Fix Go vector search result output (#32)

* Fix search result output

* Clarify environment variables

Author: PatAltimore

mongo-vcore-vector-search-go/.env.example

@@ -19,10 +19,10 @@ EMBEDDING_SIZE_BATCH=16
 
 # Data File Configuration
 # Path to source JSON file without vector embeddings
-DATA_FILE_WITHOUT_VECTORS=../data/HotelsData_toCosmosDB.json
+DATA_FILE_WITHOUT_VECTORS=data/HotelsData_toCosmosDB.json
 
 # Path to JSON file with generated vector embeddings
-DATA_FILE_WITH_VECTORS=../data/HotelsData_toCosmosDB_Vector.json
+DATA_FILE_WITH_VECTORS=data/HotelsData_toCosmosDB_Vector.json
 
 # Path to JSON file with vector similarity data (optional)
 DATA_FILE_WITH_SIMILARITY=data/HotelsData_with_similarity.json

mongo-vcore-vector-search-go/README.md

@@ -124,8 +124,8 @@ MONGO_CONNECTION_STRING=mongodb+srv://username:password@your-cluster.mongocluste
 MONGO_CLUSTER_NAME=vectorSearch
 
 # Data Configuration (defaults should work)
-DATA_FILE_WITHOUT_VECTORS=../data/HotelsData_toCosmosDB_Vector.json
-DATA_FILE_WITH_VECTORS=../data/HotelsData_toCosmosDB_Vector.json
+DATA_FILE_WITHOUT_VECTORS=data/HotelsData_toCosmosDB_Vector.json
+DATA_FILE_WITH_VECTORS=data/HotelsData_toCosmosDB_Vector.json
 FIELD_TO_EMBED=Description
 EMBEDDED_FIELD=DescriptionVector
 EMBEDDING_DIMENSIONS=1536

mongo-vcore-vector-search-go/src/create_embeddings.go

@@ -105,12 +105,12 @@ func ProcessEmbeddingBatch(ctx context.Context, dataBatch []map[string]interface
 
 // EmbeddingConfig holds configuration for the embedding creation process
 type EmbeddingConfig struct {
-	ModelName     string
-	InputFile     string
-	OutputFile    string
-	FieldToEmbed  string
-	EmbeddedField string
-	BatchSize     int
+	ModelName          string
+	DataWithoutVectors string
+	DataWithVectors    string
+	FieldToEmbed       string
+	EmbeddedField      string
+	BatchSize          int
 }
 
 // LoadEmbeddingConfig loads configuration from environment variables
@@ -124,12 +124,12 @@ func LoadEmbeddingConfig() *EmbeddingConfig {
 	batchSize, _ := strconv.Atoi(getEnvOrDefault("EMBEDDING_SIZE_BATCH", "16"))
 
 	return &EmbeddingConfig{
-		ModelName:     getEnvOrDefault("AZURE_OPENAI_EMBEDDING_MODEL", "text-embedding-ada-002"),
-		InputFile:     getEnvOrDefault("DATA_FILE_WITHOUT_VECTORS", "data/HotelsData_toCosmosDB_Vector.json"),
-		OutputFile:    getEnvOrDefault("DATA_FILE_WITH_VECTORS", "data/HotelsData_with_vectors.json"),
-		FieldToEmbed:  getEnvOrDefault("FIELD_TO_EMBED", "Description"),
-		EmbeddedField: getEnvOrDefault("EMBEDDED_FIELD", "DescriptionVector"),
-		BatchSize:     batchSize,
+		ModelName:          getEnvOrDefault("AZURE_OPENAI_EMBEDDING_MODEL", "text-embedding-ada-002"),
+		DataWithoutVectors: getEnvOrDefault("DATA_FILE_WITHOUT_VECTORS", "HotelsData_toCosmosDB.json"),
+		DataWithVectors:    getEnvOrDefault("DATA_FILE_WITH_VECTORS", "data/HotelsData_toCosmosDB_Vector.json"),
+		FieldToEmbed:       getEnvOrDefault("FIELD_TO_EMBED", "Description"),
+		EmbeddedField:      getEnvOrDefault("EMBEDDED_FIELD", "DescriptionVector"),
+		BatchSize:          batchSize,
 	}
 }
 
@@ -149,8 +149,8 @@ func main() {
 	config := LoadEmbeddingConfig()
 
 	fmt.Printf("Configuration:\n")
-	fmt.Printf("  Input file: %s\n", config.InputFile)
-	fmt.Printf("  Output file: %s\n", config.OutputFile)
+	fmt.Printf("  Input file: %s\n", config.DataWithoutVectors)
+	fmt.Printf("  Output file: %s\n", config.DataWithVectors)
 	fmt.Printf("  Field to embed: %s\n", config.FieldToEmbed)
 	fmt.Printf("  Embedding field: %s\n", config.EmbeddedField)
 	fmt.Printf("  Batch size: %d\n", config.BatchSize)
@@ -169,8 +169,8 @@ func main() {
 	}()
 
 	// Read the input data file
-	fmt.Printf("\nReading input data from %s...\n", config.InputFile)
-	data, err := ReadFileReturnJSON(config.InputFile)
+	fmt.Printf("\nReading input data from %s...\n", config.DataWithoutVectors)
+	data, err := ReadFileReturnJSON(config.DataWithoutVectors)
 	if err != nil {
 		log.Fatalf("Failed to read input file: %v", err)
 	}
@@ -212,8 +212,8 @@ func main() {
 	}
 
 	// Save the enhanced data with embeddings
-	fmt.Printf("\nSaving enhanced data to %s...\n", config.OutputFile)
-	err = WriteFileJSON(data, config.OutputFile)
+	fmt.Printf("\nSaving enhanced data to %s...\n", config.DataWithVectors)
+	err = WriteFileJSON(data, config.DataWithVectors)
 	if err != nil {
 		log.Fatalf("Failed to save output file: %v", err)
 	}

mongo-vcore-vector-search-go/src/utils.go

@@ -402,27 +402,24 @@ func PrintSearchResults(results []SearchResult, maxResults int, showScore bool)
 	for i := 0; i < maxResults; i++ {
 		result := results[i]
 
-		// Extract hotel data from the document
+		// Extract HotelName from document (assuming bson.D structure)
+		doc := result.Document.(bson.D)
 		var hotelName string
-		if doc, ok := result.Document.(bson.M); ok {
-			if name, exists := doc["HotelName"]; exists {
-				hotelName = fmt.Sprintf("%v", name)
-			}
-		} else if doc, ok := result.Document.(map[string]interface{}); ok {
-			if name, exists := doc["HotelName"]; exists {
-				hotelName = fmt.Sprintf("%v", name)
+		for _, elem := range doc {
+			if elem.Key == "HotelName" {
+				hotelName = fmt.Sprintf("%v", elem.Value)
+				break
 			}
 		}
 
+		// Display results
+		fmt.Printf("%d. HotelName: %s", i+1, hotelName)
+
 		if showScore {
-			fmt.Printf("HotelName: %s, Score: %.4f\n", hotelName, result.Score)
-		} else {
-			fmt.Printf("HotelName: %s\n", hotelName)
+			fmt.Printf(", Score: %.4f", result.Score)
 		}
-	}
 
-	if len(results) > maxResults {
-		fmt.Printf("\n... and %d more results\n", len(results)-maxResults)
+		fmt.Println()
 	}
 }