Synthesizing and Summarizing private data to generate recommendations and insights in your Applications¶

var kernel = new KernelBuilder()
    .WithLogger(NullLogger.Instance)
    .WithCompletionService(kernelSettings)
    .WithEmbeddingGenerationService(kernelSettings)
    .WithMemoryStorage(memoryStore)
    .Configure(c => c.SetDefaultHttpRetryConfig(new HttpRetryConfig
    {
        MaxRetryCount = 2,
        UseExponentialBackoff = true
    }))
    .Build();

// ========= Import Advisor skill from local filesystem =========

    // ========= Import semantic functions as plugins =========
    var pluginsDirectory = Path.Combine(Directory.GetCurrentDirectory(), "plugins");
    var advisorPlugin = _kernel.ImportSemanticSkillFromDirectory(pluginsDirectory, "AdvisorPlugin");

    // This will explained in full later in this section:
     // ========= Import native function  =========
    var userProfilePlugin = _kernel.ImportSkill(new UserProfilePlugin(), "UserProfilePlugin");

    // ========= Set context variables to populate the prompt  =========
    var context = _kernel.CreateNewContext();
    context.Variables.Set("userId", miyagiContext.UserInfo.UserId);
    context.Variables.Set("portfolio", JsonSerializer.Serialize(miyagiContext.Portfolio));
    context.Variables.Set("risk", miyagiContext.UserInfo.RiskLevel ?? DefaultRiskLevel);

    // ========= Chain and orchestrate with LLM =========
    var plan = new Plan("Execute userProfilePlugin and then advisorPlugin");
    plan.AddSteps(userProfilePlugin["GetUserAge"],
        userProfilePlugin["GetAnnualHouseholdIncome"],
        advisorPlugin["PortfolioAllocation"]);

    // Execute plan
    var ask = "Using the userId, get user age and household income, and then get the recommended asset allocation";
    context.Variables.Update(ask);
    log?.LogDebug("Planner steps: {N}", plan.Steps.Count);
    var result = await plan.InvokeAsync(context);

var userProfileSkill = _kernel.ImportSkill(new UserProfileSkill(), "UserProfileSkill");

// ========= Orchestrate with LLM using context, connector, and memory =========
    var result = await _kernel.RunAsync(
        context,
        userProfileSkill["GetUserAge"],
        userProfileSkill["GetAnnualHouseholdIncome"],
        advisorSkill["InvestmentAdvise"]);
    _kernel.Log.LogDebug("Result: {0}", result.Result);

    // Copyright (c) Microsoft. All rights reserved.

    using System.ComponentModel;
    using Microsoft.SemanticKernel.Orchestration;
    using Microsoft.SemanticKernel.SkillDefinition;

    namespace GBB.Miyagi.RecommendationService.plugins;

    /// <summary>
    ///     UserProfilePlugin shows a native skill example to look user info given userId.
    /// </summary>
    /// <example>
    ///     Usage: kernel.ImportSkill("UserProfilePlugin", new UserProfilePlugin());
    ///     Examples:
    ///     SKContext["userId"] = "000"
    /// </example>
    public class UserProfilePlugin
    {
        /// <summary>
        ///     Name of the context variable used for UserId.
        /// </summary>
        public const string UserId = "UserId";

        private const string DefaultUserId = "40";
        private const int DefaultAnnualHouseholdIncome = 150000;
        private const int Normalize = 81;

        /// <summary>
        ///     Lookup User's age for a given UserId.
        /// </summary>
        /// <example>
        ///     SKContext[UserProfilePlugin.UserId] = "000"
        /// </example>
        /// <param name="context">Contains the context variables.</param>
        [SKFunction]
        [SKName("GetUserAge")]
        [Description("Given a userId, get user age")]
        public string GetUserAge(
            [Description("Unique identifier of a user")]
            string userId,
            SKContext context)
        {
            // userId = context.Variables.ContainsKey(UserId) ? context[UserId] : DefaultUserId;
            userId = string.IsNullOrEmpty(userId) ? DefaultUserId : userId;
            context.Log.LogDebug("Returning hard coded age for {0}", userId);

            int age;

            if (int.TryParse(userId, out var parsedUserId))
                age = parsedUserId > 100 ? parsedUserId % Normalize : parsedUserId;
            else
                age = int.Parse(DefaultUserId);

            // invoke a service to get the age of the user, given the userId
            return age.ToString();
        }

        /// <summary>
        ///     Lookup User's annual income given UserId.
        /// </summary>
        /// <example>
        ///     SKContext[UserProfilePlugin.UserId] = "000"
        /// </example>
        /// <param name="context">Contains the context variables.</param>
        [SKFunction]
        [SKName("GetAnnualHouseholdIncome")]
        [Description("Given a userId, get user annual household income")]
        public string GetAnnualHouseholdIncome(
            [Description("Unique identifier of a user")]
            string userId,
            SKContext context)
        {
            // userId = context.Variables.ContainsKey(UserId) ? context[UserId] : DefaultUserId;
            userId = string.IsNullOrEmpty(userId) ? DefaultUserId : userId;
            context.Log.LogDebug("Returning userId * randomMultiplier for {0}", userId);

            var random = new Random();
            var randomMultiplier = random.Next(1000, 8000);

            // invoke a service to get the annual household income of the user, given the userId
            var annualHouseholdIncome = int.TryParse(userId, out var parsedUserId)
                ? parsedUserId * randomMultiplier
                : DefaultAnnualHouseholdIncome;

            return annualHouseholdIncome.ToString();
        }
    }