diff --git a/desktop/src-tauri/src/lib.rs b/desktop/src-tauri/src/lib.rs index ff6c5ab..539746c 100644 --- a/desktop/src-tauri/src/lib.rs +++ b/desktop/src-tauri/src/lib.rs @@ -124,8 +124,8 @@ pub fn run() { // Initialize browser state let browser_state = browser::commands::BrowserState::new(); - // Initialize memory store state - let memory_state: memory_commands::MemoryStoreState = std::sync::Arc::new(tokio::sync::Mutex::new(None)); + // Initialize memory store state (vestigial — PersistentMemoryStore removed in V13) + let memory_state: memory_commands::MemoryStoreState = std::sync::Arc::new(tokio::sync::Mutex::new(())); // Initialize intelligence layer state let heartbeat_state: intelligence::HeartbeatEngineState = std::sync::Arc::new(tokio::sync::Mutex::new(std::collections::HashMap::new())); @@ -373,8 +373,6 @@ pub fn run() { memory_commands::memory_export, memory_commands::memory_import, memory_commands::memory_db_path, - memory_commands::memory_configure_embedding, - memory_commands::memory_is_embedding_configured, memory_commands::memory_build_context, // Intelligence Layer commands (Phase 2-3) // Heartbeat Engine diff --git a/desktop/src-tauri/src/memory/mod.rs b/desktop/src-tauri/src/memory/mod.rs index 844dfaa..8afa6fb 100644 --- a/desktop/src-tauri/src/memory/mod.rs +++ b/desktop/src-tauri/src/memory/mod.rs @@ -12,9 +12,5 @@ pub mod context_builder; pub mod persistent; pub mod crypto; -// Re-export main types for convenience -pub use persistent::{ - PersistentMemory, PersistentMemoryStore, MemoryStats, - configure_embedding_client, is_embedding_configured, - EmbedFn, -}; +// Re-export frontend API types for convenience +pub use persistent::{PersistentMemory, MemoryStats}; diff --git a/desktop/src-tauri/src/memory/persistent.rs b/desktop/src-tauri/src/memory/persistent.rs index ce34382..90ef132 100644 --- a/desktop/src-tauri/src/memory/persistent.rs +++ b/desktop/src-tauri/src/memory/persistent.rs @@ -1,80 +1,17 @@ -//! Persistent Memory Storage - SQLite-backed memory for ZCLAW +//! Frontend API types for memory system //! -//! This module provides persistent storage for agent memories, -//! enabling cross-session memory retention and multi-device synchronization. -//! -//! Phase 1 of Intelligence Layer Migration: -//! - Replaces localStorage with SQLite -//! - Provides memory persistence API -//! - Enables data migration from frontend +//! PersistentMemoryStore was removed in V13 audit (FIX-06): +//! all data operations now go through VikingStorage (SqliteStorage). +//! This module retains only the frontend-facing types for Tauri command responses. use serde::{Deserialize, Serialize}; -use std::path::PathBuf; -use std::sync::Arc; -use tokio::sync::{Mutex, OnceCell}; -use uuid::Uuid; -use tauri::Manager; -use sqlx::{SqliteConnection, Connection, Row, sqlite::SqliteRow}; -use chrono::Utc; +use sqlx::{Row, sqlite::SqliteRow}; -/// Embedding function type: text -> vector of f32 -pub type EmbedFn = Arc std::pin::Pin, String>> + Send>> + Send + Sync>; - -/// Global embedding function for PersistentMemoryStore -static EMBEDDING_FN: OnceCell = OnceCell::const_new(); - -/// Configure the global embedding function for memory search -pub fn configure_embedding_client(fn_impl: EmbedFn) { - let _ = EMBEDDING_FN.set(fn_impl); - tracing::info!("[PersistentMemoryStore] Embedding client configured"); -} - -/// Check if embedding is available -pub fn is_embedding_configured() -> bool { - EMBEDDING_FN.get().is_some() -} - -/// Generate embedding for text using the configured client -async fn embed_text(text: &str) -> Result, String> { - let client = EMBEDDING_FN.get() - .ok_or_else(|| "Embedding client not configured".to_string())?; - client(text).await -} - -/// Deserialize f32 vector from BLOB (4 bytes per f32, little-endian) -fn deserialize_embedding(blob: &[u8]) -> Vec { - blob.chunks_exact(4) - .map(|chunk| f32::from_le_bytes([chunk[0], chunk[1], chunk[2], chunk[3]])) - .collect() -} - -/// Serialize f32 vector to BLOB -fn serialize_embedding(vec: &[f32]) -> Vec { - let mut bytes = Vec::with_capacity(vec.len() * 4); - for val in vec { - bytes.extend_from_slice(&val.to_le_bytes()); - } - bytes -} - -/// Compute cosine similarity between two vectors -fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 { - if a.is_empty() || b.is_empty() || a.len() != b.len() { - return 0.0; - } - let mut dot = 0.0f32; - let mut norm_a = 0.0f32; - let mut norm_b = 0.0f32; - for i in 0..a.len() { - dot += a[i] * b[i]; - norm_a += a[i] * a[i]; - norm_b += b[i] * b[i]; - } - let denom = (norm_a * norm_b).sqrt(); - if denom == 0.0 { 0.0 } else { (dot / denom).clamp(0.0, 1.0) } -} - -/// Memory entry stored in SQLite +/// Memory entry type for frontend API compatibility. +/// +/// All Tauri memory commands return this type. The actual storage backend +/// is VikingStorage (SqliteStorage); values are converted via `to_persistent()` +/// in memory_commands.rs. #[derive(Debug, Clone, Serialize, Deserialize)] pub struct PersistentMemory { pub id: String, @@ -113,20 +50,7 @@ impl<'r> sqlx::FromRow<'r, SqliteRow> for PersistentMemory { } } -/// Memory search options -#[derive(Debug, Clone, Default)] -pub struct MemorySearchQuery { - pub agent_id: Option, - pub memory_type: Option, - #[allow(dead_code)] // Reserved for future tag-based filtering - pub tags: Option>, - pub query: Option, - pub min_importance: Option, - pub limit: Option, - pub offset: Option, -} - -/// Memory statistics +/// Memory statistics returned by `memory_stats` command. #[derive(Debug, Clone, Serialize)] pub struct MemoryStats { pub total_entries: i64, @@ -136,475 +60,3 @@ pub struct MemoryStats { pub newest_entry: Option, pub storage_size_bytes: i64, } - -/// Persistent memory store backed by SQLite -pub struct PersistentMemoryStore { - path: PathBuf, - conn: Arc>, -} - -#[allow(dead_code)] -// Migration status (V13 audit FIX-06): -// - ACTIVE: new(), configure_embedding_client() — embedding config path for chat memory search -// - LEGACY: store(), get(), search(), delete(), stats(), export_all(), import_batch() — data ops moved to VikingStorage -// - Full removal requires migrating embedding config to VikingStorage (~3h, tracked in AUDIT_TRACKER) -impl PersistentMemoryStore { - /// Create a new persistent memory store - pub async fn new(app_handle: &tauri::AppHandle) -> Result { - let app_dir = app_handle - .path() - .app_data_dir() - .map_err(|e| format!("Failed to get app data dir: {}", e))?; - - let memory_dir = app_dir.join("memory"); - std::fs::create_dir_all(&memory_dir) - .map_err(|e| format!("Failed to create memory dir: {}", e))?; - - let db_path = memory_dir.join("memories.db"); - - Self::open(db_path).await - } - - /// Open an existing memory store - pub async fn open(path: PathBuf) -> Result { - let db_url = format!("sqlite:{}?mode=rwc", path.display()); - let conn = SqliteConnection::connect(&db_url) - .await - .map_err(|e| format!("Failed to open database: {}", e))?; - - let conn = Arc::new(Mutex::new(conn)); - - let store = Self { path, conn }; - - // Initialize database schema - store.init_schema().await?; - - Ok(store) - } - - /// Initialize the database schema - async fn init_schema(&self) -> Result<(), String> { - let mut conn = self.conn.lock().await; - - sqlx::query( - r#" - CREATE TABLE IF NOT EXISTS memories ( - id TEXT PRIMARY KEY, - agent_id TEXT NOT NULL, - memory_type TEXT NOT NULL, - content TEXT NOT NULL, - importance INTEGER DEFAULT 5, - source TEXT DEFAULT 'auto', - tags TEXT DEFAULT '[]', - conversation_id TEXT, - created_at TEXT NOT NULL, - last_accessed_at TEXT NOT NULL, - access_count INTEGER DEFAULT 0, - embedding BLOB - ); - - CREATE INDEX IF NOT EXISTS idx_agent_id ON memories(agent_id); - CREATE INDEX IF NOT EXISTS idx_memory_type ON memories(memory_type); - CREATE INDEX IF NOT EXISTS idx_created_at ON memories(created_at); - CREATE INDEX IF NOT EXISTS idx_importance ON memories(importance); - "#, - ) - .execute(&mut *conn) - .await - .map_err(|e| format!("Failed to create schema: {}", e))?; - - // Create FTS5 virtual table for full-text search - let _ = sqlx::query( - r#" - CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5( - id, - content, - tokenize='unicode61' - ) - "#, - ) - .execute(&mut *conn) - .await; - - // Migration: add overview column (L1 summary) - let _ = sqlx::query("ALTER TABLE memories ADD COLUMN overview TEXT") - .execute(&mut *conn) - .await; - - Ok(()) - } - - /// Store a new memory - pub async fn store(&self, memory: &PersistentMemory) -> Result<(), String> { - // Generate embedding if client is configured and memory doesn't have one - let embedding = if memory.embedding.is_some() { - memory.embedding.clone() - } else if is_embedding_configured() { - match embed_text(&memory.content).await { - Ok(vec) => { - tracing::debug!("[PersistentMemoryStore] Generated embedding for {} ({} dims)", memory.id, vec.len()); - Some(serialize_embedding(&vec)) - } - Err(e) => { - tracing::debug!("[PersistentMemoryStore] Embedding generation failed: {}", e); - None - } - } - } else { - None - }; - - let mut conn = self.conn.lock().await; - - sqlx::query( - r#" - INSERT INTO memories ( - id, agent_id, memory_type, content, importance, source, - tags, conversation_id, created_at, last_accessed_at, - access_count, embedding, overview - ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) - "#, - ) - .bind(&memory.id) - .bind(&memory.agent_id) - .bind(&memory.memory_type) - .bind(&memory.content) - .bind(memory.importance) - .bind(&memory.source) - .bind(&memory.tags) - .bind(&memory.conversation_id) - .bind(&memory.created_at) - .bind(&memory.last_accessed_at) - .bind(memory.access_count) - .bind(&embedding) - .bind(&memory.overview) - .execute(&mut *conn) - .await - .map_err(|e| format!("Failed to store memory: {}", e))?; - - // Sync FTS5 index - let _ = sqlx::query( - "INSERT OR REPLACE INTO memories_fts (id, content) VALUES (?, ?)" - ) - .bind(&memory.id) - .bind(&memory.content) - .execute(&mut *conn) - .await; - - Ok(()) - } - - /// Get a memory by ID - pub async fn get(&self, id: &str) -> Result, String> { - let mut conn = self.conn.lock().await; - - let result: Option = sqlx::query_as( - "SELECT * FROM memories WHERE id = ?", - ) - .bind(id) - .fetch_optional(&mut *conn) - .await - .map_err(|e| format!("Failed to get memory: {}", e))?; - - // Update access stats if found - if result.is_some() { - let now = Utc::now().to_rfc3339(); - sqlx::query( - "UPDATE memories SET last_accessed_at = ?, access_count = access_count + 1 WHERE id = ?", - ) - .bind(&now) - .bind(id) - .execute(&mut *conn) - .await - .ok(); - } - - Ok(result) - } - - /// Search memories with FTS5-first strategy and semantic ranking - pub async fn search(&self, query: MemorySearchQuery) -> Result, String> { - let mut conn = self.conn.lock().await; - - // When using embedding ranking, fetch more candidates - let effective_limit = if query.query.is_some() && is_embedding_configured() { - query.limit.unwrap_or(50).max(20) - } else { - query.limit.unwrap_or(50) - }; - - let results = if let Some(query_text) = &query.query { - // FTS5-first search strategy - let sanitized = sanitize_fts_query(query_text); - - if !sanitized.is_empty() { - // Try FTS5 MATCH first - let mut sql = String::from( - "SELECT m.* FROM memories m \ - INNER JOIN memories_fts f ON m.id = f.id \ - WHERE f.memories_fts MATCH ?" - ); - let mut params: Vec = vec![sanitized]; - - if let Some(agent_id) = &query.agent_id { - sql.push_str(" AND m.agent_id = ?"); - params.push(agent_id.clone()); - } - if let Some(memory_type) = &query.memory_type { - sql.push_str(" AND m.memory_type = ?"); - params.push(memory_type.clone()); - } - if let Some(min_importance) = query.min_importance { - sql.push_str(" AND m.importance >= ?"); - params.push(min_importance.to_string()); - } - sql.push_str(&format!(" ORDER BY f.rank LIMIT {}", effective_limit)); - - let mut query_builder = sqlx::query_as::<_, PersistentMemory>(&sql); - for param in params { - query_builder = query_builder.bind(param); - } - let fts_results = query_builder - .fetch_all(&mut *conn) - .await - .unwrap_or_default(); - - if !fts_results.is_empty() { - fts_results - } else { - // FTS5 miss — CJK LIKE fallback (unicode61 doesn't handle CJK) - let has_cjk = query_text.chars().any(|c| { - matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}') - }); - if has_cjk { - Self::like_search(&mut conn, &query, effective_limit).await - } else { - Vec::new() - } - } - } else { - // No meaningful FTS5 terms, use LIKE fallback - Self::like_search(&mut conn, &query, effective_limit).await - } - } else { - // No text query — plain filtered scan - Self::like_search(&mut conn, &query, effective_limit).await - }; - - // Apply semantic ranking if query and embedding are available - let mut final_results = results; - if let Some(query_text) = &query.query { - if is_embedding_configured() { - if let Ok(query_embedding) = embed_text(query_text).await { - let mut scored: Vec<(f32, PersistentMemory)> = final_results - .into_iter() - .map(|mem| { - let score = mem.embedding.as_ref() - .map(|blob| { - let vec = deserialize_embedding(blob); - cosine_similarity(&query_embedding, &vec) - }) - .unwrap_or(0.0); - (score, mem) - }) - .collect(); - - scored.sort_by(|a, b| b.0.partial_cmp(&a.0).unwrap_or(std::cmp::Ordering::Equal)); - - final_results = scored.into_iter() - .take(query.limit.unwrap_or(20)) - .map(|(_, mem)| mem) - .collect(); - } - } - } - - Ok(final_results) - } - - /// LIKE-based search fallback (used for CJK queries and non-text queries) - async fn like_search( - conn: &mut sqlx::SqliteConnection, - query: &MemorySearchQuery, - limit: usize, - ) -> Vec { - let mut sql = String::from("SELECT * FROM memories WHERE 1=1"); - let mut params: Vec = Vec::new(); - - if let Some(agent_id) = &query.agent_id { - sql.push_str(" AND agent_id = ?"); - params.push(agent_id.clone()); - } - if let Some(memory_type) = &query.memory_type { - sql.push_str(" AND memory_type = ?"); - params.push(memory_type.clone()); - } - if let Some(min_importance) = query.min_importance { - sql.push_str(" AND importance >= ?"); - params.push(min_importance.to_string()); - } - if let Some(query_text) = &query.query { - sql.push_str(" AND content LIKE ?"); - params.push(format!("%{}%", query_text)); - } - sql.push_str(&format!(" LIMIT {}", limit)); - - let mut query_builder = sqlx::query_as::<_, PersistentMemory>(&sql); - for param in params { - query_builder = query_builder.bind(param); - } - query_builder.fetch_all(conn).await.unwrap_or_default() - } - - /// Delete a memory by ID - pub async fn delete(&self, id: &str) -> Result { - let mut conn = self.conn.lock().await; - - let result = sqlx::query("DELETE FROM memories WHERE id = ?") - .bind(id) - .execute(&mut *conn) - .await - .map_err(|e| format!("Failed to delete memory: {}", e))?; - - Ok(result.rows_affected() > 0) - } - - /// Delete all memories for an agent - pub async fn delete_by_agent(&self, agent_id: &str) -> Result { - let mut conn = self.conn.lock().await; - - let result = sqlx::query("DELETE FROM memories WHERE agent_id = ?") - .bind(agent_id) - .execute(&mut *conn) - .await - .map_err(|e| format!("Failed to delete agent memories: {}", e))?; - - Ok(result.rows_affected() as usize) - } - - /// Get memory statistics - pub async fn stats(&self) -> Result { - let mut conn = self.conn.lock().await; - - let total: i64 = sqlx::query_scalar("SELECT COUNT(*) FROM memories") - .fetch_one(&mut *conn) - .await - .unwrap_or(0); - - let by_type: std::collections::HashMap = sqlx::query_as( - "SELECT memory_type, COUNT(*) as count FROM memories GROUP BY memory_type", - ) - .fetch_all(&mut *conn) - .await - .unwrap_or_default() - .into_iter() - .map(|row: (String, i64)| row) - .collect(); - - let by_agent: std::collections::HashMap = sqlx::query_as( - "SELECT agent_id, COUNT(*) as count FROM memories GROUP BY agent_id", - ) - .fetch_all(&mut *conn) - .await - .unwrap_or_default() - .into_iter() - .map(|row: (String, i64)| row) - .collect(); - - let oldest: Option = sqlx::query_scalar( - "SELECT MIN(created_at) FROM memories", - ) - .fetch_optional(&mut *conn) - .await - .unwrap_or_default(); - - let newest: Option = sqlx::query_scalar( - "SELECT MAX(created_at) FROM memories", - ) - .fetch_optional(&mut *conn) - .await - .unwrap_or_default(); - - let storage_size: i64 = sqlx::query_scalar( - "SELECT SUM(LENGTH(content) + LENGTH(tags) + COALESCE(LENGTH(embedding), 0)) FROM memories", - ) - .fetch_optional(&mut *conn) - .await - .unwrap_or(Some(0)) - .unwrap_or(0); - - Ok(MemoryStats { - total_entries: total, - by_type, - by_agent, - oldest_entry: oldest, - newest_entry: newest, - storage_size_bytes: storage_size, - }) - } - - /// Export memories for backup - pub async fn export_all(&self) -> Result, String> { - let mut conn = self.conn.lock().await; - - let memories = sqlx::query_as::<_, PersistentMemory>( - "SELECT * FROM memories ORDER BY created_at ASC", - ) - .fetch_all(&mut *conn) - .await - .map_err(|e| format!("Failed to export memories: {}", e))?; - - Ok(memories) - } - - /// Import memories from backup - pub async fn import_batch(&self, memories: &[PersistentMemory]) -> Result { - let mut imported = 0; - for memory in memories { - self.store(memory).await?; - imported += 1; - } - Ok(imported) - } - - /// Get the database path - pub fn path(&self) -> &PathBuf { - &self.path - } -} - -/// Sanitize a user query for FTS5 MATCH syntax. -/// Strips FTS5 operators and keeps only alphanumeric + CJK tokens with length > 1. -fn sanitize_fts_query(query: &str) -> String { - let terms: Vec = query - .to_lowercase() - .split(|c: char| !c.is_alphanumeric()) - .filter(|s| !s.is_empty() && s.len() > 1) - .map(|s| s.to_string()) - .collect(); - - if terms.is_empty() { - return String::new(); - } - - terms.join(" OR ") -} - -/// Generate a unique memory ID -#[allow(dead_code)] // Legacy: VikingStorage generates its own URIs -pub fn generate_memory_id() -> String { - let uuid_str = Uuid::new_v4().to_string().replace("-", ""); - let short_uuid = &uuid_str[..8]; - format!("mem_{}_{}", Utc::now().timestamp(), short_uuid) -} - -#[cfg(test)] -mod tests { - use super::*; - - #[test] - fn test_generate_memory_id() { - let memory_id = generate_memory_id(); - assert!(memory_id.starts_with("mem_")); - } -} diff --git a/desktop/src-tauri/src/memory_commands.rs b/desktop/src-tauri/src/memory_commands.rs index b9a28cd..06c1912 100644 --- a/desktop/src-tauri/src/memory_commands.rs +++ b/desktop/src-tauri/src/memory_commands.rs @@ -1,21 +1,21 @@ //! Memory Commands - Tauri commands for persistent memory operations //! -//! Unified storage: All operations delegate to VikingStorage (SqliteStorage), +//! All operations delegate to VikingStorage (SqliteStorage), //! which provides FTS5 full-text search, TF-IDF scoring, and optional embedding. //! -//! The previous dual-write to PersistentMemoryStore has been removed. //! PersistentMemory type is retained for frontend API compatibility. +//! PersistentMemoryStore was removed in V13 audit (FIX-06): all data ops +//! go through VikingStorage; the old embedding global was never read. -use crate::memory::{PersistentMemory, PersistentMemoryStore, MemoryStats, configure_embedding_client, is_embedding_configured, EmbedFn}; +use crate::memory::{PersistentMemory, MemoryStats}; use serde::{Deserialize, Serialize}; use std::sync::Arc; -use tauri::{AppHandle, State}; +use tauri::State; use tokio::sync::Mutex; -/// Shared memory store state -/// NOTE: PersistentMemoryStore is kept only for embedding configuration. -/// All actual storage goes through VikingStorage (SqliteStorage). -pub type MemoryStoreState = Arc>>; +/// Vestigial state — PersistentMemoryStore removed, all ops via VikingStorage. +/// Kept as `Arc>` to preserve Tauri state injection without dead types. +pub type MemoryStoreState = Arc>; /// Memory entry for frontend API #[derive(Debug, Clone, Serialize, Deserialize)] @@ -43,17 +43,14 @@ pub struct MemorySearchOptions { /// Initialize the memory store /// -/// Now a no-op for storage (VikingStorage initializes itself in viking_commands). -/// Only initializes PersistentMemoryStore for backward-compatible embedding config. +/// Vestigial — VikingStorage initializes itself in viking_commands. +/// Kept for frontend API compatibility (intelligence-backend.ts calls this). // @connected #[tauri::command] pub async fn memory_init( - app_handle: AppHandle, - state: State<'_, MemoryStoreState>, + _state: State<'_, MemoryStoreState>, ) -> Result<(), String> { - let store = PersistentMemoryStore::new(&app_handle).await?; - let mut state_guard = state.lock().await; - *state_guard = Some(store); + // VikingStorage auto-initializes in viking_commands::init_viking_storage() Ok(()) } @@ -370,49 +367,6 @@ pub async fn memory_db_path( Ok(db_path.to_string_lossy().to_string()) } -/// @reserved — no frontend UI yet -/// Configure embedding for PersistentMemoryStore (chat memory search) -/// This is called alongside viking_configure_embedding to enable vector search in chat flow -#[tauri::command] -pub async fn memory_configure_embedding( - provider: String, - api_key: String, - model: Option, - endpoint: Option, -) -> Result { - let config = crate::llm::EmbeddingConfig { - provider, - api_key, - endpoint, - model, - }; - let client = std::sync::Arc::new(crate::llm::EmbeddingClient::new(config)); - - let embed_fn: EmbedFn = { - let client = client.clone(); - Arc::new(move |text: &str| { - let client = client.clone(); - let text = text.to_string(); - Box::pin(async move { - let response = client.embed(&text).await?; - Ok(response.embedding) - }) - }) - }; - - configure_embedding_client(embed_fn); - - tracing::info!("[MemoryCommands] Embedding configured"); - Ok(true) -} - -/// @reserved — no frontend UI yet -/// Check if embedding is configured for PersistentMemoryStore -#[tauri::command] -pub fn memory_is_embedding_configured() -> bool { - is_embedding_configured() -} - /// Build layered memory context for chat prompt injection /// /// Uses VikingStorage (SqliteStorage) with FTS5 + TF-IDF + optional Embedding. diff --git a/desktop/src-tauri/src/viking_commands.rs b/desktop/src-tauri/src/viking_commands.rs index 4d3e3a3..92f87ce 100644 --- a/desktop/src-tauri/src/viking_commands.rs +++ b/desktop/src-tauri/src/viking_commands.rs @@ -561,7 +561,7 @@ fn parse_uri(uri: &str) -> Result<(String, MemoryType, String), String> { } /// Configure embedding for semantic memory search -/// Configures both SqliteStorage (VikingPanel) and PersistentMemoryStore (chat flow) +/// Configures SqliteStorage (VikingStorage) embedding for FTS5 + semantic search. // @connected #[tauri::command] pub async fn viking_configure_embedding( @@ -572,12 +572,11 @@ pub async fn viking_configure_embedding( ) -> Result { let storage = get_storage().await?; - // 1. Configure SqliteStorage (VikingPanel / VikingCommands) let config_viking = crate::llm::EmbeddingConfig { provider: provider.clone(), - api_key: api_key.clone(), - endpoint: endpoint.clone(), - model: model.clone(), + api_key, + endpoint, + model, }; let client_viking = crate::llm::EmbeddingClient::new(config_viking); @@ -588,30 +587,7 @@ pub async fn viking_configure_embedding( .await .map_err(|e| format!("Failed to configure embedding: {}", e))?; - // 2. Configure PersistentMemoryStore (chat flow) - let config_memory = crate::llm::EmbeddingConfig { - provider: provider.clone(), - api_key, - endpoint, - model, - }; - let client_memory = std::sync::Arc::new(crate::llm::EmbeddingClient::new(config_memory)); - - let embed_fn: crate::memory::EmbedFn = { - let client_arc = client_memory.clone(); - std::sync::Arc::new(move |text: &str| { - let client = client_arc.clone(); - let text = text.to_string(); - Box::pin(async move { - let response = client.embed(&text).await?; - Ok(response.embedding) - }) - }) - }; - - crate::memory::configure_embedding_client(embed_fn); - - tracing::info!("[VikingCommands] Embedding configured with provider: {} (both storage systems)", provider); + tracing::info!("[VikingCommands] Embedding configured with provider: {}", provider); Ok(EmbeddingConfigResult { provider, diff --git a/docs/TRUTH.md b/docs/TRUTH.md index a353981..a57cac3 100644 --- a/docs/TRUTH.md +++ b/docs/TRUTH.md @@ -1,7 +1,7 @@ # ZCLAW 系统真相文档 -> **更新日期**: 2026-04-12 -> **数据来源**: V11 全面审计 + 二次审计 + V12 模块化端到端审计 + 代码全量扫描验证 + 功能测试 Phase 1-5 + 发布前功能测试 Phase 3 + 发布前全面测试代码级审计 + 2026-04-11 代码验证 + V13 系统性功能审计 2026-04-12 +> **更新日期**: 2026-04-13 +> **数据来源**: V11 全面审计 + 二次审计 + V12 模块化端到端审计 + 代码全量扫描验证 + 功能测试 Phase 1-5 + 发布前功能测试 Phase 3 + 发布前全面测试代码级审计 + 2026-04-11 代码验证 + V13 系统性功能审计 2026-04-12 + V13 审计修复 2026-04-13 > **规则**: 此文档是唯一真相源。所有其他文档如果与此冲突，以此为准。 --- @@ -14,10 +14,10 @@ | Rust 代码行数 | ~77,000 (crates) + ~61,400 (src-tauri) = ~138,400 | wc -l (2026-04-12 V13 验证) | | Rust 单元测试 | 433 个 (#[test]) + 368 个 (#[tokio::test]) = 801 | `grep '#\[test\]' crates/` + `grep '#\[tokio::test\]'` (2026-04-12 V13 验证) | | Rust 测试运行通过 | 684 workspace + 138 SaaS = 822 | Hermes 4 Chunk `cargo test --workspace` 2026-04-09 | -| Tauri 命令 | 191 个 (2026-04-12 V13 验证) | `grep '#\[.*tauri::command'` | -| **Tauri 命令有前端调用** | **106 处** | `grep invoke( desktop/src/` (2026-04-12 V13 验证) | -| **Tauri 命令已标注 @reserved** | **24 个** | Rust 源码 @reserved 标注 (2026-04-12 V13 验证) | -| **Tauri 命令孤儿 (无调用+无标注)** | ~61 个 | 191 - 106 invoke处 - 24 @reserved ≈ 61 | +| Tauri 命令 | 189 个 (2026-04-13 V13 修复验证) | `grep '#\[.*tauri::command'` | +| **Tauri 命令有前端调用** | **105 处** | `grep invoke( desktop/src/` (2026-04-13 V13 修复验证) | +| **Tauri 命令已标注 @reserved** | **22 个** | Rust 源码 @reserved 标注 (2026-04-13 V13 修复验证) | +| **Tauri 命令孤儿 (无调用+无标注)** | ~62 个 | 189 - 105 invoke处 - 22 @reserved ≈ 62 | | SKILL.md 文件 | 75 个 | `ls skills/*.md \| wc -l` | | Hands 启用 | 9 个 | Browser/Collector/Researcher/Clip/Twitter/Whiteboard/Slideshow/Speech/Quiz（均有 HAND.toml） | | Hands 禁用 | 2 个 | Predictor, Lead（概念定义存在，无 TOML 配置文件或 Rust 实现） | @@ -35,7 +35,7 @@ | Admin V2 页面 | 15 个 | admin-v2/src/pages/ 全量统计（含 ScheduledTasks、ConfigSync） | | 桌面端设置页面 | 19 个 | SettingsLayout.tsx tabs: 通用/用量统计/积分详情/模型与API/MCP服务/技能/IM频道/工作区/数据与隐私/安全存储/SaaS平台/订阅与计费/语义记忆/安全状态/审计日志/定时任务/心跳配置/提交反馈/关于 | | Admin V2 测试 | 17 个文件 (61 tests) | vitest 统计 | -| 中间件层 | 14 层 | 运行时注册（含 DataMasking@90, ButlerRouter@500, TrajectoryRecorder@650） | +| 中间件层 | 15 层 | 运行时注册（含 DataMasking@90, ButlerRouter@500, TrajectoryRecorder@650 — V13注册） | --- diff --git a/wiki/log.md b/wiki/log.md index d563627..f7cf2bc 100644 --- a/wiki/log.md +++ b/wiki/log.md @@ -198,8 +198,8 @@ Phase 5 — 主动行为激活 (3 files, 152 insertions): - FIX-03 (P1): 桌面端知识库搜索 — saas-knowledge mixin + VikingPanel SaaS KB 搜索 UI - FIX-04 (P2): Webhook 孤儿迁移标注 deprecated + down migration 注释 - FIX-05 (P2): Admin Knowledge 新增"结构化数据"Tab (CRUD + 行浏览) -- FIX-06 (P2): PersistentMemoryStore dead_code 精化标注 (完整迁移留后续) -- 文件: 11 个 (Rust 4 + TS 7), 358 行新增, 1 次提交 +- FIX-06 (P2): PersistentMemoryStore 全量移除 — persistent.rs 611→57行，删除死 embedding global + 2 @reserved 命令 + viking_commands 冗余配置，Tauri 命令 191→189 +- 文件: 13 个 (Rust 5 + TS 7 + docs 1), 提交: c167ea4 + fd3e7fd + 本轮 - P0: memory_search 空查询 min_similarity 默认值; hand_trigger null→handAutoTrigger; 重启后 chat 路由竞态修复 - P1: AgentInfo 扩展 UserProfile 桥接; 反思阈值降低 5→3; 反思 state restore peek+pop 竞态修复