添加AOL路由和UI/UX增强组件
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docs/aol-examples.md
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docs/aol-examples.md
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# AOL (Agent Orchestration Language) 使用示例
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## 基础示例
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### 1. 简单顺序工作流
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```toml
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[workflow]
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name = "simple-pipeline"
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version = "1.0.0"
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description = "简单的研究流程"
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[workflow.input]
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topic = { type = "string", required = true, description = "研究主题" }
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[[workflow.steps.sequential]]
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id = "research"
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agent = { kind = "by_name", name = "researcher" }
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task = "搜索关于 {{input.topic}} 的最新信息"
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output = "research_result"
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[[workflow.steps.sequential]]
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id = "summarize"
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agent = { kind = "by_name", name = "writer" }
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task = "总结以下研究结果: {{research_result}}"
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output = "summary"
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```
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### 2. 并行执行工作流
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```toml
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[workflow]
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name = "parallel-research"
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version = "1.0.0"
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[workflow.input]
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topic = { type = "string", required = true }
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[[workflow.steps.parallel]]
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id = "parallel-search"
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collect = "merge"
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output = "all_results"
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max_concurrency = 3
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[[workflow.steps.parallel.steps]]
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id = "academic"
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agent = { kind = "by_name", name = "academic-researcher" }
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task = "搜索 {{input.topic}} 的学术论文"
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output = "papers"
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[[workflow.steps.parallel.steps]]
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id = "news"
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agent = { kind = "by_name", name = "news-researcher" }
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task = "搜索 {{input.topic}} 的新闻报道"
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output = "news"
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[[workflow.steps.parallel.steps]]
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id = "market"
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agent = { kind = "by_role", role = "analyst" }
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task = "分析 {{input.topic}} 的市场趋势"
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output = "market_data"
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[[workflow.steps.collect]]
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id = "combine"
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sources = ["papers", "news", "market_data"]
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strategy = "merge"
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output = "combined_research"
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[[workflow.steps.sequential]]
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id = "synthesize"
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agent = { kind = "by_name", name = "writer" }
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task = "综合以下研究结果生成报告: {{combined_research}}"
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output = "final_report"
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```
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### 3. 条件分支工作流
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```toml
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[workflow]
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name = "conditional-workflow"
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version = "1.0.0"
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[workflow.input]
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complexity = { type = "string", required = true, enum_values = ["quick", "standard", "exhaustive"] }
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topic = { type = "string", required = true }
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[[workflow.steps.sequential]]
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id = "initial-research"
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agent = { kind = "by_name", name = "researcher" }
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task = "初步研究: {{input.topic}}"
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output = "initial_result"
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[[workflow.steps.conditional]]
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id = "depth-check"
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[[workflow.steps.conditional.branches]]
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id = "exhaustive-branch"
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condition = "{{input.complexity}} == exhaustive"
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[[workflow.steps.conditional.branches.steps.sequential]]
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id = "deep-research"
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agent = { kind = "by_name", name = "expert-researcher" }
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task = "深入研究: {{initial_result}}"
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output = "deep_result"
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[[workflow.steps.conditional.branches.steps.sequential]]
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id = "peer-review"
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agent = { kind = "by_role", role = "reviewer" }
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task = "同行评审: {{deep_result}}"
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output = "reviewed_result"
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[[workflow.steps.conditional.branches]]
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id = "quick-branch"
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condition = "{{input.complexity}} == quick"
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[[workflow.steps.conditional.branches.steps.sequential]]
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id = "quick-summary"
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agent = { kind = "by_name", name = "writer" }
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task = "快速总结: {{initial_result}}"
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output = "quick_summary"
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[[workflow.steps.conditional.default]]
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[[workflow.steps.conditional.default.sequential]]
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id = "standard-summary"
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agent = { kind = "by_name", name = "writer" }
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task = "标准总结: {{initial_result}}"
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output = "standard_summary"
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```
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### 4. 循环处理工作流
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```toml
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[workflow]
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name = "batch-processor"
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version = "1.0.0"
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[workflow.input]
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items = { type = "array", required = true, description = "要处理的项目列表" }
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[[workflow.steps.loop]]
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id = "process-items"
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item_var = "item"
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index_var = "idx"
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collection = "{{input.items}}"
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collect = "merge"
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output = "processed_items"
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[[workflow.steps.loop.steps.sequential]]
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id = "process-single"
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agent = { kind = "by_name", name = "processor" }
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task = "处理第 {{loop.idx}} 个项目: {{loop.item}}"
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output = "item_result"
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```
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### 5. 错误处理与回退
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```toml
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[workflow]
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name = "robust-workflow"
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version = "1.0.0"
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[workflow.input]
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query = { type = "string", required = true }
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[workflow.config]
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default_error_mode = "retry"
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max_retries = 3
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[[workflow.steps.fallback]]
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id = "search-with-fallback"
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output = "search_result"
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[workflow.steps.fallback.primary.sequential]
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id = "primary-search"
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agent = { kind = "by_name", name = "primary-searcher" }
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task = "搜索: {{input.query}}"
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error_mode = "skip"
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timeout_secs = 30
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[[workflow.steps.fallback.fallbacks.sequential]]
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id = "fallback-search"
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agent = { kind = "by_name", name = "backup-searcher" }
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task = "备用搜索: {{input.query}}"
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[[workflow.steps.fallback.fallbacks.sequential]]
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id = "cached-search"
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agent = { kind = "by_name", name = "cache-agent" }
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task = "从缓存查找: {{input.query}}"
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```
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### 6. 完整配置示例
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```toml
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[workflow]
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name = "enterprise-research-pipeline"
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version = "2.0.0"
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description = "企业级研究流水线"
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author = "OpenFang Team"
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tags = ["research", "analysis", "enterprise"]
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[workflow.input]
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topic = { type = "string", required = true, description = "研究主题" }
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depth = { type = "string", required = false, default = "standard", enum_values = ["quick", "standard", "exhaustive"] }
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max_sources = { type = "integer", required = false, default = 10 }
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[workflow.config]
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timeout_secs = 1800 # 30分钟总超时
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max_retries = 3 # 最大重试次数
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default_error_mode = "fail"
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max_concurrency = 5 # 最大并行数
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persist_state = true # 持久化状态以支持恢复
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# ... 步骤定义 ...
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```
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## API 使用
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### 编译工作流
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```bash
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curl -X POST http://localhost:4200/api/aol/compile \
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-H "Content-Type: application/json" \
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-d '{
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"toml": "[workflow]\nname = \"test\"\nversion = \"1.0.0\"\n\n[[workflow.steps.sequential]]\nid = \"step1\"\nagent = { kind = \"by_name\", name = \"assistant\" }\ntask = \"Hello\""
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}'
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```
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响应:
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```json
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{
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"id": "uuid",
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"name": "test",
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"version": "1.0.0",
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"step_count": 1,
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"inputs": [],
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"outputs": [],
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"validation_errors": []
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}
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```
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### 执行工作流
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```bash
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curl -X POST http://localhost:4200/api/aol/execute \
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-H "Content-Type: application/json" \
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-d '{
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"workflow_id": "uuid",
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"inputs": {
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"topic": "人工智能"
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}
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}'
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```
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响应:
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```json
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{
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"execution_id": "exec-uuid",
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"workflow_id": "uuid",
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"status": "Completed",
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"step_results": [
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{
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"step_id": "step1",
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"success": true,
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"output": "处理结果...",
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"error": null,
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"duration_ms": 1234,
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"retries": 0
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}
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],
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"outputs": {
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"result": "最终输出..."
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},
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"error": null,
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"duration_ms": 1500
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}
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```
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### 查询执行状态
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```bash
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curl http://localhost:4200/api/aol/executions/exec-uuid
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```
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## Agent 引用方式
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| 类型 | 语法 | 说明 |
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|------|------|------|
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| 按ID | `{ kind = "by_id", id = "uuid" }` | 精确引用特定 Agent |
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| 按名称 | `{ kind = "by_name", name = "assistant" }` | 按名称查找 Agent |
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| 按角色 | `{ kind = "by_role", role = "researcher" }` | 按角色匹配 Agent |
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| 带能力 | `{ kind = "by_role", role = "worker", capability = "web_search" }` | 按角色+能力匹配 |
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## 收集策略
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| 策略 | 说明 |
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|------|------|
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| `merge` | 合并所有结果为数组 (默认) |
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| `first` | 只取第一个完成的结果 |
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| `last` | 只取最后一个完成的结果 |
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| `aggregate` | 聚合结果 (字符串连接/数值求和) |
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## 错误处理模式
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| 模式 | 说明 |
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|------|------|
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| `fail` | 失败时终止工作流 (默认) |
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| `skip` | 失败时跳过此步骤 |
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| `retry` | 失败时重试 (最多 max_retries 次) |
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## 模板变量
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| 变量 | 说明 |
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|------|------|
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| `{{input.xxx}}` | 输入参数 |
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| `{{output.step_name}}` | 步骤输出 |
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| `{{loop.item}}` | 循环当前项 |
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| `{{loop.idx}}` | 循环当前索引 |
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