feat: created vector search

Author: bimawa

kq-cli/src/main.rs

@@ -85,14 +85,12 @@ struct SearchArgs {
     /// Use full-text search (default, on by default)
     #[arg(long, default_value_t = true)]
     fts: bool,
-
     /// Path to the knowledge repository (auto-detected by default)
     #[arg(long, value_name = "PATH")]
     repo: Option<PathBuf>,
-
-/// Use vector search (requires embedding model)
-#[arg(long, default_value_t = false)]
-vector: bool,
+    /// Use vector search (requires embedding model)
+    #[arg(long, default_value_t = false)]
+    vector: bool,
 }
 
 #[derive(Parser)]
@@ -418,6 +416,28 @@ fn main() -> Result<()> {
                     return Ok(());
                     }
 
+            if args.vector {
+                let mut model = kq_embeddings::EmbeddingModel::new(
+                    &repo_path.join(".kq/model-cache")
+                )?;
+                match model.load() {
+                    Ok(()) => {
+                        let emb = model.embed(&args.query)?;
+                        let results = kq_core::vector::hybrid_search(
+                            &conn, &args.query, &emb, args.limit, args.limit
+                        )?;
+                        for r in &results {
+                            println!("  {:6.2}  {}", r.score, r.path);
+                        }
+                    }
+                    Err(e) => {
+                        eprintln!("Vector search unavailable: {e}");
+                        eprintln!("Model will be downloaded on first vector search.");
+                    }
+                }
+                return Ok(());
+            }
+
             let results = kq_core::search::search_fts(&conn, &args.query, args.limit)?;
 
             if results.is_empty() {

kq-core/src/db.rs

@@ -29,6 +29,7 @@ pub fn init_db(db_path: &Path) -> Result<()> {
     }
 
     let conn = Connection::open(db_path)?;
+    crate::vector::register_vec_on_connection(&conn)?;
     create_schema(&conn)?;
     DB.set(Mutex::new(conn))
         .map_err(|_| anyhow::anyhow!("Database already initialized (race)"))?;
@@ -135,6 +136,8 @@ pub fn create_schema(conn: &Connection) -> Result<()> {
         CREATE INDEX IF NOT EXISTS idx_code_anchors_anchor ON code_anchors(anchor);
         ",
     )?;
+    // Initialize vector embedding tables
+    crate::vector::init_vector(conn)?;
     Ok(())
 }