上传 mcp 参数解析bug修复

local_plugins/open_ai_service/android/src/main/kotlin/com/yunqiinnovation/open_ai_service/MCPClient.kt

@@ -199,88 +199,69 @@ class MCPSubClient(
      */
     private fun updateToolMaps() {
         toolMaps.clear()
-        
+
         try {
-            // 转换MCP工具为OpenAI函数格式
             tools.forEach { toolUnion ->
                 val tool = toolUnion.tool().getOrNull() ?: return@forEach
-                
+
                 try {
-                    // 获取工具的输入模式
                     val inputSchema = tool.inputSchema() ?: return@forEach
-                    
-                    // 使用toString()获取完整JSON字符串
                     val schemaStr = inputSchema.toString()
                     Log.d(TAG, "工具 ${tool.name()} 的Schema: $schemaStr")
-                    
+
-                    // 解析properties和required
                     val propertiesMap = HashMap<String, Any>()
                     val requiredList = ArrayList<String>()
-                    
+
                     try {
-                        // 匹配properties内部的内容
+                        // ✅ 替换原来的正则方式，使用括号匹配方式提取 properties 内容
-                        val propertiesPattern = "properties=\\{(.*?)\\}(?:,|\\s|$)".toRegex(RegexOption.DOT_MATCHES_ALL)
+                        val propertiesContent = extractPropertiesContent(schemaStr)
-                        val propertiesMatch = propertiesPattern.find(schemaStr)
+                        if (propertiesContent != null) {
-                        
-                        if (propertiesMatch != null) {
-                            val propertiesContent = propertiesMatch.groupValues[1]
-                            
-                            // 匹配每个属性字段，例如 query={description=搜索信息, type=string}
                             val fieldPattern = "([a-zA-Z0-9_]+)=\\{([^{}]+?)\\}".toRegex()
                             val fieldMatches = fieldPattern.findAll(propertiesContent)
-                            
+
                             fieldMatches.forEach { fieldMatch ->
                                 val fieldName = fieldMatch.groupValues[1]
                                 val fieldContent = fieldMatch.groupValues[2]
-                                
+
-                                // 解析字段属性
                                 val fieldMap = HashMap<String, Any>()
-                                
-                                // 解析如 description=搜索信息, type=string 格式的键值对
-                                // 同时处理带引号和不带引号的情况
                                 val keyValuePattern = "([a-zA-Z0-9_]+)=(\"[^\"]*\"|'[^']*'|[^,}\\s]+)".toRegex()
                                 val keyValueMatches = keyValuePattern.findAll(fieldContent)
-                                
+
                                 keyValueMatches.forEach { kvMatch ->
                                     val key = kvMatch.groupValues[1]
                                     var value = kvMatch.groupValues[2].trim()
-                                    
+
-                                    // 去除引号（如果有）
+                                    if ((value.startsWith("\"") && value.endsWith("\"")) ||
-                                    if ((value.startsWith("\"") && value.endsWith("\"")) || 
                                         (value.startsWith("'") && value.endsWith("'"))) {
                                         value = value.substring(1, value.length - 1)
                                     }
-                                    
+
-                                    // 处理不同类型的值
                                     val processedValue: Any = when {
                                         value.equals("true", ignoreCase = true) -> true
                                         value.equals("false", ignoreCase = true) -> false
                                         value.matches("\\d+".toRegex()) -> value.toIntOrNull() ?: value
                                         value.matches("\\d+\\.\\d+".toRegex()) -> value.toDoubleOrNull() ?: value
-                                        else -> value // 保持为字符串
+                                        else -> value
                                     }
-                                    
+
                                     fieldMap[key] = processedValue
                                 }
-                                
+
-                                // 添加到属性映射
                                 propertiesMap[fieldName] = fieldMap
                             }
-                            
+
                             Log.d(TAG, "成功解析属性: $propertiesMap")
                         }
-                        
+
-                        // 解析required
+                        // ✅ required 部分保持不变
                         val requiredPattern = "required=\\[(.*?)\\]".toRegex()
                         val requiredMatch = requiredPattern.find(schemaStr)
-                        
                         if (requiredMatch != null) {
                             val requiredStr = requiredMatch.groupValues[1]
                             if (requiredStr.isNotEmpty()) {
-                                // 处理可能带引号的字段名
+                                val fieldNames = requiredStr.split(",").map {
-                                val fieldNames = requiredStr.split(",").map { 
                                     val trimmed = it.trim()
-                                    if ((trimmed.startsWith("\"") && trimmed.endsWith("\"")) || 
+                                    if ((trimmed.startsWith("\"") && trimmed.endsWith("\"")) ||
                                         (trimmed.startsWith("'") && trimmed.endsWith("'"))) {
                                         trimmed.substring(1, trimmed.length - 1)
                                     } else {
@@ -295,8 +276,7 @@ class MCPSubClient(
                         Log.e(TAG, "解析Schema字符串失败: ${e.message}", e)
                         Log.e(TAG, "原始Schema: $schemaStr")
                     }
-                    
+
-                    // 创建OpenAI函数格式
                     val functionMap = mapOf(
                         "name" to tool.name(),
                         "description" to (tool.description() ?: ""),
@@ -306,13 +286,12 @@ class MCPSubClient(
                             "required" to requiredList
                         )
                     )
-                    
+
-                    // 添加到工具列表
                     toolMaps.add(mapOf(
                         "type" to "function",
                         "function" to functionMap
                     ))
-                    
+
                     Log.d(TAG, "成功转换工具 ${tool.name()} 到OpenAI函数格式 $functionMap")
                 } catch (e: Exception) {
                     Log.e(TAG, "转换工具 ${tool.name()} 失败: ${e.message}")
@@ -321,10 +300,36 @@ class MCPSubClient(
         } catch (e: Exception) {
             Log.e(TAG, "更新工具映射失败: ${e.message}")
         }
-        
+
         Log.d(TAG, "更新工具映射完成，共 ${toolMaps.size} 个工具")
     }
-    
+
+    private fun extractPropertiesContent(schemaStr: String): String? {
+        val startKey = "properties={"
+        val startIndex = schemaStr.indexOf(startKey)
+        if (startIndex == -1) return null
+
+        var braceCount = 0
+        var endIndex = -1
+        val contentStart = startIndex + startKey.length
+
+        for (i in contentStart until schemaStr.length) {
+            when (schemaStr[i]) {
+                '{' -> braceCount++
+                '}' -> {
+                    if (braceCount == 0) {
+                        endIndex = i
+                        break
+                    } else {
+                        braceCount--
+                    }
+                }
+            }
+        }
+
+        return if (endIndex != -1) schemaStr.substring(contentStart, endIndex) else null
+    }
+
     /**
      * 将JsonNode转换为Map
      */