//! AI 对话域 Repo:AiProviderRepo / AiConversationRepo / AiToolExecutionRepo use std::sync::Arc; use rusqlite::{params, Connection, OptionalExtension, Row}; use tokio::sync::Mutex; use df_types::error::Result; use crate::db::Database; use crate::models::{AiConversationRecord, AiProviderRecord, AiToolExecutionRecord}; use super::impl_repo; use super::{now_millis_str, storage_err, validate_column_name}; // ============================================================ // from_row 辅助函数 // ============================================================ fn ai_provider_from_row(row: &Row<'_>) -> std::result::Result { // model_configs:DB TEXT 列存 JSON 字符串。读 Option 兼容老库 NULL, // 再经 deserialize_model_configs 解析(老字符串数组/新对象数组/空 → Vec)。 // 解析失败不致命:降级为空 Vec(防单行坏数据拖垮 list_all)。 let model_configs: Vec = { let raw: Option = row.get("model_configs").ok(); match raw { None => Vec::new(), Some(s) => serde_json::from_str::(&format!( r#"{{"v":{}}}"#, if s.trim().is_empty() { "null".to_string() } else if s.trim_start().starts_with('[') || s.trim_start().starts_with('{') { s } else { // 非 JSON 字面文本(理论不会出现)→ 包装为 JSON 字符串让 deserialize 兜底 serde_json::to_string(&s).unwrap_or_else(|_| "null".into()) } )) .map(|w| w.v) .unwrap_or_default(), } }; // id 先读:① 结构体字段必填列(缺失直接 ? 报错);② enabled/weight 降级时日志带行标识, // 坏数据可定位到具体行而非只剩全局报警。 let id: String = row.get("id")?; // enabled/weight 列老库经 v19 迁移补建,DEFAULT 1 / DEFAULT 50。get 失败(列缺失 // 或 NULL 坏数据)降级默认值保功能(防单行坏数据拖垮 list_all),但 warn 留痕: // 正常新库列必然存在,此分支触发即迁移未跑/表结构被外力改动,坏数据可观测。 // from_row 按 i32 取列值兼容(SQLite 无真 BOOLEAN),0→false/非0→true。 let enabled = match row.get::<_, i32>("enabled") { Ok(v) => v != 0, Err(e) => { tracing::warn!("ai_providers[{id}] enabled 列读取失败({e}),降级默认 enabled=true"); true } }; // weight 读侧 clamp [0,100]:与 insert/update_full 落库的 `.min(100)` 对齐, // 防老库(clamp 落地前写入的)或外部直改 DB 产生的越界值污染路由权重语义。 let weight = match row.get::<_, i32>("weight") { Ok(v) => v.clamp(0, 100) as u32, Err(e) => { tracing::warn!("ai_providers[{id}] weight 列读取失败({e}),降级默认 weight=50"); 50 } }; Ok(AiProviderRecord { id, name: row.get("name")?, provider_type: row.get("provider_type")?, api_key: row.get("api_key")?, base_url: row.get("base_url")?, default_model: row.get("default_model")?, models: row.get("models")?, model_configs, is_default: row.get::<_, i32>("is_default")? != 0, config: row.get("config")?, created_at: row.get("created_at")?, updated_at: row.get("updated_at")?, enabled, weight, }) } /// from_row 内部辅助:复用 deserialize_model_configs 解析 DB TEXT 列 JSON。 /// 包一层 { "v": <原始值> } 把任意 JSON 值送进 deserialize_model_configs。 #[derive(serde::Deserialize)] struct ModelConfigsWrap { #[serde(default, deserialize_with = "df_ai_core::model::deserialize_model_configs")] v: Vec, } fn ai_conversation_from_row(row: &Row<'_>) -> std::result::Result { Ok(AiConversationRecord { id: row.get("id")?, title: row.get("title")?, messages: row.get("messages")?, provider_id: row.get("provider_id")?, model: row.get("model")?, models: row.get("models")?, archived: row.get::<_, i32>("archived")? != 0, pinned: row.get::<_, i32>("pinned")? != 0, prompt_tokens: row.get("prompt_tokens")?, completion_tokens: row.get("completion_tokens")?, pinned_goals: row.get("pinned_goals")?, pending_approvals: row.get("pending_approvals")?, created_at: row.get("created_at")?, updated_at: row.get("updated_at")?, // origin 列老库经 v44 迁移补建。unwrap_or(None) 兜底(同 message_id v21 模式): // 迁移未跑/极端情况防御,NULL=主会话。 origin: row.get("origin").unwrap_or(None), // boundary_json 列老库经 v45 迁移补建。unwrap_or(None) 兜底(NULL=未声明任务边界)。 boundary_json: row.get("boundary_json").unwrap_or(None), // loop_state 列老库经 v49 迁移补建。unwrap_or(None) 兜底(NULL=非任务会话)。 loop_state: row.get("loop_state").unwrap_or(None), // status 列老库经 v50 迁移补建(NOT NULL DEFAULT 'active')。兜底迁移未跑/极端缺列时按 active。 status: row.get("status").unwrap_or_else(|_| "active".to_string()), }) } fn ai_tool_execution_from_row(row: &Row<'_>) -> std::result::Result { Ok(AiToolExecutionRecord { id: row.get("id")?, conversation_id: row.get("conversation_id")?, // message_id 列老库经 v21 迁移补建。unwrap_or(None) 兜底: // 新库空表直接有列;老库行 ALTER 后 NULL;极端情况(迁移未跑/手工删列)防御。 message_id: row.get("message_id").unwrap_or(None), // row.get:: 后 From → ToolCallId(newtype 不直接 impl rusqlite::FromSql, // 避免 df-types 反向依赖 rusqlite;Deref 不自动给 ToSql) tool_call_id: row.get::<_, String>("tool_call_id")?.into(), tool_name: row.get("tool_name")?, arguments: row.get("arguments")?, result: row.get("result")?, status: row.get("status")?, risk_level: row.get("risk_level")?, requested_at: row.get("requested_at")?, executed_at: row.get("executed_at")?, decided_by: row.get("decided_by")?, // duration_ms 列老库经 v50 迁移补建。unwrap_or(None) 兜底(NULL=老数据/未测路径)。 duration_ms: row.get("duration_ms").unwrap_or(None), }) } // ============================================================ // Repo 实现 // ============================================================ impl_repo!( /// AI 提供商配置表 CRUD AiProviderRepo, AiProviderRecord, "ai_providers", from_row => |row| ai_provider_from_row(row), insert => |conn, rec| { let is_default = if rec.is_default { 1i32 } else { 0i32 }; // model_configs:Vec → JSON 字符串落 TEXT 列 let model_configs_json = serde_json::to_string(&rec.model_configs).unwrap_or_else(|_| "[]".into()); // enabled/weight 落库(SQLite 无 BOOLEAN,i32 承载)。 let enabled_i = if rec.enabled { 1i32 } else { 0i32 }; let weight_i = rec.weight.min(100) as i32; conn.execute( "INSERT OR REPLACE INTO ai_providers (id, name, provider_type, api_key, base_url, default_model, models, model_configs, is_default, config, created_at, updated_at, enabled, weight) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13, ?14)", params![ rec.id, rec.name, rec.provider_type, rec.api_key, rec.base_url, rec.default_model, rec.models, model_configs_json, is_default, rec.config, rec.created_at, rec.updated_at, enabled_i, weight_i ], ) }, update => |conn, rec| { let is_default = if rec.is_default { 1i32 } else { 0i32 }; let model_configs_json = serde_json::to_string(&rec.model_configs).unwrap_or_else(|_| "[]".into()); let enabled_i = if rec.enabled { 1i32 } else { 0i32 }; let weight_i = rec.weight.min(100) as i32; conn.execute( "UPDATE ai_providers SET name = ?1, provider_type = ?2, api_key = ?3, base_url = ?4, default_model = ?5, models = ?6, model_configs = ?7, is_default = ?8, config = ?9, updated_at = ?10, enabled = ?11, weight = ?12 WHERE id = ?13", params![ rec.name, rec.provider_type, rec.api_key, rec.base_url, rec.default_model, rec.models, model_configs_json, is_default, rec.config, rec.updated_at, enabled_i, weight_i, rec.id ], ) } ); impl_repo!( /// AI 对话历史表 CRUD AiConversationRepo, AiConversationRecord, "ai_conversations", from_row => |row| ai_conversation_from_row(row), insert => |conn, rec| { conn.execute( "INSERT INTO ai_conversations (id, title, messages, provider_id, model, models, archived, pinned, prompt_tokens, completion_tokens, pinned_goals, pending_approvals, created_at, updated_at, origin, boundary_json, loop_state, status) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13, ?14, ?15, ?16, ?17, ?18)", params![ rec.id, rec.title, rec.messages, rec.provider_id, rec.model, rec.models, rec.archived, if rec.pinned { 1i32 } else { 0i32 }, rec.prompt_tokens, rec.completion_tokens, rec.pinned_goals, rec.pending_approvals, rec.created_at, rec.updated_at, rec.origin, rec.boundary_json, rec.loop_state, rec.status ], ) }, update => |conn, rec| { // loop_state/status 有意不在 SET 列(V49/V50 生命周期标记独立更新,对齐 boundary 早期模式): // update_full 的调用方(save_conversation 等)从 get_by_id 读旧记录再改元数据写回, // 读改写窗口内 loop 生命周期/终局态可变更——若 SET 含二者,旧值会覆盖新值(lost-update)。 // 生命周期只经 set_loop_state / set_status 单点写。 conn.execute( "UPDATE ai_conversations SET title = ?1, messages = ?2, provider_id = ?3, model = ?4, models = ?5, archived = ?6, pinned = ?7, prompt_tokens = ?8, completion_tokens = ?9, pinned_goals = ?10, pending_approvals = ?11, updated_at = ?12, boundary_json = ?13 WHERE id = ?14", params![ rec.title, rec.messages, rec.provider_id, rec.model, rec.models, rec.archived, if rec.pinned { 1i32 } else { 0i32 }, rec.prompt_tokens, rec.completion_tokens, rec.pinned_goals, rec.pending_approvals, rec.updated_at, rec.boundary_json, rec.id ], ) } ); // ============================================================ // AuditQuery — 审批历史多条件查询入参(status / risk / 工具名关键词) // ============================================================ /// 审批历史多条件查询入参(对标 [`IdeaQuery`] 的可选字段 struct 设计)。 /// /// 所有字段可选;全 None → 等价 `list_recent`(向后兼容)。设计对齐 `查询能力补全方案`: /// 可选字段 struct 而非逐个加 IPC 参数,复用 [`IdeaRepo::list_by_query`] 的动态 WHERE 拼接 /// 模式(if-let 分支拼 SQL + 分支化参数绑定)。 /// /// - `status`:状态精确匹配(pending/approved/rejected/executing/completed/failed/interrupted) /// - `risk_level`:风险等级精确匹配(low/medium/high) /// - `tool_keyword`:`tool_name LIKE %kw%`(对齐 idea_repo 关键词 LIKE 检索,不上 FTS5) /// - `limit`/`offset`:钳制上限 200(对齐 [`AiToolExecutionRepo::list_recent`]) /// /// `Deserialize`:Tauri IPC 从前端 JSON 反序列化为命令参数。 /// `Default`:命令层兼容旧全量调用(`AuditQuery::default()` 等价无条件)。 #[derive(Debug, Clone, Default, serde::Deserialize)] pub struct AuditQuery { pub status: Option, pub risk_level: Option, pub tool_keyword: Option, pub limit: Option, pub offset: Option, } impl_repo!( /// AI 工具执行审计表 CRUD AiToolExecutionRepo, AiToolExecutionRecord, "ai_tool_executions", from_row => |row| ai_tool_execution_from_row(row), insert => |conn, rec| { conn.execute( "INSERT INTO ai_tool_executions (id, conversation_id, message_id, tool_call_id, tool_name, arguments, result, status, risk_level, requested_at, executed_at, decided_by, duration_ms) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13)", params![ rec.id, rec.conversation_id, rec.message_id, &*rec.tool_call_id, rec.tool_name, rec.arguments, rec.result, rec.status, rec.risk_level, rec.requested_at, rec.executed_at, rec.decided_by, rec.duration_ms ], ) }, update => |conn, rec| { conn.execute( "UPDATE ai_tool_executions SET conversation_id = ?1, message_id = ?2, tool_call_id = ?3, tool_name = ?4, arguments = ?5, result = ?6, status = ?7, risk_level = ?8, requested_at = ?9, executed_at = ?10, decided_by = ?11, duration_ms = ?12 WHERE id = ?13", params![ rec.conversation_id, rec.message_id, &*rec.tool_call_id, rec.tool_name, rec.arguments, rec.result, rec.status, rec.risk_level, rec.requested_at, rec.executed_at, rec.decided_by, rec.duration_ms, rec.id ], ) } ); // ai_tool_executions 无 created_at 列(用 requested_at/executed_at 计时), // 通用 query 宏硬编码 ORDER BY created_at 会触发 "no such column" → 调用方 unwrap_or_default 吞错。 // 故为此表提供专用查询,绕过通用 query。详见 ai.rs audit_finalize。 impl AiToolExecutionRepo { /// 批量插入审计记录(单事务多行 INSERT,砍 N 次串行 INSERT 尾巴)。 /// /// 对比 [`insert`](`impl_repo!` 生成,每次 spawn_blocking + 单行 execute): /// 本方法单次 `spawn_blocking` + 单事务,`prepare` 一次 INSERT stmt 循环 bind N 行, /// 一次 `COMMIT`(原子性:全插或全不插,审计留痕可追溯)。空 `records` 直接返回(无操作)。 /// /// **用途**:audit/mod.rs `process_tool_calls` 低风险工具 join_all 并行执行后的回填循环 /// (每工具一条审计),把 N 次串行 INSERT 合并为一次事务批量(治 aichat 效率 AC-EFF-T1-1)。 /// /// 安全:全部值走参数绑定(同 `insert` 宏体),无 SQL 拼接注入面;单连接 Mutex 持锁整段, /// 与单行 insert 的锁粒度相同(一次持锁换 N 次持锁)。 pub async fn insert_batch(&self, records: Vec) -> Result<()> { if records.is_empty() { return Ok(()); } let conn = self.conn.clone(); tokio::task::spawn_blocking(move || -> Result<()> { let mut guard = conn.blocking_lock(); // transaction() guard 范式(同 clear_conversation_atomic / message_repo::insert_batch): // rusqlite Transaction 在 Drop 未 commit 时自动回滚,中途 panic/早退不残留打开事务; // 原手写 BEGIN/COMMIT 无此保证,panic 后连接带开事务,后续写全部静默失败。 let tx = guard.transaction().map_err(storage_err)?; { let mut stmt = tx.prepare( "INSERT INTO ai_tool_executions (id, conversation_id, message_id, tool_call_id, tool_name, arguments, result, status, risk_level, requested_at, executed_at, decided_by, duration_ms) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13)", ) .map_err(storage_err)?; for rec in &records { stmt.execute(params![ rec.id, rec.conversation_id, rec.message_id, &*rec.tool_call_id, rec.tool_name, rec.arguments, rec.result, rec.status, rec.risk_level, rec.requested_at, rec.executed_at, rec.decided_by, rec.duration_ms ]) .map_err(storage_err)?; } } tx.commit().map_err(storage_err)?; Ok(()) }) .await .map_err(storage_err)??; Ok(()) } /// 按 tool_call_id 查最新一条审计记录(审批回填定位用)。 pub async fn find_by_tool_call_id( &self, tool_call_id: &str, ) -> Result> { let conn = self.conn.clone(); let tid = tool_call_id.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut stmt = guard .prepare( "SELECT * FROM ai_tool_executions WHERE tool_call_id = ?1 ORDER BY requested_at DESC LIMIT 1", ) .map_err(storage_err)?; let row = stmt .query_row(params![tid], |row| ai_tool_execution_from_row(row)) .optional() .map_err(storage_err)?; Ok(row) }) .await .map_err(storage_err)? } /// 按 (conversation_id, tool_name, arguments) 查最新一条审计记录(重试防护用)。 /// /// 语义:同一会话内同一工具同一参数的重试判重。区别于 `find_by_tool_call_id` /// (裸 id 匹配,弱模型 provider 的 tool_call_id 每轮重排,裸 id 判重会误杀跨轮合法调用, /// 实证 2026-08-11)。 pub async fn find_by_conv_tool_args( &self, conversation_id: &str, tool_name: &str, arguments: &str, ) -> Result> { let conn = self.conn.clone(); let cid = conversation_id.to_owned(); let tname = tool_name.to_owned(); let args = arguments.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut stmt = guard .prepare( "SELECT * FROM ai_tool_executions WHERE conversation_id = ?1 AND tool_name = ?2 AND arguments = ?3 ORDER BY requested_at DESC LIMIT 1", ) .map_err(storage_err)?; let row = stmt .query_row(params![cid, tname, args], |row| ai_tool_execution_from_row(row)) .optional() .map_err(storage_err)?; Ok(row) }) .await .map_err(storage_err)? } /// 列出所有 status=pending 的审计行(启动重建 pending_approvals 用) /// /// 专用 SELECT(非 query 宏——后者硬编码 ORDER BY created_at,而本表无该列)。 pub async fn list_pending(&self) -> Result> { let conn = self.conn.clone(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut stmt = guard .prepare("SELECT * FROM ai_tool_executions WHERE status = 'pending' ORDER BY requested_at ASC") .map_err(storage_err)?; let rows = stmt .query_map([], |row| ai_tool_execution_from_row(row)) .map_err(storage_err)?; let mut results = Vec::new(); for r in rows { results.push(r.map_err(storage_err)?); } Ok(results) }) .await .map_err(storage_err)? } /// 清理超期的残留 pending 工具调用(旧会话遗留)。 /// /// `max_age_secs`: 超过此秒数的 pending 记录被标记为 interrupted(不硬删,保留审计痕迹)。 pub async fn cleanup_stale_pending(&self, max_age_secs: u64) -> Result { let conn = self.conn.clone(); let cutoff_ms = (df_types::now_millis() as i64 - (max_age_secs as i64 * 1000)).to_string(); let affected = tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); guard.execute( "UPDATE ai_tool_executions SET status = 'interrupted' \ WHERE status = 'pending' AND CAST(requested_at AS INTEGER) < ?1", params![cutoff_ms], ).map_err(storage_err) }) .await .map_err(storage_err)??; Ok(affected as u64) } /// 审批历史面板分页查询:按 requested_at 倒序(最新在前),limit 默认 50。 /// /// 与 list_pending 同理走专用 SELECT,绕过通用 query 宏(后者硬编码 /// ORDER BY created_at,本表无该列)。limit/offset 上限钳制(limit ≤ 200), /// 防前端恶意/失误传超大值。 pub async fn list_recent( &self, limit: u32, offset: u32, ) -> Result> { let conn = self.conn.clone(); // 钳制 limit 防滥用(默认 50,最大 200) let safe_limit = limit.min(200) as i64; let safe_offset = offset as i64; tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut stmt = guard .prepare( "SELECT * FROM ai_tool_executions ORDER BY requested_at DESC LIMIT ?1 OFFSET ?2", ) .map_err(storage_err)?; let rows = stmt .query_map(params![safe_limit, safe_offset], |row| { ai_tool_execution_from_row(row) }) .map_err(storage_err)?; let mut results = Vec::new(); for r in rows { results.push(r.map_err(storage_err)?); } Ok(results) }) .await .map_err(storage_err)? } /// 多条件查询:动态 WHERE 拼接(status / risk_level / 工具名关键词) + 分页。 /// /// 复用 [`IdeaRepo::list_by_query`] 的动态 WHERE 模式:if-let 分支按可选条件拼 SQL 片段, /// 各分支化参数绑定到 `?N` 占位符。limit 钳制上限 200(对齐 [`Self::list_recent`])。 /// /// **向后兼容**:空 query(全 None)→ 无 WHERE 子句,等价 `list_recent`。 /// 与 list_pending/list_recent 同理走专用 SELECT,绕过通用 query 宏(后者硬编码 /// ORDER BY created_at,本表无该列)。 pub async fn list_by_query(&self, q: &AuditQuery) -> Result> { let conn = self.conn.clone(); let status = q.status.clone(); let risk = q.risk_level.clone(); let kw = q.tool_keyword.clone(); let limit_i: i64 = q.limit.unwrap_or(50).min(200) as i64; let offset_i: i64 = q.offset.unwrap_or(0) as i64; tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut where_clauses: Vec = Vec::new(); let mut params_vec: Vec> = Vec::new(); if let Some(s) = &status { where_clauses.push(format!("status = ?{}", params_vec.len() + 1)); params_vec.push(Box::new(s.clone())); } if let Some(r) = &risk { where_clauses.push(format!("risk_level = ?{}", params_vec.len() + 1)); params_vec.push(Box::new(r.clone())); } if let Some(k) = &kw { let escaped = k.replace('|', "||").replace('%', "|%").replace('_', "|_"); let pat = format!("%{escaped}%"); where_clauses.push(format!("tool_name LIKE ?{} ESCAPE '|'", params_vec.len() + 1)); params_vec.push(Box::new(pat)); } let where_sql = if where_clauses.is_empty() { String::new() } else { format!(" WHERE {}", where_clauses.join(" AND ")) }; let where_param_count = params_vec.len(); let sql = format!( "SELECT * FROM ai_tool_executions{where_sql} \ ORDER BY requested_at DESC LIMIT ?{lim} OFFSET ?{off}", lim = where_param_count + 1, off = where_param_count + 2, ); let mut stmt = guard.prepare(&sql).map_err(storage_err)?; params_vec.push(Box::new(limit_i)); params_vec.push(Box::new(offset_i)); let param_refs: Vec<&dyn rusqlite::ToSql> = params_vec.iter().map(|p| p.as_ref()).collect(); let rows = stmt .query_map(param_refs.as_slice(), |row| ai_tool_execution_from_row(row)) .map_err(storage_err)?; let mut results = Vec::new(); for r in rows { results.push(r.map_err(storage_err)?); } Ok(results) }) .await .map_err(storage_err)? } /// 按 [`AuditQuery`] 条件计数(不含 limit/offset,用于分页 total)。 /// /// 复用 [`Self::list_by_query`] 的 WHERE 构造逻辑(仅 WHERE,无 ORDER BY/LIMIT), /// 返回满足条件的总行数(忽略分页裁剪)。对标 [`TaskRepo::count_by_query`]。 pub async fn count_by_query(&self, q: &AuditQuery) -> Result { let conn = self.conn.clone(); let status = q.status.clone(); let risk = q.risk_level.clone(); let kw = q.tool_keyword.clone(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut where_clauses: Vec = Vec::new(); let mut params_vec: Vec> = Vec::new(); if let Some(s) = &status { where_clauses.push(format!("status = ?{}", params_vec.len() + 1)); params_vec.push(Box::new(s.clone())); } if let Some(r) = &risk { where_clauses.push(format!("risk_level = ?{}", params_vec.len() + 1)); params_vec.push(Box::new(r.clone())); } if let Some(k) = &kw { let escaped = k.replace('|', "||").replace('%', "|%").replace('_', "|_"); let pat = format!("%{escaped}%"); where_clauses.push(format!("tool_name LIKE ?{} ESCAPE '|'", params_vec.len() + 1)); params_vec.push(Box::new(pat)); } let sql = if where_clauses.is_empty() { "SELECT COUNT(*) FROM ai_tool_executions".to_string() } else { format!( "SELECT COUNT(*) FROM ai_tool_executions WHERE {}", where_clauses.join(" AND ") ) }; let param_refs: Vec<&dyn rusqlite::ToSql> = params_vec.iter().map(|p| p.as_ref()).collect(); let count: i64 = guard .query_row(&sql, param_refs.as_slice(), |row| row.get(0)) .map_err(storage_err)?; Ok(count) }) .await .map_err(storage_err)? } /// 按工具聚合执行统计(status 分布计数,AC-5 运行时失败率画像数据源)。 /// /// 单条 GROUP BY 取 `(tool_name, status, count)` 三元组;内存聚合与失败率口径 /// (failed_rate = failed / (completed + failed))在命令层完成(record.rs /// `tool_failure_stats`),本层只负责取数,不掺展示逻辑。 /// `from`:可选时间下限(millis,`requested_at >= from`),None = 全量。 /// /// 与本表其他查询同理走专用 SELECT(通用 query 宏硬编码 ORDER BY created_at, /// 本表无该列)。`requested_at` 存毫秒数字符串,`CAST AS INTEGER` 数值比较 /// (对齐 `cleanup_stale_pending` 同口径)。参数化绑定防注入。 pub async fn stats_by_tool(&self, from: Option) -> Result> { let conn = self.conn.clone(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); // 条件分支仅差 WHERE + 参数,一条 GROUP BY 复用(match 分支互斥,stmt 借用安全) let (sql, param): (&str, Option) = match from { Some(f) => ( "SELECT tool_name, status, COUNT(*) FROM ai_tool_executions \ WHERE CAST(requested_at AS INTEGER) >= ?1 GROUP BY tool_name, status", Some(f), ), None => ( "SELECT tool_name, status, COUNT(*) FROM ai_tool_executions \ GROUP BY tool_name, status", None, ), }; let row_map = |row: &rusqlite::Row| { Ok(( row.get::<_, String>(0)?, row.get::<_, String>(1)?, row.get::<_, i64>(2)?, )) }; let mut stmt = guard.prepare(sql).map_err(storage_err)?; let mut rows = match param { Some(f) => stmt.query_map(params![f], row_map).map_err(storage_err)?, None => stmt.query_map([], row_map).map_err(storage_err)?, }; let mut out = Vec::new(); for r in &mut rows { out.push(r.map_err(storage_err)?); } Ok(out) }) .await .map_err(storage_err)? } } // AiConversationRepo 的整体更新已由 impl_repo! 宏统一生成的 update_full 提供。 impl AiConversationRepo { /// 写入对话版本化快照 checkpoint(INSERT OR IGNORE,同 id 已存在则跳过)。 /// /// 参数化绑定(替代原调用方的 format! 拼 SQL + execute_batch),防 snapshot 含引号/ /// 特殊字符致注入或损坏。列对齐 conversation_checkpoints(id, conv_id, snapshot, /// token_total, created_at)。 /// /// 冲突语义:调用方 ck_id 由 (conv, 消息数) 确定性生成,同轮重复 save 撞同 id 是 /// 预期幂等跳过;但静默会掩盖另一情形——会话回退/重生成回同消息数且内容已变, /// 新 snapshot 被旧 checkpoint 挡住未落库。affected=0 时 warn 留痕,两种情形都 /// 可观测(是否异常由调用方日志上下文判别)。签名保 Result<()> 不外泄跳过信息: /// 跳过非错误,调用方对 Err 已按 warn 处理,无需改调用点。 pub async fn insert_checkpoint( &self, id: &str, conv_id: &str, snapshot: &str, token_total: i64, created_at: &str, ) -> Result<()> { let conn = self.conn.clone(); let id = id.to_string(); let conv_id = conv_id.to_string(); let snapshot = snapshot.to_string(); let created_at = created_at.to_string(); tokio::task::spawn_blocking(move || -> Result<()> { let guard = conn.blocking_lock(); let affected = guard .execute( "INSERT OR IGNORE INTO conversation_checkpoints \ (id, conv_id, snapshot, token_total, created_at) \ VALUES (?1, ?2, ?3, ?4, ?5)", params![id, conv_id, snapshot, token_total, created_at], ) .map_err(storage_err)?; if affected == 0 { tracing::warn!( "checkpoint 幂等跳过(同 id 已存在,新 snapshot 未落库): id={id} conv={conv_id}" ); } Ok(()) }) .await .map_err(storage_err)? } /// 清空对话消息内容(保留 conversation 记录本身,只清 messages JSON + 清零 token 计数) /// /// "清空对话"语义:对话壳保留(侧栏仍可见,可继续在该对话内聊),仅清空历史消息。 /// messages 是 ai_conversations 表内的 JSON 列而非独立行,故"删 messages"= 置空该列。 pub async fn clear_messages(&self, id: &str) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); let now = now_millis_str(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET messages = '[]', prompt_tokens = 0, completion_tokens = 0, updated_at = ?1 WHERE id = ?2", params![now, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 清空对话消息内容(单事务原子:ai_conversations.messages 置 '[]' + ai_messages 表全删)。 /// /// A2-B9(G3.2 clearChat 裁决):原 `clear_messages` + `delete_range` 两条独立 DB 写非原子, /// DB 失败会致 messages JSON 列与 ai_messages 表不一致(如仅一条成功)。本方法一次 transaction /// 覆盖两条写(① UPDATE ai_conversations 置空消息 + 清零 token;② DELETE ai_messages 该 conv /// 全部行),成功全成功 / 失败回滚全失败。供 `ai_chat_clear` 先停 loop 再单事务清空。 /// /// 对话壳保留(侧栏仍可见,可继续在该对话内聊);返回 Ok(())——调用方只关心成功与否 /// (对齐 replace_conversation 语义,不返回受影响行数)。 pub async fn clear_conversation_atomic(&self, id: &str) -> Result<()> { let conn = self.conn.clone(); let id = id.to_owned(); let now = now_millis_str(); tokio::task::spawn_blocking(move || -> Result<()> { let mut guard = conn.blocking_lock(); let tx = guard.transaction().map_err(storage_err)?; { // ① ai_conversations.messages 置空 + token 清零(对话壳保留) tx.execute( "UPDATE ai_conversations SET messages = '[]', prompt_tokens = 0, completion_tokens = 0, updated_at = ?1 WHERE id = ?2", params![now, id], ) .map_err(storage_err)?; // ② ai_messages 表全删(等价 delete_range min_seq=0 max=None:seq 恒 >= 0) tx.execute( "DELETE FROM ai_messages WHERE conversation_id = ?1", params![id], ) .map_err(storage_err)?; } tx.commit().map_err(storage_err)?; Ok(()) }) .await .map_err(storage_err)? } /// 设置归档标记(仅改 archived,不动 updated_at) /// /// 区别于 update_field(后者强制 SET updated_at=now,会把归档/取消归档误判为内容更新, /// 导致侧栏相对时间跳变为"刚刚")。归档是纯元数据标记,应保持时间不变。 pub async fn set_archived(&self, id: &str, archived: bool) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET archived = ?1 WHERE id = ?2", params![if archived { 1 } else { 0 }, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 设置标题(仅改 title,不动 updated_at) /// /// 区别于 update_field(强制 SET updated_at=now,会把标题生成误判为内容更新, /// 导致侧栏时间分组/排序跳变)。标题生成是系统后台操作,应保持会话相对时间不变。 pub async fn set_title(&self, id: &str, title: &str) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); let title = title.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET title = ?1 WHERE id = ?2", params![title, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 设置置顶标记(仅改 pinned,不动 updated_at) — UX-17 /// /// 同 set_archived:置顶是纯元数据标记,不应改变相对时间。前端排序读 pinned DESC, updated_at DESC。 pub async fn set_pinned(&self, id: &str, pinned: bool) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET pinned = ?1 WHERE id = ?2", params![if pinned { 1 } else { 0 }, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 无人值守任务边界快照写入(V45 boundary_json 列)。None=清除(回退逐次审批)。 /// /// 仅改 boundary_json,不动 updated_at(纯元数据标记,对齐 set_archived/set_pinned)。 /// 返回 affected>0:对话尚未落库(懒创建,首条消息前)时影响 0 行——调用方以内存 /// per_conv.boundary 为真相源,首插 save 会随 INSERT 带上,无需报错。 pub async fn set_boundary_json(&self, id: &str, boundary_json: Option<&str>) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); let value = boundary_json.map(|s| s.to_owned()); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET boundary_json = ?1 WHERE id = ?2", params![value, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// loop 生命周期标记写入(V49 loop_state,断点续跑底座)。 /// /// state: Some("running")=任务 loop spawn 时置起;Some("parked")=重启扫描改写; /// None=正常收敛/用户停止时清理。纯元数据标记不进 update_full(防 save_conversation /// 高频全量写覆盖 loop 生命周期语义),对齐 set_boundary_json/set_archived 模式。 /// 不动 updated_at(纯标记)。对话未落库(懒创建)时影响 0 行,调用方忽略。 pub async fn set_loop_state(&self, id: &str, state: Option<&str>) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); let value = state.map(|s| s.to_owned()); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET loop_state = ?1 WHERE id = ?2", params![value, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 会话终局态写入(V50 status)。 /// /// status: "active"(默认/进行中/正常完成)、"incomplete"(停靠/断流等未完成终局)、 /// "error"(循环错误终局)。纯标记不进 update_full(防 save_conversation 高频全量写覆盖), /// 对齐 set_loop_state 模式;不动 updated_at。对话未落库(懒创建)时影响 0 行,调用方忽略。 pub async fn set_status(&self, id: &str, status: &str) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); let status = status.to_owned(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET status = ?1 WHERE id = ?2", params![status, id], ) .map_err(storage_err)?; Ok(affected > 0) }) .await .map_err(storage_err)? } /// 重启扫描:把所有 loop_state='running' 残留改写为 'parked'。 /// /// 进程启动时调用一次:上次运行中 loop_state=running 的会话,进程重启后 loop 必死 /// (内存态不复存在),残留 running 是假活。改写 parked 后侧栏读 list_recoverable /// 展示「任务中断可恢复」。返回改写条数(0=无中断任务,静默)。 pub async fn mark_running_as_parked(&self) -> Result { let conn = self.conn.clone(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let affected = guard .execute( "UPDATE ai_conversations SET loop_state = 'parked' WHERE loop_state = 'running'", [], ) .map_err(storage_err)?; Ok(affected as u64) }) .await .map_err(storage_err)? } /// 列出可恢复会话(loop_state='parked',重启中断待一键恢复)。 pub async fn list_parked(&self) -> Result> { let conn = self.conn.clone(); tokio::task::spawn_blocking(move || { let guard = conn.blocking_lock(); let mut stmt = guard .prepare( "SELECT * FROM ai_conversations WHERE loop_state = 'parked' ORDER BY updated_at DESC", ) .map_err(storage_err)?; let rows = stmt .query_map([], ai_conversation_from_row) .map_err(storage_err)? .collect::, _>>() .map_err(storage_err)?; Ok(rows) }) .await .map_err(storage_err)? } /// G1.3: 删除对话 + 其全部 ai_messages 子行(单事务原子)。 /// /// 背景:原宏生成 `delete` 只删 ai_conversations 主行,而 ai_messages 表无外键级联 /// (conversation_id 仅普通索引),子行孤儿累积。本方法在同一事务内**先删子行 /// (ai_messages)再删主行(ai_conversations)**,要么全删要么全不删。 /// /// 顺序注意:先删数据再摘内存(命令层 per_conv.remove 在其后),防后台在途 /// save_conversation 在删主行后把孤儿消息写回复活。与 save_conversation 共享同一 /// conn(Mutex),事务原子性保证删除期间无中间态(半删半留)。 pub async fn delete_with_messages(&self, id: &str) -> Result { let conn = self.conn.clone(); let id = id.to_owned(); tokio::task::spawn_blocking(move || { let mut guard = conn.blocking_lock(); let tx = guard.transaction().map_err(storage_err)?; // 先删子行(ai_messages)再删主行(ai_conversations),单事务原子 tx.execute( "DELETE FROM ai_messages WHERE conversation_id = ?1", params![id], ) .map_err(storage_err)?; let conv_affected = tx .execute("DELETE FROM ai_conversations WHERE id = ?1", params![id]) .map_err(storage_err)?; tx.commit().map_err(storage_err)?; Ok(conv_affected > 0) }) .await .map_err(storage_err)? } } // ============================================================ // 单元测试 — AiProviderRepo model_configs DB roundtrip + 老库兼容 // ============================================================ #[cfg(test)] mod tests { use super::*; use crate::db::Database; use crate::models::AiProviderRecord; use df_ai_core::model::{Capability, IntelligenceTier, Modality, ModelConfig}; /// model_configs DB roundtrip + 老库空兼容 #[tokio::test] async fn ai_provider_model_configs_roundtrip_and_old_db_compat() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiProviderRepo::new(&db); // 新格式:带多模型 + 多维度配置 let configs = vec![ ModelConfig::with_defaults("glm-4-flash"), ModelConfig { model_id: "glm-4v".into(), modalities: vec![Modality::Text, Modality::Vision], capabilities: vec![Capability::ToolUse], intelligence: IntelligenceTier::Plus, weight: 70, context_window: 128_000, ..ModelConfig::with_defaults("glm-4v") }, ]; let rec = AiProviderRecord { id: "p1".into(), name: "测试".into(), provider_type: "openai_compat".into(), api_key: String::new(), base_url: "https://x".into(), default_model: "glm-4-flash".into(), models: None, model_configs: configs.clone(), is_default: false, config: None, created_at: "0".into(), updated_at: "0".into(), enabled: true, weight: 50, }; repo.insert(rec).await.expect("insert"); let got = repo.get_by_id("p1").await.expect("get").expect("row exists"); assert_eq!(got.model_configs.len(), 2); assert_eq!(got.model_configs[0].model_id, "glm-4-flash"); assert_eq!(got.model_configs[1].model_id, "glm-4v"); assert_eq!(got.model_configs[1].intelligence, IntelligenceTier::Plus); assert_eq!(got.model_configs[1].context_window, 128_000); // 老库空兼容:直接写 model_configs=NULL 的行(模拟 V18 之前的老库行) // 然后 from_row 应得空 Vec { let conn = db.conn(); let g = conn.lock().await; g.execute( "INSERT OR REPLACE INTO ai_providers \ (id,name,provider_type,api_key,base_url,default_model,models,model_configs,is_default,config,created_at,updated_at) \ VALUES ('old','','openai_compat','','','','{}',NULL,0,NULL,'0','0')", [], ) .expect("raw insert old row"); } let old = repo.get_by_id("old").await.expect("get").expect("old row"); assert!(old.model_configs.is_empty(), "NULL 列应得空 Vec"); // 老格式字符串数组 JSON(向后兼容 deserialize_model_configs) { let conn = db.conn(); let g = conn.lock().await; g.execute( "INSERT OR REPLACE INTO ai_providers \ (id,name,provider_type,api_key,base_url,default_model,models,model_configs,is_default,config,created_at,updated_at) \ VALUES ('legacy','','openai_compat','','','','{}','[\"glm-4-flash\",\"glm-4v\"]',0,NULL,'0','0')", [], ) .expect("raw insert legacy row"); } let legacy = repo.get_by_id("legacy").await.expect("get").expect("legacy row"); assert_eq!(legacy.model_configs.len(), 2, "老字符串数组应转 2 个默认 ModelConfig"); assert_eq!(legacy.model_configs[0].model_id, "glm-4-flash"); } // ---------- find_by_conv_tool_args(重试判重,SC-260811-P0-1) ---------- /// 构造一条审计记录(参数自洽,满足 NOT NULL 约束)。 fn audit_rec( id: &str, conv: &str, tc_id: &str, tool: &str, args: &str, status: &str, ) -> AiToolExecutionRecord { AiToolExecutionRecord { id: id.into(), conversation_id: Some(conv.into()), message_id: None, tool_call_id: tc_id.into(), tool_name: tool.into(), arguments: args.into(), result: None, status: status.into(), risk_level: "low".into(), requested_at: "0".into(), executed_at: None, decided_by: None, duration_ms: None, } } /// P0-1 核心语义:弱模型跨轮复用同 tool_call_id(gen_stream_0),但工具/参数不同 → /// find_by_conv_tool_args 不得误判为重试(旧 find_by_tool_call_id 会误命中)。 #[tokio::test] async fn find_by_conv_tool_args_ignores_same_id_different_tool() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiToolExecutionRepo::new(&db); // 会话开头已执行过 list_tasks(gen_stream_0),之后同会话又出现 gen_stream_0 的 advance_task repo.insert(audit_rec("a1", "conv1", "gen_stream_0", "list_tasks", "{\"limit\":50}", "completed")).await.expect("insert"); repo.insert(audit_rec("a2", "conv1", "gen_stream_0", "advance_task", "{\"id\":\"t1\",\"target_status\":\"blocked\"}", "completed")).await.expect("insert"); // 查 advance_task 同三元组 → 命中(a2) let got = repo.find_by_conv_tool_args("conv1", "advance_task", "{\"id\":\"t1\",\"target_status\":\"blocked\"}").await.expect("query"); assert!(got.is_some(), "同 (conv,tool,args) 应命中"); assert_eq!(got.unwrap().id, "a2"); // 查 list_tasks 同三元组 → 命中(a1),互不串扰 let got2 = repo.find_by_conv_tool_args("conv1", "list_tasks", "{\"limit\":50}").await.expect("query"); assert!(got2.is_some()); assert_eq!(got2.unwrap().id, "a1"); // 跨会话同 tool_call_id 不命中(不同 conv) let got3 = repo.find_by_conv_tool_args("conv2", "advance_task", "{\"id\":\"t1\",\"target_status\":\"blocked\"}").await.expect("query"); assert!(got3.is_none(), "不同会话同参数不应命中"); } /// 同 (conv,tool,args) 且已落定(completed) → 判重返回记录(调用方 retry_count≥1); /// pending 视为"尚未落定"(首次挂起审批)不判重。 #[tokio::test] async fn find_by_conv_tool_args_pending_not_retry() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiToolExecutionRepo::new(&db); repo.insert(audit_rec("a1", "conv1", "call_x", "write_file", "{\"path\":\"a.go\"}", "pending")).await.expect("insert"); // pending 记录不视为重试 let got = repo.find_by_conv_tool_args("conv1", "write_file", "{\"path\":\"a.go\"}").await.expect("query"); assert!(got.is_some(), "pending 记录也应能查到(状态判定在调用方 detect_retry_count 做,此处只负责按三元组定位)"); assert_eq!(got.unwrap().status, "pending"); // 同三元组 latest(有 completed 应返回最新一条 requested_at DESC) let mut rec2 = audit_rec("a2", "conv1", "call_x", "write_file", "{\"path\":\"a.go\"}", "completed"); rec2.requested_at = "1".into(); // 晚于 a1 的 "0",保证 DESC 序可辨 repo.insert(rec2).await.expect("insert"); let got2 = repo.find_by_conv_tool_args("conv1", "write_file", "{\"path\":\"a.go\"}").await.expect("query"); assert_eq!(got2.unwrap().id, "a2", "同三元组应返回最新落定记录"); } /// D2a 结果外置的读写兼容契约:result 列由外置层(audit 侧)决定写内联还是写句柄, /// 存储层既不解释也不改写——老行(外置落地前写入)是内联全文,读回必须原样;新行的 /// 外置句柄 JSON 同样原样存取。锁死「旧行仍读表内全文」:存储层若对 result 做截断/ /// 外置/解析等 mutation,会同时破坏两侧兼容(旧行读残缺 + 句柄被误当正文)。 #[tokio::test] async fn tool_execution_result_stored_verbatim_old_and_new() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiToolExecutionRepo::new(&db); // 旧数据:内联全文。超大值也要能原样读回(D2a 落地前的历史大结果就长这样,存储层不得追改) let legacy_big = "A".repeat(10 * 1024); let mut old_big = audit_rec("old_big", "conv1", "call_old_big", "read_file", "{}", "completed"); old_big.result = Some(legacy_big.clone()); repo.insert(old_big).await.expect("insert old big"); let mut old_small = audit_rec("old_small", "conv2", "call_old_small", "write_file", "{}", "completed"); old_small.result = Some("{\"ok\":true}".to_string()); repo.insert(old_small).await.expect("insert old small"); // 新数据:外置句柄 JSON(存储层不解析,当普通 TEXT 存取) let handle = r#"{"__offloaded__":true,"path":"/tmp/x.txt","size_bytes":20480}"#; let mut new_off = audit_rec("new_off", "conv3", "call_new", "run_command", "{}", "completed"); new_off.result = Some(handle.to_string()); repo.insert(new_off).await.expect("insert new offloaded"); // 读回:三条各自原样(旧行全文;句柄不被误解析/清空) let got_old_big = repo.get_by_id("old_big").await.expect("get").expect("row"); assert_eq!(got_old_big.result.as_deref(), Some(legacy_big.as_str()), "老行超大内联 result 须原样读回"); let got_old_small = repo.get_by_id("old_small").await.expect("get").expect("row"); assert_eq!(got_old_small.result.as_deref(), Some("{\"ok\":true}")); let got_new = repo.get_by_id("new_off").await.expect("get").expect("row"); assert_eq!(got_new.result.as_deref(), Some(handle), "外置句柄 JSON 须原样存取"); // 专用查询路径(按 tool_call_id 定位)同样原样,与通用 get_by_id 口径一致 let by_tc = repo.find_by_tool_call_id("call_old_big").await.expect("query").expect("row"); assert_eq!(by_tc.result.as_deref(), Some(legacy_big.as_str())); } /// insert_checkpoint 冲突语义:同 id 二次写入 Ok 不报错(幂等跳过,affected=0 走 warn), /// 保留首次 snapshot。锁死 OR IGNORE 行为,防未来误改成 REPLACE 静默覆盖快照。 #[tokio::test] async fn insert_checkpoint_conflict_skips_and_keeps_first() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiConversationRepo::new(&db); repo.insert_checkpoint("ck_1", "conv1", r#"[{"seq":0}]"#, 1, "100") .await .expect("首次写入"); // 同 id 不同内容:IGNORE 生效应 Ok,首次 snapshot 保留 repo.insert_checkpoint("ck_1", "conv1", r#"[{"seq":0},{"seq":1}]"#, 2, "200") .await .expect("冲突写入应幂等跳过不报错"); let conn = db.conn(); let g = conn.lock().await; let count: i64 = g .query_row("SELECT COUNT(*) FROM conversation_checkpoints WHERE id = 'ck_1'", [], |r| r.get(0)) .expect("count"); assert_eq!(count, 1, "同 id 只应有一行"); let snapshot: String = g .query_row("SELECT snapshot FROM conversation_checkpoints WHERE id = 'ck_1'", [], |r| r.get(0)) .expect("snapshot"); assert_eq!(snapshot, r#"[{"seq":0}]"#, "冲突时应保留首次快照"); } /// #904 契约:set_loop_state 写 "parked" 后 get_by_id 可读回(停靠出口写侧单点)。 /// 锁死「停靠状态写入收敛进 emit_task_parked」依赖的 repo 能力——若 set_loop_state /// 或 from_row 的 loop_state 映射回归,停靠卡「继续」将再次撞「AI 未在暂停态」。 #[tokio::test] async fn set_loop_state_parked_roundtrip() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiConversationRepo::new(&db); repo.insert(AiConversationRecord { id: "c1".into(), title: None, messages: "[]".into(), provider_id: None, model: None, models: None, archived: false, pinned: false, prompt_tokens: Some(0), completion_tokens: Some(0), pinned_goals: None, pending_approvals: None, created_at: "0".into(), updated_at: "0".into(), origin: None, boundary_json: None, loop_state: None, status: "active".into(), }) .await .expect("insert"); assert!(repo.set_loop_state("c1", Some("parked")).await.expect("set")); let got = repo.get_by_id("c1").await.expect("get").expect("row"); assert_eq!(got.loop_state.as_deref(), Some("parked"), "写 parked 应可读回"); // 清态(running 收敛出口)可读回 None assert!(repo.set_loop_state("c1", None).await.expect("clear")); let cleared = repo.get_by_id("c1").await.expect("get").expect("row"); assert_eq!(cleared.loop_state, None, "清 loop_state 应可读回 None"); } /// V50 契约:set_status 写终局态后可读回,且 insert 默认 active。 /// 锁死「会话终局态」建模能力,防 from_row 映射或 insert 列回归致默认值丢失。 #[tokio::test] async fn set_status_roundtrip_and_default_active() { let db = Database::open_in_memory().await.expect("open_in_memory"); let repo = AiConversationRepo::new(&db); repo.insert(AiConversationRecord { id: "c1".into(), title: None, messages: "[]".into(), provider_id: None, model: None, models: None, archived: false, pinned: false, prompt_tokens: Some(0), completion_tokens: Some(0), pinned_goals: None, pending_approvals: None, created_at: "0".into(), updated_at: "0".into(), origin: None, boundary_json: None, loop_state: None, status: "active".into(), }) .await .expect("insert"); let got = repo.get_by_id("c1").await.expect("get").expect("row"); assert_eq!(got.status, "active", "默认终局态应为 active"); assert!(repo.set_status("c1", "incomplete").await.expect("set")); let got2 = repo.get_by_id("c1").await.expect("get").expect("row"); assert_eq!(got2.status, "incomplete", "写 incomplete 应可读回"); } }