[dev] ai节点对接

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

@@ -0,0 +1,71 @@
+package io.github.timemachinelab.sfchain.controller;
+
+import io.github.timemachinelab.sfchain.core.logging.AICallLog;
+import io.github.timemachinelab.sfchain.core.logging.AICallLogManager;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.http.ResponseEntity;
+import org.springframework.web.bind.annotation.*;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * AI调用日志查询控制器
+ */
+@RestController
+@RequestMapping("/sf/api/ai-logs")
+public class AICallLogController {
+
+    @Autowired
+    private AICallLogManager logManager;
+
+    /**
+     * 获取所有日志
+     */
+    @GetMapping
+    public ResponseEntity<List<AICallLog>> getAllLogs() {
+        return ResponseEntity.ok(logManager.getAllLogs());
+    }
+
+    /**
+     * 根据调用ID获取日志
+     */
+    @GetMapping("/{callId}")
+    public ResponseEntity<AICallLog> getLog(@PathVariable String callId) {
+        AICallLog log = logManager.getLog(callId);
+        return log != null ? ResponseEntity.ok(log) : ResponseEntity.notFound().build();
+    }
+
+    /**
+     * 根据操作类型获取日志
+     */
+    @GetMapping("/operation/{operationType}")
+    public ResponseEntity<List<AICallLog>> getLogsByOperation(@PathVariable String operationType) {
+        return ResponseEntity.ok(logManager.getLogsByOperation(operationType));
+    }
+
+    /**
+     * 根据模型名称获取日志
+     */
+    @GetMapping("/model/{modelName}")
+    public ResponseEntity<List<AICallLog>> getLogsByModel(@PathVariable String modelName) {
+        return ResponseEntity.ok(logManager.getLogsByModel(modelName));
+    }
+
+    /**
+     * 获取统计信息
+     */
+    @GetMapping("/statistics")
+    public ResponseEntity<AICallLogManager.LogStatistics> getStatistics() {
+        return ResponseEntity.ok(logManager.getStatistics());
+    }
+
+    /**
+     * 清空所有日志
+     */
+    @DeleteMapping
+    public ResponseEntity<Map<String, String>> clearLogs() {
+        logManager.clearLogs();
+        return ResponseEntity.ok(Map.of("message", "所有日志已清空"));
+    }
+}

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

@@ -87,11 +87,11 @@ public ResponseEntity<Object> getModel(@PathVariable String modelName) {
     /**
      * 创建或更新模型配置
      */
-    @PostMapping("/{modelName}")
+    @PostMapping("/save")
     public ResponseEntity<Map<String, Object>> saveModel(
-            @PathVariable String modelName,
             @Valid @RequestBody ModelConfigData config) {
         Map<String, Object> result = new HashMap<>();
+        String modelName = config.getModelName();
         try {
             // 验证模型配置
             boolean validationResult = validateModelConfig(modelName, config);

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

@@ -94,14 +94,22 @@ public ResponseEntity<Object> getOperation(@PathVariable String operationType) {
     }
 
     /**
-     * 保存操作配置
+     * 保存操作配置 - 改为统一的save接口，从请求体获取operationType
      */
-    @PostMapping("/{operationType}")
+    @PostMapping("/save")
     public ResponseEntity<Map<String, Object>> saveOperationConfig(
-            @PathVariable String operationType,
             @Valid @RequestBody OperationConfigData config) {
         Map<String, Object> result = new HashMap<>();
         try {
+            // 从config对象中获取operationType
+            String operationType = config.getOperationType();
+
+            if (operationType == null || operationType.trim().isEmpty()) {
+                result.put("success", false);
+                result.put("message", "操作类型不能为空");
+                return ResponseEntity.badRequest().body(result);
+            }
+
             persistenceManager.saveOperationConfig(operationType, config);
 
             result.put("success", true);
@@ -110,12 +118,52 @@ public ResponseEntity<Map<String, Object>> saveOperationConfig(
 
             return ResponseEntity.ok(result);
         } catch (Exception e) {
-            log.error("保存操作配置失败: {} - {}", operationType, e.getMessage());
+            log.error("保存操作配置失败: {}", e.getMessage());
             result.put("success", false);
             result.put("message", "保存失败: " + e.getMessage());
             return ResponseEntity.badRequest().body(result);
         }
     }
+
+    /**
+     * 获取单个操作配置 - 改为POST请求体参数
+     */
+    @PostMapping("/get")
+    public ResponseEntity<Object> getOperation(@RequestBody Map<String, String> request) {
+        try {
+            String operationType = request.get("operationType");
+
+            if (operationType == null || operationType.trim().isEmpty()) {
+                return ResponseEntity.badRequest()
+                    .body(Map.of("error", "操作类型不能为空"));
+            }
+
+            Optional<OperationConfigData> operationOpt = persistenceManager.getOperationConfig(operationType);
+
+            if (operationOpt.isEmpty()) {
+                return ResponseEntity.notFound().build();
+            }
+
+            OperationConfigData operation = operationOpt.get();
+
+            // 如果有关联模型，获取模型信息
+            if (operation.getModelName() != null) {
+                Map<String, ModelConfigData> models = persistenceManager.getAllModelConfigs();
+                ModelConfigData model = models.get(operation.getModelName());
+
+                Map<String, Object> result = new HashMap<>();
+                result.put("operation", operation);
+                result.put("associatedModel", model);
+                return ResponseEntity.ok(result);
+            }
+
+            return ResponseEntity.ok(operation);
+        } catch (Exception e) {
+            log.error("获取操作配置失败: {}", e.getMessage());
+            return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR)
+                .body(Map.of("error", "获取操作配置失败: " + e.getMessage()));
+        }
+    }
 
     /**
      * 批量设置操作模型映射
@@ -179,15 +227,22 @@ public ResponseEntity<Map<String, Object>> setOperationMappings(
     }
 
     /**
-     * 设置单个操作模型映射
+     * 设置单个操作模型映射 - 改为POST请求体参数
      */
-    @PostMapping("/{operationType}/mapping")
+    @PostMapping("/mapping")
     public ResponseEntity<Map<String, Object>> setOperationMapping(
-            @PathVariable String operationType,
             @RequestBody Map<String, String> request) {
         Map<String, Object> result = new HashMap<>();
         try {
+            String operationType = request.get("operationType");
             String modelName = request.get("modelName");
+
+            if (operationType == null || operationType.trim().isEmpty()) {
+                result.put("success", false);
+                result.put("message", "操作类型不能为空");
+                return ResponseEntity.badRequest().body(result);
+            }
+
             if (modelName == null || modelName.trim().isEmpty()) {
                 result.put("success", false);
                 result.put("message", "模型名称不能为空");
@@ -218,7 +273,7 @@ public ResponseEntity<Map<String, Object>> setOperationMapping(
 
             return ResponseEntity.ok(result);
         } catch (Exception e) {
-            log.error("设置操作映射失败: {} - {}", operationType, e.getMessage());
+            log.error("设置操作映射失败: {}", e.getMessage());
             result.put("success", false);
             result.put("message", "设置失败: " + e.getMessage());
             return ResponseEntity.badRequest().body(result);

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

@@ -2,6 +2,8 @@
 
 import com.alibaba.fastjson.JSONObject;
 import io.github.timemachinelab.sfchain.annotation.AIOp;
+import io.github.timemachinelab.sfchain.core.logging.AICallLog;
+import io.github.timemachinelab.sfchain.core.logging.AICallLogManager;
 import io.github.timemachinelab.sfchain.core.openai.OpenAICompatibleModel;
 import com.fasterxml.jackson.core.JsonProcessingException;
 import com.fasterxml.jackson.databind.ObjectMapper;
@@ -12,6 +14,8 @@
 import javax.annotation.PostConstruct;
 import java.lang.reflect.ParameterizedType;
 import java.lang.reflect.Type;
+import java.time.LocalDateTime;
+import java.util.UUID;
 
 import static io.github.timemachinelab.sfchain.constants.AIOperationConstant.JSON_REPAIR_OP;
 
@@ -130,42 +134,93 @@ public OUTPUT execute(INPUT input) {
      * @param modelName 指定的模型名称，为null时使用默认模型
      * @return 输出结果
      */
+    // 在BaseAIOperation类中添加以下字段和方法
+
+    @Autowired
+    private AICallLogManager logManager;
+
+    // 在execute方法中添加详细日志记录
     public OUTPUT execute(INPUT input, String modelName) {
+        String callId = UUID.randomUUID().toString();
+        LocalDateTime startTime = LocalDateTime.now();
+        long startMillis = System.currentTimeMillis();
+
+        AICallLog.AICallLogBuilder logBuilder = AICallLog.builder()
+                .callId(callId)
+                .operationType(annotation.value())
+                .callTime(startTime)
+                .input(input)
+                .modelName(modelName)
+                .frequency(1)
+                .lastAccessTime(startTime);
+
         try {
             // 获取模型
             AIModel model = getModel(modelName);
+            logBuilder.modelName(model.getName());
 
             // 构建提示词
             String prompt = buildPrompt(input);
+            logBuilder.prompt(prompt);
 
             // 获取操作配置
             AIOperationRegistry.OperationConfig config = operationRegistry.getOperationConfig(annotation.value());
 
-            // 合并注解配置和运行时配置
+            // 合并配置
             Integer finalMaxTokens = config.getMaxTokens() > 0 ? Integer.valueOf(config.getMaxTokens()) : (annotation.defaultMaxTokens() > 0 ? annotation.defaultMaxTokens() : null);
             Double finalTemperature = config.getTemperature() >= 0 ? Double.valueOf(config.getTemperature()) : (annotation.defaultTemperature() >= 0 ? annotation.defaultTemperature() : null);
             Boolean finalJsonOutput = config.isRequireJsonOutput() || annotation.requireJsonOutput();
             boolean finalThinking = config.isSupportThinking() || annotation.supportThinking();
 
-            // 调用AI模型 - 根据模型类型选择合适的方法
+            // 记录请求参数
+            AICallLog.AIRequestParams requestParams = AICallLog.AIRequestParams.builder()
+                    .maxTokens(finalMaxTokens)
+                    .temperature(finalTemperature)
+                    .jsonOutput(finalJsonOutput)
+                    .thinking(finalThinking)
+                    .build();
+            logBuilder.requestParams(requestParams);
+
+            // 调用AI模型
             String response;
             if (model instanceof OpenAICompatibleModel openAIModel) {
-
                 if (finalThinking) {
-                    // 使用思考模式
                     response = openAIModel.generateWithThinking(prompt, finalMaxTokens, finalTemperature);
                 } else {
-                    // 使用普通模式
                     response = openAIModel.generate(prompt, finalMaxTokens, finalTemperature, finalJsonOutput);
                 }
             } else {
-                // 对于其他类型的模型，使用基础接口
                 response = model.generate(prompt);
             }
 
+            logBuilder.rawResponse(response);
+
             // 解析响应
-            return parseResponse(response, input);
+            OUTPUT result = parseResponse(response, input);
+
+            // 记录成功日志
+            long duration = System.currentTimeMillis() - startMillis;
+            AICallLog log = logBuilder
+                    .status(AICallLog.CallStatus.SUCCESS)
+                    .duration(duration)
+                    .output(result)
+                    .build();
+
+            logManager.addLog(log);
+
+            return result;
+
         } catch (Exception e) {
+            // 记录失败日志
+            long duration = System.currentTimeMillis() - startMillis;
+            AICallLog callLog = logBuilder
+                    .status(AICallLog.CallStatus.FAILED)
+                    .duration(duration)
+                    .errorMessage(e.getMessage())
+                    .build();
+
+            logManager.addLog(callLog);
+
             log.error("执行AI操作失败: {} - {}", annotation.value(), e.getMessage(), e);
             throw new RuntimeException("AI操作执行失败: " + e.getMessage(), e);
         }

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

@@ -0,0 +1,71 @@
+package io.github.timemachinelab.sfchain.core.logging;
+
+import lombok.Builder;
+import lombok.Data;
+
+import java.time.LocalDateTime;
+import java.util.Map;
+
+/**
+ * AI调用日志实体
+ */
+@Data
+@Builder
+public class AICallLog {
+
+    /** 调用ID */
+    private String callId;
+
+    /** 操作类型 */
+    private String operationType;
+
+    /** 模型名称 */
+    private String modelName;
+
+    /** 调用时间 */
+    private LocalDateTime callTime;
+
+    /** 执行耗时(毫秒) */
+    private long duration;
+
+    /** 调用状态 */
+    private CallStatus status;
+
+    /** 原始输入参数 */
+    private Object input;
+
+    /** 构建的提示词 */
+    private String prompt;
+
+    /** AI请求参数 */
+    private AIRequestParams requestParams;
+
+    /** 模型原始返回结果 */
+    private String rawResponse;
+
+    /** 最终输出结果 */
+    private Object output;
+
+    /** 错误信息(如果有) */
+    private String errorMessage;
+
+    /** 调用频次(用于LFU) */
+    private int frequency;
+
+    /** 最后访问时间(用于LFU) */
+    private LocalDateTime lastAccessTime;
+
+    public enum CallStatus {
+        SUCCESS, FAILED, TIMEOUT
+    }
+
+    @Data
+    @Builder
+    public static class AIRequestParams {
+        private Integer maxTokens;
+        private Double temperature;
+        private Boolean jsonOutput;
+        private Boolean thinking;
+        private Map<String, Object> additionalParams;
+    }
+}