Azure Semantic Kernel Example with Embeddings and Pinecone

Question

Microsoft recently released Semantic Kernel on Azure. It is a mechanism around the Azure OpenAI API, similar to LangChain, but both in C# and Python. It has a bunch of examples, and I am trying to run Example38 in my project. Specifically, this code:

public static async Task RunAsync()
{
    using (Log.VerboseCall())
    {
        string apiKey = "...xxxxxxxxxxxxxxxxxxx...";  // I got this from Pinecone
        string pineconeEnvironment = "us-west1-gcp-free"; // I got this from Pinecone

        string openAiKey = "...xxxxxxxxxxxxxxxxxxxxx..."; // I got this from OpenAI

        PineconeMemoryStore memoryStore = new(pineconeEnvironment, apiKey);
        IKernel kernel = Kernel.Builder
            .WithOpenAITextCompletionService("text-davinci-003", openAiKey)
            .WithOpenAITextEmbeddingGenerationService("text-embedding-ada-002", openAiKey)
            .WithMemoryStorage(memoryStore)
            .Build();


        Console.WriteLine("== Printing Collections in DB ==");

        IAsyncEnumerable<string> collections = memoryStore.GetCollectionsAsync();

        await foreach (string collection in collections)
        {
            Console.WriteLine(collection);
        }

        Console.WriteLine("== Adding Memories ==");

        Dictionary<string, object> metadata = new()
        {
            { "type", "text" },
            { "tags", new List<string>() { "memory", "cats" } }
        };

        string additionalMetadata = System.Text.Json.JsonSerializer.Serialize(metadata);

        try
        {
            // !!! This line throws exception - see below. !!!
            string key1 = await kernel.Memory.SaveInformationAsync(MemoryCollectionName, "british short hair", "cat1", null, additionalMetadata);
            string key2 = await kernel.Memory.SaveInformationAsync(MemoryCollectionName, "orange tabby", "cat2", null, additionalMetadata);
            string key3 = await kernel.Memory.SaveInformationAsync(MemoryCollectionName, "norwegian forest cat", "cat3", null, additionalMetadata);

            Console.WriteLine("== Retrieving Memories Through the Kernel ==");
            MemoryQueryResult? lookup = await kernel.Memory.GetAsync(MemoryCollectionName, "cat1");
            Console.WriteLine(lookup != null ? lookup.Metadata.Text : "ERROR: memory not found");

            Console.WriteLine("== Retrieving Memories Directly From the Store ==");
            var memory1 = await memoryStore.GetAsync(MemoryCollectionName, key1);
            var memory2 = await memoryStore.GetAsync(MemoryCollectionName, key2);
            var memory3 = await memoryStore.GetAsync(MemoryCollectionName, key3);

            Console.WriteLine(memory1 != null ? memory1.Metadata.Text : "ERROR: memory not found");
            Console.WriteLine(memory2 != null ? memory2.Metadata.Text : "ERROR: memory not found");
            Console.WriteLine(memory3 != null ? memory3.Metadata.Text : "ERROR: memory not found");

            Console.WriteLine("== Similarity Searching Memories: My favorite color is orange ==");
            IAsyncEnumerable<MemoryQueryResult> searchResults = kernel.Memory.SearchAsync(MemoryCollectionName, "My favorite color is orange", 1, 0.8);

            await foreach (MemoryQueryResult item in searchResults)
            {
                Console.WriteLine(item.Metadata.Text + " : " + item.Relevance);
            }
        }
        catch (Exception ex)
        {
            Log.Verbose(ex);
        }
    }
}

I get the following exception at the indicated line:

Index creation is not supported within memory store. It should be created manually or using CreateIndexAsync. Ensure index state is Ready.

Answer 1

I am also doing tests to integrate Pinecone with SK. On the line:

string key1 = await kernel.Memory.SaveInformationAsync(MemoryCollectionName, "british short hair", "cat1", null, additionalMetadata);

I have tried to put the name of the index in the first parameter and it has worked for me.

When you refer to example 38, where are these examples?

Answer 2

In the current SK memory design, vector index creation is assumed to be a quick operation, taking only milliseconds to a few seconds (similar to Azure Search and Qdrant). However, when Pinecone was integrated, it was discovered that index creation takes significantly longer, sometimes requiring minutes to complete. This necessitates polling the API to check if the index is ready, leading to unexpected timeouts in applications designed to create indexes on-the-fly (e.g., example 38).

As a workaround, the Pinecone integration in SK currently requires app developers to create indexes manually, either through the portal or by using Microsoft.SemanticKernel.Connectors.Memory.Pinecone.PineconeClient.CreateIndexAsync(). This avoids the need to queue the operation and wait for an extended period while polling the service.

A potential improvement could be adding a comment in example 38 to clarify this behavior or providing an option to override the default behavior and allow waiting. This would be a valuable enhancement for those interested in implementing it.