SemanticKernelWithMongoDBAtlas

asking_questions.cs

Console.WriteLine("Welcome to the Movie Recommendation System!");
Console.WriteLine("Type 'x' and press Enter to exit.");
Console.WriteLine("============================================");
Console.WriteLine();

while(true)
{
    Console.WriteLine("Tell me what sort of film you want to watch..");
    Console.WriteLine();

    Console.Write("> ");

    var userInput = Console.ReadLine();

    if(userInput.ToLower() == "x")
    {
        Console.WriteLine("Exiting application..");
        break;
    }

    Console.WriteLine();

    var memories = memory.SearchAsync(CollectionName, userInput, limit: 3, minRelevanceScore: 0.6);

    Console.WriteLine(String.Format("{0,-20} {1,-50} {2,-10} {3,-15}", "Title", "Plot", "Year", "Relevance (0 - 1)"));
    Console.WriteLine(new String('-', 95)); // Adjust the length based on your column widths

    await foreach (var mem in memories)
    {
        Console.WriteLine(String.Format("{0,-20} {1,-50} {2,-10} {3,-15}", 
            mem.Metadata.Id, 
            mem.Metadata.Description.Length > 47 ? mem.Metadata.Description.Substring(0, 47) + "..." : mem.Metadata.Description, // Truncate long descriptions
            mem.Metadata.AdditionalMetadata, 
            mem.Relevance.ToString("0.00"))); // Format relevance score to two decimal places
    }
}

fetch_documents.cs

private static async Task FetchAndSaveMovieDocuments(ISemanticTextMemory memory, int limitSize)
    {
        MongoClient mongoClient = new MongoClient(MongoDBAtlasConnectionString);
        var movieDB = mongoClient.GetDatabase("sample_mflix");
        var movieCollection = movieDB.GetCollection<Movie>("movies");
        List<Movie> movieDocuments;

        Console.WriteLine("Fetching documents from MongoDB...");

        movieDocuments = movieCollection.Find(m => true).Limit(limitSize).ToList();

        movieDocuments.ForEach(movie =>
        {
            if (movie.Plot == null)
            {
                movie.Plot = "UNKNOWN";
            }
        });

        foreach (var movie in movieDocuments)
        {
            try
            {
                await memory.SaveReferenceAsync(
                collection: CollectionName,
                description: movie.Plot,
                text: movie.Plot,
                externalId: movie.Title,
                externalSourceName: "Sample_Mflix_Movies",
                additionalMetadata: movie.Year.ToString());
            }
            catch (Exception ex)
            {
                Console.WriteLine(ex.Message);

            }
        }
    }

movie.cs

public class Movie
{
    [BsonId]
    [BsonRepresentation(BsonType.ObjectId)]
    public string Id { get; set; }

    [BsonElement("plot")]
    public string Plot { get; set; }

    [BsonElement("genres")]
    public List<string> Genres { get; set; }

    [BsonElement("runtime")]
    public int Runtime { get; set; }

    [BsonElement("cast")]
    public List<string> Cast { get; set; }

    [BsonElement("num_mflix_comments")]
    public int NumMflixComments { get; set; }

    [BsonElement("poster")]
    public string Poster { get; set; }

    [BsonElement("title")]
    public string Title { get; set; }

    [BsonElement("fullplot")]
    public string Fullplot { get; set; }

    [BsonElement("languages")]
    public List<string> Languages { get; set; }

    [BsonElement("released")]
    public DateTime Released { get; set; }

    [BsonElement("directors")]
    public List<string> Directors { get; set; }

    [BsonElement("writers")]
    public List<string> Writers { get; set; }

    [BsonElement("awards")]
    public Awards Awards { get; set; }

    [BsonElement("rated")]
    public string? Rated { get; set; }

    [BsonElement("lastupdated")]
    public string Lastupdated { get; set; }


    [BsonElement("year")]
    public object Year { get; set; }

    [BsonElement("imdb")]
    public Imdb Imdb { get; set; }

    [BsonElement("countries")]
    public List<string> Countries { get; set; }

    [BsonElement("type")]
    public string Type { get; set; }

    [BsonElement("tomatoes")]
    public Tomatoes Tomatoes { get; set; }

    [BsonElement("metacritic")]
    public int? Metacritic { get; set; }

    [BsonElement("awesome")]
    public bool? Awesome { get; set; }
}

public class Awards
{
    [BsonElement("wins")]
    public int Wins { get; set; }

    [BsonElement("nominations")]
    public int Nominations { get; set; }

    [BsonElement("text")]
    public string Text { get; set; }
}

public class Imdb
{
    [BsonElement("id")]
    public object ImdbId { get; set; }

    [BsonElement("votes")]
    public object Votes { get; set; }

    [BsonElement("rating")]
    public object Rating { get; set; }
}

public class Tomatoes
{
    [BsonElement("viewer")]
    public Viewer Viewer { get; set; }

    [BsonElement("lastUpdated")]
    public DateTime LastUpdated { get; set; }

    [BsonElement("dvd")]
    public DateTime? DVD { get; set; }

    [BsonElement("website")]
    public string? Website { get; set; }

    [BsonElement("production")]
    public string? Production { get; set; }

    [BsonElement("critic")]
    public Critic? Critic { get; set; }

    [BsonElement("rotten")]
    public int? Rotten { get; set; }

    [BsonElement("fresh")]
    public int? Fresh { get; set; }

    [BsonElement("boxOffice")]
    public string? BoxOffice { get; set; }

    [BsonElement("consensus")]
    public string? Consensus { get; set; }

}

public class Viewer
{
    [BsonElement("rating")]
    public double Rating { get; set; }

    [BsonElement("numReviews")]
    public int NumReviews { get; set; }

    [BsonElement("meter")]
    public int Meter { get; set; }
}

public class Critic
{
    [BsonElement("rating")]
    public double Rating { get; set; }

    [BsonElement("numReviews")]
    public int NumReviews { get; set; }

    [BsonElement("meter")]
    public int Meter { get; set; }
}

setting_up_configuration.cs

using Microsoft.SemanticKernel.Memory;

#pragma warning disable SKEXP0001, SKEXP0010, SKEXP0020, SKEXP0050
public static class Program {
    static string TextEmbeddingModelName = "text-embedding-ada-002";
    static string OpenAIAPIKey = "<YOUR OPENAI PROJECT API KEY>";
  
    static string MongoDBAtlasConnectionString = "<YOUR ATLAS CONNECTION STRING>";
    static string SearchIndexName = "default";
    static string DatabaseName = "semantic-kernel";
    static string CollectionName = "movies";
    static MemoryBuilder memoryBuilder;

    public static async Task Main(string[] args) {

    }
}

setting_up_memorystore_1.cs

memoryBuilder = new MemoryBuilder();

        memoryBuilder.WithOpenAITextEmbeddingGeneration(
            TextEmbeddingModelName,
            OpenAIAPIKey
            );

setting_up_memorystore_2.cs

using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.MongoDB;
using Microsoft.SemanticKernel.Connectors.OpenAI;
using Microsoft.SemanticKernel.Memory;
using MongoDB.Driver;
using Kernel = Microsoft.SemanticKernel.Kernel;

setting_up_memorystore_3.cs

var mongoDBMemoryStore = new MongoDBMemoryStore(MongoDBAtlasConnectionString, DatabaseName, SearchIndexName);
        memoryBuilder.WithMemoryStore(mongoDBMemoryStore);       
        var memory = memoryBuilder.Build();

vector_search.json

{
  "fields": [
    {
      "numDimensions": 1536,
      "path": "embedding",
      "similarity": "dotProduct",
      "type": "vector"
    }
  ]
}