sf-chain框架对接日志能力

prompto-lab-app/src/main/java/io/github/timemachinelab/sfchain/constants/AIOperationConstant.java

@@ -13,11 +13,6 @@ public class AIOperationConstant {
      * JSON修复操作
      */
     public static final String JSON_REPAIR_OP = "JSON_REPAIR_OP";
-
-    /**
-     * 文本分类操作
-     */
-    public static final String TEXT_CLASSIFICATION_OP = "TEXT_CLASSIFICATION";
 
     /**
      * 模型验证操作

prompto-lab-app/src/main/java/io/github/timemachinelab/sfchain/controller/AICallLogController.java

@@ -2,10 +2,11 @@
 
 import io.github.timemachinelab.sfchain.core.logging.AICallLog;
 import io.github.timemachinelab.sfchain.core.logging.AICallLogManager;
-import org.springframework.beans.factory.annotation.Autowired;
+import io.github.timemachinelab.sfchain.core.logging.AICallLogSummary;
 import org.springframework.http.ResponseEntity;
 import org.springframework.web.bind.annotation.*;
 
+import javax.annotation.Resource;
 import java.util.List;
 import java.util.Map;
 
@@ -14,42 +15,43 @@
  */
 @RestController
 @RequestMapping("/sf/api/ai-logs")
+@CrossOrigin(origins = "*")
 public class AICallLogController {
 
-    @Autowired
+    @Resource
     private AICallLogManager logManager;
 
     /**
-     * 获取所有日志
+     * 获取所有日志摘要（轻量级）
      */
     @GetMapping
-    public ResponseEntity<List<AICallLog>> getAllLogs() {
-        return ResponseEntity.ok(logManager.getAllLogs());
+    public ResponseEntity<List<AICallLogSummary>> getAllLogSummaries() {
+        return ResponseEntity.ok(logManager.getAllLogSummaries());
     }
 
     /**
-     * 根据调用ID获取日志
+     * 根据调用ID获取完整日志详情
      */
     @GetMapping("/{callId}")
-    public ResponseEntity<AICallLog> getLog(@PathVariable String callId) {
-        AICallLog log = logManager.getLog(callId);
+    public ResponseEntity<AICallLog> getFullLog(@PathVariable String callId) {
+        AICallLog log = logManager.getFullLog(callId);
         return log != null ? ResponseEntity.ok(log) : ResponseEntity.notFound().build();
     }
 
     /**
-     * 根据操作类型获取日志
+     * 根据操作类型获取日志摘要（轻量级）
      */
     @GetMapping("/operation/{operationType}")
-    public ResponseEntity<List<AICallLog>> getLogsByOperation(@PathVariable String operationType) {
-        return ResponseEntity.ok(logManager.getLogsByOperation(operationType));
+    public ResponseEntity<List<AICallLogSummary>> getLogSummariesByOperation(@PathVariable String operationType) {
+        return ResponseEntity.ok(logManager.getLogSummariesByOperation(operationType));
     }
 
     /**
-     * 根据模型名称获取日志
+     * 根据模型名称获取日志摘要（轻量级）
      */
     @GetMapping("/model/{modelName}")
-    public ResponseEntity<List<AICallLog>> getLogsByModel(@PathVariable String modelName) {
-        return ResponseEntity.ok(logManager.getLogsByModel(modelName));
+    public ResponseEntity<List<AICallLogSummary>> getLogSummariesByModel(@PathVariable String modelName) {
+        return ResponseEntity.ok(logManager.getLogSummariesByModel(modelName));
     }
 
     /**

prompto-lab-app/src/main/java/io/github/timemachinelab/sfchain/controller/AIModelController.java

@@ -93,19 +93,19 @@ public ResponseEntity<Map<String, Object>> saveModel(
         Map<String, Object> result = new HashMap<>();
         String modelName = config.getModelName();
         try {
-            // 验证模型配置
-            boolean validationResult = validateModelConfig(modelName, config);
+            // 检查模型是否已存在
+            Map<String, ModelConfigData> existingModels = persistenceManager.getAllModelConfigs();
+            boolean modelExists = existingModels.containsKey(modelName);
+
+            // 验证模型配置（临时验证，不影响现有模型）
+            boolean validationResult = validateModelConfig(modelName, config, true);
 
             if (!validationResult) {
                 result.put("success", false);
                 result.put("message", "模型验证失败，请检查配置参数");
                 return ResponseEntity.badRequest().body(result);
             }
 
-            // 检查模型是否已存在
-            Map<String, ModelConfigData> existingModels = persistenceManager.getAllModelConfigs();
-            boolean modelExists = existingModels.containsKey(modelName);
-
             // 根据模型是否存在选择添加或更新
             if (modelExists) {
                 persistenceManager.updateModelConfig(modelName, config);
@@ -132,31 +132,12 @@ public ResponseEntity<Map<String, Object>> saveModel(
         }
     }
 
-    /**
-     * 删除模型配置
-     */
-    @DeleteMapping("/{modelName}")
-    public ResponseEntity<Map<String, Object>> deleteModel(@PathVariable String modelName) {
-        Map<String, Object> result = new HashMap<>();
-        try {
-            persistenceManager.deleteModelConfig(modelName);
-            result.put("success", true);
-            result.put("message", "模型配置删除成功");
-            result.put("modelName", modelName);
-            return ResponseEntity.ok(result);
-        } catch (Exception e) {
-            log.error("删除模型配置失败: {} - {}", modelName, e.getMessage());
-            result.put("success", false);
-            result.put("message", "删除失败: " + e.getMessage());
-            return ResponseEntity.badRequest().body(result);
-        }
-    }
-
     /**
      * 测试模型连接
      */
-    @PostMapping("/{modelName}/test")
-    public ResponseEntity<Map<String, Object>> testModel(@PathVariable String modelName) {
+    @PostMapping("/test")
+    public ResponseEntity<Map<String, Object>> testModel(@RequestBody Map<String, String> request) {
+        String modelName = request.get("modelName");
         Map<String, Object> result = new HashMap<>();
         try {
             Map<String, ModelConfigData> models = persistenceManager.getAllModelConfigs();
@@ -168,7 +149,8 @@ public ResponseEntity<Map<String, Object>> testModel(@PathVariable String modelN
                 return ResponseEntity.notFound().build();
             }
 
-            boolean testResult = validateModelConfig(modelName, config);
+            // 测试已存在的模型，不需要临时注册
+            boolean testResult = validateModelConfig(modelName, config, false);
             result.put("success", testResult);
             result.put("message", testResult ? "模型连接测试成功" : "模型连接测试失败");
             result.put("modelName", modelName);
@@ -186,21 +168,27 @@ public ResponseEntity<Map<String, Object>> testModel(@PathVariable String modelN
 
     /**
      * 验证模型配置是否可用
+     * @param modelName 模型名称
+     * @param config 模型配置
+     * @param isTemporaryValidation 是否为临时验证（true: 验证后移除临时模型，false: 验证已存在的模型）
      */
-    private boolean validateModelConfig(String modelName, ModelConfigData config) {
+    private boolean validateModelConfig(String modelName, ModelConfigData config, boolean isTemporaryValidation) {
         boolean tempRegistered = false;
         try {
-            log.info("开始验证模型配置: {}", modelName);
+            log.info("开始验证模型配置: {} (临时验证: {})", modelName, isTemporaryValidation);
 
             ModelValidationOperation validationOp = (ModelValidationOperation) operationRegistry.getOperation(MODEL_VALIDATION_OP);
             if (validationOp == null) {
                 log.warn("未找到模型验证操作，跳过验证");
                 return true;
             }
 
-            OpenAIModelConfig tempConfig = convertToOpenAIConfig(config);
-            modelFactory.registerModel(tempConfig);
-            tempRegistered = true;
+            // 如果是临时验证，需要临时注册模型
+            if (isTemporaryValidation) {
+                OpenAIModelConfig tempConfig = convertToOpenAIConfig(config);
+                modelFactory.registerModel(tempConfig);
+                tempRegistered = true;
+            }
 
             ModelValidationOperation.ValidationRequest request = 
                 new ModelValidationOperation.ValidationRequest("请回答：2+3等于几？");
@@ -213,15 +201,38 @@ private boolean validateModelConfig(String modelName, ModelConfigData config) {
             log.error("模型验证失败: {} - {}", modelName, e.getMessage());
             return false;
         } finally {
-            if (tempRegistered) {
+            // 只有在临时验证时才清理临时模型
+            if (tempRegistered && isTemporaryValidation) {
                 try {
                     modelFactory.removeModel(modelName);
+                    log.debug("已清理临时模型配置: {}", modelName);
                 } catch (Exception e) {
                     log.warn("清理临时模型配置失败: {}", e.getMessage());
                 }
             }
         }
     }
+
+
+    /**
+     * 删除模型配置
+     */
+    @DeleteMapping("/{modelName}")
+    public ResponseEntity<Map<String, Object>> deleteModel(@PathVariable String modelName) {
+        Map<String, Object> result = new HashMap<>();
+        try {
+            persistenceManager.deleteModelConfig(modelName);
+            result.put("success", true);
+            result.put("message", "模型配置删除成功");
+            result.put("modelName", modelName);
+            return ResponseEntity.ok(result);
+        } catch (Exception e) {
+            log.error("删除模型配置失败: {} - {}", modelName, e.getMessage());
+            result.put("success", false);
+            result.put("message", "删除失败: " + e.getMessage());
+            return ResponseEntity.badRequest().body(result);
+        }
+    }
 
     /**
      * 转换配置格式

prompto-lab-app/src/main/java/io/github/timemachinelab/sfchain/core/AIOperationRegistry.java

@@ -86,13 +86,7 @@ public void registerOperation(String operationType, BaseAIOperation<?, ?> operat
      */
     public String getModelForOperation(String operationType) {
         // 优先从内存缓存获取
-        String cachedModel = modelMapping.get(operationType);
-        if (cachedModel != null) {
-            return cachedModel;
-        }
-
-        // 如果缓存中没有，可以从 PersistenceManager 获取操作配置中的模型名称
-        return null; // 或者注入 PersistenceManager 来获取
+        return modelMapping.get(operationType);
     }
 
     /**

prompto-lab-app/src/main/java/io/github/timemachinelab/sfchain/core/AIPromptBuilder.java

@@ -0,0 +1,155 @@
+package io.github.timemachinelab.sfchain.core;
+
+import java.time.LocalDateTime;
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
+
+/**
+ * AI提示词构建器
+ * 用于构建结构化的AI提示词，支持与AIResponseParser配合使用
+ * @author suifeng
+ * 日期: 2025/04/18
+ */
+public class AIPromptBuilder {
+
+    private final StringBuilder promptBuilder = new StringBuilder();
+    private boolean hasJsonOutput = false;
+
+    /**
+     * 创建一个提示词构建器
+     * @param title 提示词标题
+     */
+    public AIPromptBuilder(String title) {
+        promptBuilder.append("# ").append(title).append("\n\n");
+    }
+
+    /**
+     * 添加角色描述
+     * @param roleDescription 角色描述
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addRole(String roleDescription) {
+        // 获取当前北京时间
+        LocalDateTime now = LocalDateTime.now(ZoneId.of("Asia/Shanghai"));
+        String formattedTime = now.format(DateTimeFormatter.ofPattern("yyyy年MM月dd日 HH:mm:ss"));
+        promptBuilder.append("# 当前的时间是北京时间：").append(formattedTime).append("\n");
+        promptBuilder.append(roleDescription).append("\n\n");
+        return this;
+    }
+
+    /**
+     * 添加章节
+     * @param sectionTitle 章节标题
+     * @param content 章节内容
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addSection(String sectionTitle, String content) {
+        promptBuilder.append("## ").append(sectionTitle).append("\n");
+        promptBuilder.append(content).append("\n\n");
+        return this;
+    }
+
+    /**
+     * 添加子章节
+     * @param subSectionTitle 子章节标题
+     * @param content 子章节内容
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addSubSection(String subSectionTitle, String content) {
+        promptBuilder.append("### ").append(subSectionTitle).append("\n");
+        promptBuilder.append(content).append("\n\n");
+        return this;
+    }
+
+    /**
+     * 添加JSON输出格式
+     * @param jsonExample JSON示例
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addJsonOutput(String jsonExample) {
+        promptBuilder.append("## 输出格式要求\n");
+        promptBuilder.append("所有字符串中的引用部分只能用英文单引号 ' 包裹，内容中禁止出现英文双引号, 但是你要注意json格式规范是要加\"的，保证我能正常解析JSON 。\n");
+        promptBuilder.append("```json\n");
+        promptBuilder.append(jsonExample).append("\n");
+        promptBuilder.append("```\n");
+        promptBuilder.append("不需要给我任何额外的信息，我只需要最终的json结果，以保证生成和响应的速度\n");
+        hasJsonOutput = true;
+        return this;
+    }
+
+    /**
+     * 添加表格输出格式
+     * @param headers 表头
+     * @param example 示例行
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addTableOutput(String[] headers, String[] example) {
+        promptBuilder.append("## 输出格式要求\n");
+        promptBuilder.append("你必须严格按照以下表格格式返回结果：\n");
+        promptBuilder.append("```\n");
+
+        // 构建表头
+        promptBuilder.append("| ");
+        for (String header : headers) {
+            promptBuilder.append(header).append(" | ");
+        }
+        promptBuilder.append("\n");
+
+        // 构建分隔行
+        promptBuilder.append("| ");
+        for (int i = 0; i < headers.length; i++) {
+            promptBuilder.append("--- | ");
+        }
+        promptBuilder.append("\n");
+
+        // 构建示例行
+        if (example != null) {
+            promptBuilder.append("| ");
+            for (String cell : example) {
+                promptBuilder.append(cell).append(" | ");
+            }
+            promptBuilder.append("\n");
+        }
+
+        promptBuilder.append("```\n\n");
+        return this;
+    }
+
+    /**
+     * 添加自定义输出格式
+     * @param formatDescription 格式描述
+     * @param example 示例
+     * @param formatType 格式类型（用于AIResponseParser识别）
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addCustomOutput(String formatDescription, String example, String formatType) {
+        promptBuilder.append("## 输出格式要求\n");
+        promptBuilder.append(formatDescription).append("\n");
+        promptBuilder.append("```").append(formatType).append("\n");
+        promptBuilder.append(example).append("\n");
+        promptBuilder.append("```\n\n");
+        return this;
+    }
+
+    /**
+     * 添加原始文本（不添加任何格式）
+     * @param text 原始文本
+     * @return 构建器实例
+     */
+    public AIPromptBuilder addRawText(String text) {
+        promptBuilder.append(text).append("\n\n");
+        return this;
+    }
+
+    /**
+     * 构建提示词
+     * @return 完整的提示词字符串
+     */
+    public String build() {
+        if (!hasJsonOutput) {
+            // 如果没有指定输出格式，添加默认提示
+            promptBuilder.append("请确保你的回答简洁明了，直接提供所需信息。\n");
+        }
+        return promptBuilder.toString();
+    }
+}