5599c1a4db
Phase 2 P1 Tasks Completed: API Layer (gateway-client.ts, gatewayStore.ts): - Add Channels CRUD: getChannel, createChannel, updateChannel, deleteChannel - Add Triggers CRUD: getTrigger, createTrigger, updateTrigger, deleteTrigger - Add Skills CRUD: getSkill, createSkill, updateSkill, deleteSkill - Add Scheduled Tasks API: createScheduledTask, deleteScheduledTask, toggleScheduledTask - Add loadModels action for dynamic model list UI Components: - ModelsAPI.tsx: Dynamic model loading from API with loading/error states - SchedulerPanel.tsx: Full CreateJobModal with cron/interval/once scheduling - SecurityStatus.tsx: Loading states, error handling, retry functionality - WorkflowEditor.tsx: New workflow creation/editing modal (new file) - WorkflowHistory.tsx: Workflow execution history viewer (new file) - WorkflowList.tsx: Integrated editor and history access Configuration: - Add 4 Hands TOML configs: clip, collector, predictor, twitter Documentation (SYSTEM_ANALYSIS.md): - Update API coverage: 65% → 89% (53/62 endpoints) - Update UI completion: 85% → 92% - Mark Phase 2 P1 tasks as completed - Update technical debt cleanup status Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
144 lines
2.8 KiB
TOML
144 lines
2.8 KiB
TOML
# Predictor Hand - 预测分析能力包
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#
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# OpenFang Hand 配置
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# 这个 Hand 提供预测分析、趋势预测和数据建模能力
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[hand]
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name = "predictor"
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version = "1.0.0"
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description = "预测分析能力包 - 执行回归、分类和时间序列预测"
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author = "ZCLAW Team"
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# Hand 类型
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type = "data"
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# 是否需要人工审批才能执行
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requires_approval = false
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# 默认超时时间（秒）
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timeout = 600
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# 最大并发执行数
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max_concurrent = 2
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# 能力标签
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tags = ["prediction", "analytics", "forecasting", "ml", "statistics"]
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[hand.config]
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# 模型配置
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default_model = "auto" # auto, regression, classification, timeseries
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model_storage = "/tmp/zclaw/predictor/models"
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# 训练配置
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train_test_split = 0.8
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cross_validation = 5
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# 输出配置
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output_format = "report" # report, json, chart
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include_visualization = true
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confidence_level = 0.95
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# 特征工程
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auto_feature_selection = true
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max_features = 50
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[hand.triggers]
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# 触发器配置
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manual = true
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schedule = true
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webhook = false
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# 事件触发器
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[[hand.triggers.events]]
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type = "data.updated"
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pattern = ".*(forecast|predict|analyze).*"
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priority = 7
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[[hand.triggers.events]]
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type = "chat.intent"
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pattern = "预测|分析|趋势|forecast|predict|analyze|trend"
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priority = 5
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[hand.permissions]
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# 权限要求
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requires = [
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"file.read",
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"file.write",
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"compute.ml"
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]
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# RBAC 角色要求
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roles = ["operator.read", "operator.write"]
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# 速率限制
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[hand.rate_limit]
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max_requests = 20
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window_seconds = 3600 # 1 hour
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# 审计配置
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[hand.audit]
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log_inputs = true
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log_outputs = true
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retention_days = 30
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# 参数定义
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[[hand.parameters]]
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name = "dataSource"
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label = "数据源"
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type = "text"
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required = true
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description = "数据文件路径或 URL"
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[[hand.parameters]]
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name = "model"
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label = "模型类型"
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type = "select"
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required = true
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options = ["regression", "classification", "timeseries"]
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description = "预测模型的类型"
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[[hand.parameters]]
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name = "targetColumn"
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label = "目标列"
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type = "text"
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required = true
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description = "要预测的目标变量列名"
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[[hand.parameters]]
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name = "featureColumns"
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label = "特征列"
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type = "text"
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required = false
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description = "用于预测的特征列（逗号分隔，留空自动选择）"
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# 工作流步骤
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[[hand.workflow]]
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id = "load"
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name = "加载数据"
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description = "读取和验证输入数据"
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[[hand.workflow]]
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id = "preprocess"
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name = "数据预处理"
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description = "清洗数据、处理缺失值、特征工程"
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[[hand.workflow]]
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id = "train"
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name = "训练模型"
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description = "训练预测模型并进行交叉验证"
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[[hand.workflow]]
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id = "evaluate"
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name = "评估模型"
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description = "计算模型性能指标"
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[[hand.workflow]]
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id = "predict"
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name = "执行预测"
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description = "使用训练好的模型进行预测"
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[[hand.workflow]]
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id = "report"
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name = "生成报告"
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description = "生成包含可视化的分析报告"
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