Added basic hnsw query test (raw vector result)

Tests/SwiftNLPTests/2. Encoding/HNSWTests.swift

@@ -103,6 +103,39 @@ final class HNSWTests: XCTestCase {
         XCTAssert(corpus.count == 17999)
     }
     
+    // Refer to AllMiniLM_sampleTest.swift for reference
+    func testBasicQueryExample() async throws {
+
+        let docs = [
+            "The quick brown fox jumps over the lazy dog",
+            "I enjoy taking long walks along the beach at sunset",
+            "Advances in neural networks have enabled new AI capabilities",
+            "The stock market experienced a significant downturn last week",
+            "Cooking a good meal can be both an art and a science",
+            "The exploration of space is both challenging and rewarding",
+            "Machine learning models are becoming increasingly sophisticated",
+            "I love reading about history and ancient civilizations"
+        ]
+
+        let query = "I like to read about new technology and artificial intelligence"
+        
+        let _documentEncoder = ContextFreeEncoder<Double>(source: .glove6B50d)
+        var corpus = HNSWCorpus(encoder: _documentEncoder)
+        corpus.addUntokenizedDocuments(docs)
+        
+        let size = MemoryLayout.size(ofValue: corpus)
+        print("Approximate memory footprint: \(size) bytes")
+        
+        do {
+            print("Attempting to query corpus.encodedDocuments.find()...")
+            let query_embedding: [Double] = _documentEncoder.encodeToken(query).map { Double($0) }
+            let results = try corpus.encodedDocuments.find(near: query_embedding, limit: 8)
+            print(results)
+            print("Query successful!")
+        } catch {
+            print("Error when trying corpus.encodedDocuments.find: \(error)")
+        }
+    }
 }
 #endif