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基于全面审计报告的 P0-P2 修复工作： P0 (已完成): - intelligence 模块: 精确注释 dead_code 标注原因（Tauri runtime 注册） - compactor.rs: 实现 LLM 摘要生成（compact_with_llm） - pipeline_commands.rs: 替换 println! 为 tracing 宏 P1 (已完成): - 移除 8 个 gateway_* 向后兼容别名（OpenClaw 遗留） - 前端 tauri-gateway.ts 改为调用 zclaw_* 命令 - 清理 generation.rs 6 个重复的实例方法（-217 行） - A2A dead_code 注释更新 P2 (已完成): - Predictor/Lead HAND.toml 设置 enabled=false - Wasm/Native SkillMode 添加未实现说明 - browser/mod.rs 移除未使用的 re-export（消除 4 个警告） 文档更新: - feature-checklist.md 从 v0.4.0 更新到 v0.6.0 - CLAUDE.md Hands 状态更新 验证: cargo check 零警告, 42 测试通过, 净减 371 行代码
150 lines
3.1 KiB
TOML
150 lines
3.1 KiB
TOML
# Predictor Hand - 预测分析能力包
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#
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# ZCLAW 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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#
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# ⚠️ 注意: 此 Hand 尚未实现 Rust 后端，仅作为设计文档保留。
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# 启用状态设为 false，前端不会显示为可用能力。
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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（未实现）"
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author = "ZCLAW Team"
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# Hand 类型
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type = "data"
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# 未实现，禁用此 Hand
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enabled = false
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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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