Patched re-ranking for JavaScript

korvus/javascript/package.json

@@ -1,6 +1,6 @@
 {
   "name": "korvus",
-  "version": "1.1.2",
+  "version": "1.1.3",
   "description": "Open Source Alternative for Building End-to-End Vector Search Applications without OpenAI & Pinecone",
   "keywords": [
     "postgres",

korvus/javascript/tests/typescript-tests/test.ts

@@ -164,6 +164,46 @@ it("can vector search with query builder", async () => {
   await collection.archive();
 });
 
+it("can vector search with re-ranking", async () => {
+  let pipeline = korvus.newPipeline("1", {
+    title: {
+      semantic_search: { model: "intfloat/e5-small-v2", parameters: { prompt: "passage: " } },
+      full_text_search: { configuration: "english" },
+    },
+    body: {
+      splitter: { model: "recursive_character" },
+      semantic_search: {
+        model: "text-embedding-ada-002",
+        source: "openai",
+      },
+    },
+  });
+  let collection = korvus.newCollection("test_j_c_cvswr_0")
+  await collection.add_pipeline(pipeline)
+  await collection.upsert_documents(generate_dummy_documents(5))
+  let results = await collection.vector_search(
+    {
+      query: {
+        fields: {
+          title: { query: "Test document: 2", parameters: { prompt: "query: " }, full_text_filter: "test" },
+          body: { query: "Test document: 2" },
+        },
+        filter: { id: { "$gt": 2 } },
+      },
+      rerank: {
+        model: "mixedbread-ai/mxbai-rerank-base-v1",
+        query: "Test query",
+        num_documents_to_rerank: 100
+      },
+      limit: 5,
+    },
+    pipeline,
+  );
+  let ids = results.map(r => r["document"]["id"]);
+  expect(ids).toEqual([4, 3, 3, 4]);
+  await collection.archive();
+});
+
 ///////////////////////////////////////////////////
 // Test rag ///////////////////////////////////////
 ///////////////////////////////////////////////////

korvus/python/tests/test.py

@@ -212,6 +212,60 @@ async def test_can_vector_search_with_query_builder():
     await collection.archive()
 
 
+@pytest.mark.asyncio
+async def test_can_vector_search_with_rerank():
+    pipeline = korvus.Pipeline(
+        "test_p_p_tcvswr_0",
+        {
+            "title": {
+                "semantic_search": {
+                    "model": "intfloat/e5-small-v2",
+                    "parameters": {"prompt": "passage: "},
+                },
+                "full_text_search": {"configuration": "english"},
+            },
+            "text": {
+                "splitter": {"model": "recursive_character"},
+                "semantic_search": {
+                    "model": "intfloat/e5-small-v2",
+                    "parameters": {"prompt": "passage: "},
+                },
+            },
+        },
+    )
+    collection = korvus.Collection("test_p_c_tcvs_3")
+    await collection.add_pipeline(pipeline)
+    await collection.upsert_documents(generate_dummy_documents(5))
+    results = await collection.vector_search(
+        {
+            "query": {
+                "fields": {
+                    "title": {
+                        "query": "Test document: 2",
+                        "parameters": {"prompt": "passage: "},
+                        "full_text_filter": "test",
+                    },
+                    "text": {
+                        "query": "Test document: 2",
+                        "parameters": {"prompt": "passage: "},
+                    },
+                },
+                "filter": {"id": {"$gt": 2}},
+            },
+            "rerank": {
+                "model": "mixedbread-ai/mxbai-rerank-base-v1",
+                "query": "Test query",
+                "num_documents_to_rerank": 100,
+            },
+            "limit": 5,
+        },
+        pipeline,
+    )
+    ids = [result["document"]["id"] for result in results]
+    assert ids == [3, 3, 4, 4]
+    await collection.archive()
+
+
 ###################################################
 ## Test RAG #######################################
 ###################################################

korvus/src/collection.rs

@@ -345,7 +345,7 @@ impl Collection {
         let pool = get_or_initialize_pool(&self.database_url).await?;
         let pipelines_table_name = format!("{}.pipelines", project_info.name);
         let exists: bool = sqlx::query_scalar(&query_builder!(
-            "SELECT EXISTS (SELECT id FROM %s WHERE name = $1 AND active = TRUE)",
+            "SELECT EXISTS (SELECT id FROM %s WHERE name = $1)",
             pipelines_table_name
         ))
         .bind(&pipeline.name)

korvus/src/lib.rs

@@ -610,7 +610,7 @@ mod tests {
     #[tokio::test]
     async fn can_upsert_documents_and_enable_pipeline() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test_r_c_cudaep_43";
+        let collection_name = "test_r_c_cudaep_44";
         let mut collection = Collection::new(collection_name, None)?;
         let pipeline_name = "0";
         let mut pipeline = Pipeline::new(
@@ -654,7 +654,7 @@ mod tests {
     #[tokio::test]
     async fn random_pipelines_documents_test() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test_r_c_rpdt_3";
+        let collection_name = "test_r_c_rpdt_4";
         let mut collection = Collection::new(collection_name, None)?;
         let documents = generate_dummy_documents(6);
         collection
@@ -818,7 +818,7 @@ mod tests {
     #[tokio::test]
     async fn pipeline_sync_status() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test_r_c_pss_6";
+        let collection_name = "test_r_c_pss_7";
         let mut collection = Collection::new(collection_name, None)?;
         let pipeline_name = "0";
         let mut pipeline = Pipeline::new(
@@ -1140,7 +1140,7 @@ mod tests {
     #[tokio::test]
     async fn can_search_with_remote_embeddings() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test r_c_cswre_66";
+        let collection_name = "test r_c_cswre_67";
         let mut collection = Collection::new(collection_name, None)?;
         let documents = generate_dummy_documents(10);
         collection.upsert_documents(documents.clone(), None).await?;
@@ -1314,7 +1314,7 @@ mod tests {
     #[tokio::test]
     async fn can_vector_search_with_remote_embeddings() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test r_c_cvswre_7";
+        let collection_name = "test r_c_cvswre_8";
         let mut collection = Collection::new(collection_name, None)?;
         let documents = generate_dummy_documents(10);
         collection.upsert_documents(documents.clone(), None).await?;
@@ -1455,7 +1455,7 @@ mod tests {
     async fn can_vector_search_with_local_embeddings_and_specify_document_keys(
     ) -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test r_c_cvswleasdk_1";
+        let collection_name = "test r_c_cvswleasdk_2";
         let mut collection = Collection::new(collection_name, None)?;
         let documents = generate_dummy_documents(2);
         collection.upsert_documents(documents.clone(), None).await?;
@@ -1556,7 +1556,7 @@ mod tests {
     #[tokio::test]
     async fn can_vector_search_with_local_embeddings_and_rerank() -> anyhow::Result<()> {
         internal_init_logger(None, None).ok();
-        let collection_name = "test r_c_cvswlear_1";
+        let collection_name = "test r_c_cvswlear_2";
         let mut collection = Collection::new(collection_name, None)?;
         let documents = generate_dummy_documents(10);
         collection.upsert_documents(documents.clone(), None).await?;

korvus/src/vector_search_query_builder.rs

@@ -45,12 +45,14 @@ const fn default_num_documents_to_rerank() -> u64 {
     10
 }
 
+#[serde_as]
 #[derive(Debug, Deserialize, Serialize, Clone)]
 #[serde(deny_unknown_fields)]
 struct ValidRerank {
     query: String,
     model: String,
     #[serde(default = "default_num_documents_to_rerank")]
+    #[serde_as(as = "FromInto<CustomU64Convertor>")]
     num_documents_to_rerank: u64,
     parameters: Option<Json>,
 }
@@ -61,7 +63,7 @@ const fn default_limit() -> u64 {
 
 #[serde_as]
 #[derive(Debug, Deserialize, Serialize, Clone)]
-// #[serde(deny_unknown_fields)]
+#[serde(deny_unknown_fields)]
 pub struct ValidQuery {
     query: ValidQueryActions,
     // Need this when coming from JavaScript as everything is an f64 from JS