，需手动审核发布</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.basic.autoPublish" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
<!-- Slider: 最大对话轮次 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">最大对话轮次</span>
|
||||
<span class="form-badge">{{ settings.basic.maxConversationRounds }}</span>
|
||||
</div>
|
||||
<span class="form-hint">同一评论线程中AI最多自动回复的轮次</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.basic.maxConversationRounds" min="1" max="100" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1</span><span>50</span><span>100</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Input: 速率限制 -->
|
||||
<div class="form-field">
|
||||
<label class="form-label">速率限制</label>
|
||||
<span class="form-hint">每分钟最大AI回复数量</span>
|
||||
<input type="number" v-model.number="settings.basic.rateLimitPerMinute" min="1" max="100" class="form-input" placeholder="10" />
|
||||
</div>
|
||||
<!-- Slider: 最大重试次数 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">最大重试次数</span>
|
||||
<span class="form-badge">{{ settings.basic.maxRetryCount }}</span>
|
||||
</div>
|
||||
<span class="form-hint">AI生成失败时的最大重试次数，采用指数退避策略</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.basic.maxRetryCount" min="1" max="10" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1</span><span>5</span><span>10</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Textarea: 评论者黑名单 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">评论者黑名单</span>
|
||||
<button class="btn-link" @click="openCommenterDialog">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M18 9v3m0 0v3m0-3h3m-3 0h-3m-2-5a4 4 0 11-8 0 4 4 0 018 0zM3 20a6 6 0 0112 0v1H3v-1z"/></svg>
|
||||
添加评论者
|
||||
</button>
|
||||
</div>
|
||||
<span class="form-hint">支持名称、邮箱和正则表达式。正则以 regex: 开头，如 regex:^spam.*</span>
|
||||
<textarea v-model="settings.basic.blockedCommenters" rows="2" class="form-textarea" placeholder="例如：张三, spam@example.com, 李四"></textarea>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
<div v-if="!loading">
|
||||
<!-- Tab Navigation (full width, above the grid) -->
|
||||
<div class="settings-tabs">
|
||||
<button
|
||||
v-for="tab in tabItems"
|
||||
:key="tab.value"
|
||||
class="settings-tab"
|
||||
:class="{ 'settings-tab--active': activeTab === tab.value }"
|
||||
@click="activeTab = tab.value"
|
||||
>
|
||||
{{ tab.label }}
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<!-- ========== AI角色设置 ========== -->
|
||||
<section class="settings-section">
|
||||
<div class="section-header section-header--purple">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M16 7a4 4 0 11-8 0 4 4 0 018 0zM12 14a7 7 0 00-7 7h14a7 7 0 00-7-7z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>AI角色设置</h3>
|
||||
<p>定义AI虚拟评论者的身份和风格</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Persona List -->
|
||||
<VLoading v-if="personasLoading" />
|
||||
<div v-else-if="personas.length === 0" class="persona-empty">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M17 20h5v-2a3 3 0 00-5.356-1.857M17 20H7m10 0v-2c0-.656-.126-1.283-.356-1.857M7 20H2v-2a3 3 0 015.356-1.857M7 20v-2c0-.656.126-1.283.356-1.857m0 0a5.002 5.002 0 019.288 0M15 7a3 3 0 11-6 0 3 3 0 016 0z"/></svg>
|
||||
<span>请添加至少一个AI角色</span>
|
||||
</div>
|
||||
<div v-else class="persona-list">
|
||||
<div v-for="p in personas" :key="p.metadata.name" class="persona-card">
|
||||
<div class="persona-card__avatar">
|
||||
<img v-if="getPersonaAvatar(p)" :src="getPersonaAvatar(p)" alt="头像" />
|
||||
<span v-else class="persona-card__avatar-fallback">{{ (p.spec.displayName || '?').charAt(0) }}</span>
|
||||
</div>
|
||||
<div class="persona-card__info">
|
||||
<div class="persona-card__name">
|
||||
{{ p.spec.displayName || '未命名' }}
|
||||
<span v-if="p.spec.isDefault" class="persona-card__badge">默认</span>
|
||||
</div>
|
||||
<div class="persona-card__prompt">{{ p.spec.prompt || '暂无提示词' }}</div>
|
||||
</div>
|
||||
<div class="persona-card__actions">
|
||||
<button class="btn-icon" title="编辑" @click="openPersonaDialog(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"/></svg>
|
||||
</button>
|
||||
<button v-if="!p.spec?.isDefault" class="btn-icon btn-icon--danger" title="删除" @click="deletePersona(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"/></svg>
|
||||
</button>
|
||||
<button v-if="!p.spec?.isDefault" class="btn-icon" title="设为默认" @click="setDefaultPersona(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M11.049 2.927c.3-.921 1.603-.921 1.902 0l1.519 4.674a1 1 0 00.95.69h4.915c.969 0 1.371 1.24.588 1.81l-3.976 2.888a1 1 0 00-.363 1.118l1.518 4.674c.3.922-.755 1.688-1.538 1.118l-3.976-2.888a1 1 0 00-1.176 0l-3.976 2.888c-.783.57-1.838-.197-1.538-1.118l1.518-4.674a1 1 0 00-.363-1.118l-3.976-2.888c-.784-.57-.38-1.81.588-1.81h4.914a1 1 0 00.951-.69l1.519-4.674z"/></svg>
|
||||
</button>
|
||||
</div>
|
||||
<!-- Settings Grid: sections (left) + sidebar (right) -->
|
||||
<div class="settings-container">
|
||||
<!-- Left: Settings Sections -->
|
||||
<div class="settings-sections space-y-5">
|
||||
<!-- ========== 基本设置 ========== -->
|
||||
<section v-if="activeTab === 'basic'" class="settings-section">
|
||||
<div class="section-header section-header--blue">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M10.325 4.317c.426-1.756 2.924-1.756 3.35 0a1.724 1.724 0 002.573 1.066c1.543-.94 3.31.826 2.37 2.37a1.724 1.724 0 001.066 2.573c1.756.426 1.756 2.924 0 3.35a1.724 1.724 0 00-1.066 2.573c.94 1.543-.826 3.31-2.37 2.37a1.724 1.724 0 00-2.573 1.066c-.426 1.756-2.924 1.756-3.35 0a1.724 1.724 0 00-2.573-1.066c-1.543.94-3.31-.826-2.37-2.37a1.724 1.724 0 00-1.066-2.573c-1.756-.426-1.756-2.924 0-3.35a1.724 1.724 0 001.066-2.573c-.94-1.543.826-3.31 2.37-2.37.996.608 2.296.07 2.572-1.065z"/><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M15 12a3 3 0 11-6 0 3 3 0 016 0z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>基本设置</h3>
|
||||
<p>控制AI回复的基本行为</p>
|
||||
</div>
|
||||
</div>
|
||||
<VButton type="secondary" @click="openPersonaDialog(null)">
|
||||
<svg style="width:16px;height:16px;margin-right:4px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M12 4v16m8-8H4"/></svg>
|
||||
添加角色
|
||||
</VButton>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== 模型设置 ========== -->
|
||||
<section class="settings-section">
|
||||
<div class="section-header section-header--green">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9.75 17L9 20l-1 1h8l-1-1-.75-3M3 13h18M5 17h14a2 2 0 002-2V5a2 2 0 00-2-2H5a2 2 0 00-2 2v10a2 2 0 002 2z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>模型设置</h3>
|
||||
<p>配置AI Foundation提供的模型</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<div class="form-field">
|
||||
<label class="form-label">AI模型名称</label>
|
||||
<span class="form-hint">留空使用AI Foundation默认模型，填写AiModel资源名称可指定模型</span>
|
||||
<input type="text" v-model="settings.model.modelName" class="form-input" placeholder="留空使用默认模型" />
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== Prompt设置 ========== -->
|
||||
<section class="settings-section">
|
||||
<div class="section-header section-header--amber">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>Prompt设置</h3>
|
||||
<p>自定义AI回复的提示词模板</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Preset Selection -->
|
||||
<div class="form-field">
|
||||
<label class="form-label">Prompt预设</label>
|
||||
<span class="form-hint">选择预设风格，可多选</span>
|
||||
<div class="preset-grid">
|
||||
<label v-for="p in promptPresets" :key="p.key" class="preset-item" :class="{ 'preset-item--active': isPresetEnabled(p.key) }">
|
||||
<input type="checkbox" :checked="isPresetEnabled(p.key)" @change="togglePreset(p.key)" class="preset-checkbox" />
|
||||
<div class="preset-item__content">
|
||||
<span class="preset-item__label">{{ p.label }}</span>
|
||||
<span class="preset-item__desc">{{ p.desc }}</span>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Switch Row: 自动回复 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">自动回复</span>
|
||||
<span class="form-hint">启用后，AI将自动回复新评论</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.basic.autoReply" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<label class="form-label">自定义Prompt模板</label>
|
||||
<span class="form-hint--inline">留空使用默认模板</span>
|
||||
<!-- Switch Row: 自动发布 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">自动发布</span>
|
||||
<span class="form-hint">关闭后AI回复将存为草稿，需手动审核发布</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.basic.autoPublish" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
<div class="var-tags">
|
||||
<span v-for="v in promptVariables" :key="v.name" class="var-tag">
|
||||
<code>{{ v.name }}</code> {{ v.desc }}
|
||||
</span>
|
||||
</div>
|
||||
<textarea v-model="settings.prompt.customPromptTemplate" rows="10" class="form-textarea form-textarea--mono" placeholder="自定义Prompt模板"></textarea>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== 数据清理 ========== -->
|
||||
<section class="settings-section">
|
||||
<div class="section-header section-header--red">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>数据清理</h3>
|
||||
<p>自动清理过期的AI回复记录</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Switch: 启用自动清理 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">启用自动清理</span>
|
||||
<span class="form-hint">每天自动清理超过保留天数的记录</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.cleanup.cleanupEnabled" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
<!-- Slider: 保留天数 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">保留天数</span>
|
||||
<span class="form-badge">{{ settings.cleanup.retentionDays }} 天</span>
|
||||
</div>
|
||||
<span class="form-hint">超过此天数的AI回复记录将被自动清理</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.cleanup.retentionDays" min="1" max="365" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1天</span><span>180天</span><span>365天</span>
|
||||
<!-- Slider: 最大对话轮次 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">最大对话轮次</span>
|
||||
<span class="form-badge">{{ settings.basic.maxConversationRounds }}</span>
|
||||
</div>
|
||||
<span class="form-hint">同一评论线程中AI最多自动回复的轮次</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.basic.maxConversationRounds" min="1" max="100" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1</span><span>50</span><span>100</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Manual Cleanup -->
|
||||
<div class="form-row form-row--bordered">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">手动清理</span>
|
||||
<span class="form-hint">立即执行一次清理操作</span>
|
||||
<!-- Input: 速率限制 -->
|
||||
<div class="form-field">
|
||||
<label class="form-label">速率限制</label>
|
||||
<span class="form-hint">每分钟最大AI回复数量</span>
|
||||
<input type="number" v-model.number="settings.basic.rateLimitPerMinute" min="1" max="100" class="form-input" placeholder="10" />
|
||||
</div>
|
||||
<div class="form-row__action">
|
||||
<VButton size="sm" type="secondary" @click="performCleanup" :disabled="cleanupLoading">
|
||||
{{ cleanupLoading ? '清理中...' : '立即清理' }}
|
||||
<!-- Slider: 最大重试次数 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">最大重试次数</span>
|
||||
<span class="form-badge">{{ settings.basic.maxRetryCount }}</span>
|
||||
</div>
|
||||
<span class="form-hint">AI生成失败时的最大重试次数，采用指数退避策略</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.basic.maxRetryCount" min="1" max="10" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1</span><span>5</span><span>10</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Textarea: 评论者黑名单 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">评论者黑名单</span>
|
||||
<button class="btn-link" @click="openCommenterDialog">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M18 9v3m0 0v3m0-3h3m-3 0h-3m-2-5a4 4 0 11-8 0 4 4 0 018 0zM3 20a6 6 0 0112 0v1H3v-1z"/></svg>
|
||||
添加评论者
|
||||
</button>
|
||||
</div>
|
||||
<span class="form-hint">支持名称、邮箱和正则表达式。正则以 regex: 开头，如 regex:^spam.*</span>
|
||||
<textarea v-model="settings.basic.blockedCommenters" rows="2" class="form-textarea" placeholder="例如：张三, spam@example.com, 李四"></textarea>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== AI角色设置 ========== -->
|
||||
<section v-if="activeTab === 'persona'" class="settings-section">
|
||||
<div class="section-header section-header--purple">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M16 7a4 4 0 11-8 0 4 4 0 018 0zM12 14a7 7 0 00-7 7h14a7 7 0 00-7-7z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>AI角色设置</h3>
|
||||
<p>定义AI虚拟评论者的身份和风格</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Persona List -->
|
||||
<VLoading v-if="personasLoading" />
|
||||
<div v-else-if="personas.length === 0" class="persona-empty">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M17 20h5v-2a3 3 0 00-5.356-1.857M17 20H7m10 0v-2c0-.656-.126-1.283-.356-1.857M7 20H2v-2a3 3 0 015.356-1.857M7 20v-2c0-.656.126-1.283.356-1.857m0 0a5.002 5.002 0 019.288 0M15 7a3 3 0 11-6 0 3 3 0 016 0z"/></svg>
|
||||
<span>请添加至少一个AI角色</span>
|
||||
</div>
|
||||
<div v-else class="persona-list">
|
||||
<div v-for="p in personas" :key="p.metadata.name" class="persona-card">
|
||||
<div class="persona-card__avatar">
|
||||
<img v-if="getPersonaAvatar(p)" :src="getPersonaAvatar(p)" alt="头像" />
|
||||
<span v-else class="persona-card__avatar-fallback">{{ (p.spec.displayName || '?').charAt(0) }}</span>
|
||||
</div>
|
||||
<div class="persona-card__info">
|
||||
<div class="persona-card__name">
|
||||
{{ p.spec.displayName || '未命名' }}
|
||||
<span v-if="p.spec.isDefault" class="persona-card__badge">默认</span>
|
||||
</div>
|
||||
<div class="persona-card__prompt">{{ p.spec.prompt || '暂无提示词' }}</div>
|
||||
</div>
|
||||
<div class="persona-card__actions">
|
||||
<button class="btn-icon" title="编辑" @click="openPersonaDialog(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M11 5H6a2 2 0 00-2 2v11a2 2 0 002 2h11a2 2 0 002-2v-5m-1.414-9.414a2 2 0 112.828 2.828L11.828 15H9v-2.828l8.586-8.586z"/></svg>
|
||||
</button>
|
||||
<button v-if="!p.spec?.isDefault" class="btn-icon btn-icon--danger" title="删除" @click="deletePersona(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"/></svg>
|
||||
</button>
|
||||
<button v-if="!p.spec?.isDefault" class="btn-icon" title="设为默认" @click="setDefaultPersona(p)">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M11.049 2.927c.3-.921 1.603-.921 1.902 0l1.519 4.674a1 1 0 00.95.69h4.915c.969 0 1.371 1.24.588 1.81l-3.976 2.888a1 1 0 00-.363 1.118l1.518 4.674c.3.922-.755 1.688-1.538 1.118l-3.976-2.888a1 1 0 00-1.176 0l-3.976 2.888c-.783.57-1.838-.197-1.538-1.118l1.518-4.674a1 1 0 00-.363-1.118l-3.976-2.888c-.784-.57-.38-1.81.588-1.81h4.914a1 1 0 00.951-.69l1.519-4.674z"/></svg>
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<VButton type="secondary" @click="openPersonaDialog(null)">
|
||||
<svg style="width:16px;height:16px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M12 4v16m8-8H4"/></svg>
|
||||
添加角色
|
||||
</VButton>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== 模型设置 ========== -->
|
||||
<section v-if="activeTab === 'model'" class="settings-section">
|
||||
<div class="section-header section-header--green">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9.75 17L9 20l-1 1h8l-1-1-.75-3M3 13h18M5 17h14a2 2 0 002-2V5a2 2 0 00-2-2H5a2 2 0 00-2 2v10a2 2 0 002 2z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>模型设置</h3>
|
||||
<p>配置AI Foundation提供的模型</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<div class="form-field">
|
||||
<label class="form-label">AI模型名称</label>
|
||||
<span class="form-hint">留空使用AI Foundation默认模型，填写AiModel资源名称可指定模型</span>
|
||||
<input type="text" v-model="settings.model.modelName" class="form-input" placeholder="留空使用默认模型" />
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== Prompt设置 ========== -->
|
||||
<section v-if="activeTab === 'prompt'" class="settings-section">
|
||||
<div class="section-header section-header--amber">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>Prompt设置</h3>
|
||||
<p>自定义AI回复的提示词模板</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Preset Selection -->
|
||||
<div class="form-field">
|
||||
<label class="form-label">Prompt预设</label>
|
||||
<span class="form-hint">选择预设风格，可多选</span>
|
||||
<div class="preset-grid">
|
||||
<label v-for="p in promptPresets" :key="p.key" class="preset-item" :class="{ 'preset-item--active': isPresetEnabled(p.key) }">
|
||||
<input type="checkbox" :checked="isPresetEnabled(p.key)" @change="togglePreset(p.key)" class="preset-checkbox" />
|
||||
<div class="preset-item__content">
|
||||
<span class="preset-item__label">{{ p.label }}</span>
|
||||
<span class="preset-item__desc">{{ p.desc }}</span>
|
||||
</div>
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<label class="form-label">自定义Prompt模板</label>
|
||||
<span class="form-hint--inline">留空使用默认模板</span>
|
||||
</div>
|
||||
<div class="var-tags">
|
||||
<span v-for="v in promptVariables" :key="v.name" class="var-tag">
|
||||
<code>{{ v.name }}</code> {{ v.desc }}
|
||||
</span>
|
||||
</div>
|
||||
<textarea v-model="settings.prompt.customPromptTemplate" rows="10" class="form-textarea form-textarea--mono" placeholder="自定义Prompt模板"></textarea>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- ========== 数据清理 ========== -->
|
||||
<section v-if="activeTab === 'cleanup'" class="settings-section">
|
||||
<div class="section-header section-header--red">
|
||||
<div class="section-header__icon">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"/></svg>
|
||||
</div>
|
||||
<div class="section-header__text">
|
||||
<h3>数据清理</h3>
|
||||
<p>自动清理过期的AI回复记录</p>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section-body">
|
||||
<!-- Switch: 启用自动清理 -->
|
||||
<div class="form-row">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">启用自动清理</span>
|
||||
<span class="form-hint">每天自动清理超过保留天数的记录</span>
|
||||
</div>
|
||||
<label class="toggle">
|
||||
<input type="checkbox" v-model="settings.cleanup.cleanupEnabled" />
|
||||
<span class="toggle__track"><span class="toggle__thumb"></span></span>
|
||||
</label>
|
||||
</div>
|
||||
<!-- Slider: 保留天数 -->
|
||||
<div class="form-field">
|
||||
<div class="form-field__header">
|
||||
<span class="form-label">保留天数</span>
|
||||
<span class="form-badge">{{ settings.cleanup.retentionDays }} 天</span>
|
||||
</div>
|
||||
<span class="form-hint">超过此天数的AI回复记录将被自动清理</span>
|
||||
<div class="slider">
|
||||
<input type="range" v-model.number="settings.cleanup.retentionDays" min="1" max="365" class="slider__input" />
|
||||
<div class="slider__marks">
|
||||
<span>1天</span><span>180天</span><span>365天</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<!-- Manual Cleanup -->
|
||||
<div class="form-row form-row--bordered">
|
||||
<div class="form-row__label">
|
||||
<span class="form-label">手动清理</span>
|
||||
<span class="form-hint">立即执行一次清理操作</span>
|
||||
</div>
|
||||
<div class="form-row__action">
|
||||
<VButton size="sm" type="secondary" @click="performCleanup" :disabled="cleanupLoading">
|
||||
{{ cleanupLoading ? '清理中...' : '立即清理' }}
|
||||
</VButton>
|
||||
</div>
|
||||
</div>
|
||||
<div v-if="cleanupResult !== null" class="cleanup-result">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 12l2 2 4-4m6 2a9 9 0 11-18 0 9 9 0 0118 0z"/></svg>
|
||||
清理完成，共删除 {{ cleanupResult }} 条记录
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
</div>
|
||||
|
||||
<!-- Right: Sticky Save Bar -->
|
||||
<div class="settings-sidebar">
|
||||
<div class="settings-sidebar__inner">
|
||||
<div class="sidebar-card sidebar-card--primary">
|
||||
<div class="sidebar-card__header">
|
||||
<h4 class="sidebar-card__title">操作</h4>
|
||||
<span v-if="hasUnsavedChanges" class="sidebar-card__badge">未保存</span>
|
||||
</div>
|
||||
<div class="sidebar-card__actions">
|
||||
<VButton block type="primary" @click="saveSettings" :disabled="saving">
|
||||
<template v-if="!saving">
|
||||
<svg style="width:14px;height:14px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M5 13l4 4L19 7"/></svg>
|
||||
</template>
|
||||
{{ saving ? '保存中...' : '保存设置' }}
|
||||
</VButton>
|
||||
<VButton block @click="fetchSettings" :disabled="saving">
|
||||
<svg style="width:14px;height:14px" fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 4v5h.582m15.356 2A8.001 8.001 0 004.582 9m0 0H9m11 11v-5h-.581m0 0a8.003 8.003 0 01-15.357-2m15.357 2H15"/></svg>
|
||||
重置为当前值
|
||||
</VButton>
|
||||
</div>
|
||||
</div>
|
||||
<div v-if="cleanupResult !== null" class="cleanup-result">
|
||||
<svg fill="none" stroke="currentColor" viewBox="0 0 24 24"><path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 12l2 2 4-4m6 2a9 9 0 11-18 0 9 9 0 0118 0z"/></svg>
|
||||
清理完成，共删除 {{ cleanupResult }} 条记录
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
</div>
|
||||
|
||||
<!-- Right: Sticky Save Bar -->
|
||||
<div class="settings-sidebar">
|
||||
<div class="settings-sidebar__inner">
|
||||
<div class="sidebar-card">
|
||||
<h4 class="sidebar-card__title">操作</h4>
|
||||
<div class="sidebar-card__actions">
|
||||
<VButton block type="primary" @click="saveSettings" :disabled="saving">
|
||||
{{ saving ? '保存中...' : '保存设置' }}
|
||||
</VButton>
|
||||
<VButton block @click="fetchSettings">重置为当前值</VButton>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sidebar-card">
|
||||
<h4 class="sidebar-card__title">可用模板变量</h4>
|
||||
<div class="sidebar-card__vars">
|
||||
<div v-for="v in promptVariables" :key="v.name" class="sidebar-var">
|
||||
<code>{{ v.name }}</code>
|
||||
<span>{{ v.desc }}</span>
|
||||
<div v-if="activeTab === 'prompt'" class="sidebar-card">
|
||||
<h4 class="sidebar-card__title">可用模板变量</h4>
|
||||
<div class="sidebar-card__vars">
|
||||
<div v-for="v in promptVariables" :key="v.name" class="sidebar-var">
|
||||
<code>{{ v.name }}</code>
|
||||
<span>{{ v.desc }}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@@ -414,8 +447,16 @@
|
||||
<script setup lang="ts">
|
||||
import { ref, reactive, computed, onMounted, watch } from "vue"
|
||||
import { axiosInstance, coreApiClient } from "@halo-dev/api-client"
|
||||
import { VPageHeader, VButton, VLoading, Toast, VModal, VSpace } from "@halo-dev/components"
|
||||
import { IconPlug } from "@halo-dev/components"
|
||||
import { VPageHeader, VButton, VLoading, Toast, VModal, VSpace, IconPlug } from "@halo-dev/components"
|
||||
|
||||
const activeTab = ref("basic")
|
||||
const tabItems = [
|
||||
{ label: "基本设置", value: "basic" },
|
||||
{ label: "AI角色", value: "persona" },
|
||||
{ label: "模型设置", value: "model" },
|
||||
{ label: "Prompt", value: "prompt" },
|
||||
{ label: "数据清理", value: "cleanup" },
|
||||
]
|
||||
|
||||
const promptVariables = [
|
||||
{ name: '{{persona_prompt}}', desc: '人格提示词' },
|
||||
@@ -489,6 +530,12 @@ const settings = reactive({
|
||||
cleanup: { cleanupEnabled: true, retentionDays: 30 },
|
||||
})
|
||||
|
||||
// Track unsaved changes: snapshot of settings after last fetch/save
|
||||
const lastSavedSnapshot = ref("")
|
||||
const hasUnsavedChanges = computed(() => {
|
||||
return JSON.stringify(settings) !== lastSavedSnapshot.value
|
||||
})
|
||||
|
||||
const configMapName = "comment-ai-autopilot-configmap"
|
||||
const apiBase = "/apis/console.api.comment-ai-autopilot.nxxy335.top/v1alpha1"
|
||||
|
||||
@@ -817,7 +864,11 @@ const fetchSettings = async () => {
|
||||
if (Object.keys(cleanup).length) { settings.cleanup.cleanupEnabled = cleanup.cleanupEnabled !== false; settings.cleanup.retentionDays = (cleanup.retentionDays as number) || 30 }
|
||||
}
|
||||
} catch (e) { console.error("Failed to fetch settings", e) }
|
||||
finally { loading.value = false }
|
||||
finally {
|
||||
loading.value = false
|
||||
// Update snapshot after fetch to reset unsaved indicator
|
||||
lastSavedSnapshot.value = JSON.stringify(settings)
|
||||
}
|
||||
}
|
||||
|
||||
const saveSettings = async () => {
|
||||
@@ -834,6 +885,8 @@ const saveSettings = async () => {
|
||||
}
|
||||
await coreApiClient.configMap.updateConfigMap({ name: configMapName, configMap: updated })
|
||||
Toast.success("设置已保存")
|
||||
// Update snapshot after save to reset unsaved indicator
|
||||
lastSavedSnapshot.value = JSON.stringify(settings)
|
||||
} catch (e) { console.error("Failed to save settings", e); Toast.error("保存设置失败") }
|
||||
finally { saving.value = false }
|
||||
}
|
||||
@@ -847,6 +900,43 @@ onMounted(async () => {
|
||||
|
||||
<style scoped>
|
||||
/* ===== Layout ===== */
|
||||
.settings-tabs {
|
||||
display: flex;
|
||||
gap: 4px;
|
||||
margin-bottom: 20px;
|
||||
padding: 4px;
|
||||
background: #fff;
|
||||
border: 1px solid #e5e7eb;
|
||||
border-radius: 12px;
|
||||
overflow-x: auto;
|
||||
}
|
||||
.settings-tab {
|
||||
flex: 1;
|
||||
padding: 10px 16px;
|
||||
font-size: 14px;
|
||||
font-weight: 500;
|
||||
color: #6b7280;
|
||||
background: transparent;
|
||||
border: none;
|
||||
border-radius: 8px;
|
||||
cursor: pointer;
|
||||
transition: all 0.15s ease;
|
||||
white-space: nowrap;
|
||||
text-align: center;
|
||||
}
|
||||
.settings-tab:hover {
|
||||
background: #f3f4f6;
|
||||
color: #374151;
|
||||
}
|
||||
.settings-tab--active {
|
||||
background: #3b82f6;
|
||||
color: #fff;
|
||||
}
|
||||
.settings-tab--active:hover {
|
||||
background: #2563eb;
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
.settings-container {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 280px;
|
||||
@@ -1221,14 +1311,39 @@ onMounted(async () => {
|
||||
background: #fff; border: 1px solid #e5e7eb; border-radius: 12px;
|
||||
padding: 20px;
|
||||
}
|
||||
.sidebar-card--primary {
|
||||
border-color: #dbeafe;
|
||||
background: linear-gradient(135deg, #eff6ff 0%, #fff 100%);
|
||||
}
|
||||
.sidebar-card__header {
|
||||
display: flex; align-items: center; justify-content: space-between;
|
||||
margin-bottom: 14px; padding-bottom: 10px;
|
||||
border-bottom: 1px solid #f3f4f6;
|
||||
}
|
||||
.sidebar-card__badge {
|
||||
display: inline-flex; align-items: center;
|
||||
padding: 2px 8px; font-size: 11px; font-weight: 500;
|
||||
background: #fef3c7; color: #d97706; border-radius: 4px;
|
||||
}
|
||||
.sidebar-card__title {
|
||||
font-size: 14px; font-weight: 600; color: #1f2937;
|
||||
margin: 0 0 14px; padding-bottom: 10px;
|
||||
border-bottom: 1px solid #f3f4f6;
|
||||
}
|
||||
.sidebar-card--primary .sidebar-card__title {
|
||||
margin-bottom: 0; padding-bottom: 0; border-bottom: none;
|
||||
}
|
||||
.sidebar-card__actions {
|
||||
display: flex; flex-direction: column; gap: 8px;
|
||||
}
|
||||
/* Align icon + text inside VButton (btn-content wraps the default slot) */
|
||||
.sidebar-card__actions :deep(.btn-content),
|
||||
.section-body :deep(.btn-content) {
|
||||
display: inline-flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
gap: 4px;
|
||||
}
|
||||
.sidebar-card__vars {
|
||||
display: flex; flex-direction: column; gap: 8px;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user