绝尘
bd6a41fe6e
后端: - 工作流推进链(D-03):advance_task/状态机/闸门走 df-nodes Node trait,conditions 条件引擎扩展 - 想法评估闭环:启发式评分+对抗评估,df-ideas/scoring + df-storage/idea_eval_repo + idea 前端打通 - 全局事件数据总线:df-ai/context+context_helpers+augmentation 跨模块解耦 - AI planner/plan_hint/intent:aichat B 路线并行多轮基础 - patch_file 加固(TD-03/04):读改写整体锁防 lost update,expected_hash 合约闭环 - 压缩超时兜底(F-15 卡死根治) - F-09 多会话并发:LlmConcurrency per-conv + streamingGuard 前端守护 + verify 脚本 - 知识注入 DRY/skills/audit 扩展 清理: - aichat 技术债(误报 allow/死导入/过时注释 30 项) - URGENT.md 删除(11 项加急全解决/迁 todo) - 文档整理(todo/待决策/待审查/ARCHITECTURE/INDEX + 总线/技术债审查新文档)
323 lines
13 KiB
Rust
323 lines
13 KiB
Rust
//! 数据模型定义 — 与数据库表对应的 Rust 结构体
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use df_ai_core::model::{deserialize_model_configs, ModelConfig};
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use serde::{Deserialize, Serialize};
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// ============================================================
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// 想法相关模型
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// ============================================================
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/// 想法记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct IdeaRecord {
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pub id: String,
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pub title: String,
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pub description: String,
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pub status: String,
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pub priority: i32,
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pub score: Option<f64>,
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pub tags: Option<String>, // JSON 数组
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pub source: Option<String>,
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pub promoted_to: Option<String>, // 晋升后的 project_id
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pub ai_analysis: Option<String>, // AI 分析结果 JSON
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pub scores: Option<String>, // 多维评分 JSON (feasibility/impact/urgency/overall)
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pub related_ids: Option<String>, // 关联灵感 id JSON 数组(同 tags 模式,为关联关系 UI 打底)
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pub created_at: String,
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pub updated_at: String,
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}
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/// 灵感评估历史记录(追加型审计表 idea_evaluations,V22)
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///
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/// 每次灵感 AI 评估产生一行快照,version 单调递增。
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/// 替代覆写 ideas.ai_analysis / ideas.scores:保留评估历史可追溯。
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/// ai_analysis/scores 为 JSON 字符串,score 为综合评分,evaluated_by 标评估发起者。
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct IdeaEvaluationRecord {
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pub id: String,
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pub idea_id: String,
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pub version: i64,
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pub ai_analysis: Option<String>,
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pub scores: Option<String>,
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pub score: Option<f64>,
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pub evaluated_by: Option<String>,
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pub evaluated_at: String,
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}
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// ============================================================
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// 项目相关模型
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// ============================================================
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/// 项目记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ProjectRecord {
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pub id: String,
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pub name: String,
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pub description: String,
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pub status: String,
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pub idea_id: Option<String>,
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/// 绑定的本地代码目录(绝对路径,可空=未绑定,第二步导入历史项目时复用)
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pub path: Option<String>,
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/// 技术栈 JSON 数组字符串(如 ["rust","vue","tauri"],由探测填充,可空)
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pub stack: Option<String>,
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pub created_at: String,
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pub updated_at: String,
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}
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// ============================================================
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// 任务相关模型
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// ============================================================
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/// 任务记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct TaskRecord {
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pub id: String,
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pub project_id: String,
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pub title: String,
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pub description: String,
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pub status: String,
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pub priority: i32,
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pub branch_name: Option<String>,
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pub assignee: Option<String>,
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pub workflow_def_id: Option<String>, // 关联的工作流定义 ID
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pub base_branch: Option<String>, // 基础分支
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/// review 退回累计轮数(in_review→in_progress / testing→in_review 时 +1,
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/// 由 advance_task 原子写入,见 df-nodes::task_advance_node)。
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/// #[serde(default)] 兼容旧前端无该字段的 JSON(老任务记录默认 0)。
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#[serde(default)]
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pub review_rounds: i32,
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/// 任务产出 JSON 字符串(AiNode 自审闭环,决策 a:task 中心,产出跟 task 走)。
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///
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/// 三方读写约定:ai_execute 写产出 / ai_self_review 读产出做自审 / human_review 展示产出对象。
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/// 经通用 update_field 写白名单(非 status 那种状态机收口字段),TEXT NULL 向后兼容。
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/// #[serde(skip_serializing_if)] 无产出不序列化(省前端字段空值),#[serde(default)] 兼容旧 JSON。
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#[serde(skip_serializing_if = "Option::is_none")]
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#[serde(default)]
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pub output_json: Option<String>,
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/// 关联灵感 ID(F-260619-01,1对1 单向,任务→灵感)。
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/// 复用 projects.idea_id 模式(REFERENCES ideas(id) 外键),可空(任务可不关联灵感)。
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/// 老任务无 idea_id → None。#[serde(default)] 兼容旧前端 JSON(无该字段时为 None)。
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#[serde(default)]
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pub idea_id: Option<String>,
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pub created_at: String,
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pub updated_at: String,
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}
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/// 分支记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct BranchRecord {
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pub id: String,
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pub project_id: String,
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pub task_id: Option<String>,
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pub name: String,
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pub base: String,
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pub status: String,
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pub created_at: String,
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pub updated_at: String,
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pub merged_at: Option<String>,
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}
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/// 发布记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ReleaseRecord {
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pub id: String,
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pub project_id: String,
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pub version: String,
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pub status: String,
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pub task_ids: String, // JSON 数组
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pub changelog: Option<String>,
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pub created_at: String,
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pub released_at: Option<String>,
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}
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// ============================================================
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// 工作流相关模型
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// ============================================================
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/// 工作流执行记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct WorkflowRecord {
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pub id: String,
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pub name: String,
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pub dag_json: String, // DAG 的 JSON 序列化
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pub status: String,
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pub triggered_by: Option<String>,
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pub project_id: Option<String>, // 关联项目 ID
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pub task_id: Option<String>, // 关联任务 ID
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pub created_at: String,
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pub completed_at: Option<String>,
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}
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/// 节点执行记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct NodeExecutionRecord {
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pub id: String,
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pub workflow_id: String,
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pub node_id: String,
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pub node_type: String,
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pub status: String,
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pub input_json: Option<String>,
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pub output_json: Option<String>,
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pub error_message: Option<String>,
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pub started_at: Option<String>,
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pub completed_at: Option<String>,
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}
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// ============================================================
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// AI 相关模型 (V3)
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// ============================================================
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/// AI 提供商配置记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct AiProviderRecord {
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pub id: String,
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pub name: String,
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pub provider_type: String,
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pub api_key: String,
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pub base_url: String,
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pub default_model: String,
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pub models: Option<String>, // JSON array of model names
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/// 模型能力配置数组(F-01 阶段1,4 维度 + 路由控制)。
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/// DB TEXT 列存 JSON 字符串,from_row 经 deserialize_model_configs 解析。
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/// 向后兼容:老库 NULL/空/老字符串数组 → 空 Vec 或转默认 ModelConfig。default_model 保留过渡。
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#[serde(default, deserialize_with = "deserialize_model_configs")]
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pub model_configs: Vec<ModelConfig>,
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pub is_default: bool,
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pub config: Option<String>, // JSON extra config
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pub created_at: String,
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pub updated_at: String,
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/// provider 是否进入负载均衡池(F-260614-04)。false = 仅作为配置存在,不参与主链路由/选池。
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/// 老库迁移默认 1(单 provider 路径零变化)。
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#[serde(default = "default_enabled")]
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pub enabled: bool,
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/// provider 在负载均衡池中的选择权重(0-100,F-260614-04)。高权重优先被选为主;
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/// 同权重时退化近似轮询。老库迁移默认 50。
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#[serde(default = "default_weight")]
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pub weight: u32,
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}
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/// AiProviderRecord.enabled 的 serde 默认(true)。老库/缺字段 JSON → enabled。
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fn default_enabled() -> bool {
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true
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}
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/// AiProviderRecord.weight 的 serde 默认(50)。老库/缺字段 JSON → 50。
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fn default_weight() -> u32 {
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50
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}
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/// AI 对话记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct AiConversationRecord {
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pub id: String,
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pub title: Option<String>,
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pub messages: String, // JSON array of ChatMessage
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pub provider_id: Option<String>,
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pub model: Option<String>,
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pub models: Option<String>, // 用过的所有 model(JSON 数组字符串,去重)
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pub archived: bool, // 是否归档(侧栏折叠展示)
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pub pinned: bool, // 是否置顶(排序置前;UX-17)
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pub prompt_tokens: Option<i64>, // 输入 token 累计(流式 usage 落库)
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pub completion_tokens: Option<i64>, // 输出 token 累计(流式 usage 落库)
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pub created_at: String,
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pub updated_at: String,
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}
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/// AI 工具执行审计记录
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct AiToolExecutionRecord {
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pub id: String,
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pub conversation_id: Option<String>,
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/// 消息级溯源:工具调用所属的 ChatMessage.id(F-260619-04)。
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/// NULL = 老库行 / 消息级溯源未启用期的记录 / 无法关联的调用。
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/// 升级后,audit 写入从 ContextManager 取当前 assistant 消息 id 填入(P1 接入,P0 只建列)。
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#[serde(default, skip_serializing_if = "Option::is_none")]
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pub message_id: Option<String>,
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pub tool_call_id: String,
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pub tool_name: String,
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pub arguments: String,
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pub result: Option<String>,
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pub status: String, // pending/approved/rejected/executing/completed/failed
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pub risk_level: String, // low/medium/high
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pub requested_at: String,
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pub executed_at: Option<String>,
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pub decided_by: Option<String>, // human/auto
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}
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/// 消息记录(ai_messages 表,F-260619-03 消息拆分存储)。
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///
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/// 每条 ChatMessage 一行,替代 `ai_conversations.messages` 的整对话 JSON 列存。
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/// 主键 `id` = ChatMessage.id(构造时 ULID 风格生成),(conversation_id, seq) UNIQUE
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/// 保证对话内序号唯一。本结构仅承载持久化映射,P0 阶段 ContextManager 仍走旧 JSON 列,
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/// 切读策略待用户决策(P2)。
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct AiMessageRecord {
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/// 消息全局唯一 ID(= ChatMessage.id),主键
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pub id: String,
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/// 关联对话 ID
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pub conversation_id: String,
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/// 对话内序号(排序用,从 0 起)
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pub seq: i64,
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/// 消息角色:system/user/assistant/tool
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pub role: String,
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/// 文本内容(parts 的 Text 片与 content 一致)
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pub content: String,
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/// 多模态 parts JSON(可空)
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pub parts: Option<String>,
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/// 工具调用 ID(role=Tool 时必填)
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pub tool_call_id: Option<String>,
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/// AI 发起的工具调用 JSON(可空)
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pub tool_calls: Option<String>,
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/// 生成该消息的 model(仅 assistant)
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pub model: Option<String>,
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/// 消息状态:active/compressed/archived_segment/truncated(默认 active)
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pub status: String,
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/// DeepSeek thinking 推理内容(可空)
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pub reasoning_content: Option<String>,
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/// 消息创建时间(Unix 毫秒,可空)
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pub timestamp: Option<i64>,
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/// 落库时间字符串(迁移期 fallback 到对话 created_at)
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pub created_at: String,
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}
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// ============================================================
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// 知识库模型 (V7)
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// ============================================================
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/// 知识条目记录(经验沉淀基本单元,共享记忆层)
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct KnowledgeRecord {
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pub id: String,
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pub kind: String, // KnowledgeKind snake_case(7 种)
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pub title: String,
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pub content: String,
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pub tags: Option<String>, // JSON 数组字符串
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pub status: String, // candidate|pending_review|published|archived
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pub confidence: Option<String>, // high|medium|low(AI 提炼自评,可空)
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pub reuse_count: i32, // 唯一客观排序信号
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pub verified: bool, // 发布审核时一次性人工标
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pub source_project: Option<String>, // 来源项目(仅溯源不过滤)
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pub source_ref: Option<String>, // 来源实体引用(如 conv:{id})
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pub reasoning: Option<String>, // AI 提炼判断依据("为何值得沉淀"),手动录入为 None
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/// 嵌入生成状态(V23):None/pending=未生成,done=成功,failed=失败可重试。
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///
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/// P1 修复(嵌入失败无标记):spawn_embedding_for_knowledge 此前 fire-and-forget,
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/// provider 临时不可用 → 仅 warn,该条永久无向量索引无人感知。
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/// 现写入 done/failed,failed 可由 knowledge_retry_embedding 触发补偿重试。
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/// `#[serde(default)]` 兼容老前端/老 JSON(未带该字段反序列化为 None)。
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#[serde(default)]
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pub embedding_status: Option<String>,
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pub created_at: String,
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pub updated_at: String,
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}
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/// 知识生命线事件记录(追加型审计:产生/审核/引用/归档)
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct KnowledgeEventRecord {
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pub id: String,
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pub knowledge_id: String,
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pub event_type: String, // created | extracted | status_changed | referenced | archived
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pub source_ref: Option<String>, // 触发来源: conv:{id} / manual / system
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pub context_json: Option<String>, // JSON: 因 event_type 而异
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pub timestamp: String,
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}
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