Update delete, query APIs to support new changes

README.md

@@ -66,33 +66,40 @@ import ballerinax/ai.weaviate;
 
 ```ballerina
 ai:VectorStore vectorStore = check new weaviate:VectorStore(
-    serviceUrl = "add-weaviate-service-url", 
-    config = {
-        className: "add-collection-name"
-    }, 
-    auth = {
-        token: "add-access-token"
-    }
+   serviceUrl = "add-weaviate-service-url", 
+   config = {
+      collectionName: "add-collection-name"
+   }, 
+   auth = {
+      token: "add-access-token"
+   }
 );
 ```
 
 ### Step 3: Add vectors
 
 ```ballerina
 ai:Error? result = vectorStore.add(
-    [
-        {
-            id: uuid:createRandomUuid(),
-            embedding: [1.0, 2.0, 3.0],
-            chunk: {
-                'type: "text", 
-                content: "This is a chunk"
-            }
-        }
-    ]
+   [
+      {
+         id: uuid:createRandomUuid(),
+         embedding: [1.0, 2.0, 3.0],
+         chunk: {
+            'type: "text", 
+            content: "This is a chunk"
+         }
+      }
+   ]
 );
 ```
 
+## Examples
+
+The Ballerina Weaviate vector store module provides practical examples illustrating usage in various scenarios. Explore these [examples](https://github.com/ballerina-platform/module-ballerinax-ai.weaviate/tree/main/examples).
+
+1. [Book Recommendation System](https://github.com/ballerina-platform/module-ballerinax-ai.weaviate/tree/main/examples/book-recommendation-system)
+   This example shows how to use Weaviate vector store APIs to implement a book recommendation system that stores book embeddings and queries them to find similar books based on vector similarity and metadata filtering.
+
 ## Issues and projects
 
 Issues and Projects tabs are disabled for this repository as this is part of the Ballerina Library. To report bugs, request new features, start new discussions, view project boards, etc., go to the [Ballerina Library parent repository](https://github.com/ballerina-platform/ballerina-standard-library).

ballerina/Dependencies.toml

@@ -10,7 +10,7 @@ distribution-version = "2201.12.0"
 [[package]]
 org = "ballerina"
 name = "ai"
-version = "1.1.4"
+version = "1.5.0"
 dependencies = [
 	{org = "ballerina", name = "constraint"},
 	{org = "ballerina", name = "data.jsondata"},
@@ -87,7 +87,7 @@ dependencies = [
 [[package]]
 org = "ballerina"
 name = "data.xmldata"
-version = "1.4.2"
+version = "1.5.0"
 dependencies = [
 	{org = "ballerina", name = "jballerina.java"},
 	{org = "ballerina", name = "lang.object"}
@@ -241,6 +241,14 @@ dependencies = [
 	{org = "ballerina", name = "lang.regexp"}
 ]
 
+[[package]]
+org = "ballerina"
+name = "lang.transaction"
+version = "0.0.0"
+dependencies = [
+	{org = "ballerina", name = "jballerina.java"}
+]
+
 [[package]]
 org = "ballerina"
 name = "lang.value"
@@ -391,6 +399,27 @@ dependencies = [
 	{org = "ballerina", name = "observe"}
 ]
 
+[[package]]
+org = "ballerinai"
+name = "transaction"
+version = "0.0.0"
+dependencies = [
+	{org = "ballerina", name = "cache"},
+	{org = "ballerina", name = "http"},
+	{org = "ballerina", name = "io"},
+	{org = "ballerina", name = "jballerina.java"},
+	{org = "ballerina", name = "lang.runtime"},
+	{org = "ballerina", name = "lang.transaction"},
+	{org = "ballerina", name = "lang.value"},
+	{org = "ballerina", name = "log"},
+	{org = "ballerina", name = "task"},
+	{org = "ballerina", name = "time"},
+	{org = "ballerina", name = "uuid"}
+]
+modules = [
+	{org = "ballerinai", packageName = "transaction", moduleName = "transaction"}
+]
+
 [[package]]
 org = "ballerinax"
 name = "ai.weaviate"
@@ -400,6 +429,7 @@ dependencies = [
 	{org = "ballerina", name = "http"},
 	{org = "ballerina", name = "test"},
 	{org = "ballerina", name = "uuid"},
+	{org = "ballerinai", name = "transaction"},
 	{org = "ballerinax", name = "weaviate"}
 ]
 modules = [

ballerina/README.md

@@ -63,7 +63,7 @@ import ballerinax/ai.weaviate;
 ai:VectorStore vectorStore = check new weaviate:VectorStore(
     serviceUrl = "add-weaviate-service-url", 
     config = {
-        className: "add-collection-name"
+        collectionName: "add-collection-name"
     }, 
     auth = {
         token: "add-access-token"
@@ -87,3 +87,10 @@ ai:Error? result = vectorStore.add(
     ]
 );
 ```
+
+## Examples
+
+The Ballerina Weaviate vector store module provides practical examples illustrating usage in various scenarios. Explore these [examples](https://github.com/ballerina-platform/module-ballerinax-ai.weaviate/tree/main/examples).
+
+1. [Book Recommendation System](https://github.com/ballerina-platform/module-ballerinax-ai.weaviate/tree/main/examples/book-recommendation-system)
+   This example shows how to use Weaviate vector store APIs to implement a book recommendation system that stores book embeddings and queries them to find similar books based on vector similarity and metadata filtering.

ballerina/tests/test.bal

@@ -28,11 +28,13 @@ final VectorStore mockVectorStore = check new (
     }
 );
 
+string id = uuid:createRandomUuid();
+
 @test:Config {}
 function testAddingValuesToVectorStore() returns error? {
     ai:VectorEntry[] entries = [
         {
-            id: uuid:createRandomUuid(),
+            id,
             embedding: [1.0, 2.0, 3.0],
             chunk: {
                 'type: "text", 
@@ -45,15 +47,32 @@ function testAddingValuesToVectorStore() returns error? {
 }
 
 @test:Config {}
-function testDeleteValuesFromVectorStore() returns error? {
-    ai:Error? result = mockVectorStore.delete("mock-id");
+function testDeleteValueFromVectorStore() returns error? {
+    ai:Error? result = mockVectorStore.delete(id);
+    test:assertTrue(result !is error);
+}
+
+@test:Config {}
+function testDeleteMultipleValuesFromVectorStore() returns error? {
+    string index = uuid:createRandomUuid();
+    ai:VectorEntry[] entries = [
+        {
+            id: index,
+            embedding: [1.0, 2.0, 3.0],
+            chunk: {
+                'type: "text", 
+                content: "This is a test chunk"
+            }
+        }
+    ];
+    _ = check mockVectorStore.add(entries);
+    ai:Error? result = mockVectorStore.delete([id, index]);
     test:assertTrue(result !is error);
 }
 
 @test:Config {}
 function testQueryValuesFromVectorStore() returns error? {
     ai:VectorStoreQuery query = {
-        embedding: [1.0, 2.0, 3.0],
         filters: {
             filters: [
                 {
@@ -67,3 +86,48 @@ function testQueryValuesFromVectorStore() returns error? {
     ai:VectorMatch[]|ai:Error result = mockVectorStore.query(query);
     test:assertTrue(result !is error);
 }
+
+@test:Config {}
+function testVectorStoreInitializationWithInvalidURL() returns error? {
+    VectorStore store = check new (
+        serviceUrl = "invalid-url",
+        config = {
+            collectionName: "TestChunk"
+        },
+        auth = {
+            token: "test-token"
+        }
+    );
+    ai:VectorMatch[]|ai:Error result = store.query({
+        topK: 0,
+        embedding: [1.0, 2.0, 3.0]
+    });
+    test:assertTrue(result is ai:Error);
+}
+
+@test:Config {}
+function testAddEmptyVectorEntriesArray() returns error? {
+    ai:VectorEntry[] emptyEntries = [];
+    ai:Error? result = mockVectorStore.add(emptyEntries);
+    test:assertTrue(result is error, "");
+}
+
+@test:Config {}
+function testQueryWithTopKZero() returns error? {
+    ai:VectorStoreQuery query = {
+        topK: 0,
+        embedding: [1.0, 2.0, 3.0]
+    };
+    ai:VectorMatch[]|ai:Error result = mockVectorStore.query(query);
+    test:assertTrue(result is error);
+}
+
+@test:Config {}
+function testQueryWithNegativeTopK() returns error? {
+    ai:VectorStoreQuery query = {
+        topK: -5,
+        embedding: [1.0, 2.0, 3.0]
+    };
+    ai:VectorMatch[]|ai:Error result = mockVectorStore.query(query);
+    test:assertTrue(result is error);
+}

ballerina/types.bal

@@ -19,17 +19,15 @@
 #
 # + collectionName - The name of the collection to use
 # + chunkFieldName - The name of the field to contain the chunk details
-# + topK - The number of top similar vectors to return in queries
 public type Configuration record {|
     string collectionName;
     string chunkFieldName?;
-    int topK = 10;
 |};
 
 type QueryResult record {
     record {
         string? id;
-        float certainty;
+        float? certainty;
         float[] vector;
     } _additional;
     string content?;