多场景分析代码架构

2026-01-06 22:07:30 +08:00
parent 146d56fbd4
commit be1554cd9a
3 changed files with 218 additions and 0 deletions
--- a/src/main/java/com/rj/service/impl/AudioTextAnalysisLlmServiceImpl.java
+++ b/src/main/java/com/rj/service/impl/AudioTextAnalysisLlmServiceImpl.java
@@ -0,0 +1,134 @@
+package com.rj.service.impl;
+
+import com.alibaba.dashscope.aigc.generation.Generation;
+import com.alibaba.dashscope.aigc.generation.GenerationParam;
+import com.alibaba.dashscope.aigc.generation.GenerationResult;
+import com.alibaba.dashscope.common.Message;
+import com.alibaba.dashscope.common.Role;
+import com.alibaba.dashscope.exception.InputRequiredException;
+import com.alibaba.dashscope.exception.NoApiKeyException;
+import com.rj.common.AudioAnalysisSceneType;
+import com.rj.service.IAudioTextAnalysisLlmService;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Service;
+
+import java.io.InputStream;
+import java.nio.charset.StandardCharsets;
+import java.util.Arrays;
+import java.util.Map;
+import java.util.Scanner;
+import java.util.concurrent.ConcurrentHashMap;
+
+/**
+ * 音频文本分析 - 大模型通用服务实现
+ */
+@Service
+@Slf4j
+public class AudioTextAnalysisLlmServiceImpl implements IAudioTextAnalysisLlmService {
+
+    private static final Map<String, String> SYSTEM_PROMPT_CACHE = new ConcurrentHashMap<>();
+    private static final Map<String, String> USER_PROMPT_CACHE = new ConcurrentHashMap<>();
+
+    @Override
+    public String generateSummaryByLLM(AudioAnalysisSceneType sceneType, String recordingText) {
+        long startTime = System.currentTimeMillis();
+        log.info("开始调用大模型生成总结，场景: {}", sceneType);
+
+        String systemPrompt = getSystemPrompt(sceneType);
+        String userPromptTemplate = getUserPromptTemplate(sceneType);
+        String userPrompt = buildPrompt(userPromptTemplate, recordingText);
+
+        Generation gen = new Generation();
+        Message systemMsg = Message.builder()
+                .role(Role.SYSTEM.getValue())
+                .content(systemPrompt)
+                .build();
+        Message userMsg = Message.builder()
+                .role(Role.USER.getValue())
+                .content(userPrompt)
+                .build();
+
+        GenerationParam param = GenerationParam.builder()
+                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
+                .model(sceneType.getModelName())
+                .messages(Arrays.asList(systemMsg, userMsg))
+                .resultFormat(GenerationParam.ResultFormat.MESSAGE)
+                .build();
+
+        try {
+            GenerationResult call = gen.call(param);
+            String rawContent = call.getOutput().getChoices().get(0).getMessage().getContent();
+            log.info("大模型生成总结完成，场景: {}, 结果长度: {}", sceneType, rawContent != null ? rawContent.length() : 0);
+            return rawContent;
+        } catch (NoApiKeyException e) {
+            log.error("API密钥未配置", e);
+            throw new RuntimeException("API密钥未配置: " + e.getMessage(), e);
+        } catch (InputRequiredException e) {
+            log.error("输入参数错误", e);
+            throw new RuntimeException("输入参数错误: " + e.getMessage(), e);
+        } catch (Exception e) {
+            log.error("调用大模型生成总结失败, 场景: {}", sceneType, e);
+            throw new RuntimeException("调用大模型失败: " + e.getMessage(), e);
+        } finally {
+            long endTime = System.currentTimeMillis();
+            long durationMillis = endTime - startTime;
+            double durationSeconds = durationMillis / 1000.0;
+            double durationMinutes = durationSeconds / 60.0;
+            log.info("调用大模型耗时: {} 毫秒, {} 秒, {} 分钟, 场景: {}",
+                    durationMillis,
+                    String.format("%.2f", durationSeconds),
+                    String.format("%.2f", durationMinutes),
+                    sceneType);
+        }
+    }
+
+    private String buildPrompt(String template, String recordingText) {
+        if (template == null) {
+            return recordingText != null ? recordingText : "";
+        }
+        return template.replace("{RECORDING_TEXT}", recordingText != null ? recordingText : "");
+    }
+
+    private String getSystemPrompt(AudioAnalysisSceneType sceneType) {
+        return SYSTEM_PROMPT_CACHE.computeIfAbsent(sceneType.name(), key -> {
+            String path = sceneType.getSystemPromptPath();
+            String content = readResourceFile(path);
+            if (content == null || content.trim().isEmpty()) {
+                log.warn("无法读取系统提示词文件: {}，场景: {}，请检查资源文件是否存在", path, sceneType);
+            }
+            return content != null ? content : "";
+        });
+    }
+
+    private String getUserPromptTemplate(AudioAnalysisSceneType sceneType) {
+        return USER_PROMPT_CACHE.computeIfAbsent(sceneType.name(), key -> {
+            String path = sceneType.getUserPromptPath();
+            String content = readResourceFile(path);
+            if (content == null || content.trim().isEmpty()) {
+                log.warn("无法读取用户提示词模板文件: {}，场景: {}，请检查资源文件是否存在", path, sceneType);
+            }
+            return content != null ? content : "";
+        });
+    }
+
+    private String readResourceFile(String resourcePath) {
+        try {
+            ClassLoader classLoader = getClass().getClassLoader();
+            InputStream inputStream = classLoader.getResourceAsStream(resourcePath);
+            if (inputStream == null) {
+                log.error("无法找到资源文件: {}", resourcePath);
+                return null;
+            }
+            try (Scanner scanner = new Scanner(inputStream, StandardCharsets.UTF_8.name()).useDelimiter("\\A")) {
+                String content = scanner.hasNext() ? scanner.next() : "";
+                log.info("成功读取提示词文件: {}, 长度: {}", resourcePath, content.length());
+                return content;
+            }
+        } catch (Exception e) {
+            log.error("读取资源文件失败: {}", resourcePath, e);
+            return null;
+        }
+    }
+}
+
+