.Net: Update Milvus and MongoDB memory connectors (#4218)

### Motivation and Context

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Related item: #3997

### Description
1. Validate the following memory connectors: Chroma, MongoDB, Milvus,
and Weaviate, by running the integration tests.
2. Update the README of the MongoDB memory connector to make it easier
to follow.
3. Add an optional parameter named `indexName` to the constructors of
the Milvus memory connector. Otherwise, it will fail to find an index.

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

dotnet/src/Connectors/Connectors.Memory.Milvus/MilvusMemoryStore.cs

@@ -22,7 +22,9 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
     private readonly int _vectorSize;
     private readonly SimilarityMetricType _metricType;
     private readonly bool _ownsMilvusClient;
+    private readonly string _indexName;
 
+    private const string DefaultIndexName = "default";
     private const string IsReferenceFieldName = "is_reference";
     private const string ExternalSourceNameFieldName = "external_source_name";
     private const string IdFieldName = "id";
@@ -62,12 +64,13 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
     /// <summary>
     /// Creates a new <see cref="MilvusMemoryStore" />, connecting to the given hostname on the default Milvus port of 19530.
     /// For more advanced configuration opens, construct a <see cref="MilvusClient" /> instance and pass it to
-    /// <see cref="MilvusMemoryStore(MilvusClient, int, SimilarityMetricType)" />.
+    /// <see cref="MilvusMemoryStore(MilvusClient, string, int, SimilarityMetricType)" />.
     /// </summary>
     /// <param name="host">The hostname or IP address to connect to.</param>
     /// <param name="port">The port to connect to. Defaults to 19530.</param>
     /// <param name="ssl">Whether to use TLS/SSL. Defaults to <c>false</c>.</param>
     /// <param name="database">The database to connect to. Defaults to the default Milvus database.</param>
+    /// <param name="indexName">The name of the index to use. Defaults to <see cref="DefaultIndexName" />.</param>
     /// <param name="vectorSize">The size of the vectors used in Milvus. Defaults to 1536.</param>
     /// <param name="metricType">The metric used to measure similarity between vectors. Defaults to <see cref="SimilarityMetricType.Ip" />.</param>
     /// <param name="loggerFactory">An optional logger factory through which the Milvus client will log.</param>
@@ -76,25 +79,27 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
         int port = DefaultMilvusPort,
         bool ssl = false,
         string? database = null,
+        string? indexName = null,
         int vectorSize = 1536,
         SimilarityMetricType metricType = SimilarityMetricType.Ip,
         ILoggerFactory? loggerFactory = null)
-        : this(new MilvusClient(host, port, ssl, database, callOptions: default, loggerFactory), vectorSize, metricType)
+        : this(new MilvusClient(host, port, ssl, database, callOptions: default, loggerFactory), indexName, vectorSize, metricType)
     {
         this._ownsMilvusClient = true;
     }
 
     /// <summary>
     /// Creates a new <see cref="MilvusMemoryStore" />, connecting to the given hostname on the default Milvus port of 19530.
     /// For more advanced configuration opens, construct a <see cref="MilvusClient" /> instance and pass it to
-    /// <see cref="MilvusMemoryStore(MilvusClient, int, SimilarityMetricType)" />.
+    /// <see cref="MilvusMemoryStore(MilvusClient, string, int, SimilarityMetricType)" />.
     /// </summary>
     /// <param name="host">The hostname or IP address to connect to.</param>
     /// <param name="username">The username to use for authentication.</param>
     /// <param name="password">The password to use for authentication.</param>
     /// <param name="port">The port to connect to. Defaults to 19530.</param>
     /// <param name="ssl">Whether to use TLS/SSL. Defaults to <c>false</c>.</param>
     /// <param name="database">The database to connect to. Defaults to the default Milvus database.</param>
+    /// <param name="indexName">The name of the index to use. Defaults to <see cref="DefaultIndexName" />.</param>
     /// <param name="vectorSize">The size of the vectors used in Milvus. Defaults to 1536.</param>
     /// <param name="metricType">The metric used to measure similarity between vectors. Defaults to <see cref="SimilarityMetricType.Ip" />.</param>
     /// <param name="loggerFactory">An optional logger factory through which the Milvus client will log.</param>
@@ -105,24 +110,26 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
         int port = DefaultMilvusPort,
         bool ssl = false,
         string? database = null,
+        string? indexName = null,
         int vectorSize = 1536,
         SimilarityMetricType metricType = SimilarityMetricType.Ip,
         ILoggerFactory? loggerFactory = null)
-        : this(new MilvusClient(host, username, password, port, ssl, database, callOptions: default, loggerFactory), vectorSize, metricType)
+        : this(new MilvusClient(host, username, password, port, ssl, database, callOptions: default, loggerFactory), indexName, vectorSize, metricType)
     {
         this._ownsMilvusClient = true;
     }
 
     /// <summary>
     /// Creates a new <see cref="MilvusMemoryStore" />, connecting to the given hostname on the default Milvus port of 19530.
     /// For more advanced configuration opens, construct a <see cref="MilvusClient" /> instance and pass it to
-    /// <see cref="MilvusMemoryStore(MilvusClient, int, SimilarityMetricType)" />.
+    /// <see cref="MilvusMemoryStore(MilvusClient, string, int, SimilarityMetricType)" />.
     /// </summary>
     /// <param name="host">The hostname or IP address to connect to.</param>
     /// <param name="apiKey">An API key to be used for authentication, instead of a username and password.</param>
     /// <param name="port">The port to connect to. Defaults to 19530.</param>
     /// <param name="ssl">Whether to use TLS/SSL. Defaults to <c>false</c>.</param>
     /// <param name="database">The database to connect to. Defaults to the default Milvus database.</param>
+    /// <param name="indexName">The name of the index to use. Defaults to <see cref="DefaultIndexName" />.</param>
     /// <param name="vectorSize">The size of the vectors used in Milvus. Defaults to 1536.</param>
     /// <param name="metricType">The metric used to measure similarity between vectors. Defaults to <see cref="SimilarityMetricType.Ip" />.</param>
     /// <param name="loggerFactory">An optional logger factory through which the Milvus client will log.</param>
@@ -132,10 +139,11 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
         int port = DefaultMilvusPort,
         bool ssl = false,
         string? database = null,
+        string? indexName = null,
         int vectorSize = 1536,
         SimilarityMetricType metricType = SimilarityMetricType.Ip,
         ILoggerFactory? loggerFactory = null)
-        : this(new MilvusClient(host, apiKey, port, ssl, database, callOptions: default, loggerFactory), vectorSize, metricType)
+        : this(new MilvusClient(host, apiKey, port, ssl, database, callOptions: default, loggerFactory), indexName, vectorSize, metricType)
     {
         this._ownsMilvusClient = true;
     }
@@ -144,23 +152,27 @@ public class MilvusMemoryStore : IMemoryStore, IDisposable
     /// Initializes a new instance of <see cref="MilvusMemoryStore" /> over the given <see cref="MilvusClient" />.
     /// </summary>
     /// <param name="client">A <see cref="MilvusClient" /> configured with the necessary endpoint and authentication information.</param>
+    /// <param name="indexName">The name of the index to use. Defaults to <see cref="DefaultIndexName" />.</param>
     /// <param name="vectorSize">The size of the vectors used in Milvus. Defaults to 1536.</param>
     /// <param name="metricType">The metric used to measure similarity between vectors. Defaults to <see cref="SimilarityMetricType.Ip" />.</param>
     public MilvusMemoryStore(
         MilvusClient client,
+        string? indexName = null,
         int vectorSize = 1536,
         SimilarityMetricType metricType = SimilarityMetricType.Ip)
-        : this(client, ownsMilvusClient: false, vectorSize, metricType)
+        : this(client, ownsMilvusClient: false, indexName, vectorSize, metricType)
     {
     }
 
     private MilvusMemoryStore(
         MilvusClient client,
         bool ownsMilvusClient,
+        string? indexName = null,
         int vectorSize = 1536,
         SimilarityMetricType metricType = SimilarityMetricType.Ip)
     {
         this.Client = client;
+        this._indexName = indexName ?? DefaultIndexName;
         this._vectorSize = vectorSize;
         this._metricType = metricType;
         this._ownsMilvusClient = ownsMilvusClient;
@@ -186,8 +198,8 @@ public async Task CreateCollectionAsync(string collectionName, CancellationToken
 
             MilvusCollection collection = await this.Client.CreateCollectionAsync(collectionName, schema, DefaultConsistencyLevel, cancellationToken: cancellationToken).ConfigureAwait(false);
 
-            await collection.CreateIndexAsync(EmbeddingFieldName, metricType: this._metricType, cancellationToken: cancellationToken).ConfigureAwait(false);
-            await collection.WaitForIndexBuildAsync("float_vector", cancellationToken: cancellationToken).ConfigureAwait(false);
+            await collection.CreateIndexAsync(EmbeddingFieldName, metricType: this._metricType, indexName: this._indexName, cancellationToken: cancellationToken).ConfigureAwait(false);
+            await collection.WaitForIndexBuildAsync("float_vector", this._indexName, cancellationToken: cancellationToken).ConfigureAwait(false);
 
             await collection.LoadAsync(cancellationToken: cancellationToken).ConfigureAwait(false);
             await collection.WaitForCollectionLoadAsync(waitingInterval: TimeSpan.FromMilliseconds(100), timeout: TimeSpan.FromMinutes(1), cancellationToken: cancellationToken).ConfigureAwait(false);

dotnet/src/Connectors/Connectors.Memory.MongoDB/MongoDBMemoryStore.cs

@@ -20,7 +20,7 @@ public class MongoDBMemoryStore : IMemoryStore, IDisposable
     /// </summary>
     /// <param name="connectionString">MongoDB connection string.</param>
     /// <param name="databaseName">Database name.</param>
-    /// /// <param name="indexName">Name of the search index. If no value is provided default index will be used.</param>
+    /// <param name="indexName">Name of the search index. If no value is provided default index will be used.</param>
     public MongoDBMemoryStore(string connectionString, string databaseName, string? indexName = default) :
         this(new MongoClient(connectionString), databaseName, indexName)
     {

dotnet/src/Connectors/Connectors.Memory.MongoDB/README.md

@@ -6,26 +6,26 @@ This connector uses [MongoDB Atlas Vector Search](https://www.mongodb.com/produc
 
 1. Create [Atlas cluster](https://www.mongodb.com/docs/atlas/getting-started/)
 
-2. Create a collection
+2. Create a [collection](https://www.mongodb.com/docs/atlas/atlas-ui/collections/)
+
+3. Create [Vector Search Index](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/) for the collection. The index has to be defined on a field called `embedding`. For example:
 
-3. Create [Vector Search Index](https://www.mongodb.com/docs/atlas/atlas-search/field-types/knn-vector/) for the collection.
-The index has to be defined on a field called ```embedding```. For example:
 ```
 {
-  "mappings": {
-    "dynamic": true,
-    "fields": {
-      "embedding": {
-        "dimension": 1024,
-        "similarity": "cosine",
-        "type": "knnVector"
-      }
+  "type": "vectorSearch",
+  "fields": [
+    {
+      "numDimensions": <number-of-dimensions>,
+      "path": "embedding",
+      "similarity": "euclidean | cosine | dotProduct",
+      "type": "vector"
     }
-  }
+  ]
 }
 ```
 
 4. Create the MongoDB memory store
+
 ```csharp
 var connectionString = "MONGODB ATLAS CONNECTION STRING"
 MongoDBMemoryStore memoryStore = new(connectionString, "MyDatabase");
@@ -38,9 +38,12 @@ Kernel kernel = Kernel.Builder
     .Build();
 ```
 
+> Guide to find the connection string: https://www.mongodb.com/docs/manual/reference/connection-string/
+
 ## Important Notes
 
 ### Vector search indexes
-In this version, vector search index management is outside of ```MongoDBMemoryStore``` scope.
+
+In this version, vector search index management is outside of `MongoDBMemoryStore` scope.
 Creation and maintenance of the indexes have to be done by the user. Please note that deleting a collection
-(```memoryStore.DeleteCollectionAsync```) will delete the index as well.
+(`memoryStore.DeleteCollectionAsync`) will delete the index as well.