Bump up to version 1.14.0

src/ai/embedding.rs

@@ -202,10 +202,10 @@ async fn ollama(
             }
         }
     }
-    log::info!(
-        "Ollama embedding result {:?} {:?}",
-        embedding_result.get(0),
-        embedding_result.get(1)
-    );
+    // log::info!(
+    //     "Ollama embedding result {:?} {:?}",
+    //     embedding_result.get(0),
+    //     embedding_result.get(1)
+    // );
     Ok(embedding_result)
 }

src/db/embedding.rs

@@ -46,8 +46,11 @@ fn get_idx_db() -> Result<Database> {
 
 async fn create_idx_db(robot_id: &str) -> Result<()> {
     let config = SourceConfig::new(robot_id, "id", "vectors").with_metadata(vec!["intent_id"]);
-    let params = ParamsIVFPQ::default();
-    let algorithm = IndexAlgorithm::IVFPQ(params);
+    // let params = ParamsIVFPQ::default();
+    // let algorithm = IndexAlgorithm::IVFPQ(params);
+    let mut params = ParamsFlat::default();
+    params.metric = oasysdb::types::distance::DistanceMetric::Cosine;
+    let algorithm = IndexAlgorithm::Flat(params);
     get_idx_db()?
         .async_create_index(robot_id, algorithm, config)
         .await?;
@@ -104,7 +107,7 @@ pub(crate) async fn init_datasource() -> Result<()> {
         .acquire_timeout(Duration::from_secs(5))
         .test_before_acquire(true);
     let conn_str = get_sqlite_url()?;
-    log::info!("Embedding database path: {}", &conn_str);
+    // log::info!("Embedding database path: {}", &conn_str);
     let pool = pool_ops.connect(conn_str.as_str()).await?;
     DATA_SOURCE
         .set(pool)

src/intent/detector.rs

@@ -5,17 +5,19 @@ use crate::result::{Error, Result};
 pub(crate) async fn detect(robot_id: &str, s: &str) -> Result<Option<String>> {
     // let now = std::time::Instant::now();
     let embedding = embedding(robot_id, s).await?;
+    // log::info!("Generate embedding cost {:?}", now.elapsed());
     // let s = format!("{:?}", &embedding);
     // let regex = regex::Regex::new(r"\s").unwrap();
     // log::info!("detect embedding {}", regex.replace_all(&s, ""));
+    // let now = std::time::Instant::now();
     let search_vector: Vec<f32> = embedding.0.into();
     let similarity_threshold = embedding.1;
     let result = embedding_db::search_idx_db(robot_id, search_vector.into())?;
-    // println!("inner intent detect {:?}", now.elapsed());
-    if result.len() == 0 {
+    // log::info!("Searching vector took {:?}", now.elapsed());
+    if !result.is_empty() {
         if let Some(record) = result.get(0) {
             log::info!("Record distance: {}", record.distance);
-            if similarity_threshold >= record.distance {
+            if (1f32 - record.distance) >= similarity_threshold {
                 if let Some(data) = record.data.get("intent_id") {
                     if let Some(metadata) = data {
                         if let oasysdb::types::record::DataValue::String(s) = metadata {