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P0: - BUG-H1: Dashboard 路由 /api/v1/stats/dashboard → /api/v1/admin/dashboard P1: - BUG-H2: viking_add 预检查 content_hash 去重，返回 "deduped" 状态；SqliteStorage 启动时回填已有条目 content_hash - BUG-M5: saas-relay-client 发送前调用 viking_inject_prompt 注入跨会话记忆 P2: - BUG-M1: PaymentResult 添加 invoice_id 字段，query_payment_status 返回 invoice_id - BUG-M2: UpdatePromptRequest 添加内容字段，更新时自动创建新版本并递增 current_version - BUG-M3: viking_find scope 参数文档化（设计行为，调用方需传 agent scope） - BUG-M4: Dashboard 路由缺失已修复，handler 层 require_admin 已正确返回 403 P3 (确认已修复/非代码问题): - BUG-L1: pain_seed_categories 已统一，无 pain_seeds 残留 - BUG-L2: pipeline_create 参数格式正确，E2E 测试方法问题
1049 lines
38 KiB
Rust
1049 lines
38 KiB
Rust
//! SQLite Storage Backend
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//!
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//! Persistent storage backend using SQLite for production use.
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//! Provides efficient querying and full-text search capabilities.
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use crate::retrieval::semantic::{EmbeddingClient, SemanticScorer};
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use crate::types::MemoryEntry;
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use crate::viking_adapter::{FindOptions, VikingStorage};
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use async_trait::async_trait;
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use sqlx::sqlite::{SqlitePool, SqlitePoolOptions, SqliteRow};
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use sqlx::Row;
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use std::path::PathBuf;
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use std::sync::Arc;
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use tokio::sync::RwLock;
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use zclaw_types::Result;
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use zclaw_types::ZclawError;
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/// SQLite storage backend with TF-IDF semantic scoring
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pub struct SqliteStorage {
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/// Database connection pool
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pool: SqlitePool,
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/// Semantic scorer for similarity computation
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scorer: Arc<RwLock<SemanticScorer>>,
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/// Database path (for reference)
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#[allow(dead_code)]
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path: PathBuf,
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}
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/// Database row structure for memory entry
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pub(crate) struct MemoryRow {
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uri: String,
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memory_type: String,
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content: String,
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keywords: String,
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importance: i32,
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access_count: i32,
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created_at: String,
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last_accessed: String,
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overview: Option<String>,
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abstract_summary: Option<String>,
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}
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impl SqliteStorage {
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/// Get a reference to the underlying connection pool
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pub fn pool(&self) -> &SqlitePool {
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&self.pool
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}
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/// Create a new SQLite storage at the given path
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pub async fn new(path: impl Into<PathBuf>) -> Result<Self> {
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let path = path.into();
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// Ensure parent directory exists
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if let Some(parent) = path.parent() {
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if parent.to_str() != Some(":memory:") {
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tokio::fs::create_dir_all(parent).await.map_err(|e| {
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ZclawError::StorageError(format!("Failed to create storage directory: {}", e))
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})?;
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}
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}
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// Build connection string
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let db_url = if path.to_str() == Some(":memory:") {
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"sqlite::memory:".to_string()
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} else {
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format!("sqlite:{}?mode=rwc", path.to_string_lossy())
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};
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// Create connection pool
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let pool = SqlitePoolOptions::new()
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.max_connections(5)
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.connect(&db_url)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to connect to database: {}", e)))?;
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let storage = Self {
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pool,
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scorer: Arc::new(RwLock::new(SemanticScorer::new())),
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path,
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};
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storage.initialize_schema().await?;
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storage.warmup_scorer().await?;
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Ok(storage)
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}
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/// Create an in-memory SQLite database (for testing)
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pub async fn in_memory() -> Self {
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Self::new(":memory:").await.expect("Failed to create in-memory database")
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}
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/// Configure embedding client for semantic search
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/// Replaces the current scorer with a new one that has embedding support
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pub async fn configure_embedding(
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&self,
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client: Arc<dyn EmbeddingClient>,
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) -> Result<()> {
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let new_scorer = SemanticScorer::with_embedding(client);
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let mut scorer = self.scorer.write().await;
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*scorer = new_scorer;
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tracing::info!("[SqliteStorage] Embedding client configured, re-indexing with embeddings...");
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self.warmup_scorer_with_embedding().await
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}
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/// Check if embedding is available
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pub async fn is_embedding_available(&self) -> bool {
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let scorer = self.scorer.read().await;
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scorer.is_embedding_available()
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}
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/// Initialize database schema with FTS5
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async fn initialize_schema(&self) -> Result<()> {
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// Create main memories table
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sqlx::query(
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r#"
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CREATE TABLE IF NOT EXISTS memories (
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uri TEXT PRIMARY KEY,
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memory_type TEXT NOT NULL,
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content TEXT NOT NULL,
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keywords TEXT NOT NULL DEFAULT '[]',
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importance INTEGER NOT NULL DEFAULT 5,
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access_count INTEGER NOT NULL DEFAULT 0,
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created_at TEXT NOT NULL,
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last_accessed TEXT NOT NULL
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)
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"#,
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)
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to create memories table: {}", e)))?;
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// Create FTS5 virtual table for full-text search
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// Use trigram tokenizer for CJK (Chinese/Japanese/Korean) support.
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// unicode61 cannot tokenize CJK characters, causing memory search to fail.
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// trigram indexes overlapping 3-character slices, works well for all languages.
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sqlx::query(
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r#"
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CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
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uri,
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content,
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keywords,
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tokenize='trigram'
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)
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"#,
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)
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to create FTS5 table: {}", e)))?;
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// Create index on memory_type for filtering
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sqlx::query("CREATE INDEX IF NOT EXISTS idx_memory_type ON memories(memory_type)")
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to create index: {}", e)))?;
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// Create index on importance for sorting
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sqlx::query("CREATE INDEX IF NOT EXISTS idx_importance ON memories(importance DESC)")
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to create importance index: {}", e)))?;
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// Migration: add overview column (L1 summary)
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let _ = sqlx::query("ALTER TABLE memories ADD COLUMN overview TEXT")
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.execute(&self.pool)
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.await;
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// Migration: add abstract_summary column (L0 keywords)
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let _ = sqlx::query("ALTER TABLE memories ADD COLUMN abstract_summary TEXT")
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.execute(&self.pool)
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.await;
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// P2-24: Migration — content fingerprint for deduplication
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let _ = sqlx::query("ALTER TABLE memories ADD COLUMN content_hash TEXT")
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.execute(&self.pool)
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.await;
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let _ = sqlx::query("CREATE INDEX IF NOT EXISTS idx_content_hash ON memories(content_hash)")
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.execute(&self.pool)
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.await;
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// Backfill content_hash for existing entries that have NULL content_hash
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{
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use std::hash::{Hash, Hasher};
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let rows: Vec<(String, String)> = sqlx::query_as(
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"SELECT uri, content FROM memories WHERE content_hash IS NULL"
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)
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.fetch_all(&self.pool)
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.await
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.unwrap_or_default();
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if !rows.is_empty() {
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for (uri, content) in &rows {
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let normalized = content.trim().to_lowercase();
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let mut hasher = std::collections::hash_map::DefaultHasher::new();
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normalized.hash(&mut hasher);
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let hash = format!("{:016x}", hasher.finish());
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let _ = sqlx::query("UPDATE memories SET content_hash = ? WHERE uri = ?")
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.bind(&hash)
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.bind(uri)
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.execute(&self.pool)
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.await;
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}
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tracing::info!(
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"[SqliteStorage] Backfilled content_hash for {} existing entries",
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rows.len()
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);
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}
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}
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// Create metadata table
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sqlx::query(
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r#"
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CREATE TABLE IF NOT EXISTS metadata (
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key TEXT PRIMARY KEY,
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json TEXT NOT NULL
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)
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"#,
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)
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to create metadata table: {}", e)))?;
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// Migration: Rebuild FTS5 table if using old unicode61 tokenizer (can't handle CJK)
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// Check tokenizer by inspecting the existing FTS5 table definition
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let needs_rebuild: bool = sqlx::query_scalar::<_, i64>(
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"SELECT COUNT(*) FROM sqlite_master WHERE type='table' AND name='memories_fts' AND sql LIKE '%unicode61%'"
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)
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.fetch_one(&self.pool)
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.await
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.unwrap_or(0) > 0;
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if needs_rebuild {
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tracing::info!("[SqliteStorage] Rebuilding FTS5 table: unicode61 → trigram for CJK support");
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// Drop old FTS5 table
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let _ = sqlx::query("DROP TABLE IF EXISTS memories_fts")
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.execute(&self.pool)
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.await;
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// Recreate with trigram tokenizer
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sqlx::query(
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r#"
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CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
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uri,
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content,
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keywords,
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tokenize='trigram'
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)
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"#,
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)
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to recreate FTS5 table: {}", e)))?;
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// Reindex all existing memories into FTS5
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let reindexed = sqlx::query(
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"INSERT INTO memories_fts (uri, content, keywords) SELECT uri, content, keywords FROM memories"
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)
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.execute(&self.pool)
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.await
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.map(|r| r.rows_affected())
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.unwrap_or(0);
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tracing::info!("[SqliteStorage] FTS5 rebuild complete, reindexed {} entries", reindexed);
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}
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tracing::info!("[SqliteStorage] Database schema initialized");
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Ok(())
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}
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/// Warmup semantic scorer with existing entries
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async fn warmup_scorer(&self) -> Result<()> {
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let rows = sqlx::query_as::<_, MemoryRow>(
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"SELECT uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary FROM memories"
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)
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.fetch_all(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to load memories for warmup: {}", e)))?;
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let mut scorer = self.scorer.write().await;
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for row in rows {
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let entry = self.row_to_entry(&row);
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scorer.index_entry(&entry);
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}
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let stats = scorer.stats();
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tracing::info!(
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"[SqliteStorage] Warmed up scorer with {} entries, {} terms",
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stats.indexed_entries,
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stats.unique_terms
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);
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Ok(())
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}
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/// Warmup semantic scorer with embedding support for existing entries
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async fn warmup_scorer_with_embedding(&self) -> Result<()> {
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let rows = sqlx::query_as::<_, MemoryRow>(
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"SELECT uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary FROM memories"
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)
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.fetch_all(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to load memories for warmup: {}", e)))?;
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let mut scorer = self.scorer.write().await;
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for row in rows {
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let entry = self.row_to_entry(&row);
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scorer.index_entry_with_embedding(&entry).await;
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}
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let stats = scorer.stats();
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tracing::info!(
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"[SqliteStorage] Warmed up scorer with {} entries ({} with embeddings), {} terms",
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stats.indexed_entries,
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stats.embedding_entries,
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stats.unique_terms
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);
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Ok(())
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}
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/// Convert database row to MemoryEntry
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fn row_to_entry(&self, row: &MemoryRow) -> MemoryEntry {
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let memory_type = crate::types::MemoryType::parse(&row.memory_type);
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let keywords: Vec<String> = serde_json::from_str(&row.keywords).unwrap_or_default();
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let created_at = chrono::DateTime::parse_from_rfc3339(&row.created_at)
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.map(|dt| dt.with_timezone(&chrono::Utc))
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.unwrap_or_else(|_| chrono::Utc::now());
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let last_accessed = chrono::DateTime::parse_from_rfc3339(&row.last_accessed)
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.map(|dt| dt.with_timezone(&chrono::Utc))
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.unwrap_or_else(|_| chrono::Utc::now());
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MemoryEntry {
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uri: row.uri.clone(),
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memory_type,
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content: row.content.clone(),
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keywords,
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importance: row.importance as u8,
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access_count: row.access_count as u32,
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created_at,
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last_accessed,
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overview: row.overview.clone(),
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abstract_summary: row.abstract_summary.clone(),
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}
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}
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/// Update access count and last accessed time
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async fn touch_entry(&self, uri: &str) -> Result<()> {
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let now = chrono::Utc::now().to_rfc3339();
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sqlx::query(
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"UPDATE memories SET access_count = access_count + 1, last_accessed = ? WHERE uri = ?"
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)
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.bind(&now)
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.bind(uri)
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.execute(&self.pool)
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.await
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.map_err(|e| ZclawError::StorageError(format!("Failed to update access count: {}", e)))?;
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Ok(())
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}
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/// Decay stale memories: reduce importance for long-unaccessed entries
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/// and archive those below the minimum threshold.
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///
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/// - For every `decay_interval_days` since last access, importance drops by 1.
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/// - Memories with importance ≤ `archive_threshold` are deleted.
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pub async fn decay_memories(
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&self,
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decay_interval_days: u32,
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archive_threshold: u8,
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) -> crate::types::DecayResult {
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// Step 1: Reduce importance of stale memories
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let decay_result = sqlx::query(
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r#"
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UPDATE memories
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SET importance = MAX(1, importance - CAST(
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(julianday('now') - julianday(last_accessed)) / ? AS INTEGER
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))
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WHERE last_accessed < datetime('now', '-' || ? || ' days')
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AND importance > 1
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"#,
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)
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.bind(decay_interval_days)
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.bind(decay_interval_days)
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.execute(&self.pool)
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.await;
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let decayed = decay_result
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.map(|r| r.rows_affected())
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.unwrap_or(0);
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// Step 2: Remove memories that fell below archive threshold
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// and haven't been accessed in 90+ days
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let archive_result = sqlx::query(
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r#"
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DELETE FROM memories
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WHERE importance <= ?
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AND last_accessed < datetime('now', '-90 days')
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"#,
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)
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.bind(archive_threshold as i32)
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.execute(&self.pool)
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.await;
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|
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// Also clean up FTS entries for archived memories
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let _ = sqlx::query(
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r#"
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DELETE FROM memories_fts
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WHERE uri NOT IN (SELECT uri FROM memories)
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"#,
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)
|
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.execute(&self.pool)
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.await;
|
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let archived = archive_result
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.map(|r| r.rows_affected())
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.unwrap_or(0);
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if decayed > 0 || archived > 0 {
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tracing::info!(
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"[SqliteStorage] Memory decay: {} decayed, {} archived",
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decayed,
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archived
|
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);
|
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}
|
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|
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crate::types::DecayResult { decayed, archived }
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}
|
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}
|
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|
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impl sqlx::FromRow<'_, SqliteRow> for MemoryRow {
|
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fn from_row(row: &SqliteRow) -> sqlx::Result<Self> {
|
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Ok(MemoryRow {
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uri: row.try_get("uri")?,
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memory_type: row.try_get("memory_type")?,
|
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content: row.try_get("content")?,
|
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keywords: row.try_get("keywords")?,
|
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importance: row.try_get("importance")?,
|
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access_count: row.try_get("access_count")?,
|
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created_at: row.try_get("created_at")?,
|
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last_accessed: row.try_get("last_accessed")?,
|
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overview: row.try_get("overview").ok(),
|
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abstract_summary: row.try_get("abstract_summary").ok(),
|
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})
|
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}
|
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}
|
|
|
|
/// Private helper methods on SqliteStorage (NOT in impl VikingStorage block)
|
|
impl SqliteStorage {
|
|
/// Sanitize a user query for FTS5 MATCH syntax.
|
|
///
|
|
/// FTS5 treats several characters as operators (`+`, `-`, `*`, `"`, `(`, `)`, `:`).
|
|
/// Strips these and keeps only alphanumeric + CJK tokens with length > 1,
|
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/// then joins them with `OR` for broad matching.
|
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fn sanitize_fts_query(query: &str) -> String {
|
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// trigram tokenizer requires quoted phrases for substring matching
|
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// and needs at least 3 characters per term to produce results.
|
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let lower = query.to_lowercase();
|
|
|
|
// Check if query contains CJK characters — trigram handles them natively
|
|
let has_cjk = lower.chars().any(|c| {
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matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}')
|
|
});
|
|
|
|
if has_cjk {
|
|
// For CJK, use the full query as a quoted phrase for substring matching
|
|
// trigram will match any 3-char subsequence
|
|
if lower.len() >= 3 {
|
|
format!("\"{}\"", lower)
|
|
} else {
|
|
String::new()
|
|
}
|
|
} else {
|
|
// For non-CJK, split into terms and join with OR
|
|
let terms: Vec<String> = lower
|
|
.split(|c: char| !c.is_alphanumeric())
|
|
.filter(|s| !s.is_empty() && s.len() > 1)
|
|
.map(|s| format!("\"{}\"", s))
|
|
.collect();
|
|
|
|
if terms.is_empty() {
|
|
return String::new();
|
|
}
|
|
|
|
terms.join(" OR ")
|
|
}
|
|
}
|
|
|
|
/// Fetch memories by scope with importance-based ordering.
|
|
/// Used internally by find() for scope-based queries.
|
|
pub(crate) async fn fetch_by_scope_priv(&self, scope: Option<&str>, limit: usize) -> Result<Vec<MemoryRow>> {
|
|
let rows = if let Some(scope) = scope {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary
|
|
FROM memories
|
|
WHERE uri LIKE ?
|
|
ORDER BY importance DESC, access_count DESC
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(format!("{}%", scope))
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to fetch by scope: {}", e)))?
|
|
} else {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary
|
|
FROM memories
|
|
ORDER BY importance DESC
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to fetch by scope: {}", e)))?
|
|
};
|
|
Ok(rows)
|
|
}
|
|
}
|
|
|
|
#[async_trait]
|
|
impl VikingStorage for SqliteStorage {
|
|
async fn store(&self, entry: &MemoryEntry) -> Result<()> {
|
|
let keywords_json = serde_json::to_string(&entry.keywords)
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to serialize keywords: {}", e)))?;
|
|
|
|
let created_at = entry.created_at.to_rfc3339();
|
|
let last_accessed = entry.last_accessed.to_rfc3339();
|
|
let memory_type = entry.memory_type.to_string();
|
|
|
|
// P2-24: Content-hash deduplication
|
|
let normalized_content = entry.content.trim().to_lowercase();
|
|
let content_hash = {
|
|
use std::hash::{Hash, Hasher};
|
|
let mut hasher = std::collections::hash_map::DefaultHasher::new();
|
|
normalized_content.hash(&mut hasher);
|
|
format!("{:016x}", hasher.finish())
|
|
};
|
|
|
|
// Check for existing entry with the same content hash (within same agent scope)
|
|
let agent_scope = entry.uri.split('/').nth(2).unwrap_or("");
|
|
let existing: Option<(String, i32, i32)> = sqlx::query_as::<_, (String, i32, i32)>(
|
|
"SELECT uri, importance, access_count FROM memories WHERE content_hash = ? AND uri LIKE ? LIMIT 1"
|
|
)
|
|
.bind(&content_hash)
|
|
.bind(format!("agent://{agent_scope}/%"))
|
|
.fetch_optional(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Dedup check failed: {}", e)))?;
|
|
|
|
if let Some((existing_uri, existing_importance, existing_access)) = existing {
|
|
// Merge: keep higher importance, bump access count, update last_accessed
|
|
let merged_importance = existing_importance.max(entry.importance as i32);
|
|
let merged_access = existing_access + 1;
|
|
sqlx::query(
|
|
"UPDATE memories SET importance = ?, access_count = ?, last_accessed = ? WHERE uri = ?"
|
|
)
|
|
.bind(merged_importance)
|
|
.bind(merged_access)
|
|
.bind(&last_accessed)
|
|
.bind(&existing_uri)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Dedup merge failed: {}", e)))?;
|
|
|
|
tracing::debug!(
|
|
"[SqliteStorage] Dedup: merged '{}' into existing '{}' (importance={}, access_count={})",
|
|
entry.uri, existing_uri, merged_importance, merged_access
|
|
);
|
|
return Ok(());
|
|
}
|
|
|
|
// Insert into main table
|
|
sqlx::query(
|
|
r#"
|
|
INSERT OR REPLACE INTO memories
|
|
(uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary, content_hash)
|
|
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
|
"#,
|
|
)
|
|
.bind(&entry.uri)
|
|
.bind(&memory_type)
|
|
.bind(&entry.content)
|
|
.bind(&keywords_json)
|
|
.bind(entry.importance as i32)
|
|
.bind(entry.access_count as i32)
|
|
.bind(&created_at)
|
|
.bind(&last_accessed)
|
|
.bind(&entry.overview)
|
|
.bind(&entry.abstract_summary)
|
|
.bind(&content_hash)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to store memory: {}", e)))?;
|
|
|
|
// Update FTS index - delete old and insert new
|
|
let _ = sqlx::query("DELETE FROM memories_fts WHERE uri = ?")
|
|
.bind(&entry.uri)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| {
|
|
tracing::warn!("[SqliteStorage] Failed to delete old FTS entry: {}", e);
|
|
});
|
|
|
|
let keywords_text = entry.keywords.join(" ");
|
|
let _ = sqlx::query(
|
|
r#"
|
|
INSERT INTO memories_fts (uri, content, keywords)
|
|
VALUES (?, ?, ?)
|
|
"#,
|
|
)
|
|
.bind(&entry.uri)
|
|
.bind(&entry.content)
|
|
.bind(&keywords_text)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| {
|
|
tracing::warn!("[SqliteStorage] Failed to insert FTS entry: {}", e);
|
|
});
|
|
|
|
// Update semantic scorer (use embedding when available)
|
|
let mut scorer = self.scorer.write().await;
|
|
if scorer.is_embedding_available() {
|
|
scorer.index_entry_with_embedding(entry).await;
|
|
} else {
|
|
scorer.index_entry(entry);
|
|
}
|
|
|
|
tracing::debug!("[SqliteStorage] Stored memory: {}", entry.uri);
|
|
Ok(())
|
|
}
|
|
|
|
async fn get(&self, uri: &str) -> Result<Option<MemoryEntry>> {
|
|
let row = sqlx::query_as::<_, MemoryRow>(
|
|
"SELECT uri, memory_type, content, keywords, importance, access_count, created_at, last_accessed, overview, abstract_summary FROM memories WHERE uri = ?"
|
|
)
|
|
.bind(uri)
|
|
.fetch_optional(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to get memory: {}", e)))?;
|
|
|
|
if let Some(row) = row {
|
|
let entry = self.row_to_entry(&row);
|
|
|
|
// Update access count
|
|
self.touch_entry(&entry.uri).await?;
|
|
|
|
Ok(Some(entry))
|
|
} else {
|
|
Ok(None)
|
|
}
|
|
}
|
|
|
|
async fn find(&self, query: &str, options: FindOptions) -> Result<Vec<MemoryEntry>> {
|
|
let limit = options.limit.unwrap_or(50).max(20); // Fetch more candidates for reranking
|
|
|
|
// Strategy: use FTS5 for initial filtering when query is non-empty,
|
|
// then score candidates with TF-IDF / embedding for precise ranking.
|
|
// When FTS5 returns nothing, we return empty — do NOT fall back to
|
|
// scope scan (that returns irrelevant high-importance memories).
|
|
let rows = if !query.is_empty() {
|
|
// Sanitize query for FTS5: strip operators that cause syntax errors
|
|
let sanitized = Self::sanitize_fts_query(query);
|
|
|
|
if sanitized.is_empty() {
|
|
// Query had no meaningful terms after sanitization (e.g., "1+2")
|
|
tracing::debug!(
|
|
"[SqliteStorage] Query '{}' produced no FTS5-searchable terms, skipping",
|
|
query.chars().take(50).collect::<String>()
|
|
);
|
|
return Ok(Vec::new());
|
|
}
|
|
|
|
// FTS5-powered candidate retrieval (fast, index-based)
|
|
let fts_candidates = if let Some(ref scope) = options.scope {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT m.uri, m.memory_type, m.content, m.keywords, m.importance,
|
|
m.access_count, m.created_at, m.last_accessed, m.overview, m.abstract_summary
|
|
FROM memories m
|
|
INNER JOIN memories_fts f ON m.uri = f.uri
|
|
WHERE f.memories_fts MATCH ?
|
|
AND m.uri LIKE ?
|
|
ORDER BY f.rank
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(&sanitized)
|
|
.bind(format!("{}%", scope))
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
} else {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT m.uri, m.memory_type, m.content, m.keywords, m.importance,
|
|
m.access_count, m.created_at, m.last_accessed, m.overview, m.abstract_summary
|
|
FROM memories m
|
|
INNER JOIN memories_fts f ON m.uri = f.uri
|
|
WHERE f.memories_fts MATCH ?
|
|
ORDER BY f.rank
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(&sanitized)
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
};
|
|
|
|
match fts_candidates {
|
|
Ok(rows) if !rows.is_empty() => rows,
|
|
Ok(_) | Err(_) => {
|
|
// FTS5 returned no results or failed — check if query contains CJK
|
|
// characters. unicode61 tokenizer doesn't index CJK, so fall back
|
|
// to LIKE-based search for CJK queries.
|
|
let has_cjk = query.chars().any(|c| {
|
|
matches!(c, '\u{4E00}'..='\u{9FFF}' | '\u{3400}'..='\u{4DBF}' | '\u{F900}'..='\u{FAFF}')
|
|
});
|
|
|
|
if !has_cjk {
|
|
tracing::debug!(
|
|
"[SqliteStorage] FTS5 returned no results for query: '{}'",
|
|
query.chars().take(50).collect::<String>()
|
|
);
|
|
return Ok(Vec::new());
|
|
}
|
|
|
|
tracing::debug!(
|
|
"[SqliteStorage] FTS5 miss for CJK query, falling back to LIKE: '{}'",
|
|
query.chars().take(50).collect::<String>()
|
|
);
|
|
|
|
let pattern = format!("%{}%", query);
|
|
if let Some(ref scope) = options.scope {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT uri, memory_type, content, keywords, importance,
|
|
access_count, created_at, last_accessed, overview, abstract_summary
|
|
FROM memories
|
|
WHERE content LIKE ?
|
|
AND uri LIKE ?
|
|
ORDER BY importance DESC, access_count DESC
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(&pattern)
|
|
.bind(format!("{}%", scope))
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
.unwrap_or_default()
|
|
} else {
|
|
sqlx::query_as::<_, MemoryRow>(
|
|
r#"
|
|
SELECT uri, memory_type, content, keywords, importance,
|
|
access_count, created_at, last_accessed, overview, abstract_summary
|
|
FROM memories
|
|
WHERE content LIKE ?
|
|
ORDER BY importance DESC, access_count DESC
|
|
LIMIT ?
|
|
"#
|
|
)
|
|
.bind(&pattern)
|
|
.bind(limit as i64)
|
|
.fetch_all(&self.pool)
|
|
.await
|
|
.unwrap_or_default()
|
|
}
|
|
}
|
|
}
|
|
} else {
|
|
// Empty query: scope-based scan only (no FTS5 needed)
|
|
self.fetch_by_scope_priv(options.scope.as_deref(), limit).await?
|
|
};
|
|
|
|
// Convert to entries and compute semantic scores
|
|
let use_embedding = {
|
|
let scorer = self.scorer.read().await;
|
|
scorer.is_embedding_available()
|
|
};
|
|
|
|
let mut scored_entries: Vec<(f32, f32, MemoryEntry)> = Vec::new();
|
|
|
|
for row in rows {
|
|
let entry = self.row_to_entry(&row);
|
|
|
|
// Compute semantic score: use embedding when available, fallback to TF-IDF
|
|
let semantic_score = if use_embedding {
|
|
let scorer = self.scorer.read().await;
|
|
let tfidf_score = scorer.score_similarity(query, &entry);
|
|
let entry_embedding = scorer.get_entry_embedding(&entry.uri);
|
|
drop(scorer);
|
|
|
|
match entry_embedding {
|
|
Some(entry_emb) => {
|
|
// Try embedding the query for hybrid scoring
|
|
let embedding_client = {
|
|
let scorer2 = self.scorer.read().await;
|
|
scorer2.get_embedding_client()
|
|
};
|
|
|
|
match embedding_client.embed(query).await {
|
|
Ok(query_emb) => {
|
|
let emb_score = SemanticScorer::cosine_similarity_embedding(&query_emb, &entry_emb);
|
|
// Hybrid: 70% embedding + 30% TF-IDF
|
|
emb_score * 0.7 + tfidf_score * 0.3
|
|
}
|
|
Err(_) => {
|
|
tracing::debug!("[SqliteStorage] Query embedding failed, using TF-IDF only");
|
|
tfidf_score
|
|
}
|
|
}
|
|
}
|
|
None => tfidf_score,
|
|
}
|
|
} else {
|
|
let scorer = self.scorer.read().await;
|
|
scorer.score_similarity(query, &entry)
|
|
};
|
|
|
|
// Apply similarity threshold
|
|
if let Some(min_similarity) = options.min_similarity {
|
|
if semantic_score < min_similarity {
|
|
continue;
|
|
}
|
|
}
|
|
|
|
// Apply time decay to importance before final scoring
|
|
let time_decayed_importance = crate::types::effective_importance(&entry);
|
|
|
|
scored_entries.push((semantic_score, time_decayed_importance, entry));
|
|
}
|
|
|
|
// Sort by: semantic score → time-decayed importance → access count (all descending)
|
|
scored_entries.sort_by(|a, b| {
|
|
b.0.partial_cmp(&a.0)
|
|
.unwrap_or(std::cmp::Ordering::Equal)
|
|
.then_with(|| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal))
|
|
.then_with(|| b.2.access_count.cmp(&a.2.access_count))
|
|
});
|
|
|
|
// Apply limit
|
|
if let Some(limit) = options.limit {
|
|
scored_entries.truncate(limit);
|
|
}
|
|
|
|
Ok(scored_entries.into_iter().map(|(_, _, entry)| entry).collect())
|
|
}
|
|
|
|
async fn find_by_prefix(&self, prefix: &str) -> Result<Vec<MemoryEntry>> {
|
|
let rows = self.fetch_by_scope_priv(Some(prefix), 100).await?;
|
|
let entries = rows.iter().map(|row| self.row_to_entry(row)).collect();
|
|
Ok(entries)
|
|
}
|
|
|
|
async fn delete(&self, uri: &str) -> Result<()> {
|
|
sqlx::query("DELETE FROM memories WHERE uri = ?")
|
|
.bind(uri)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to delete memory: {}", e)))?;
|
|
|
|
// Remove from FTS index
|
|
let _ = sqlx::query("DELETE FROM memories_fts WHERE uri = ?")
|
|
.bind(uri)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| {
|
|
tracing::warn!("[SqliteStorage] Failed to delete FTS entry: {}", e);
|
|
});
|
|
|
|
// Remove from in-memory scorer
|
|
let mut scorer = self.scorer.write().await;
|
|
scorer.remove_entry(uri);
|
|
|
|
tracing::debug!("[SqliteStorage] Deleted memory: {}", uri);
|
|
Ok(())
|
|
}
|
|
|
|
async fn store_metadata_json(&self, key: &str, json: &str) -> Result<()> {
|
|
sqlx::query(
|
|
r#"
|
|
INSERT OR REPLACE INTO metadata (key, json)
|
|
VALUES (?, ?)
|
|
"#,
|
|
)
|
|
.bind(key)
|
|
.bind(json)
|
|
.execute(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to store metadata: {}", e)))?;
|
|
|
|
Ok(())
|
|
}
|
|
|
|
async fn get_metadata_json(&self, key: &str) -> Result<Option<String>> {
|
|
let result = sqlx::query_scalar::<_, String>("SELECT json FROM metadata WHERE key = ?")
|
|
.bind(key)
|
|
.fetch_optional(&self.pool)
|
|
.await
|
|
.map_err(|e| ZclawError::StorageError(format!("Failed to get metadata: {}", e)))?;
|
|
|
|
Ok(result)
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
use crate::types::MemoryType;
|
|
|
|
#[tokio::test]
|
|
async fn test_sqlite_storage_store_and_get() {
|
|
let storage = SqliteStorage::in_memory().await;
|
|
let entry = MemoryEntry::new(
|
|
"test-agent",
|
|
MemoryType::Preference,
|
|
"style",
|
|
"User prefers concise responses".to_string(),
|
|
);
|
|
|
|
storage.store(&entry).await.unwrap();
|
|
let retrieved = storage.get(&entry.uri).await.unwrap();
|
|
|
|
assert!(retrieved.is_some());
|
|
assert_eq!(retrieved.unwrap().content, "User prefers concise responses");
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_sqlite_storage_semantic_search() {
|
|
let storage = SqliteStorage::in_memory().await;
|
|
|
|
// Store entries with different content
|
|
let entry1 = MemoryEntry::new(
|
|
"agent-1",
|
|
MemoryType::Knowledge,
|
|
"rust",
|
|
"Rust is a systems programming language focused on safety".to_string(),
|
|
).with_keywords(vec!["rust".to_string(), "programming".to_string(), "safety".to_string()]);
|
|
|
|
let entry2 = MemoryEntry::new(
|
|
"agent-1",
|
|
MemoryType::Knowledge,
|
|
"python",
|
|
"Python is a high-level programming language".to_string(),
|
|
).with_keywords(vec!["python".to_string(), "programming".to_string()]);
|
|
|
|
storage.store(&entry1).await.unwrap();
|
|
storage.store(&entry2).await.unwrap();
|
|
|
|
// Search for "rust safety"
|
|
let results = storage.find(
|
|
"rust safety",
|
|
FindOptions {
|
|
scope: Some("agent://agent-1".to_string()),
|
|
limit: Some(10),
|
|
min_similarity: Some(0.1),
|
|
},
|
|
).await.unwrap();
|
|
|
|
// Should find the Rust entry with higher score
|
|
assert!(!results.is_empty());
|
|
assert!(results[0].content.contains("Rust"));
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_sqlite_storage_delete() {
|
|
let storage = SqliteStorage::in_memory().await;
|
|
let entry = MemoryEntry::new(
|
|
"test-agent",
|
|
MemoryType::Preference,
|
|
"style",
|
|
"test".to_string(),
|
|
);
|
|
|
|
storage.store(&entry).await.unwrap();
|
|
storage.delete(&entry.uri).await.unwrap();
|
|
|
|
let retrieved = storage.get(&entry.uri).await.unwrap();
|
|
assert!(retrieved.is_none());
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_persistence() {
|
|
let path = std::env::temp_dir().join("zclaw_test_memories.db");
|
|
|
|
// Clean up any existing test db
|
|
let _ = std::fs::remove_file(&path);
|
|
|
|
// Create and store
|
|
{
|
|
let storage = SqliteStorage::new(&path).await.unwrap();
|
|
let entry = MemoryEntry::new(
|
|
"persist-test",
|
|
MemoryType::Knowledge,
|
|
"test",
|
|
"This should persist".to_string(),
|
|
);
|
|
storage.store(&entry).await.unwrap();
|
|
}
|
|
|
|
// Reopen and verify
|
|
{
|
|
let storage = SqliteStorage::new(&path).await.unwrap();
|
|
let results = storage.find_by_prefix("agent://persist-test").await.unwrap();
|
|
assert!(!results.is_empty());
|
|
assert_eq!(results[0].content, "This should persist");
|
|
}
|
|
|
|
// Clean up
|
|
let _ = std::fs::remove_file(&path);
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_metadata_storage() {
|
|
let storage = SqliteStorage::in_memory().await;
|
|
|
|
let json = r#"{"test": "value"}"#;
|
|
storage.store_metadata_json("test-key", json).await.unwrap();
|
|
|
|
let retrieved = storage.get_metadata_json("test-key").await.unwrap();
|
|
assert_eq!(retrieved, Some(json.to_string()));
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_access_count() {
|
|
let storage = SqliteStorage::in_memory().await;
|
|
let entry = MemoryEntry::new(
|
|
"test-agent",
|
|
MemoryType::Knowledge,
|
|
"test",
|
|
"test content".to_string(),
|
|
);
|
|
|
|
storage.store(&entry).await.unwrap();
|
|
|
|
// Access multiple times
|
|
for _ in 0..3 {
|
|
let _ = storage.get(&entry.uri).await.unwrap();
|
|
}
|
|
|
|
let retrieved = storage.get(&entry.uri).await.unwrap().unwrap();
|
|
assert!(retrieved.access_count >= 3);
|
|
}
|
|
}
|