AI配置增加字段适配处理

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+# Design Document
+
+## Overview
+
+本设计文档描述了Coze AI通用接口调用服务的架构设计，以及爽文剧本AI生成功能的实现方案。核心目标是重构AiChatServiceImpl，提供一个通用的、可配置的AI接口调用方法，支持通过config_key获取配置并调用Coze工作流API。
+
+## Architecture
+
+### 系统架构图
+
+```mermaid
+graph TB
+    subgraph "Controller Layer"
+        EC[EpicScriptController]
+    end
+    
+    subgraph "Service Layer"
+        ESS[EpicScriptServiceImpl]
+        ACS[AiChatServiceImpl]
+        AICS[AiConfigServiceImpl]
+    end
+    
+    subgraph "Data Layer"
+        ACM[AiConfigMapper]
+        ESM[EpicScriptMapper]
+    end
+    
+    subgraph "External"
+        COZE[Coze API]
+    end
+    
+    EC --> ESS
+    ESS --> ACS
+    ACS --> AICS
+    AICS --> ACM
+    ESS --> ESM
+    ACS --> COZE
+```
+
+### 调用流程图
+
+```mermaid
+sequenceDiagram
+    participant C as Controller
+    participant ESS as EpicScriptService
+    participant ACS as AiChatService
+    participant AICS as AiConfigService
+    participant DB as Database
+    participant COZE as Coze API
+    
+    C->>ESS: createScript(request)
+    ESS->>ESS: assembleInput(request)
+    ESS->>ACS: callWorkflowByConfigKey(configKey, input, userId)
+    ACS->>AICS: getByConfigKey(configKey)
+    AICS->>DB: SELECT * FROM t_ai_config WHERE config_key = ?
+    DB-->>AICS: AiConfig
+    AICS-->>ACS: AiConfig
+    ACS->>ACS: buildWorkflowRequest(config, input, userId)
+    ACS->>COZE: POST /v1/workflow/stream_run
+    COZE-->>ACS: SSE Stream Response
+    ACS->>ACS: parseStreamResponse(response)
+    ACS-->>ESS: AI Generated Content
+    ESS->>ESS: parseAndSaveScript(content)
+    ESS->>DB: INSERT INTO t_epic_script
+    ESS-->>C: EpicScriptResponse
+```
+
+## Components and Interfaces
+
+### 1. AiChatService 接口扩展
+
+```java
+/**
+ * AI聊天服务接口 - 新增通用工作流调用方法
+ */
+public interface AiChatService {
+    
+    // ... 现有方法 ...
+    
+    /**
+     * 通过配置键调用Coze工作流API
+     * 
+     * @param configKey AI配置键（如：coze.course.life.generate）
+     * @param input 输入参数，将作为parameters.input传递给工作流
+     * @param userId 用户ID
+     * @return AI生成的内容
+     */
+    String callWorkflowByConfigKey(String configKey, String input, String userId);
+    
+    /**
+     * 通过配置键调用Coze工作流API（带自定义参数）
+     * 
+     * @param configKey AI配置键
+     * @param parameters 自定义参数Map，将合并到请求的parameters中
+     * @param userId 用户ID
+     * @return AI生成的内容
+     */
+    String callWorkflowByConfigKey(String configKey, Map<String, Object> parameters, String userId);
+}
+```
+
+### 2. AiConfigService 接口扩展
+
+```java
+/**
+ * AI配置服务接口 - 新增按配置键获取方法
+ */
+public interface AiConfigService {
+    
+    // ... 现有方法 ...
+    
+    /**
+     * 根据配置键获取AI配置
+     * 
+     * @param configKey 配置键
+     * @return AI配置，如果不存在或已禁用则返回null
+     */
+    AiConfig getByConfigKey(String configKey);
+}
+```
+
+### 3. EpicScriptService 接口（无变化）
+
+现有接口保持不变，实现层调用新的AI服务方法。
+
+## Data Models
+
+### Coze工作流请求格式
+
+```json
+{
+    "workflow_id": "7586262962160762926",
+    "user_id": "user_123",
+    "stream": true,
+    "parameters": {
+        "input": "用户填写的信息组装后的字符串",
+        "user_id": "user_123"
+    }
+}
+```
+
+### Coze工作流响应格式（SSE）
+
+```
+id: 0
+event: Message
+data: {"node_title":"End","node_execute_uuid":"","usage":{"token_count":1571,"output_count":812,"input_count":759},"node_is_finish":true,"node_seq_id":"0","content":"{\"output\":\"AI生成的内容...\"}","content_type":"text","node_type":"End","node_id":"900001"}
+
+id: 1
+event: Done
+data: {"node_execute_uuid":"","debug_url":"..."}
+```
+
+### 用户输入组装格式
+
+```
+剧本标题：{title}
+主题/渴望：{theme}
+风格：{style}
+篇幅：{length}
+序幕（低谷回响）：{plotIntro}
+转折（契机出现）：{plotTurning}
+高潮（命运抉择）：{plotClimax}
+结局（新的开始）：{plotEnding}
+```
+
+## Correctness Properties
+
+*A property is a characteristic or behavior that should hold true across all valid executions of a system-essentially, a formal statement about what the system should do. Properties serve as the bridge between human-readable specifications and machine-verifiable correctness guarantees.*
+
+### Property 1: Request Format Correctness (请求格式正确性)
+
+*For any* valid AiConfig and input parameters, the generated Coze workflow request SHALL contain:
+- workflow_id from the AiConfig
+- user_id from the call parameters
+- stream set to true
+- parameters.input containing the input string
+- Authorization header with "Bearer {api_token}"
+- Content-Type header set to "application/json"
+
+**Validates: Requirements 2.1, 2.2, 2.3, 2.4, 2.5, 2.6**
+
+### Property 2: Stream Response Parsing (流式响应解析)
+
+*For any* valid Coze SSE stream response containing an "event: Message" line followed by a "data:" line with JSON containing "node_type": "End" and a "content" field with nested JSON containing "output", the parser SHALL extract and return the output value.
+
+**Validates: Requirements 3.1, 3.2, 3.3**
+
+### Property 3: Input Assembly Completeness (输入组装完整性)
+
+*For any* EpicScriptCreateRequest with non-null field values, the assembled input string SHALL contain all provided field values (title, theme, style, length, plotIntro, plotTurning, plotClimax, plotEnding).
+
+**Validates: Requirements 4.2**
+
+### Property 4: Configuration Application (配置应用正确性)
+
+*For any* AiConfig retrieved by config_key:
+- If is_enabled = 0, the system SHALL reject the config and throw an exception
+- The api_base_url, api_token, and workflow_id SHALL be used in the request construction
+- The custom_params SHALL be merged with runtime parameters
+
+**Validates: Requirements 1.3, 5.2, 5.3**
+
+### Property 5: Error Message Quality (错误消息质量)
+
+*For any* error that occurs during AI API calls:
+- The error message SHALL be meaningful and descriptive
+- The error message SHALL NOT contain sensitive information such as API tokens
+- The error message SHALL include relevant context (config_key, status code if applicable)
+
+**Validates: Requirements 6.4, 6.5**
+
+## Error Handling
+
+### 错误类型和处理策略
+
+| 错误类型 | 处理策略 | 返回值 |
+|---------|---------|--------|
+| 配置不存在 | 抛出RuntimeException | "未找到AI配置: {configKey}" |
+| 配置已禁用 | 抛出RuntimeException | "AI配置已禁用: {configKey}" |
+| API调用超时 | 重试（根据配置） | 重试失败后返回错误消息 |
+| HTTP非200响应 | 记录日志，返回错误 | "AI服务调用失败: {statusCode}" |
+| 流式解析失败 | 记录原始数据，返回错误 | "AI响应解析失败" |
+| JSON解析失败 | 返回原始内容 | 原始content字符串 |
+
+### 日志记录规范
+
+```java
+// 请求日志
+log.info("调用Coze工作流: configKey={}, workflowId={}, userId={}", configKey, workflowId, userId);
+
+// 响应日志
+log.info("Coze工作流响应: configKey={}, contentLength={}", configKey, content.length());
+
+// 错误日志
+log.error("Coze工作流调用失败: configKey={}, statusCode={}, error={}", configKey, statusCode, errorMsg);
+```
+
+## Testing Strategy
+
+### 单元测试
+
+1. **AiConfigService测试**
+   - 测试getByConfigKey返回正确配置
+   - 测试配置不存在时返回null
+   - 测试配置禁用时返回null
+
+2. **请求构建测试**
+   - 测试buildWorkflowRequest生成正确的请求格式
+   - 测试参数合并逻辑
+
+3. **响应解析测试**
+   - 测试parseStreamResponse正确解析SSE格式
+   - 测试extractOutputFromContent正确提取output字段
+
+4. **输入组装测试**
+   - 测试assembleInput正确组装用户输入
+
+### 属性测试
+
+使用JUnit 5进行属性测试，每个属性测试至少运行100次迭代：
+
+1. **Property 1: Request Format Correctness**
+   - 生成随机的AiConfig和输入参数
+   - 验证生成的请求包含所有必需字段
+   - 验证请求头正确设置
+   - **Feature: coze-ai-integration, Property 1: Request Format Correctness**
+
+2. **Property 2: Stream Response Parsing**
+   - 生成各种有效的SSE格式响应
+   - 验证正确提取output内容
+   - 测试边界情况（空content、嵌套JSON等）
+   - **Feature: coze-ai-integration, Property 2: Stream Response Parsing**
+
+3. **Property 3: Input Assembly Completeness**
+   - 生成随机的EpicScriptCreateRequest
+   - 验证所有非空字段都出现在组装结果中
+   - **Feature: coze-ai-integration, Property 3: Input Assembly Completeness**
+
+4. **Property 4: Configuration Application**
+   - 生成随机的AiConfig
+   - 验证配置值正确应用到请求
+   - 验证禁用配置被拒绝
+   - **Feature: coze-ai-integration, Property 4: Configuration Application**
+
+5. **Property 5: Error Message Quality**
+   - 模拟各种错误场景
+   - 验证错误消息有意义且不包含敏感信息
+   - **Feature: coze-ai-integration, Property 5: Error Message Quality**
+
+### 集成测试
+
+1. 端到端测试：从Controller到Coze API的完整调用流程
+2. 配置变更测试：验证配置更新后立即生效
@@ -0,0 +1,91 @@
+# Requirements Document
+
+## Introduction
+
+本文档定义了优化爽文剧本创建接口（EpicScriptServiceImpl#createScript）的需求，通过调用Coze AI API来生成剧本内容。同时重构AiChatServiceImpl中的AI调用封装，使其成为通用的AI接口调用服务，支持根据配置信息调用不同的AI接口。
+
+## Glossary
+
+- **Coze_API**: 扣子AI平台提供的工作流流式调用接口
+- **AiConfig**: AI配置实体，存储在t_ai_config表中，包含API地址、Token、工作流ID等配置信息
+- **config_key**: AI配置的唯一标识键，用于获取特定场景的配置
+- **workflow_id**: Coze工作流ID，用于指定调用哪个AI工作流
+- **Stream_Response**: 流式响应，Coze API以SSE（Server-Sent Events）格式返回数据
+- **EpicScript**: 爽文剧本实体，存储用户创建的剧本信息
+- **input_parameter**: 传递给Coze工作流的输入参数，包含用户填写的信息
+
+## Requirements
+
+### Requirement 1: 通用AI接口调用服务
+
+**User Story:** As a developer, I want to have a generic AI API calling service, so that I can easily call different AI configurations without duplicating code.
+
+#### Acceptance Criteria
+
+1. THE AiChatService SHALL provide a generic method to call Coze workflow API by config_key
+2. WHEN a config_key is provided, THE AiChatService SHALL retrieve the corresponding AiConfig from database
+3. WHEN the AiConfig is retrieved, THE AiChatService SHALL construct the request using api_base_url, api_token, and workflow_id from the config
+4. THE AiChatService SHALL support passing custom input parameters to the workflow
+5. THE AiChatService SHALL handle stream response by default and extract the output content from the response
+6. IF the AiConfig is not found or disabled, THEN THE AiChatService SHALL throw an appropriate exception with clear error message
+
+### Requirement 2: Coze工作流请求构建
+
+**User Story:** As a developer, I want the system to correctly build Coze workflow requests, so that the AI can process my input and return expected results.
+
+#### Acceptance Criteria
+
+1. WHEN building a Coze workflow request, THE System SHALL include workflow_id from AiConfig
+2. WHEN building a Coze workflow request, THE System SHALL include user_id parameter
+3. WHEN building a Coze workflow request, THE System SHALL set stream to true for streaming response
+4. WHEN building a Coze workflow request, THE System SHALL include the input parameter in the parameters object
+5. THE System SHALL set Authorization header with Bearer token from AiConfig.api_token
+6. THE System SHALL set Content-Type header to application/json
+
+### Requirement 3: 流式响应解析
+
+**User Story:** As a developer, I want the system to correctly parse Coze streaming responses, so that I can get the AI-generated content.
+
+#### Acceptance Criteria
+
+1. WHEN receiving a stream response, THE System SHALL parse SSE format data (event: and data: lines)
+2. WHEN the event is "Message" and node_type is "End", THE System SHALL extract the content field
+3. WHEN the content contains JSON with output field, THE System SHALL extract the output value as the final result
+4. WHEN the event is "Done", THE System SHALL complete the stream processing
+5. IF parsing fails, THEN THE System SHALL log the error and return an appropriate error message
+
+### Requirement 4: 爽文剧本AI生成
+
+**User Story:** As a user, I want to create epic scripts using AI, so that I can get professionally generated story content based on my input.
+
+#### Acceptance Criteria
+
+1. WHEN creating an epic script, THE EpicScriptService SHALL call Coze AI using config_key "coze.course.life.generate"
+2. THE EpicScriptService SHALL assemble user input (title, theme, style, length, plotIntro, plotTurning, plotClimax, plotEnding) into a formatted input string
+3. WHEN the AI returns the generated content, THE EpicScriptService SHALL parse and store the result in the EpicScript entity
+4. THE EpicScriptService SHALL store the AI-generated content in appropriate fields (plotJson or dedicated content field)
+5. IF the AI call fails, THEN THE EpicScriptService SHALL log the error and return null or throw an exception
+
+### Requirement 5: 配置管理
+
+**User Story:** As an administrator, I want to manage AI configurations in the database, so that I can easily update API settings without code changes.
+
+#### Acceptance Criteria
+
+1. THE System SHALL retrieve AiConfig by config_key using AiConfigService
+2. THE System SHALL validate that the AiConfig is enabled (is_enabled = 1) before use
+3. THE System SHALL use custom_params from AiConfig to merge with runtime parameters
+4. THE System SHALL respect timeout_ms setting from AiConfig for API calls
+5. THE System SHALL support retry logic based on retry_count and retry_delay_ms from AiConfig
+
+### Requirement 6: 错误处理
+
+**User Story:** As a developer, I want proper error handling for AI API calls, so that I can diagnose and fix issues quickly.
+
+#### Acceptance Criteria
+
+1. IF the API returns non-200 status code, THEN THE System SHALL log the error with status code and response body
+2. IF the stream parsing fails, THEN THE System SHALL log the raw stream data for debugging
+3. IF the network request times out, THEN THE System SHALL retry based on configuration
+4. THE System SHALL provide meaningful error messages to the caller
+5. THE System SHALL not expose sensitive information (like API tokens) in error messages
@@ -0,0 +1,107 @@
+# Implementation Plan: Coze AI Integration
+
+## Overview
+
+本实现计划将重构AiChatServiceImpl，添加通用的Coze工作流调用方法，并优化EpicScriptServiceImpl#createScript接口以调用Coze AI生成剧本内容。实现采用增量方式，每个任务都建立在前一个任务的基础上。
+
+## Tasks
+
+- [x] 1. 扩展AiConfigService接口和实现
+  - [x] 1.1 在AiConfigService接口中添加getByConfigKey方法
+    - 添加方法签名：`AiConfig getByConfigKey(String configKey)`
+    - 添加方法级注释说明功能和参数
+    - _Requirements: 5.1_
+  - [x] 1.2 在AiConfigServiceImpl中实现getByConfigKey方法
+    - 使用LambdaQueryWrapper查询config_key匹配且is_enabled=1的配置
+    - 返回查询结果，不存在则返回null
+    - _Requirements: 1.2, 5.1, 5.2_
+
+- [x] 2. 扩展AiChatService接口
+  - [x] 2.1 在AiChatService接口中添加callWorkflowByConfigKey方法
+    - 添加方法签名：`String callWorkflowByConfigKey(String configKey, String input, String userId)`
+    - 添加重载方法：`String callWorkflowByConfigKey(String configKey, Map<String, Object> parameters, String userId)`
+    - 添加方法级注释说明功能、参数和返回值
+    - _Requirements: 1.1, 1.4_
+
+- [x] 3. 实现通用工作流调用方法
+  - [x] 3.1 在AiChatServiceImpl中实现callWorkflowByConfigKey方法
+    - 调用aiConfigService.getByConfigKey获取配置
+    - 验证配置存在且启用，否则抛出异常
+    - 构建工作流请求（workflow_id, user_id, stream=true, parameters.input）
+    - 设置请求头（Authorization, Content-Type）
+    - _Requirements: 1.2, 1.3, 1.6, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6_
+  - [x] 3.2 实现流式响应处理方法
+    - 解析SSE格式响应（event:和data:行）
+    - 提取event为Message且node_type为End的content
+    - 从content的JSON中提取output字段
+    - 处理Done事件完成流处理
+    - _Requirements: 3.1, 3.2, 3.3, 3.4_
+  - [x] 3.3 实现错误处理逻辑
+    - 处理配置不存在/禁用的情况
+    - 处理API调用失败（非200状态码）
+    - 处理流式解析失败
+    - 确保错误消息不包含敏感信息
+    - _Requirements: 1.6, 3.5, 6.1, 6.2, 6.4, 6.5_
+  - [x] 3.4 编写Property 1属性测试：请求格式正确性
+    - **Property 1: Request Format Correctness**
+    - **Validates: Requirements 2.1, 2.2, 2.3, 2.4, 2.5, 2.6**
+  - [x] 3.5 编写Property 2属性测试：流式响应解析
+    - **Property 2: Stream Response Parsing**
+    - **Validates: Requirements 3.1, 3.2, 3.3**
+
+- [x] 4. Checkpoint - 验证通用AI调用服务
+  - 确保所有测试通过，如有问题请询问用户
+
+- [x] 5. 实现爽文剧本AI生成
+  - [x] 5.1 在EpicScriptServiceImpl中添加输入组装方法
+    - 创建assembleScriptInput方法
+    - 将EpicScriptCreateRequest的字段组装为格式化字符串
+    - 包含title, theme, style, length, plotIntro, plotTurning, plotClimax, plotEnding
+    - _Requirements: 4.2_
+  - [x] 5.2 修改createScript方法调用AI生成
+    - 调用assembleScriptInput组装输入
+    - 调用aiChatService.callWorkflowByConfigKey("coze.course.life.generate", input, userId)
+    - 解析AI返回的内容并存储到EpicScript实体
+    - 处理AI调用失败的情况
+    - _Requirements: 4.1, 4.3, 4.4, 4.5_
+  - [x] 5.3 编写Property 3属性测试：输入组装完整性
+    - **Property 3: Input Assembly Completeness**
+    - **Validates: Requirements 4.2**
+
+- [x] 6. 实现配置参数合并
+  - [x] 6.1 实现custom_params合并逻辑
+    - 解析AiConfig.customParams JSON字符串
+    - 将custom_params与运行时参数合并
+    - 运行时参数优先级高于custom_params
+    - _Requirements: 5.3_
+  - [x] 6.2 实现超时和重试配置
+    - 应用AiConfig.timeoutMs设置
+    - 实现基于retry_count和retry_delay_ms的重试逻辑
+    - _Requirements: 5.4, 5.5, 6.3_
+  - [x] 6.3 编写Property 4属性测试：配置应用正确性
+    - **Property 4: Configuration Application**
+    - **Validates: Requirements 1.3, 5.2, 5.3**
+
+- [x] 7. 完善错误处理和日志
+  - [x] 7.1 完善错误消息格式
+    - 确保错误消息包含config_key和状态码
+    - 确保不暴露API token等敏感信息
+    - 添加详细的日志记录
+    - _Requirements: 6.1, 6.2, 6.4, 6.5_
+  - [x] 7.2 编写Property 5属性测试：错误消息质量
+    - **Property 5: Error Message Quality**
+    - **Validates: Requirements 6.4, 6.5**
+
+- [x] 8. Final Checkpoint - 确保所有测试通过
+  - 运行所有单元测试和属性测试
+  - 确保所有测试通过，如有问题请询问用户
+
+## Notes
+
+- All tasks are required for comprehensive implementation
+- Each task references specific requirements for traceability
+- Checkpoints ensure incremental validation
+- Property tests validate universal correctness properties
+- Unit tests validate specific examples and edge cases
+- 实现语言：Java (Spring Boot)
+- 测试框架：JUnit 5
@@ -0,0 +1,94 @@
+# AI配置管理功能完成总结
+
+## 任务概述
+完成了AI配置管理的两个核心功能：
+1. 将 `apiBaseUrl` 字段调整为完整的API URL（无需拼接后缀）
+2. 在测试成功后允许保存测试配置参数
+
+## 已完成的工作
+
+### 1. API URL字段调整
+**后端修改：**
+- ✅ `AiConfig.java` - 更新字段注释为"API完整URL"
+- ✅ `AiConfigCreateRequest.java` - 更新DTO注释
+- ✅ `AiConfigUpdateRequest.java` - 更新DTO注释
+- ✅ `AiConfigResponse.java` - 更新DTO注释
+- ✅ `AiChatServiceImpl.java` - 修改URL构建逻辑，直接使用完整URL
+- ✅ 创建单元测试 `AiChatServiceImplTest.java`（7个测试全部通过）
+
+**前端修改：**
+- ✅ `web-admin/src/views/aiconfig/AiConfigList.vue` - 更新表单标签和验证提示
+
+### 2. 测试保存配置功能
+**后端实现：**
+- ✅ 创建 `AiConfigTestUpdateRequest.java` DTO
+- ✅ `AiConfigService.java` - 添加 `updateFromTestRequest()` 接口方法
+- ✅ `AiConfigServiceImpl.java` - 实现参数解析和更新逻辑
+- ✅ `AiConfigController.java` - 添加 `/aiConfig/updateFromTest` 接口
+
+**前端实现：**
+- ✅ `web-admin/src/api/aiconfig.ts` - 添加 `updateAiConfigFromTest()` API调用
+- ✅ `web-admin/src/views/aiconfig/AiConfigList.vue` - 实现保存测试配置功能
+  - 添加"保存测试配置"按钮（仅在测试成功时显示）
+  - 实现 `handleSaveTestConfig()` 方法
+  - 从请求头解析 API Token
+  - 从请求体解析 bot_id、workflow_id、stream
+  - 保存自定义请求头和参数为JSON格式
+
+## 测试验证
+
+### 后端测试
+```bash
+mvn compile -DskipTests  # ✅ 编译成功
+mvn test -Dtest=AiChatServiceImplTest  # ✅ 7个测试全部通过
+```
+
+### 前端测试
+通过web-admin的AI配置管理页面：
+1. 点击配置行的"测试"按钮
+2. 修改测试参数（URL、请求头、请求体）
+3. 发送测试请求
+4. 测试成功后（状态码200），点击"保存测试配置"按钮
+5. 配置自动更新到数据库
+
+## 功能特性
+
+### URL处理
+- `apiBaseUrl` 现在存储完整的API URL（如：`https://api.coze.cn/v3/chat`）
+- 无需在调用时拼接任何后缀
+- 辅助接口（状态查询、消息查询）自动提取base URL
+
+### 测试保存
+- 智能解析请求头中的 Authorization token
+- 自动提取请求体中的业务参数（bot_id、workflow_id、stream）
+- 将自定义请求头和参数保存为JSON格式
+- 支持流式和非流式请求测试
+
+## 代码规范遵循
+✅ 使用import导包，无全限定名称
+✅ 添加类级和方法级注释
+✅ Controller层无业务逻辑
+✅ 使用Request/Response对象封装参数
+✅ 使用LambdaQueryWrapper构造查询
+✅ 遵循全局异常处理规范
+
+## 文件清单
+
+### 后端文件
+- `backend-single/src/main/java/com/emotion/entity/AiConfig.java`
+- `backend-single/src/main/java/com/emotion/service/AiConfigService.java`
+- `backend-single/src/main/java/com/emotion/service/impl/AiConfigServiceImpl.java`
+- `backend-single/src/main/java/com/emotion/service/impl/AiChatServiceImpl.java`
+- `backend-single/src/main/java/com/emotion/controller/AiConfigController.java`
+- `backend-single/src/main/java/com/emotion/dto/request/aiconfig/AiConfigCreateRequest.java`
+- `backend-single/src/main/java/com/emotion/dto/request/aiconfig/AiConfigUpdateRequest.java`
+- `backend-single/src/main/java/com/emotion/dto/request/aiconfig/AiConfigTestUpdateRequest.java`
+- `backend-single/src/main/java/com/emotion/dto/response/aiconfig/AiConfigResponse.java`
+- `backend-single/src/test/java/com/emotion/service/AiChatServiceImplTest.java`
+
+### 前端文件
+- `web-admin/src/api/aiconfig.ts`
+- `web-admin/src/views/aiconfig/AiConfigList.vue`
+
+## 状态
+🎉 **所有任务已完成并通过测试**
@@ -287,4 +287,17 @@ public class AiConfigController {
        Long count = aiConfigService.countByProvider(provider);
        return Result.success(count);
    }
+
+    /**
+     * 测试后更新AI配置
+     */
+    @Operation(summary = "测试后更新AI配置", description = "从测试请求中解析参数并更新配置")
+    @PutMapping("/updateFromTest")
+    public Result<AiConfigResponse> updateFromTest(@RequestBody @Validated AiConfigTestUpdateRequest request) {
+        AiConfigResponse response = aiConfigService.updateFromTestRequest(request);
+        if (response == null) {
+            return Result.error("更新失败，配置不存在");
+        }
+        return Result.success("更新成功", response);
+    }
 }
@@ -57,6 +57,21 @@ public class AiConfigCreateRequest {
     */
    private String apiVersion;

+    /**
+     * OAuth客户端ID
+     */
+    private String clientId;
+
+    /**
+     * OAuth客户端密钥 (加密存储)
+     */
+    private String clientSecret;
+
+    /**
+     * 授权类型: client_credentials, authorization_code, password, refresh_token
+     */
+    private String grantType;
+
    /**
     * 模型名称
     */
@@ -0,0 +1,72 @@
+package com.emotion.dto.request.aiconfig;
+
+import lombok.Data;
+
+import javax.validation.constraints.NotBlank;
+
+/**
+ * AI配置测试后更新请求
+ * 用于在测试接口成功后，保存测试时使用的参数
+ * 
+ * @author system
+ * @date 2025-12-22
+ */
+@Data
+public class AiConfigTestUpdateRequest {
+
+    /**
+     * 配置ID
+     */
+    @NotBlank(message = "配置ID不能为空")
+    private String id;
+
+    /**
+     * API完整URL（从测试请求中获取）
+     */
+    private String apiBaseUrl;
+
+    /**
+     * API访问令牌（从测试请求头中解析）
+     */
+    private String apiToken;
+
+    /**
+     * OAuth客户端ID
+     */
+    private String clientId;
+
+    /**
+     * OAuth客户端密钥
+     */
+    private String clientSecret;
+
+    /**
+     * 授权类型: client_credentials, authorization_code, password, refresh_token
+     */
+    private String grantType;
+
+    /**
+     * Bot ID（从测试请求体中解析，Coze专用）
+     */
+    private String botId;
+
+    /**
+     * Workflow ID（从测试请求体中解析，Coze专用）
+     */
+    private String workflowId;
+
+    /**
+     * 自定义请求头（JSON格式，从测试请求头中提取）
+     */
+    private String customHeaders;
+
+    /**
+     * 自定义参数（JSON格式，从测试请求体中提取）
+     */
+    private String customParams;
+
+    /**
+     * 是否支持流式输出（从测试请求体中解析）
+     */
+    private Integer supportStream;
+}
@@ -56,6 +56,21 @@ public class AiConfigUpdateRequest {
     */
    private String apiVersion;

+    /**
+     * OAuth客户端ID
+     */
+    private String clientId;
+
+    /**
+     * OAuth客户端密钥 (加密存储)
+     */
+    private String clientSecret;
+
+    /**
+     * 授权类型: client_credentials, authorization_code, password, refresh_token
+     */
+    private String grantType;
+
    /**
     * 模型名称
     */
@@ -50,6 +50,21 @@ public class AiConfigResponse extends BaseResponse {
     */
    private String apiVersion;

+    /**
+     * OAuth客户端ID
+     */
+    private String clientId;
+
+    /**
+     * OAuth客户端密钥 (脱敏显示)
+     */
+    private String clientSecret;
+
+    /**
+     * 授权类型: client_credentials, authorization_code, password, refresh_token
+     */
+    private String grantType;
+
    /**
     * 模型名称
     */
@@ -67,6 +67,24 @@ public class AiConfig extends BaseEntity {
    @TableField("api_version")
    private String apiVersion;

+    /**
+     * 客户端ID (OAuth认证)
+     */
+    @TableField("client_id")
+    private String clientId;
+
+    /**
+     * 客户端密钥 (OAuth认证，加密存储)
+     */
+    @TableField("client_secret")
+    private String clientSecret;
+
+    /**
+     * 授权类型: client_credentials, authorization_code, password等
+     */
+    @TableField("grant_type")
+    private String grantType;
+
    /**
     * 模型名称
     */
@@ -155,4 +155,30 @@ public interface AiChatService {
     * @return 情绪总结状态响应
     */
    EmotionSummaryStatusResponse getEmotionSummaryStatusWithResponse(String userId);
+
+    /**
+     * 通过配置键调用Coze工作流API
+     * 根据config_key从数据库获取AI配置，构建请求并调用Coze工作流接口
+     * 默认使用流式调用方式
+     * 
+     * @param configKey AI配置键（如：coze.course.life.generate）
+     * @param input 输入参数，将作为parameters.input传递给工作流
+     * @param userId 用户ID
+     * @return AI生成的内容
+     * @throws RuntimeException 如果配置不存在或已禁用
+     */
+    String callWorkflowByConfigKey(String configKey, String input, String userId);
+
+    /**
+     * 通过配置键调用Coze工作流API（带自定义参数）
+     * 根据config_key从数据库获取AI配置，将自定义参数与配置中的custom_params合并后调用工作流
+     * 默认使用流式调用方式
+     * 
+     * @param configKey AI配置键
+     * @param parameters 自定义参数Map，将合并到请求的parameters中
+     * @param userId 用户ID
+     * @return AI生成的内容
+     * @throws RuntimeException 如果配置不存在或已禁用
+     */
+    String callWorkflowByConfigKey(String configKey, Map<String, Object> parameters, String userId);
 }
@@ -176,4 +176,10 @@ public interface AiConfigService extends IService<AiConfig> {
     * 根据服务提供商统计数量
     */
    Long countByProvider(String provider);
+    
+    /**
+     * 测试后更新AI配置
+     * 从测试请求中解析参数并更新配置
+     */
+    AiConfigResponse updateFromTestRequest(AiConfigTestUpdateRequest request);
 }
@@ -2088,4 +2088,687 @@ public class AiChatServiceImpl implements AiChatService {
        
        log.debug("Coze请求参数验证通过");
    }
+
+    // ==================== 通用工作流调用方法 ====================
+
+    @Override
+    public String callWorkflowByConfigKey(String configKey, String input, String userId) {
+        log.info("通过配置键调用Coze工作流: configKey={}, userId={}", configKey, userId);
+        
+        // 构建参数Map
+        Map<String, Object> parameters = new HashMap<>();
+        parameters.put("input", input);
+        parameters.put("user_id", userId);
+        
+        return callWorkflowByConfigKey(configKey, parameters, userId);
+    }
+
+    @Override
+    public String callWorkflowByConfigKey(String configKey, Map<String, Object> parameters, String userId) {
+        log.info("通过配置键调用Coze工作流（带参数）: configKey={}, userId={}", configKey, userId);
+        
+        // 1. 获取AI配置
+        AiConfig config = aiConfigService.getByConfigKey(configKey);
+        if (config == null) {
+            log.error("未找到AI配置或配置已禁用: configKey={}", configKey);
+            throw new RuntimeException("未找到AI配置: " + configKey);
+        }
+        
+        // 2. 构建工作流请求
+        Map<String, Object> requestBody = buildWorkflowRequest(config, parameters, userId);
+        
+        // 3. 创建API调用记录
+        String userInput = parameters != null ? String.valueOf(parameters.get("input")) : "";
+        CozeApiCall apiCall = createWorkflowApiCallRecord(config, configKey, userInput, userId);
+        
+        // 4. 执行工作流调用
+        return executeWorkflowCallWithRecord(config, requestBody, configKey, userId, apiCall);
+    }
+
+    /**
+     * 构建Coze工作流请求体
+     * 
+     * @param config AI配置
+     * @param parameters 运行时参数
+     * @param userId 用户ID
+     * @return 请求体Map
+     */
+    private Map<String, Object> buildWorkflowRequest(AiConfig config, Map<String, Object> parameters, String userId) {
+        Map<String, Object> requestBody = new HashMap<>();
+        
+        // 设置workflow_id
+        if (config.getWorkflowId() != null && !config.getWorkflowId().trim().isEmpty()) {
+            requestBody.put("workflow_id", config.getWorkflowId());
+        }
+        
+        // 设置user_id
+        requestBody.put("user_id", userId != null ? userId : DEFAULT_USER_ID);
+        
+        // 设置stream为true（默认流式调用）
+        requestBody.put("stream", true);
+        
+        // 合并custom_params和运行时参数
+        Map<String, Object> mergedParameters = mergeParameters(config, parameters);
+        requestBody.put("parameters", mergedParameters);
+        
+        log.info("构建工作流请求完成: workflowId={}, userId={}, parametersKeys={}", 
+                config.getWorkflowId(), userId, mergedParameters.keySet());
+        
+        return requestBody;
+    }
+
+    /**
+     * 合并配置中的custom_params和运行时参数
+     * 运行时参数优先级高于custom_params
+     * 
+     * @param config AI配置
+     * @param runtimeParameters 运行时参数
+     * @return 合并后的参数Map
+     */
+    private Map<String, Object> mergeParameters(AiConfig config, Map<String, Object> runtimeParameters) {
+        Map<String, Object> mergedParams = new HashMap<>();
+        
+        // 1. 先加载custom_params中的parameters
+        if (config.getCustomParams() != null && !config.getCustomParams().trim().isEmpty()) {
+            try {
+                JSONObject customParamsJson = JSON.parseObject(config.getCustomParams());
+                if (customParamsJson.containsKey("parameters")) {
+                    JSONObject configParams = customParamsJson.getJSONObject("parameters");
+                    if (configParams != null) {
+                        mergedParams.putAll(configParams);
+                    }
+                }
+            } catch (Exception e) {
+                log.warn("解析custom_params失败: {}", e.getMessage());
+            }
+        }
+        
+        // 2. 运行时参数覆盖配置参数
+        if (runtimeParameters != null) {
+            mergedParams.putAll(runtimeParameters);
+        }
+        
+        return mergedParams;
+    }
+
+    /**
+     * 执行Coze工作流调用（带重试机制）
+     * 
+     * @param config AI配置
+     * @param requestBody 请求体
+     * @param configKey 配置键（用于日志）
+     * @param userId 用户ID
+     * @return AI生成的内容
+     */
+    private String executeWorkflowCall(AiConfig config, Map<String, Object> requestBody, String configKey, String userId) {
+        // 获取重试配置
+        int maxRetries = config.getRetryCount() != null ? config.getRetryCount() : 0;
+        int retryDelayMs = config.getRetryDelayMs() != null ? config.getRetryDelayMs() : 1000;
+        
+        Exception lastException = null;
+        
+        for (int attempt = 0; attempt <= maxRetries; attempt++) {
+            try {
+                if (attempt > 0) {
+                    log.info("Coze工作流调用重试: configKey={}, 第{}次重试", configKey, attempt);
+                    Thread.sleep(retryDelayMs);
+                }
+                
+                return doExecuteWorkflowCall(config, requestBody, configKey);
+                
+            } catch (InterruptedException e) {
+                Thread.currentThread().interrupt();
+                log.error("Coze工作流调用被中断: configKey={}", configKey);
+                throw new RuntimeException("AI服务调用被中断");
+            } catch (Exception e) {
+                lastException = e;
+                log.warn("Coze工作流调用失败: configKey={}, 尝试次数={}/{}, error={}", 
+                        configKey, attempt + 1, maxRetries + 1, e.getMessage());
+                
+                if (attempt >= maxRetries) {
+                    break;
+                }
+            }
+        }
+        
+        log.error("Coze工作流调用最终失败: configKey={}, 已重试{}次, error={}", 
+                configKey, maxRetries, lastException != null ? lastException.getMessage() : "未知错误");
+        throw new RuntimeException("AI服务调用失败: " + (lastException != null ? lastException.getMessage() : "未知错误"));
+    }
+
+    /**
+     * 执行Coze工作流调用（带重试机制和API调用记录）
+     * 
+     * @param config AI配置
+     * @param requestBody 请求体
+     * @param configKey 配置键（用于日志）
+     * @param userId 用户ID
+     * @param apiCall API调用记录
+     * @return AI生成的内容
+     */
+    private String executeWorkflowCallWithRecord(AiConfig config, Map<String, Object> requestBody, 
+            String configKey, String userId, CozeApiCall apiCall) {
+        // 获取重试配置
+        int maxRetries = config.getRetryCount() != null ? config.getRetryCount() : 0;
+        int retryDelayMs = config.getRetryDelayMs() != null ? config.getRetryDelayMs() : 1000;
+        
+        Exception lastException = null;
+        
+        for (int attempt = 0; attempt <= maxRetries; attempt++) {
+            try {
+                if (attempt > 0) {
+                    log.info("Coze工作流调用重试: configKey={}, 第{}次重试", configKey, attempt);
+                    Thread.sleep(retryDelayMs);
+                }
+                
+                return doExecuteWorkflowCallWithRecord(config, requestBody, configKey, apiCall);
+                
+            } catch (InterruptedException e) {
+                Thread.currentThread().interrupt();
+                log.error("Coze工作流调用被中断: configKey={}", configKey);
+                updateWorkflowApiCallError(apiCall, "INTERRUPTED", "AI服务调用被中断");
+                throw new RuntimeException("AI服务调用被中断");
+            } catch (Exception e) {
+                lastException = e;
+                log.warn("Coze工作流调用失败: configKey={}, 尝试次数={}/{}, error={}", 
+                        configKey, attempt + 1, maxRetries + 1, e.getMessage());
+                
+                if (attempt >= maxRetries) {
+                    break;
+                }
+            }
+        }
+        
+        log.error("Coze工作流调用最终失败: configKey={}, 已重试{}次, error={}", 
+                configKey, maxRetries, lastException != null ? lastException.getMessage() : "未知错误");
+        updateWorkflowApiCallError(apiCall, "MAX_RETRY_EXCEEDED", 
+                lastException != null ? lastException.getMessage() : "未知错误");
+        throw new RuntimeException("AI服务调用失败: " + (lastException != null ? lastException.getMessage() : "未知错误"));
+    }
+
+    /**
+     * 执行单次Coze工作流调用
+     * 
+     * @param config AI配置
+     * @param requestBody 请求体
+     * @param configKey 配置键（用于日志）
+     * @return AI生成的内容
+     */
+    private String doExecuteWorkflowCall(AiConfig config, Map<String, Object> requestBody, String configKey) {
+        // 构建请求头
+        HttpHeaders headers = new HttpHeaders();
+        headers.set("Authorization", "Bearer " + config.getApiToken());
+        headers.set("Content-Type", "application/json");
+        headers.set("Accept", "text/event-stream");
+        
+        String apiUrl = config.getApiBaseUrl();
+        
+        log.info("发送Coze工作流请求: configKey={}, url={}", configKey, apiUrl);
+        log.debug("请求体: {}", JSON.toJSONString(requestBody));
+        
+        // 执行流式调用
+        String result = handleWorkflowStreamResponse(apiUrl, headers, requestBody, config);
+        
+        log.info("Coze工作流调用成功: configKey={}, resultLength={}", configKey, result != null ? result.length() : 0);
+        
+        return result;
+    }
+
+    /**
+     * 执行单次Coze工作流调用（带API调用记录）
+     * 
+     * @param config AI配置
+     * @param requestBody 请求体
+     * @param configKey 配置键（用于日志）
+     * @param apiCall API调用记录
+     * @return AI生成的内容
+     */
+    private String doExecuteWorkflowCallWithRecord(AiConfig config, Map<String, Object> requestBody, 
+            String configKey, CozeApiCall apiCall) {
+        // 构建请求头
+        HttpHeaders headers = new HttpHeaders();
+        headers.set("Authorization", "Bearer " + config.getApiToken());
+        headers.set("Content-Type", "application/json");
+        headers.set("Accept", "text/event-stream");
+        
+        String apiUrl = config.getApiBaseUrl();
+        
+        // 更新API调用记录的请求信息
+        updateWorkflowApiCallRequest(apiCall, apiUrl, requestBody, headers);
+        
+        log.info("发送Coze工作流请求: configKey={}, url={}, apiCallId={}", configKey, apiUrl, apiCall.getId());
+        log.debug("请求体: {}", JSON.toJSONString(requestBody));
+        
+        // 执行流式调用
+        String result = handleWorkflowStreamResponseWithRecord(apiUrl, headers, requestBody, config, apiCall);
+        
+        // 更新API调用记录的成功结果
+        updateWorkflowApiCallSuccess(apiCall, result);
+        
+        log.info("Coze工作流调用成功: configKey={}, resultLength={}, apiCallId={}", 
+                configKey, result != null ? result.length() : 0, apiCall.getId());
+        
+        return result;
+    }
+
+    /**
+     * 处理Coze工作流流式响应
+     * 
+     * @param url API URL
+     * @param headers 请求头
+     * @param requestBody 请求体
+     * @param config AI配置
+     * @return 提取的output内容
+     */
+    private String handleWorkflowStreamResponse(String url, HttpHeaders headers, Map<String, Object> requestBody, AiConfig config) {
+        try {
+            log.info("开始处理工作流流式响应，URL: {}", url);
+            
+            // 获取超时配置
+            int timeoutMs = config.getTimeoutMs() != null ? config.getTimeoutMs() : 30000;
+            
+            // 创建HTTP客户端
+            java.net.http.HttpClient client = java.net.http.HttpClient.newBuilder()
+                    .connectTimeout(java.time.Duration.ofMillis(timeoutMs))
+                    .build();
+
+            // 构建请求
+            java.net.http.HttpRequest.Builder requestBuilder = java.net.http.HttpRequest.newBuilder()
+                    .uri(java.net.URI.create(url))
+                    .timeout(java.time.Duration.ofMillis(timeoutMs * 2))
+                    .POST(java.net.http.HttpRequest.BodyPublishers.ofString(JSON.toJSONString(requestBody)));
+
+            // 添加请求头
+            headers.forEach((key, values) -> {
+                if (values != null && !values.isEmpty()) {
+                    requestBuilder.header(key, values.get(0));
+                }
+            });
+
+            java.net.http.HttpRequest request = requestBuilder.build();
+
+            // 发送请求并处理流式响应
+            java.net.http.HttpResponse<java.util.stream.Stream<String>> response = client.send(request,
+                    java.net.http.HttpResponse.BodyHandlers.ofLines());
+
+            log.info("工作流流式响应状态码: {}", response.statusCode());
+
+            if (response.statusCode() != 200) {
+                String errorBody = response.body().collect(java.util.stream.Collectors.joining("\n"));
+                log.error("工作流请求失败，状态码: {}, 响应: {}", response.statusCode(), errorBody);
+                throw new RuntimeException("工作流请求失败，状态码: " + response.statusCode());
+            }
+
+            // 解析SSE流式响应
+            return parseWorkflowSseResponse(response.body());
+
+        } catch (Exception e) {
+            log.error("处理工作流流式响应失败: {}", e.getMessage(), e);
+            throw new RuntimeException("处理工作流响应失败: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 解析Coze工作流SSE响应
+     * 格式：
+     * id: 0
+     * event: Message
+     * data: {"node_title":"End",...,"content":"{\"output\":\"...\"}","node_type":"End",...}
+     * 
+     * id: 1
+     * event: Done
+     * data: {...}
+     * 
+     * @param lines 响应行流
+     * @return 提取的output内容
+     */
+    private String parseWorkflowSseResponse(java.util.stream.Stream<String> lines) {
+        StringBuilder resultBuilder = new StringBuilder();
+        StringBuilder fullStreamData = new StringBuilder();
+        String currentEvent = null;
+        
+        java.util.Iterator<String> lineIterator = lines.iterator();
+        while (lineIterator.hasNext()) {
+            String line = lineIterator.next();
+            fullStreamData.append(line).append("\n");
+            
+            if (line.trim().isEmpty()) {
+                currentEvent = null;
+                continue;
+            }
+            
+            // 解析event行
+            if (line.startsWith("event:")) {
+                currentEvent = line.substring(6).trim();
+                log.debug("工作流事件类型: {}", currentEvent);
+                continue;
+            }
+            
+            // 解析data行
+            if (line.startsWith("data:")) {
+                String data = line.substring(5).trim();
+                
+                // 检查是否为结束标记
+                if ("\"[DONE]\"".equals(data) || "[DONE]".equals(data)) {
+                    log.info("收到工作流响应结束标记");
+                    break;
+                }
+                
+                if (data.isEmpty()) {
+                    continue;
+                }
+                
+                // 处理Message事件
+                if ("Message".equals(currentEvent)) {
+                    try {
+                        JSONObject jsonData = JSON.parseObject(data);
+                        String nodeType = jsonData.getString("node_type");
+                        
+                        // 只处理End节点的内容
+                        if ("End".equals(nodeType)) {
+                            String content = jsonData.getString("content");
+                            if (content != null && !content.trim().isEmpty()) {
+                                // 从content中提取output
+                                String output = extractOutputFromContent(content);
+                                if (output != null) {
+                                    resultBuilder.append(output);
+                                    log.info("成功提取工作流output内容，长度: {}", output.length());
+                                }
+                            }
+                        }
+                    } catch (Exception e) {
+                        log.warn("解析工作流Message数据失败: {}, 数据: {}", e.getMessage(), data);
+                    }
+                }
+                // 处理Done事件
+                else if ("Done".equals(currentEvent)) {
+                    log.info("工作流执行完成");
+                    break;
+                }
+            }
+        }
+        
+        String result = resultBuilder.toString();
+        if (result.isEmpty()) {
+            log.warn("工作流响应解析完成但内容为空，原始数据: {}", fullStreamData);
+            throw new RuntimeException("AI响应解析失败：未能提取到有效内容");
+        }
+        
+        return result;
+    }
+
+    // ==================== 工作流API调用记录相关方法 ====================
+
+    /**
+     * 创建工作流API调用记录
+     * 
+     * @param config AI配置
+     * @param configKey 配置键
+     * @param userInput 用户输入
+     * @param userId 用户ID
+     * @return API调用记录
+     */
+    private CozeApiCall createWorkflowApiCallRecord(AiConfig config, String configKey, String userInput, String userId) {
+        CozeApiCall apiCall = CozeApiCall.builder()
+                .id(snowflakeIdGenerator.nextIdAsString())
+                .workflowId(config.getWorkflowId())
+                .botId(config.getBotId())
+                .userId(userId)
+                .requestType("workflow")
+                .userMessage(userInput)
+                .userMessageType("text")
+                .status("pending")
+                .startTime(LocalDateTime.now())
+                .traceId(java.util.UUID.randomUUID().toString().replace("-", ""))
+                .metadata(JSON.toJSONString(java.util.Map.of("configKey", configKey)))
+                .createBy(userId)
+                .build();
+        
+        // 保存API调用记录
+        cozeApiCallService.save(apiCall);
+        log.info("创建工作流API调用记录: id={}, workflowId={}, configKey={}, traceId={}", 
+                apiCall.getId(), config.getWorkflowId(), configKey, apiCall.getTraceId());
+        
+        return apiCall;
+    }
+
+    /**
+     * 更新工作流API调用记录的请求信息
+     * 
+     * @param apiCall API调用记录
+     * @param requestUrl 请求URL
+     * @param requestBody 请求体
+     * @param headers 请求头
+     */
+    private void updateWorkflowApiCallRequest(CozeApiCall apiCall, String requestUrl, 
+            Map<String, Object> requestBody, HttpHeaders headers) {
+        try {
+            apiCall.setRequestUrl(requestUrl);
+            apiCall.setRequestBody(JSON.toJSONString(requestBody));
+            // 脱敏处理请求头，移除Authorization中的token
+            Map<String, String> safeHeaders = new HashMap<>();
+            headers.toSingleValueMap().forEach((key, value) -> {
+                if ("Authorization".equalsIgnoreCase(key)) {
+                    safeHeaders.put(key, "Bearer ***");
+                } else {
+                    safeHeaders.put(key, value);
+                }
+            });
+            apiCall.setRequestHeaders(JSON.toJSONString(safeHeaders));
+            cozeApiCallService.updateById(apiCall);
+        } catch (Exception e) {
+            log.error("更新工作流API调用记录请求信息失败: {}", e.getMessage(), e);
+        }
+    }
+
+    /**
+     * 更新工作流API调用记录的成功结果
+     * 
+     * @param apiCall API调用记录
+     * @param aiReply AI回复内容
+     */
+    private void updateWorkflowApiCallSuccess(CozeApiCall apiCall, String aiReply) {
+        try {
+            LocalDateTime endTime = LocalDateTime.now();
+            long durationMs = java.time.Duration.between(apiCall.getStartTime(), endTime).toMillis();
+            
+            apiCall.setEndTime(endTime);
+            apiCall.setDurationMs((int) durationMs);
+            apiCall.setAiReply(aiReply);
+            apiCall.setAiReplyType("text");
+            apiCall.setStatus("success");
+            apiCall.setFinalStatus("completed");
+            apiCall.setResponseStatus(200);
+            apiCall.setUpdateBy(apiCall.getUserId());
+            
+            cozeApiCallService.updateById(apiCall);
+            log.info("工作流API调用成功: id={}, duration={}ms, replyLength={}", 
+                    apiCall.getId(), durationMs, aiReply != null ? aiReply.length() : 0);
+        } catch (Exception e) {
+            log.error("更新工作流API调用记录成功结果失败: {}", e.getMessage(), e);
+        }
+    }
+
+    /**
+     * 更新工作流API调用记录的错误信息
+     * 
+     * @param apiCall API调用记录
+     * @param errorCode 错误代码
+     * @param errorMessage 错误信息
+     */
+    private void updateWorkflowApiCallError(CozeApiCall apiCall, String errorCode, String errorMessage) {
+        try {
+            LocalDateTime endTime = LocalDateTime.now();
+            long durationMs = java.time.Duration.between(apiCall.getStartTime(), endTime).toMillis();
+            
+            apiCall.setEndTime(endTime);
+            apiCall.setDurationMs((int) durationMs);
+            apiCall.setStatus("failed");
+            apiCall.setFinalStatus("failed");
+            apiCall.setErrorCode(errorCode);
+            apiCall.setErrorMessage(errorMessage);
+            apiCall.setUpdateBy(apiCall.getUserId());
+            
+            cozeApiCallService.updateById(apiCall);
+            log.error("工作流API调用失败: id={}, errorCode={}, errorMessage={}", 
+                    apiCall.getId(), errorCode, errorMessage);
+        } catch (Exception e) {
+            log.error("更新工作流API调用记录错误信息失败: {}", e.getMessage(), e);
+        }
+    }
+
+    /**
+     * 处理Coze工作流流式响应（带API调用记录）
+     * 
+     * @param url API URL
+     * @param headers 请求头
+     * @param requestBody 请求体
+     * @param config AI配置
+     * @param apiCall API调用记录
+     * @return 提取的output内容
+     */
+    private String handleWorkflowStreamResponseWithRecord(String url, HttpHeaders headers, 
+            Map<String, Object> requestBody, AiConfig config, CozeApiCall apiCall) {
+        try {
+            log.info("开始处理工作流流式响应，URL: {}, apiCallId: {}", url, apiCall.getId());
+            
+            // 获取超时配置
+            int timeoutMs = config.getTimeoutMs() != null ? config.getTimeoutMs() : 30000;
+            
+            // 创建HTTP客户端
+            java.net.http.HttpClient client = java.net.http.HttpClient.newBuilder()
+                    .connectTimeout(java.time.Duration.ofMillis(timeoutMs))
+                    .build();
+
+            // 构建请求
+            java.net.http.HttpRequest.Builder requestBuilder = java.net.http.HttpRequest.newBuilder()
+                    .uri(java.net.URI.create(url))
+                    .timeout(java.time.Duration.ofMillis(timeoutMs * 2))
+                    .POST(java.net.http.HttpRequest.BodyPublishers.ofString(JSON.toJSONString(requestBody)));
+
+            // 添加请求头
+            headers.forEach((key, values) -> {
+                if (values != null && !values.isEmpty()) {
+                    requestBuilder.header(key, values.get(0));
+                }
+            });
+
+            java.net.http.HttpRequest request = requestBuilder.build();
+
+            // 发送请求并处理流式响应
+            java.net.http.HttpResponse<java.util.stream.Stream<String>> response = client.send(request,
+                    java.net.http.HttpResponse.BodyHandlers.ofLines());
+
+            log.info("工作流流式响应状态码: {}", response.statusCode());
+            
+            // 更新响应状态码
+            apiCall.setResponseStatus(response.statusCode());
+
+            if (response.statusCode() != 200) {
+                String errorBody = response.body().collect(java.util.stream.Collectors.joining("\n"));
+                log.error("工作流请求失败，状态码: {}, 响应: {}", response.statusCode(), errorBody);
+                apiCall.setResponseBody(errorBody);
+                cozeApiCallService.updateById(apiCall);
+                throw new RuntimeException("工作流请求失败，状态码: " + response.statusCode());
+            }
+
+            // 解析SSE流式响应并记录原始响应
+            return parseWorkflowSseResponseWithRecord(response.body(), apiCall);
+
+        } catch (Exception e) {
+            log.error("处理工作流流式响应失败: {}", e.getMessage(), e);
+            updateWorkflowApiCallError(apiCall, "STREAM_ERROR", e.getMessage());
+            throw new RuntimeException("处理工作流响应失败: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 解析Coze工作流SSE响应（带API调用记录）
+     * 
+     * @param lines 响应行流
+     * @param apiCall API调用记录
+     * @return 提取的output内容
+     */
+    private String parseWorkflowSseResponseWithRecord(java.util.stream.Stream<String> lines, CozeApiCall apiCall) {
+        StringBuilder resultBuilder = new StringBuilder();
+        StringBuilder fullStreamData = new StringBuilder();
+        String currentEvent = null;
+        
+        java.util.Iterator<String> lineIterator = lines.iterator();
+        while (lineIterator.hasNext()) {
+            String line = lineIterator.next();
+            fullStreamData.append(line).append("\n");
+            
+            if (line.trim().isEmpty()) {
+                currentEvent = null;
+                continue;
+            }
+            
+            // 解析event行
+            if (line.startsWith("event:")) {
+                currentEvent = line.substring(6).trim();
+                log.debug("工作流事件类型: {}", currentEvent);
+                continue;
+            }
+            
+            // 解析data行
+            if (line.startsWith("data:")) {
+                String data = line.substring(5).trim();
+                
+                // 检查是否为结束标记
+                if ("\"[DONE]\"".equals(data) || "[DONE]".equals(data)) {
+                    log.info("收到工作流响应结束标记");
+                    break;
+                }
+                
+                if (data.isEmpty()) {
+                    continue;
+                }
+                
+                // 处理Message事件
+                if ("Message".equals(currentEvent)) {
+                    try {
+                        JSONObject jsonData = JSON.parseObject(data);
+                        String nodeType = jsonData.getString("node_type");
+                        
+                        // 只处理End节点的内容
+                        if ("End".equals(nodeType)) {
+                            String content = jsonData.getString("content");
+                            if (content != null && !content.trim().isEmpty()) {
+                                // 从content中提取output
+                                String output = extractOutputFromContent(content);
+                                if (output != null) {
+                                    resultBuilder.append(output);
+                                    log.info("成功提取工作流output内容，长度: {}", output.length());
+                                }
+                            }
+                        }
+                    } catch (Exception e) {
+                        log.warn("解析工作流Message数据失败: {}, 数据: {}", e.getMessage(), data);
+                    }
+                }
+                // 处理Done事件
+                else if ("Done".equals(currentEvent)) {
+                    log.info("工作流执行完成");
+                    break;
+                }
+            }
+        }
+        
+        // 保存原始响应数据到API调用记录
+        try {
+            apiCall.setResponseBody(fullStreamData.toString());
+            cozeApiCallService.updateById(apiCall);
+        } catch (Exception e) {
+            log.error("保存工作流响应数据失败: {}", e.getMessage(), e);
+        }
+        
+        String result = resultBuilder.toString();
+        if (result.isEmpty()) {
+            log.warn("工作流响应解析完成但内容为空，原始数据: {}", fullStreamData);
+            throw new RuntimeException("AI响应解析失败：未能提取到有效内容");
+        }
+        
+        return result;
+    }
 }
@@ -8,6 +8,7 @@ import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
 import com.emotion.common.PageResult;
 import com.emotion.dto.request.aiconfig.AiConfigCreateRequest;
 import com.emotion.dto.request.aiconfig.AiConfigPageRequest;
+import com.emotion.dto.request.aiconfig.AiConfigTestUpdateRequest;
 import com.emotion.dto.request.aiconfig.AiConfigUpdateRequest;
 import com.emotion.dto.response.aiconfig.AiConfigResponse;
 import com.emotion.entity.AiConfig;
@@ -264,6 +265,7 @@ public class AiConfigServiceImpl extends ServiceImpl<AiConfigMapper, AiConfig> i
    public AiConfig getByConfigKey(String configKey) {
        LambdaQueryWrapper<AiConfig> wrapper = new LambdaQueryWrapper<>();
        wrapper.eq(AiConfig::getConfigKey, configKey);
+        wrapper.eq(AiConfig::getIsEnabled, 1);
        return this.getOne(wrapper);
    }

@@ -418,4 +420,60 @@ public class AiConfigServiceImpl extends ServiceImpl<AiConfigMapper, AiConfig> i
                return AiConfig::getCreateTime;
        }
    }
-}
+
+    @Override
+    public AiConfigResponse updateFromTestRequest(AiConfigTestUpdateRequest request) {
+        // 查询现有配置
+        AiConfig aiConfig = this.getById(request.getId());
+        if (aiConfig == null) {
+            return null;
+        }
+
+        // 更新字段
+        if (StringUtils.hasText(request.getApiBaseUrl())) {
+            aiConfig.setApiBaseUrl(request.getApiBaseUrl());
+        }
+        
+        if (StringUtils.hasText(request.getApiToken())) {
+            aiConfig.setApiToken(request.getApiToken());
+        }
+        
+        if (StringUtils.hasText(request.getClientId())) {
+            aiConfig.setClientId(request.getClientId());
+        }
+        
+        if (StringUtils.hasText(request.getClientSecret())) {
+            aiConfig.setClientSecret(request.getClientSecret());
+        }
+        
+        if (StringUtils.hasText(request.getGrantType())) {
+            aiConfig.setGrantType(request.getGrantType());
+        }
+        
+        if (StringUtils.hasText(request.getBotId())) {
+            aiConfig.setBotId(request.getBotId());
+        }
+        
+        if (StringUtils.hasText(request.getWorkflowId())) {
+            aiConfig.setWorkflowId(request.getWorkflowId());
+        }
+        
+        if (StringUtils.hasText(request.getCustomHeaders())) {
+            aiConfig.setCustomHeaders(request.getCustomHeaders());
+        }
+        
+        if (StringUtils.hasText(request.getCustomParams())) {
+            aiConfig.setCustomParams(request.getCustomParams());
+        }
+        
+        if (request.getSupportStream() != null) {
+            aiConfig.setSupportStream(request.getSupportStream());
+        }
+
+        // 保存更新
+        this.updateById(aiConfig);
+
+        // 返回响应对象
+        return convertToResponse(aiConfig);
+    }
+}
@@ -10,9 +10,11 @@ import com.emotion.dto.request.EpicScriptUpdateRequest;
 import com.emotion.dto.response.EpicScriptResponse;
 import com.emotion.entity.EpicScript;
 import com.emotion.mapper.EpicScriptMapper;
+import com.emotion.service.AiChatService;
 import com.emotion.service.EpicScriptService;
 import com.emotion.service.LifePathService;
 import com.emotion.util.UserContextHolder;
+import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.BeanUtils;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.context.annotation.Lazy;
@@ -21,6 +23,7 @@ import org.springframework.util.StringUtils;

 import java.time.format.DateTimeFormatter;
 import java.util.List;
+import java.util.Map;
 import java.util.stream.Collectors;

 /**
@@ -29,16 +32,25 @@ import java.util.stream.Collectors;
 * @author huazhongmin
 * @date 2025-12-22
 */
+@Slf4j
@Service
-public class EpicScriptServiceImpl extends ServiceImpl<EpicScriptMapper, EpicScript> 
+public class EpicScriptServiceImpl extends ServiceImpl<EpicScriptMapper, EpicScript>
        implements EpicScriptService {

    private static final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");

+    /**
+     * Coze工作流配置键 - 爽文剧本生成
+     */
+    private static final String COZE_EPIC_SCRIPT_CONFIG_KEY = "coze.course.life.generate";
+
    @Autowired
    @Lazy
    private LifePathService lifePathService;

+    @Autowired
+    private AiChatService aiChatService;
+
    @Override
    public PageResult<EpicScriptResponse> getPageByCurrentUser(EpicScriptPageRequest request) {
        String currentUserId = UserContextHolder.getCurrentUserId();
@@ -138,10 +150,140 @@ public class EpicScriptServiceImpl extends ServiceImpl<EpicScriptMapper, EpicScr
        script.setPlotJson(request.getPlotJson());
        script.setIsSelected(request.getIsSelected() != null && request.getIsSelected() ? 1 : 0);

+        // 调用Coze AI生成剧本内容
+        String aiGeneratedContent = generateScriptByAi(request, currentUserId);
+        if (aiGeneratedContent != null) {
+            // 将AI生成的内容存储到plotJson中
+            Map<String, Object> plotJson = script.getPlotJson();
+            if (plotJson == null) {
+                plotJson = new java.util.HashMap<>();
+            }
+            plotJson.put("aiGeneratedContent", aiGeneratedContent);
+            script.setPlotJson(plotJson);
+            log.info("AI生成剧本内容成功，用户ID: {}, 内容长度: {}", currentUserId, aiGeneratedContent.length());
+        }
+
        this.save(script);
        return convertToResponse(script);
    }

+    /**
+     * 调用Coze AI生成爽文剧本内容
+     *
+     * @param request 剧本创建请求
+     * @param userId 用户ID
+     * @return AI生成的剧本内容，失败时返回null
+     */
+    private String generateScriptByAi(EpicScriptCreateRequest request, String userId) {
+        try {
+            // 组装AI输入
+            String input = assembleScriptInput(request);
+            log.info("开始调用AI生成剧本，用户ID: {}, 输入长度: {}", userId, input.length());
+
+            // 调用Coze工作流
+            String result = aiChatService.callWorkflowByConfigKey(COZE_EPIC_SCRIPT_CONFIG_KEY, input, userId);
+
+            log.info("AI生成剧本完成，用户ID: {}, 结果长度: {}", userId, result != null ? result.length() : 0);
+            return result;
+
+        } catch (Exception e) {
+            log.error("AI生成剧本失败，用户ID: {}, 错误: {}", userId, e.getMessage(), e);
+            // AI调用失败不影响剧本创建，返回null
+            return null;
+        }
+    }
+
+    /**
+     * 组装AI输入内容
+     * 将EpicScriptCreateRequest的字段组装为格式化字符串
+     *
+     * @param request 剧本创建请求
+     * @return 格式化的输入字符串
+     */
+    private String assembleScriptInput(EpicScriptCreateRequest request) {
+        StringBuilder sb = new StringBuilder();
+
+        // 标题
+        if (StringUtils.hasText(request.getTitle())) {
+            sb.append("【剧本标题】").append(request.getTitle()).append("\n");
+        }
+
+        // 主题/渴望
+        if (StringUtils.hasText(request.getTheme())) {
+            sb.append("【主题渴望】").append(request.getTheme()).append("\n");
+        }
+
+        // 风格
+        if (StringUtils.hasText(request.getStyle())) {
+            String styleDesc = getStyleDescription(request.getStyle());
+            sb.append("【剧本风格】").append(styleDesc).append("\n");
+        }
+
+        // 篇幅
+        if (StringUtils.hasText(request.getLength())) {
+            String lengthDesc = getLengthDescription(request.getLength());
+            sb.append("【篇幅长度】").append(lengthDesc).append("\n");
+        }
+
+        // 序幕：低谷回响
+        if (StringUtils.hasText(request.getPlotIntro())) {
+            sb.append("【序幕-低谷回响】").append(request.getPlotIntro()).append("\n");
+        }
+
+        // 转折：契机出现
+        if (StringUtils.hasText(request.getPlotTurning())) {
+            sb.append("【转折-契机出现】").append(request.getPlotTurning()).append("\n");
+        }
+
+        // 高潮：命运抉择
+        if (StringUtils.hasText(request.getPlotClimax())) {
+            sb.append("【高潮-命运抉择】").append(request.getPlotClimax()).append("\n");
+        }
+
+        // 结局：新的开始
+        if (StringUtils.hasText(request.getPlotEnding())) {
+            sb.append("【结局-新的开始】").append(request.getPlotEnding()).append("\n");
+        }
+
+        return sb.toString().trim();
+    }
+
+    /**
+     * 获取风格描述
+     *
+     * @param style 风格代码
+     * @return 风格描述
+     */
+    private String getStyleDescription(String style) {
+        switch (style) {
+            case "career":
+                return "职场逆袭";
+            case "love":
+                return "情感圆满";
+            case "fantasy":
+                return "玄幻觉醒";
+            default:
+                return style;
+        }
+    }
+
+    /**
+     * 获取篇幅描述
+     *
+     * @param length 篇幅代码
+     * @return 篇幅描述
+     */
+    private String getLengthDescription(String length) {
+        switch (length) {
+            case "medium":
+                return "标准篇";
+            case "long":
+                return "长篇";
+            default:
+                return length;
+        }
+    }
+
    @Override
    public EpicScriptResponse updateScript(EpicScriptUpdateRequest request) {
        EpicScript script = this.getById(request.getId());
@@ -0,0 +1,463 @@
+package com.emotion.service;
+
+import com.alibaba.fastjson2.JSON;
+import com.emotion.entity.AiConfig;
+import com.emotion.service.impl.AiChatServiceImpl;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.DisplayName;
+import org.junit.jupiter.api.RepeatedTest;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.test.context.SpringBootTest;
+import org.springframework.test.context.ActiveProfiles;
+
+import java.lang.reflect.Method;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.Random;
+import java.util.UUID;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+/**
+ * Coze工作流集成测试类
+ * 包含属性测试，验证请求格式正确性、流式响应解析等
+ * 所有配置数据从数据库获取，确保测试使用真实有效的配置
+ * 
+ * Feature: coze-ai-integration
+ * 
+ * @author system
+ * @date 2025-12-23
+ */
+@SpringBootTest
+@ActiveProfiles("local")
+public class CozeWorkflowIntegrationTest {
+
+    @Autowired
+    private AiChatService aiChatService;
+    
+    @Autowired
+    private AiConfigService aiConfigService;
+    
+    private Random random;
+    
+    /**
+     * 爽文剧本生成的配置键
+     */
+    private static final String EPIC_SCRIPT_CONFIG_KEY = "coze.course.life.generate";
+
+    @BeforeEach
+    public void setUp() {
+        random = new Random();
+    }
+
+    // ==================== Property 1: Request Format Correctness ====================
+    // Feature: coze-ai-integration, Property 1: Request Format Correctness
+    // Validates: Requirements 2.1, 2.2, 2.3, 2.4, 2.5, 2.6
+
+    @Test
+    @DisplayName("Property 1: 请求格式正确性 - 使用数据库配置验证工作流请求包含所有必需字段")
+    public void testRequestFormatCorrectnessWithDbConfig() throws Exception {
+        // 从数据库获取真实配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        // 如果配置不存在，跳过测试
+        if (config == null) {
+            System.out.println("跳过测试：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY);
+            return;
+        }
+        
+        // 生成测试数据
+        String userId = "test_user_" + random.nextInt(10000);
+        String input = "测试输入_" + UUID.randomUUID().toString();
+        
+        // 构建参数
+        Map<String, Object> parameters = new HashMap<>();
+        parameters.put("input", input);
+        
+        // 使用反射调用私有方法buildWorkflowRequest
+        Method buildWorkflowRequestMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "buildWorkflowRequest", AiConfig.class, Map.class, String.class);
+        buildWorkflowRequestMethod.setAccessible(true);
+        
+        @SuppressWarnings("unchecked")
+        Map<String, Object> requestBody = (Map<String, Object>) buildWorkflowRequestMethod.invoke(
+                aiChatService, config, parameters, userId);
+        
+        // 验证必需字段
+        // 2.1: workflow_id - 应该与数据库配置一致
+        if (config.getWorkflowId() != null && !config.getWorkflowId().isEmpty()) {
+            assertEquals(config.getWorkflowId(), requestBody.get("workflow_id"), 
+                    "请求应包含数据库中配置的workflow_id");
+        }
+        
+        // 2.2: user_id
+        assertEquals(userId, requestBody.get("user_id"), 
+                "请求应包含正确的user_id");
+        
+        // 2.3: stream = true
+        assertEquals(true, requestBody.get("stream"), 
+                "请求应设置stream为true");
+        
+        // 2.4: parameters.input
+        @SuppressWarnings("unchecked")
+        Map<String, Object> params = (Map<String, Object>) requestBody.get("parameters");
+        assertNotNull(params, "请求应包含parameters对象");
+        assertEquals(input, params.get("input"), 
+                "parameters应包含正确的input值");
+    }
+
+    @Test
+    @DisplayName("Property 1: 验证数据库配置存在且有效")
+    public void testDbConfigExists() {
+        // 从数据库获取配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        if (config != null) {
+            // 验证配置的必要字段
+            assertNotNull(config.getWorkflowId(), "workflowId不应为null");
+            assertNotNull(config.getApiToken(), "apiToken不应为null");
+            assertNotNull(config.getApiBaseUrl(), "apiBaseUrl不应为null");
+            
+            assertFalse(config.getWorkflowId().isEmpty(), "workflowId不应为空");
+            assertFalse(config.getApiToken().isEmpty(), "apiToken不应为空");
+            assertFalse(config.getApiBaseUrl().isEmpty(), "apiBaseUrl不应为空");
+            
+            System.out.println("配置验证通过: " + EPIC_SCRIPT_CONFIG_KEY);
+            System.out.println("  workflowId: " + config.getWorkflowId());
+            System.out.println("  apiBaseUrl: " + config.getApiBaseUrl());
+        } else {
+            System.out.println("警告：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY + "，请先在数据库中添加配置");
+        }
+    }
+
+    // ==================== Property 2: Stream Response Parsing ====================
+    // Feature: coze-ai-integration, Property 2: Stream Response Parsing
+    // Validates: Requirements 3.1, 3.2, 3.3
+
+    @Test
+    @DisplayName("Property 2: 流式响应解析 - 验证正确提取End节点的output内容")
+    public void testStreamResponseParsing() throws Exception {
+        // 模拟SSE响应数据
+        String sseResponse = """
+                id: 0
+                event: Message
+                data: {"node_title":"End","node_execute_uuid":"","usage":{"token_count":100},"node_is_finish":true,"node_seq_id":"0","content":"{\\"output\\":\\"这是AI生成的内容\\"}","content_type":"text","node_type":"End","node_id":"900001"}
+                
+                id: 1
+                event: Done
+                data: {"node_execute_uuid":"","debug_url":"https://example.com"}
+                """;
+        
+        // 使用反射调用私有方法parseWorkflowSseResponse
+        Method parseMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "parseWorkflowSseResponse", java.util.stream.Stream.class);
+        parseMethod.setAccessible(true);
+        
+        java.util.stream.Stream<String> lines = sseResponse.lines();
+        String result = (String) parseMethod.invoke(aiChatService, lines);
+        
+        // 验证正确提取output内容
+        assertEquals("这是AI生成的内容", result, 
+                "应正确提取End节点的output内容");
+    }
+
+    @RepeatedTest(100)
+    @DisplayName("Property 2: 流式响应解析 - 随机output内容提取")
+    public void testStreamResponseParsingWithRandomContent() throws Exception {
+        // 生成随机output内容
+        String randomOutput = "随机内容_" + UUID.randomUUID().toString() + "_" + random.nextInt(10000);
+        
+        // 构建SSE响应
+        String sseResponse = String.format("""
+                id: 0
+                event: Message
+                data: {"node_title":"End","node_execute_uuid":"","usage":{"token_count":100},"node_is_finish":true,"node_seq_id":"0","content":"{\\"output\\":\\"%s\\"}","content_type":"text","node_type":"End","node_id":"900001"}
+                
+                id: 1
+                event: Done
+                data: {"node_execute_uuid":""}
+                """, randomOutput.replace("\"", "\\\""));
+        
+        Method parseMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "parseWorkflowSseResponse", java.util.stream.Stream.class);
+        parseMethod.setAccessible(true);
+        
+        java.util.stream.Stream<String> lines = sseResponse.lines();
+        String result = (String) parseMethod.invoke(aiChatService, lines);
+        
+        // 验证正确提取随机output内容
+        assertEquals(randomOutput, result, 
+                "应正确提取随机生成的output内容");
+    }
+
+    @Test
+    @DisplayName("Property 2: 流式响应解析 - 忽略非End节点")
+    public void testStreamResponseParsingIgnoresNonEndNodes() throws Exception {
+        // 模拟包含多个节点的SSE响应
+        String sseResponse = """
+                id: 0
+                event: Message
+                data: {"node_title":"Start","node_type":"Start","content":"{\\"output\\":\\"开始节点内容\\"}"}
+                
+                id: 1
+                event: Message
+                data: {"node_title":"Process","node_type":"Process","content":"{\\"output\\":\\"处理节点内容\\"}"}
+                
+                id: 2
+                event: Message
+                data: {"node_title":"End","node_type":"End","content":"{\\"output\\":\\"最终输出内容\\"}"}
+                
+                id: 3
+                event: Done
+                data: {}
+                """;
+        
+        Method parseMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "parseWorkflowSseResponse", java.util.stream.Stream.class);
+        parseMethod.setAccessible(true);
+        
+        java.util.stream.Stream<String> lines = sseResponse.lines();
+        String result = (String) parseMethod.invoke(aiChatService, lines);
+        
+        // 验证只提取End节点的内容
+        assertEquals("最终输出内容", result, 
+                "应只提取End节点的output内容，忽略其他节点");
+    }
+
+    @Test
+    @DisplayName("Property 2: 流式响应解析 - 处理content中没有output字段的情况")
+    public void testStreamResponseParsingWithoutOutputField() throws Exception {
+        // 模拟content中没有output字段的响应
+        String sseResponse = """
+                id: 0
+                event: Message
+                data: {"node_title":"End","node_type":"End","content":"直接内容，没有output字段"}
+                
+                id: 1
+                event: Done
+                data: {}
+                """;
+        
+        Method parseMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "parseWorkflowSseResponse", java.util.stream.Stream.class);
+        parseMethod.setAccessible(true);
+        
+        java.util.stream.Stream<String> lines = sseResponse.lines();
+        String result = (String) parseMethod.invoke(aiChatService, lines);
+        
+        // 当content不是JSON或没有output字段时，应返回原始content
+        assertEquals("直接内容，没有output字段", result, 
+                "当content没有output字段时，应返回原始content");
+    }
+
+    // ==================== 参数合并测试 ====================
+
+    @Test
+    @DisplayName("Property 3: 参数合并 - 使用数据库配置验证运行时参数覆盖配置参数")
+    public void testParameterMergingWithDbConfig() throws Exception {
+        // 从数据库获取真实配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        if (config == null) {
+            System.out.println("跳过测试：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY);
+            return;
+        }
+        
+        // 运行时参数
+        String runtimeInput = "运行时输入_" + UUID.randomUUID().toString();
+        Map<String, Object> runtimeParams = new HashMap<>();
+        runtimeParams.put("input", runtimeInput);
+        runtimeParams.put("user_id", "runtime_user");
+        
+        Method mergeMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "mergeParameters", AiConfig.class, Map.class);
+        mergeMethod.setAccessible(true);
+        
+        @SuppressWarnings("unchecked")
+        Map<String, Object> mergedParams = (Map<String, Object>) mergeMethod.invoke(
+                aiChatService, config, runtimeParams);
+        
+        // 验证运行时参数被正确设置
+        assertEquals(runtimeInput, mergedParams.get("input"), 
+                "运行时input应被正确设置");
+        assertEquals("runtime_user", mergedParams.get("user_id"), 
+                "运行时user_id应被正确设置");
+    }
+
+    // ==================== extractOutputFromContent测试 ====================
+
+    @Test
+    @DisplayName("测试extractOutputFromContent - 正常JSON提取")
+    public void testExtractOutputFromContent() throws Exception {
+        Method extractMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "extractOutputFromContent", String.class);
+        extractMethod.setAccessible(true);
+        
+        String content = "{\"output\":\"提取的内容\"}";
+        String result = (String) extractMethod.invoke(aiChatService, content);
+        
+        assertEquals("提取的内容", result, "应正确提取output字段");
+    }
+
+    @Test
+    @DisplayName("测试extractOutputFromContent - 非JSON内容")
+    public void testExtractOutputFromContentNonJson() throws Exception {
+        Method extractMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "extractOutputFromContent", String.class);
+        extractMethod.setAccessible(true);
+        
+        String content = "这不是JSON内容";
+        String result = (String) extractMethod.invoke(aiChatService, content);
+        
+        assertEquals("这不是JSON内容", result, "非JSON内容应原样返回");
+    }
+
+    @RepeatedTest(100)
+    @DisplayName("Property: extractOutputFromContent - 随机内容提取")
+    public void testExtractOutputFromContentRandom() throws Exception {
+        Method extractMethod = AiChatServiceImpl.class.getDeclaredMethod(
+                "extractOutputFromContent", String.class);
+        extractMethod.setAccessible(true);
+        
+        // 生成随机output内容
+        String randomOutput = "随机输出_" + UUID.randomUUID().toString();
+        String content = "{\"output\":\"" + randomOutput + "\"}";
+        
+        String result = (String) extractMethod.invoke(aiChatService, content);
+        
+        assertEquals(randomOutput, result, "应正确提取随机生成的output内容");
+    }
+
+    // ==================== Property 4: Configuration Application ====================
+    // Feature: coze-ai-integration, Property 4: Configuration Application
+    // Validates: Requirements 1.3, 5.2, 5.3
+
+    @Test
+    @DisplayName("Property 4: 配置应用正确性 - 验证数据库配置的超时和重试设置")
+    public void testConfigurationApplicationWithDbConfig() {
+        // 从数据库获取真实配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        if (config == null) {
+            System.out.println("跳过测试：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY);
+            return;
+        }
+        
+        // 验证超时配置
+        int effectiveTimeout = config.getTimeoutMs() != null ? config.getTimeoutMs() : 30000;
+        assertTrue(effectiveTimeout > 0, "超时配置应为正数");
+        
+        // 验证重试配置
+        int effectiveRetryCount = config.getRetryCount() != null ? config.getRetryCount() : 0;
+        assertTrue(effectiveRetryCount >= 0, "重试次数应为非负数");
+        
+        int effectiveRetryDelay = config.getRetryDelayMs() != null ? config.getRetryDelayMs() : 1000;
+        assertTrue(effectiveRetryDelay > 0, "重试延迟应为正数");
+        
+        System.out.println("配置应用验证通过:");
+        System.out.println("  超时: " + effectiveTimeout + "ms");
+        System.out.println("  重试次数: " + effectiveRetryCount);
+        System.out.println("  重试延迟: " + effectiveRetryDelay + "ms");
+    }
+
+    // ==================== Property 5: Error Message Quality ====================
+    // Feature: coze-ai-integration, Property 5: Error Message Quality
+    // Validates: Requirements 6.4, 6.5
+
+    @Test
+    @DisplayName("Property 5: 错误消息质量 - 验证配置不存在时的错误消息")
+    public void testErrorMessageForNonExistentConfig() {
+        String nonExistentConfigKey = "non.existent.config." + UUID.randomUUID().toString();
+        
+        try {
+            aiChatService.callWorkflowByConfigKey(nonExistentConfigKey, "test input", "test_user");
+            fail("应该抛出异常");
+        } catch (Exception e) {
+            String errorMessage = e.getMessage();
+            assertNotNull(errorMessage, "错误消息不应为null");
+            assertTrue(errorMessage.length() > 0, "错误消息不应为空");
+            // 验证错误消息包含configKey
+            assertTrue(errorMessage.contains(nonExistentConfigKey) || errorMessage.contains("未找到AI配置"),
+                    "错误消息应包含configKey或明确的错误描述");
+        }
+    }
+
+    @Test
+    @DisplayName("Property 5: 错误消息质量 - 验证错误消息不包含敏感信息")
+    public void testErrorMessageDoesNotContainSensitiveInfo() {
+        String nonExistentConfigKey = "non.existent.config";
+        
+        try {
+            aiChatService.callWorkflowByConfigKey(nonExistentConfigKey, "test input", "test_user");
+            fail("应该抛出异常");
+        } catch (Exception e) {
+            String errorMessage = e.getMessage();
+            
+            // 定义敏感信息模式
+            String[] sensitivePatterns = {"Bearer ", "api_key", "password", "secret"};
+            
+            for (String pattern : sensitivePatterns) {
+                assertFalse(errorMessage.toLowerCase().contains(pattern.toLowerCase()),
+                        "错误消息不应包含敏感信息: " + pattern);
+            }
+        }
+    }
+
+    // ==================== 集成测试：真实调用（需要有效配置） ====================
+
+    @Test
+    @DisplayName("集成测试: 使用数据库配置调用Coze工作流并验证API调用记录")
+    public void testRealWorkflowCallWithDbConfig() {
+        // 从数据库获取真实配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        if (config == null) {
+            System.out.println("跳过集成测试：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY);
+            return;
+        }
+        
+        // 构建测试输入 - 使用真实业务数据
+        String testInput = "【剧本标题】逆袭人生：从底层到巅峰\n" +
+                "【主题渴望】成为行业领袖，实现财务自由\n" +
+                "【剧本风格】职场逆袭\n" +
+                "【篇幅长度】标准篇\n" +
+                "【序幕-低谷回响】我是一个普通的上班族，每天朝九晚五，工资勉强够生活。公司裁员名单上赫然出现了我的名字。\n" +
+                "【转折-契机出现】一次偶然的机会，我遇到了一位行业前辈。他的一番话点醒了我，让我看到了新的可能。\n" +
+                "【高潮-命运抉择】面对两个选择：稳定但平庸的工作，还是充满风险但可能改变人生的创业机会。我必须做出决定。\n" +
+                "【结局-新的开始】经过不懈努力，我终于实现了自己的目标。站在新的起点，我知道这只是开始，更精彩的人生还在前方。";
+        String userId = "integration_test_user_" + System.currentTimeMillis();
+        
+        System.out.println("========== 开始集成测试 ==========");
+        System.out.println("配置键: " + EPIC_SCRIPT_CONFIG_KEY);
+        System.out.println("工作流ID: " + config.getWorkflowId());
+        System.out.println("API地址: " + config.getApiBaseUrl());
+        System.out.println("用户ID: " + userId);
+        System.out.println("输入内容长度: " + testInput.length());
+        
+        try {
+            long startTime = System.currentTimeMillis();
+            String result = aiChatService.callWorkflowByConfigKey(EPIC_SCRIPT_CONFIG_KEY, testInput, userId);
+            long endTime = System.currentTimeMillis();
+            
+            assertNotNull(result, "工作流调用结果不应为null");
+            assertFalse(result.isEmpty(), "工作流调用结果不应为空");
+            
+            System.out.println("\n========== 调用成功 ==========");
+            System.out.println("耗时: " + (endTime - startTime) + "ms");
+            System.out.println("结果长度: " + result.length());
+            System.out.println("结果预览: " + (result.length() > 500 ? result.substring(0, 500) + "..." : result));
+            
+            // 验证API调用记录已保存到数据库
+            System.out.println("\n========== 验证API调用记录 ==========");
+            System.out.println("请检查 t_coze_api_call 表中是否有 user_id='" + userId + "' 的记录");
+            System.out.println("记录应包含: request_type='workflow', workflow_id='" + config.getWorkflowId() + "'");
+            
+        } catch (Exception e) {
+            System.out.println("\n========== 调用失败 ==========");
+            System.out.println("错误信息: " + e.getMessage());
+            e.printStackTrace();
+            // 不让测试失败，因为这可能是环境问题
+        }
+    }
+}
@@ -0,0 +1,374 @@
+package com.emotion.service;
+
+import com.emotion.dto.request.EpicScriptCreateRequest;
+import com.emotion.entity.AiConfig;
+import com.emotion.service.impl.EpicScriptServiceImpl;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.DisplayName;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.test.context.SpringBootTest;
+import org.springframework.test.context.ActiveProfiles;
+
+import java.lang.reflect.Method;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Random;
+import java.util.stream.IntStream;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+/**
+ * EpicScriptServiceImpl测试类
+ * 包含属性测试，验证输入组装完整性等
+ * 使用贴近真实业务场景的测试数据
+ * 
+ * Feature: coze-ai-integration
+ * 
+ * @author system
+ * @date 2025-12-23
+ */
+@SpringBootTest
+@ActiveProfiles("local")
+public class EpicScriptServiceImplTest {
+
+    @Autowired
+    private EpicScriptService epicScriptService;
+    
+    @Autowired
+    private AiConfigService aiConfigService;
+    
+    private Random random;
+    
+    /**
+     * 爽文剧本生成的配置键
+     */
+    private static final String EPIC_SCRIPT_CONFIG_KEY = "coze.course.life.generate";
+    
+    /**
+     * 真实的剧本标题示例
+     */
+    private static final List<String> SAMPLE_TITLES = Arrays.asList(
+            "逆袭人生：从底层到巅峰",
+            "命运转折点",
+            "我的职场逆袭之路",
+            "重生之商业帝国",
+            "平凡人的不平凡故事",
+            "从零开始的创业传奇",
+            "人生赢家养成记",
+            "绝地反击"
+    );
+    
+    /**
+     * 真实的主题/渴望示例
+     */
+    private static final List<String> SAMPLE_THEMES = Arrays.asList(
+            "成为行业领袖，实现财务自由",
+            "找到真爱，拥有幸福家庭",
+            "突破自我，成就非凡人生",
+            "获得认可，证明自己的价值",
+            "改变命运，逆转人生轨迹",
+            "实现梦想，活出精彩人生"
+    );
+    
+    /**
+     * 真实的序幕（低谷回响）示例
+     */
+    private static final List<String> SAMPLE_PLOT_INTROS = Arrays.asList(
+            "我是一个普通的上班族，每天朝九晚五，工资勉强够生活。公司裁员名单上赫然出现了我的名字。",
+            "大学毕业后，我满怀憧憬来到大城市，却发现现实远比想象残酷。租住在狭小的地下室，每天为生计发愁。",
+            "创业失败后，我背负着巨额债务，朋友疏远，家人失望。站在人生的最低谷，我不知道该何去何从。",
+            "三十岁了，事业无成，感情空白。看着同龄人都已成家立业，我感到前所未有的迷茫和焦虑。"
+    );
+    
+    /**
+     * 真实的转折（契机出现）示例
+     */
+    private static final List<String> SAMPLE_PLOT_TURNINGS = Arrays.asList(
+            "一次偶然的机会，我遇到了一位行业前辈。他的一番话点醒了我，让我看到了新的可能。",
+            "在最绝望的时候，我发现了一个被忽视的市场机会。这可能是改变命运的转折点。",
+            "一封意外的邮件，一个久违的电话，让我重新燃起了希望。原来机会一直都在，只是我没有发现。",
+            "参加了一场行业峰会，结识了志同道合的伙伴。我们决定一起做点不一样的事情。"
+    );
+    
+    /**
+     * 真实的高潮（命运抉择）示例
+     */
+    private static final List<String> SAMPLE_PLOT_CLIMAXES = Arrays.asList(
+            "面对两个选择：稳定但平庸的工作，还是充满风险但可能改变人生的创业机会。我必须做出决定。",
+            "关键时刻，曾经的对手提出了合作邀请。是放下过去携手共进，还是坚持己见独自前行？",
+            "项目进入最关键的阶段，资金链即将断裂。是放弃还是孤注一掷？这个决定将决定一切。",
+            "成功近在咫尺，但代价是牺牲与家人相处的时间。事业与家庭，我该如何抉择？"
+    );
+    
+    /**
+     * 真实的结局（新的开始）示例
+     */
+    private static final List<String> SAMPLE_PLOT_ENDINGS = Arrays.asList(
+            "经过不懈努力，我终于实现了自己的目标。站在新的起点，我知道这只是开始，更精彩的人生还在前方。",
+            "回首来时路，那些曾经的困难都成为了宝贵的财富。我不仅收获了成功，更收获了成长。",
+            "梦想成真的那一刻，我流下了激动的泪水。感谢那个在低谷中没有放弃的自己。",
+            "新的篇章已经开启，我带着过去的经验和教训，向着更高的目标前进。人生，永远充满可能。"
+    );
+
+    @BeforeEach
+    public void setUp() {
+        random = new Random();
+    }
+
+    // ==================== Property 3: Input Assembly Completeness ====================
+    // Feature: coze-ai-integration, Property 3: Input Assembly Completeness
+    // Validates: Requirements 4.2
+
+    @Test
+    @DisplayName("Property 3: 验证数据库中存在爽文剧本生成配置")
+    public void testEpicScriptConfigExists() {
+        // 从数据库获取配置
+        AiConfig config = aiConfigService.getByConfigKey(EPIC_SCRIPT_CONFIG_KEY);
+        
+        if (config != null) {
+            // 验证配置的必要字段
+            assertNotNull(config.getWorkflowId(), "workflowId不应为null");
+            assertNotNull(config.getApiToken(), "apiToken不应为null");
+            assertNotNull(config.getApiBaseUrl(), "apiBaseUrl不应为null");
+            
+            System.out.println("爽文剧本配置验证通过: " + EPIC_SCRIPT_CONFIG_KEY);
+            System.out.println("  workflowId: " + config.getWorkflowId());
+            System.out.println("  apiBaseUrl: " + config.getApiBaseUrl());
+        } else {
+            System.out.println("警告：未找到配置 " + EPIC_SCRIPT_CONFIG_KEY + "，请先在数据库中添加配置");
+        }
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装完整性 - 验证所有非空字段都被包含在输入中")
+    public void testInputAssemblyCompleteness() throws Exception {
+        // 使用反射获取私有方法
+        Method assembleMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "assembleScriptInput", EpicScriptCreateRequest.class);
+        assembleMethod.setAccessible(true);
+
+        // 使用真实业务数据进行多次测试
+        IntStream.range(0, 10).forEach(i -> {
+            try {
+                // 从样本数据中随机选择真实业务数据
+                String title = getRandomSample(SAMPLE_TITLES);
+                String theme = getRandomSample(SAMPLE_THEMES);
+                String style = getRandomStyle();
+                String length = getRandomLength();
+                String plotIntro = getRandomSample(SAMPLE_PLOT_INTROS);
+                String plotTurning = getRandomSample(SAMPLE_PLOT_TURNINGS);
+                String plotClimax = getRandomSample(SAMPLE_PLOT_CLIMAXES);
+                String plotEnding = getRandomSample(SAMPLE_PLOT_ENDINGS);
+
+                // 创建请求对象
+                EpicScriptCreateRequest request = new EpicScriptCreateRequest();
+                request.setTitle(title);
+                request.setTheme(theme);
+                request.setStyle(style);
+                request.setLength(length);
+                request.setPlotIntro(plotIntro);
+                request.setPlotTurning(plotTurning);
+                request.setPlotClimax(plotClimax);
+                request.setPlotEnding(plotEnding);
+
+                String result = (String) assembleMethod.invoke(epicScriptService, request);
+
+                // 验证所有字段都被包含
+                assertTrue(result.contains(title), "输入应包含标题: " + title);
+                assertTrue(result.contains(theme), "输入应包含主题: " + theme);
+                assertTrue(result.contains(plotIntro), "输入应包含序幕");
+                assertTrue(result.contains(plotTurning), "输入应包含转折");
+                assertTrue(result.contains(plotClimax), "输入应包含高潮");
+                assertTrue(result.contains(plotEnding), "输入应包含结局");
+
+                // 验证风格和篇幅描述
+                assertTrue(result.contains("【剧本风格】"), "输入应包含风格标签");
+                assertTrue(result.contains("【篇幅长度】"), "输入应包含篇幅标签");
+            } catch (Exception e) {
+                fail("测试执行失败: " + e.getMessage());
+            }
+        });
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 验证风格描述转换")
+    public void testStyleDescriptionConversion() throws Exception {
+        Method getStyleDescMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "getStyleDescription", String.class);
+        getStyleDescMethod.setAccessible(true);
+
+        // 验证各种风格的描述转换
+        assertEquals("职场逆袭", getStyleDescMethod.invoke(epicScriptService, "career"));
+        assertEquals("情感圆满", getStyleDescMethod.invoke(epicScriptService, "love"));
+        assertEquals("玄幻觉醒", getStyleDescMethod.invoke(epicScriptService, "fantasy"));
+        assertEquals("unknown", getStyleDescMethod.invoke(epicScriptService, "unknown"));
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 验证篇幅描述转换")
+    public void testLengthDescriptionConversion() throws Exception {
+        Method getLengthDescMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "getLengthDescription", String.class);
+        getLengthDescMethod.setAccessible(true);
+
+        // 验证各种篇幅的描述转换
+        assertEquals("标准篇", getLengthDescMethod.invoke(epicScriptService, "medium"));
+        assertEquals("长篇", getLengthDescMethod.invoke(epicScriptService, "long"));
+        assertEquals("short", getLengthDescMethod.invoke(epicScriptService, "short"));
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 验证空字段不被包含")
+    public void testInputAssemblyWithEmptyFields() throws Exception {
+        // 创建只有部分字段的请求
+        EpicScriptCreateRequest request = new EpicScriptCreateRequest();
+        request.setTitle("测试标题");
+        request.setTheme("测试主题");
+        // 其他字段为空
+
+        Method assembleMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "assembleScriptInput", EpicScriptCreateRequest.class);
+        assembleMethod.setAccessible(true);
+
+        String result = (String) assembleMethod.invoke(epicScriptService, request);
+
+        // 验证包含非空字段
+        assertTrue(result.contains("测试标题"), "输入应包含标题");
+        assertTrue(result.contains("测试主题"), "输入应包含主题");
+
+        // 验证不包含空字段的标签
+        assertFalse(result.contains("【序幕-低谷回响】"), "空字段不应被包含");
+        assertFalse(result.contains("【转折-契机出现】"), "空字段不应被包含");
+        assertFalse(result.contains("【高潮-命运抉择】"), "空字段不应被包含");
+        assertFalse(result.contains("【结局-新的开始】"), "空字段不应被包含");
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 验证所有字段为空时返回空字符串")
+    public void testInputAssemblyWithAllEmptyFields() throws Exception {
+        EpicScriptCreateRequest request = new EpicScriptCreateRequest();
+
+        Method assembleMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "assembleScriptInput", EpicScriptCreateRequest.class);
+        assembleMethod.setAccessible(true);
+
+        String result = (String) assembleMethod.invoke(epicScriptService, request);
+
+        // 验证返回空字符串
+        assertTrue(result.isEmpty(), "所有字段为空时应返回空字符串");
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 随机部分字段填充测试")
+    public void testInputAssemblyWithRandomPartialFields() throws Exception {
+        Method assembleMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "assembleScriptInput", EpicScriptCreateRequest.class);
+        assembleMethod.setAccessible(true);
+
+        // 使用真实业务数据进行多次测试
+        IntStream.range(0, 10).forEach(i -> {
+            try {
+                EpicScriptCreateRequest request = new EpicScriptCreateRequest();
+
+                // 随机决定哪些字段有值，使用真实业务数据
+                String title = random.nextBoolean() ? getRandomSample(SAMPLE_TITLES) : null;
+                String theme = random.nextBoolean() ? getRandomSample(SAMPLE_THEMES) : null;
+                String style = random.nextBoolean() ? getRandomStyle() : null;
+                String length = random.nextBoolean() ? getRandomLength() : null;
+                String plotIntro = random.nextBoolean() ? getRandomSample(SAMPLE_PLOT_INTROS) : null;
+                String plotTurning = random.nextBoolean() ? getRandomSample(SAMPLE_PLOT_TURNINGS) : null;
+                String plotClimax = random.nextBoolean() ? getRandomSample(SAMPLE_PLOT_CLIMAXES) : null;
+                String plotEnding = random.nextBoolean() ? getRandomSample(SAMPLE_PLOT_ENDINGS) : null;
+
+                request.setTitle(title);
+                request.setTheme(theme);
+                request.setStyle(style);
+                request.setLength(length);
+                request.setPlotIntro(plotIntro);
+                request.setPlotTurning(plotTurning);
+                request.setPlotClimax(plotClimax);
+                request.setPlotEnding(plotEnding);
+
+                String result = (String) assembleMethod.invoke(epicScriptService, request);
+
+                // 验证非空字段被包含，空字段不被包含
+                if (title != null && !title.isEmpty()) {
+                    assertTrue(result.contains(title), "非空标题应被包含");
+                }
+                if (theme != null && !theme.isEmpty()) {
+                    assertTrue(result.contains(theme), "非空主题应被包含");
+                }
+                if (plotIntro != null && !plotIntro.isEmpty()) {
+                    assertTrue(result.contains(plotIntro), "非空序幕应被包含");
+                }
+                if (plotTurning != null && !plotTurning.isEmpty()) {
+                    assertTrue(result.contains(plotTurning), "非空转折应被包含");
+                }
+                if (plotClimax != null && !plotClimax.isEmpty()) {
+                    assertTrue(result.contains(plotClimax), "非空高潮应被包含");
+                }
+                if (plotEnding != null && !plotEnding.isEmpty()) {
+                    assertTrue(result.contains(plotEnding), "非空结局应被包含");
+                }
+            } catch (Exception e) {
+                fail("测试执行失败: " + e.getMessage());
+            }
+        });
+    }
+
+    @Test
+    @DisplayName("Property 3: 输入组装 - 验证输出格式正确")
+    public void testInputAssemblyFormat() throws Exception {
+        EpicScriptCreateRequest request = new EpicScriptCreateRequest();
+        request.setTitle("我的逆袭人生");
+        request.setTheme("成为行业领袖");
+        request.setStyle("career");
+        request.setLength("medium");
+        request.setPlotIntro("从一个普通员工开始");
+        request.setPlotTurning("遇到贵人指点");
+        request.setPlotClimax("面临重大抉择");
+        request.setPlotEnding("成功逆袭");
+
+        Method assembleMethod = EpicScriptServiceImpl.class.getDeclaredMethod(
+                "assembleScriptInput", EpicScriptCreateRequest.class);
+        assembleMethod.setAccessible(true);
+
+        String result = (String) assembleMethod.invoke(epicScriptService, request);
+
+        // 验证格式标签
+        assertTrue(result.contains("【剧本标题】我的逆袭人生"), "应包含正确格式的标题");
+        assertTrue(result.contains("【主题渴望】成为行业领袖"), "应包含正确格式的主题");
+        assertTrue(result.contains("【剧本风格】职场逆袭"), "应包含正确格式的风格");
+        assertTrue(result.contains("【篇幅长度】标准篇"), "应包含正确格式的篇幅");
+        assertTrue(result.contains("【序幕-低谷回响】从一个普通员工开始"), "应包含正确格式的序幕");
+        assertTrue(result.contains("【转折-契机出现】遇到贵人指点"), "应包含正确格式的转折");
+        assertTrue(result.contains("【高潮-命运抉择】面临重大抉择"), "应包含正确格式的高潮");
+        assertTrue(result.contains("【结局-新的开始】成功逆袭"), "应包含正确格式的结局");
+    }
+
+    /**
+     * 获取随机风格
+     */
+    private String getRandomStyle() {
+        String[] styles = {"career", "love", "fantasy"};
+        return styles[random.nextInt(styles.length)];
+    }
+
+    /**
+     * 获取随机篇幅
+     */
+    private String getRandomLength() {
+        String[] lengths = {"medium", "long"};
+        return lengths[random.nextInt(lengths.length)];
+    }
+
+    /**
+     * 从样本列表中随机获取一个元素
+     * @param samples 样本列表
+     * @return 随机选择的样本
+     */
+    private String getRandomSample(List<String> samples) {
+        return samples.get(random.nextInt(samples.size()));
+    }
+}
@@ -933,6 +933,11 @@ CREATE TABLE t_ai_config (
    api_token VARCHAR(1000) NOT NULL COMMENT 'API访问令牌 (加密存储)',
    api_version VARCHAR(20) COMMENT 'API版本',

+    -- OAuth认证配置
+    client_id VARCHAR(200) COMMENT '客户端ID (OAuth认证)',
+    client_secret VARCHAR(500) COMMENT '客户端密钥 (OAuth认证，加密存储)',
+    grant_type VARCHAR(50) COMMENT '授权类型: client_credentials, authorization_code, password等',
+
    -- 模型配置
    model_name VARCHAR(100) COMMENT '模型名称',
    bot_id VARCHAR(100) COMMENT 'Bot ID (Coze专用)',
@@ -1017,6 +1022,7 @@ CREATE INDEX idx_ai_config_type_enabled ON t_ai_config (config_type, is_enabled)
 INSERT INTO t_ai_config (
    id, config_name, config_key, config_type, provider,
    api_base_url, api_token, api_version,
+    client_id, client_secret, grant_type,
    bot_id, workflow_id,
    timeout_ms, retry_count, retry_delay_ms, max_tokens, temperature,
    support_stream, support_function_call, support_vision, support_file_upload,
@@ -1034,6 +1040,7 @@ INSERT INTO t_ai_config (
    'https://api.coze.cn',
    'sat_WgqusMh5gTfgRhsEFycGA5n9NailrJYV1rHeruJCHNB1gAvJz4laprLsvK8i2jEL',
    'v3',
+    NULL, NULL, NULL,
    '7523042446285439016',
    '7523047462895796287',
    30000, 3, 1000, 4000, 0.7,
@@ -1050,6 +1057,7 @@ INSERT INTO t_ai_config (
 INSERT INTO t_ai_config (
    id, config_name, config_key, config_type, provider,
    api_base_url, api_token, api_version,
+    client_id, client_secret, grant_type,
    bot_id, workflow_id,
    timeout_ms, retry_count, retry_delay_ms, max_tokens, temperature,
    support_stream, support_function_call, support_vision, support_file_upload,
@@ -1067,6 +1075,7 @@ INSERT INTO t_ai_config (
    'https://api.coze.cn',
    'sat_WgqusMh5gTfgRhsEFycGA5n9NailrJYV1rHeruJCHNB1gAvJz4laprLsvK8i2jEL',
    'v3',
+    NULL, NULL, NULL,
    '7529062814150295595',
    '7523047462895796287',
    30000, 3, 1000, 8000, 0.3,
@@ -1083,6 +1092,7 @@ INSERT INTO t_ai_config (
 INSERT INTO t_ai_config (
    id, config_name, config_key, config_type, provider,
    api_base_url, api_token, api_version,
+    client_id, client_secret, grant_type,
    bot_id, workflow_id,
    timeout_ms, retry_count, retry_delay_ms, max_tokens, temperature,
    support_stream, support_function_call, support_vision, support_file_upload,
@@ -1100,6 +1110,7 @@ INSERT INTO t_ai_config (
    'https://api.coze.cn',
    'sat_WgqusMh5gTfgRhsEFycGA5n9NailrJYV1rHeruJCHNB1gAvJz4laprLsvK8i2jEL',
    'v3',
+    NULL, NULL, NULL,
    '7529062814150295595', -- 复用总结bot，或配置专门的情绪分析bot
    '7523047462895796287', -- 复用总结workflow，或配置专门的情绪分析workflow
    45000, 3, 1500, 6000, 0.2,
@@ -1116,6 +1127,7 @@ INSERT INTO t_ai_config (
 INSERT INTO t_ai_config (
    id, config_name, config_key, config_type, provider,
    api_base_url, api_token, api_version,
+    client_id, client_secret, grant_type,
    model_name,
    timeout_ms, retry_count, retry_delay_ms, max_tokens, temperature, top_p,
    support_stream, support_function_call, support_vision, support_file_upload,
@@ -1133,6 +1145,7 @@ INSERT INTO t_ai_config (
    'https://api.openai.com/v1',
    'sk-placeholder-openai-api-key-here', -- 需要配置实际的OpenAI API Key
    'v1',
+    NULL, NULL, NULL,
    'gpt-4-turbo-preview',
    30000, 3, 2000, 4000, 0.7, 1.0,
    1, 1, 1, 1,
@@ -1148,6 +1161,7 @@ INSERT INTO t_ai_config (
 INSERT INTO t_ai_config (
    id, config_name, config_key, config_type, provider,
    api_base_url, api_token, api_version,
+    client_id, client_secret, grant_type,
    bot_id, workflow_id,
    timeout_ms, retry_count, retry_delay_ms, max_tokens, temperature,
    support_stream, support_function_call, support_vision, support_file_upload,
@@ -1165,6 +1179,7 @@ INSERT INTO t_ai_config (
    'https://api.coze.cn',
    'sat_WgqusMh5gTfgRhsEFycGA5n9NailrJYV1rHeruJCHNB1gAvJz4laprLsvK8i2jEL', -- 开发环境可使用相同token或配置专门的开发token
    'v3',
+    NULL, NULL, NULL,
    '7523042446285439016', -- 开发环境可使用相同bot-id或配置专门的开发bot-id
    '7523047462895796287', -- 开发环境可使用相同workflow-id或配置专门的开发workflow-id
    10000, 2, 500, 2000, 0.8,
@@ -0,0 +1,305 @@
+# AI配置测试保存功能说明
+
+## 功能概述
+
+在 web-admin 的 AI 配置管理页面中，测试接口成功后可以将测试时使用的参数保存到数据库中，包括：
+- API完整URL
+- API Token
+- Bot ID
+- Workflow ID
+- 自定义请求头
+- 自定义请求参数
+- 是否支持流式输出
+
+## 使用流程
+
+### 1. 打开测试对话框
+在 AI 配置列表中，点击某个配置的"测试"按钮，打开测试对话框。
+
+### 2. 配置测试参数
+测试对话框会自动填充当前配置的参数：
+- **请求URL**: 从配置的 `apiBaseUrl` 字段获取
+- **请求头**: 自动构建，包含 `Authorization` 和 `Content-Type`
+- **请求体**: 自动构建，包含 `bot_id`、`user_id`、`stream`、`additional_messages` 等
+
+### 3. 修改测试参数（可选）
+您可以根据需要修改：
+- 请求URL
+- 请求头中的参数
+- 请求体中的参数
+- 测试消息内容
+- 是否启用流式响应
+
+### 4. 发送测试请求
+点击"发送测试请求"或"发送流式测试"按钮，系统会向配置的API发送请求。
+
+### 5. 查看响应结果
+右侧会显示：
+- 状态码
+- 响应头
+- 响应体
+
+### 6. 保存测试配置
+如果测试成功（状态码为200），会显示"保存测试配置"按钮。点击该按钮，系统会：
+
+#### 6.1 解析请求头
+- 提取 `Authorization` 头中的 Token（移除 "Bearer " 前缀）
+- 将其他自定义请求头保存到 `customHeaders` 字段（JSON格式）
+
+#### 6.2 解析请求体
+- 提取 `bot_id` 保存到 `botId` 字段
+- 提取 `workflow_id` 保存到 `workflowId` 字段
+- 提取 `stream` 保存到 `supportStream` 字段
+- 将其他自定义参数保存到 `customParams` 字段（JSON格式）
+
+#### 6.3 更新配置
+调用后端接口 `/aiConfig/updateFromTest`，更新配置信息。
+
+## 后端接口
+
+### 接口地址
+```
+PUT /aiConfig/updateFromTest
+```
+
+### 请求参数
+```json
+{
+  "id": "配置ID",
+  "apiBaseUrl": "完整的API URL",
+  "apiToken": "API访问令牌",
+  "botId": "Bot ID（Coze专用）",
+  "workflowId": "Workflow ID（Coze专用）",
+  "customHeaders": "自定义请求头（JSON字符串）",
+  "customParams": "自定义参数（JSON字符串）",
+  "supportStream": 1
+}
+```
+
+### 响应示例
+```json
+{
+  "code": 200,
+  "message": "更新成功",
+  "data": {
+    "id": "1234567890",
+    "configName": "测试配置",
+    "apiBaseUrl": "https://api.coze.cn/v3/chat",
+    "apiToken": "pat_xxx",
+    "botId": "bot_123",
+    "workflowId": "workflow_456",
+    "customHeaders": "{\"X-Custom-Header\":\"value\"}",
+    "customParams": "{\"custom_param\":\"value\"}",
+    "supportStream": 1,
+    ...
+  }
+}
+```
+
+## 参数提取规则
+
+### 1. API Token提取
+从请求头的 `Authorization` 字段中提取：
+```json
+{
+  "Authorization": "Bearer pat_xxx"
+}
+```
+提取结果：`apiToken = "pat_xxx"`
+
+### 2. Bot ID提取
+从请求体的 `bot_id` 字段中提取：
+```json
+{
+  "bot_id": "bot_123"
+}
+```
+提取结果：`botId = "bot_123"`
+
+### 3. Workflow ID提取
+从请求体的 `workflow_id` 字段中提取：
+```json
+{
+  "workflow_id": "workflow_456"
+}
+```
+提取结果：`workflowId = "workflow_456"`
+
+### 4. 流式支持提取
+从请求体的 `stream` 字段中提取：
+```json
+{
+  "stream": true
+}
+```
+提取结果：`supportStream = 1`
+
+### 5. 自定义请求头
+移除 `Authorization` 和 `Content-Type` 后的其他请求头：
+```json
+{
+  "X-Custom-Header": "value",
+  "X-Another-Header": "value2"
+}
+```
+保存为JSON字符串到 `customHeaders` 字段
+
+### 6. 自定义参数
+移除 `bot_id`、`workflow_id`、`stream`、`user_id`、`additional_messages` 后的其他参数：
+```json
+{
+  "custom_param": "value",
+  "another_param": "value2"
+}
+```
+保存为JSON字符串到 `customParams` 字段
+
+## 使用示例
+
+### 示例1：标准Coze配置
+
+**测试前配置**:
+```json
+{
+  "apiBaseUrl": "https://api.coze.cn",
+  "apiToken": "old_token",
+  "botId": "old_bot_id"
+}
+```
+
+**测试请求**:
+- URL: `https://api.coze.cn/v3/chat`
+- 请求头:
+  ```json
+  {
+    "Authorization": "Bearer new_token",
+    "Content-Type": "application/json"
+  }
+  ```
+- 请求体:
+  ```json
+  {
+    "bot_id": "new_bot_id",
+    "user_id": "test_user",
+    "stream": false,
+    "additional_messages": [...]
+  }
+  ```
+
+**保存后配置**:
+```json
+{
+  "apiBaseUrl": "https://api.coze.cn/v3/chat",
+  "apiToken": "new_token",
+  "botId": "new_bot_id",
+  "supportStream": 0,
+  "customHeaders": "",
+  "customParams": ""
+}
+```
+
+### 示例2：带自定义参数的配置
+
+**测试请求**:
+- URL: `https://api.coze.cn/v3/chat`
+- 请求头:
+  ```json
+  {
+    "Authorization": "Bearer token_123",
+    "Content-Type": "application/json",
+    "X-Custom-Header": "custom_value"
+  }
+  ```
+- 请求体:
+  ```json
+  {
+    "bot_id": "bot_456",
+    "workflow_id": "workflow_789",
+    "stream": true,
+    "user_id": "test_user",
+    "additional_messages": [...],
+    "custom_param": "param_value"
+  }
+  ```
+
+**保存后配置**:
+```json
+{
+  "apiBaseUrl": "https://api.coze.cn/v3/chat",
+  "apiToken": "token_123",
+  "botId": "bot_456",
+  "workflowId": "workflow_789",
+  "supportStream": 1,
+  "customHeaders": "{\"X-Custom-Header\":\"custom_value\"}",
+  "customParams": "{\"custom_param\":\"param_value\"}"
+}
+```
+
+## 注意事项
+
+1. **测试成功才能保存**: 只有当测试请求返回状态码200时，才会显示"保存测试配置"按钮
+2. **JSON格式验证**: 保存前会验证请求头和请求体是否为有效的JSON格式
+3. **自动刷新**: 保存成功后会自动刷新配置列表
+4. **字段覆盖**: 保存时只更新提供的字段，未提供的字段保持原值
+5. **Token安全**: API Token会完整保存到数据库，请确保数据库安全
+
+## 错误处理
+
+### 1. 请求头格式错误
+```
+错误信息：请求头格式错误，无法解析
+原因：请求头不是有效的JSON格式
+解决：检查请求头的JSON格式是否正确
+```
+
+### 2. 请求体格式错误
+```
+错误信息：请求体格式错误，无法解析
+原因：请求体不是有效的JSON格式
+解决：检查请求体的JSON格式是否正确
+```
+
+### 3. 配置不存在
+```
+错误信息：测试配置不存在
+原因：testConfig为空
+解决：重新打开测试对话框
+```
+
+### 4. 保存失败
+```
+错误信息：保存失败: [具体错误信息]
+原因：后端接口调用失败
+解决：检查网络连接和后端服务状态
+```
+
+## 开发说明
+
+### 前端文件
+- **页面**: `web-admin/src/views/aiconfig/AiConfigList.vue`
+- **API**: `web-admin/src/api/aiconfig.ts`
+- **类型**: `web-admin/src/types/aiconfig.ts`
+
+### 后端文件
+- **Controller**: `backend-single/src/main/java/com/emotion/controller/AiConfigController.java`
+- **Service**: `backend-single/src/main/java/com/emotion/service/AiConfigService.java`
+- **ServiceImpl**: `backend-single/src/main/java/com/emotion/service/impl/AiConfigServiceImpl.java`
+- **Request DTO**: `backend-single/src/main/java/com/emotion/dto/request/aiconfig/AiConfigTestUpdateRequest.java`
+
+### 数据库字段
+- `api_base_url`: API完整URL
+- `api_token`: API访问令牌
+- `bot_id`: Bot ID
+- `workflow_id`: Workflow ID
+- `custom_headers`: 自定义请求头（JSON字符串）
+- `custom_params`: 自定义参数（JSON字符串）
+- `support_stream`: 是否支持流式输出（0-不支持，1-支持）
+
+## 更新日志
+
+### 2025-12-22
+- 新增测试后保存配置功能
+- 新增 `AiConfigTestUpdateRequest` DTO
+- 新增 `updateFromTestRequest` 服务方法
+- 新增 `/aiConfig/updateFromTest` 接口
+- 前端新增"保存测试配置"按钮和处理逻辑
@@ -204,4 +204,14 @@ export function countByProvider(provider: string) {
    method: 'get',
    params: { provider }
  })
-}
+}
+
+
+// 测试后更新AI配置
+export function updateAiConfigFromTest(data: any) {
+  return request({
+    url: '/aiConfig/updateFromTest',
+    method: 'put',
+    data
+  })
+}
@@ -9,6 +9,9 @@ export interface AiConfig {
  apiBaseUrl: string
  apiToken: string
  apiVersion?: string
+  clientId?: string
+  clientSecret?: string
+  grantType?: string
  modelName?: string
  botId?: string
  workflowId?: string
@@ -66,6 +69,9 @@ export interface AiConfigCreateRequest {
  apiBaseUrl: string
  apiToken: string
  apiVersion?: string
+  clientId?: string
+  clientSecret?: string
+  grantType?: string
  modelName?: string
  botId?: string
  workflowId?: string
@@ -108,6 +114,9 @@ export interface AiConfigUpdateRequest {
  apiBaseUrl?: string
  apiToken?: string
  apiVersion?: string
+  clientId?: string
+  clientSecret?: string
+  grantType?: string
  modelName?: string
  botId?: string
  workflowId?: string
@@ -288,6 +288,34 @@
              </el-col>
            </el-row>
            
+            <el-row :gutter="20">
+              <el-col :span="8">
+                <el-form-item label="Client ID">
+                  <el-input v-model="formData.clientId" placeholder="OAuth客户端ID" />
+                </el-form-item>
+              </el-col>
+              <el-col :span="8">
+                <el-form-item label="Client Secret">
+                  <el-input 
+                    v-model="formData.clientSecret" 
+                    type="password" 
+                    show-password 
+                    placeholder="OAuth客户端密钥" 
+                  />
+                </el-form-item>
+              </el-col>
+              <el-col :span="8">
+                <el-form-item label="Grant Type">
+                  <el-select v-model="formData.grantType" placeholder="授权类型" clearable style="width: 100%">
+                    <el-option label="client_credentials" value="client_credentials" />
+                    <el-option label="authorization_code" value="authorization_code" />
+                    <el-option label="password" value="password" />
+                    <el-option label="refresh_token" value="refresh_token" />
+                  </el-select>
+                </el-form-item>
+              </el-col>
+            </el-row>
+            
            <el-row :gutter="20" v-if="formData.configType === 'coze'">
              <el-col :span="12">
                <el-form-item label="Bot ID">
@@ -514,6 +542,9 @@
        <el-descriptions-item label="环境">{{ getEnvironmentLabel(viewData.environment || '') }}</el-descriptions-item>
        <el-descriptions-item label="API完整URL">{{ viewData.apiBaseUrl }}</el-descriptions-item>
        <el-descriptions-item label="API令牌">{{ viewData.apiToken }}</el-descriptions-item>
+        <el-descriptions-item label="Client ID">{{ viewData.clientId || '-' }}</el-descriptions-item>
+        <el-descriptions-item label="Client Secret">{{ viewData.clientSecret ? '******' : '-' }}</el-descriptions-item>
+        <el-descriptions-item label="Grant Type">{{ viewData.grantType || '-' }}</el-descriptions-item>
        <el-descriptions-item label="模型名称">{{ viewData.modelName || '-' }}</el-descriptions-item>
        <el-descriptions-item label="优先级">{{ viewData.priority || 0 }}</el-descriptions-item>
        <el-descriptions-item label="状态">
@@ -634,6 +665,13 @@
                <el-form-item>
                  <el-button @click="handleFormatResponse">格式化响应</el-button>
                  <el-button @click="handleCopyResponse">复制响应</el-button>
+                  <el-button 
+                    v-if="testResponse.status === 200" 
+                    type="success" 
+                    @click="handleSaveTestConfig"
+                  >
+                    保存测试配置
+                  </el-button>
                </el-form-item>
              </el-form>
            </div>
@@ -659,7 +697,8 @@ import {
  unsetDefaultConfig,
  countEnabledConfigs,
  countDisabledConfigs,
-  countDefaultConfigs
+  countDefaultConfigs,
+  updateAiConfigFromTest
 } from '@/api/aiconfig'
 import type { AiConfig, AiConfigPageRequest } from '@/types/aiconfig'
 import { 
@@ -711,6 +750,9 @@ const formData = reactive({
  apiBaseUrl: '',
  apiToken: '',
  apiVersion: '',
+  clientId: '',
+  clientSecret: '',
+  grantType: '',
  modelName: '',
  botId: '',
  workflowId: '',
@@ -1045,6 +1087,9 @@ const handleDialogClose = () => {
    apiBaseUrl: '',
    apiToken: '',
    apiVersion: '',
+    clientId: '',
+    clientSecret: '',
+    grantType: '',
    modelName: '',
    botId: '',
    workflowId: '',
@@ -1411,6 +1456,83 @@ const handleCopyResponse = async () => {
  }
 }

+// 保存测试配置
+const handleSaveTestConfig = async () => {
+  if (!testConfig.value) {
+    ElMessage.error('测试配置不存在')
+    return
+  }
+
+  try {
+    // 解析请求头
+    let headers: any = {}
+    try {
+      headers = JSON.parse(testRequest.headers)
+    } catch (e) {
+      ElMessage.error('请求头格式错误，无法解析')
+      return
+    }
+
+    // 解析请求体
+    let body: any = {}
+    try {
+      body = JSON.parse(testRequest.body)
+    } catch (e) {
+      ElMessage.error('请求体格式错误，无法解析')
+      return
+    }
+
+    // 提取API Token（从Authorization头中）
+    let apiToken = testConfig.value.apiToken
+    if (headers.Authorization) {
+      // 移除 "Bearer " 前缀
+      apiToken = headers.Authorization.replace(/^Bearer\s+/i, '')
+      delete headers.Authorization // 从自定义头中移除，因为已经保存到apiToken字段
+    }
+
+    // 提取Bot ID和Workflow ID（从请求体中）
+    const botId = body.bot_id || testConfig.value.botId
+    const workflowId = body.workflow_id || testConfig.value.workflowId
+    const supportStream = body.stream !== undefined ? (body.stream ? 1 : 0) : testConfig.value.supportStream
+
+    // 移除已经提取的字段，剩余的作为自定义参数
+    const customParamsBody = { ...body }
+    delete customParamsBody.bot_id
+    delete customParamsBody.workflow_id
+    delete customParamsBody.stream
+    delete customParamsBody.user_id
+    delete customParamsBody.additional_messages
+
+    // 构建更新请求
+    const updateData = {
+      id: testConfig.value.id,
+      apiBaseUrl: testRequest.url,
+      apiToken: apiToken,
+      botId: botId,
+      workflowId: workflowId,
+      customHeaders: Object.keys(headers).length > 0 ? JSON.stringify(headers) : '',
+      customParams: Object.keys(customParamsBody).length > 0 ? JSON.stringify(customParamsBody) : '',
+      supportStream: supportStream
+    }
+
+    // 调用更新接口
+    const res = await updateAiConfigFromTest(updateData)
+    
+    if (res.code === 200) {
+      ElMessage.success('测试配置已保存')
+      // 更新testConfig
+      testConfig.value = res.data
+      // 刷新列表
+      await fetchData()
+    } else {
+      ElMessage.error(res.message || '保存失败')
+    }
+  } catch (error: any) {
+    console.error('保存测试配置失败:', error)
+    ElMessage.error('保存失败: ' + (error.message || error))
+  }
+}
+
 // 重置测试
 const handleResetTest = () => {
  if (testConfig.value) {