ControllingTheInter.net – Tech News, Legal and Daily Blog

C# Discord bot for .NET 8.0

// See https://aka.ms/new-console-template for more information

//leaderboards
//https://huggingface.co/spaces/mteb/leaderboard

//Implement with Python
//https://www.llamaindex.ai/
//https://docs.llamaindex.ai/en/stable/getting_started/discover_llamaindex/

//Install-Package LLamaSharp
//Install-Package LLamaSharp.Backend.Cuda11
//https://dotnet.microsoft.com/en-us/download/dotnet/8.0
//https://dotnet.microsoft.com/en-us/download/dotnet

//The top line returns waaayy better results then the bottom
//Assistant: discovery\r\nUser:
//discovery

using LLama.Common;
using LLama;
#pragma warning disable SKEXP0050, SKEXP0001, SKEXP0020
//RAG
//Install-Package LLamaSharp.Semantic-Kernel
//https://github.com/SciSharp/LLamaSharp/issues/648
using LLamaSharp.SemanticKernel.TextEmbedding;
//Install-Package Microsoft.SemanticKernel
using Microsoft.SemanticKernel.Connectors;
using Microsoft.SemanticKernel.Memory;
using Microsoft.SemanticKernel.Text;
//Install-Package Microsoft.SemanticKernel.Connectors.Sqlite -Version 1.18.0-alpha
using Microsoft.SemanticKernel.Connectors.Sqlite;
//
using System.IO;
using System.Text.RegularExpressions;
using System.Diagnostics;
using System.Net.WebSockets;
using System.Text;
using System.Net;
using System.Management;
using SQLitePCL;
using System;
using System.Collections;
using System.Windows.Documents;
using System.Runtime.InteropServices;
using static System.Net.Mime.MediaTypeNames;
using System.CodeDom.Compiler;
using System.Reflection;
using Microsoft.Data.Sqlite;
using static System.Collections.Specialized.BitVector32;
using LLama.Native;

//LLava
//Install-package spectre.console


[DllImport("user32.dll")]
static extern IntPtr SetForegroundWindow(IntPtr hWnd);

[DllImport("user32.dll")]
static extern bool ShowWindow(IntPtr hWnd, int nCmdShow); //ShowWindow needs an IntPtr


Console.ForegroundColor = ConsoleColor.White;
Console.WriteLine("Starting ISPortal AI!");

HttpListenerWebSocketContext webSocketContext = null;

//https://huggingface.co/mradermacher/llava-v1.6-mistral-7b-GGUF/tree/main

string RagModelPath = @"D:\LLM\bge-large-en-v1.5-q8_0.gguf";

//string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q6_K.gguf";
string modelPath = @"D:\LLM\Saul-Instruct-v1.Q8_0.gguf";


//string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q8_0.gguf"; // change it to your own model path.
//string modelPath = @"D:\Meta-Llama-3.1-70B-Instruct-Q6_K-00001-of-00002.gguf"; // Way too large for my computer
//var embeddingModelPath = Path.GetFullPath("<path to embed model>/nomic-embed.gguf");
string LocalMemoryPath = @"C:\Users\User\Desktop\MyMemory.db";
string PathToFilesToIngest = "D:\\Embeddings";

ManagementObjectSearcher searcher = new ManagementObjectSearcher("SELECT * FROM Win32_Processor");
List<int> coresCPUs = new List<int>();
foreach (ManagementObject mo in searcher.Get())
{
    coresCPUs.Add(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));
    Debug.WriteLine(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));
}

//RAG variables
ModelParams RAGparameters = null;
ISemanticTextMemory MyMemoryStore = null;
//All operations
LLamaWeights model = null;
LLamaContext context = null;
InteractiveExecutor executor = null;

var MyStartupMethod = MyLoadedMethod.RAG;
string collectionName = "TestCollection";

// Add chat histories as prompt to tell AI how to act.
var chatHistory = new ChatHistory();
var chatHistory2 = new ChatHistory();
string Str = null;

switch ("rag")
{
    case "train":
        chatHistory.AddMessage(AuthorRole.System, "Generate new examples based on user input examples, once asked to write additional samples, take the previous request and continue to generate addtional samples. All answers need to strictly be formed into a statement and then answered as a JSON array of strings, always add a semicolon after each string array to close the statement properly. All commands should be for use by the windows operating system. Do not explain, add notes or say anything else unless specifically asked to for any reason.");
        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate to program files in windows, find a folder with the word steam in it then create a subfolder inside with two text files and populate a random string in each text file. Write the commands using a json array of strings to be processed by an interrupter."); //10000
        Str = "myArray = [\"CD \\\\\", \"CD C:\\\\Program Files\\\\\", \"DIR /OD \\\"*steam*\\\"\", \"MKDIR \\\"SteamFolder\\\"\", \"MD \\\"SteamFolder\\\\subfolder\\\", \\\"ECHO New content 1 > \\\"SteamFolder\\\\subfolder\\\\file1.txt\", \"COPY \\\"asdawdafag\\\" > \\\"SteamFolder\\\\subfolder\\\\file2.txt\\\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000
        Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "Great, now continue to write addtional samples, remember to keep the format as a statement, then followed by a JSON answer with a semicolon at the end of each JSON answer. I will ask for over 100 samples."); //10000

        chatHistory.AddMessage(AuthorRole.Assistant, "Ping google.com and write the the results to a text file then open the program files folder using explorer. myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];"); //10000
        chatHistory.AddMessage(AuthorRole.User, "y"); //10000
        chatHistory.AddMessage(AuthorRole.Assistant, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside. myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];"); //10000
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Use Moveit.exe to move a file named NTFS.mbr localy, then zip the moved file and display its size. myArray = [\"Moveit \\\"NTFS.mbr\\\" C:\", \"7z a ntfs.zip ntfs.mbr\", \"7z l ntfs.zip\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to direct a LAN IP to a temp directory, download a single file using curl and extract the extracted content into a subfolder named debug. myArray = [\"MKDIR C:\\\\tmp\\\", \"curl \\\"http://192.168.1.100/somefile.zip\\\" -o C:\\\\tmp\", \"7z e C:\\\\tmp\\\\somefile.zip -od C:\\\\tmp\\\\debug\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Create a random 32 character hexadecimal color code, then use the color picker tool in Windows to open up a default browser using this new color as its background. myArray = [\"wmic os get version > C:\\versions.txt\", \"color cc233330cc2233c2\", \"explorer https://www.google.com\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to create an Ecrypted zip archive and store it in the users desktop directory, than extract this zip file with AES encryption using 7z. myArray = [\"cipher /E /S:C:\\\\Users\\\\username\\\\Documents\" > C:\\UserEnv, \"cipher /D /S:C:\\\\Users\\\\username\\\\Documents\", \"CIPHER /P\"aVeryStrongPassword123\\* \\\"C:\\\\Users\\\\username\\\\Desktop\\\\enc.zip\\\"\", \"7z e -hp\"aVeryStrongPassword123 \\*.zip\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Display user accounts with administrative privileges, and list the user object properties in Windows registry. myArray = [\"wmic useraccount where Enabled=TRUE and Administrator=TRUE get *\", \"reg query HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\\\Winlogon /v DefaultUserName\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Change password for a service called misconfigure-MDViewer, change priority of CpuGroup1; write a list of commands to accomplish these tasks. myArray = [\"net user \\\"misconfigure-MDViewer\\\" changesPassword!!\"], \"wmic cpu Get Name\", \"wmic process where ProcessID=1234 set Priority=5\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Use the Windows Task Scheduler to create a scheduled task to download a simple text file from a remote server every 10 minutes. myArray = [\"schtasks /create /tn \"MyTask\" /tr \"curl http://192.168.1.100/textfile.txt -o C:\\tmp\\mytext.txt\\\"\", \"schtasks /change /tn \"MyTask\\\" /st 00:00 /ri 10\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a batch file that opens up Internet Explorer with two tabs one with the url google.com and another with bing.com. myArray = [\"start iexplore.exe \\\"http://www.google.com\\\", start iexplore.exe \\\"http://www.bing.com\\\"\"];");
        break;
    case "production":
        chatHistory.AddMessage(AuthorRole.System, "Transcribe request from the user into an array of JSON strings labeled 'myArray' to be processed by an interpreter that will parse an array of strings and execute them on a system. All answers need to strictly be formed into a JSON array of strings for the windows operating system. Only give the results in JSON format and do not explain or say anything else unless asked specifically.");
        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate to program files in windows, find a folder with the word steam in it then create a subfolder inside with two text files and populate a random string in each text file. Write the commands using a json array of strings to be processed by an interrupter."); //10000
        Str = "myArray = [\"CD \\\\\", \"CD C:\\\\Program Files\\\\\", \"DIR /OD \\\"*steam*\\\"\", \"MKDIR \\\"SteamFolder\\\"\", \"MD \\\"SteamFolder\\\\subfolder\\\", \\\"ECHO New content 1 > \\\"SteamFolder\\\\subfolder\\\\file1.txt\", \"COPY \\\"asdawdafag\\\" > \\\"SteamFolder\\\\subfolder\\\\file2.txt\\\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000
        Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "Ping google.com and write the the results to a text file then open the program files folder using explorer."); //10000
        Str = "myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside."); //10000
        Str = "myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);
        break;
    case "rag":
        //chatHistory.AddMessage(AuthorRole.System, "You are a legal assistance. You will be provided context to some data and will answer any questions you receive the best you can with the context provided and do not include information outside of the information provided.");
        break;
    default:
        Console.WriteLine("Number is not between 1 and 4");
        break;
}
//LLM variables
var LLMparameters = new ModelParams(modelPath)
{
    ContextSize = 13107, // Does not require alot of memory
                         //ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl
                         //If commented out, swaps to CPU
                         //GpuLayerCount = 0
    GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.
};
LLamaWeights LLMmodel = null;

LLamaContext LLMcontext = null;
LLamaContext.State CleanContext = null;

InteractiveExecutor LLMexecutor = null;
StatelessExecutor LLMStatelessExecutor = null; //Not currently in use. Results were bad.
StatefulExecutorBase.ExecutorBaseState CleanExectuor = null;

ChatSession LLMChatSession = null;
SessionState CleanChatSession = null;

InferenceParams inferenceParams = new InferenceParams()
{
    Temperature = 0.4f,
    MaxTokens = 512, // No more than 256 tokens should appear in answer. Remove it if antiprompt is enough for control.
    AntiPrompts = new List<string> { "\nUser:" } // Stop generation once antiprompts appear.
};

async Task LoadModule()
{
    if (MyStartupMethod == MyLoadedMethod.RAG) //RAG //Checks for enum need to be wrapped in a function to be valid.
    {
        RAGparameters = new ModelParams(RagModelPath)
        {
            ContextSize = 32000, // Does not require alot of memory
                                 //ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl
            Embeddings = true,
            //GpuLayerCount = 0 //If commented out, swaps to CPU
            GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.
        };

        model = LLamaWeights.LoadFromFile(RAGparameters);
        context = model.CreateContext(RAGparameters);
        executor = new InteractiveExecutor(context);

        var embedder = new LLamaEmbedder(model, RAGparameters);
        var service = new LLamaSharpEmbeddingGeneration(embedder);

        MyMemoryStore = new MemoryBuilder().WithMemoryStore(await SqliteMemoryStore.ConnectAsync(LocalMemoryPath)).WithTextEmbeddingGeneration(service).Build();

        await IngestFile();

        LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);

        LLMStatelessExecutor = new StatelessExecutor(LLMmodel, LLMparameters);

        LLMcontext = LLMmodel.CreateContext(LLMparameters);
        LLMexecutor = new InteractiveExecutor(LLMcontext);
        LLMChatSession = new(LLMexecutor, chatHistory);
    }
    else
    {
        LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);
        LLMcontext = LLMmodel.CreateContext(LLMparameters);
        LLMexecutor = new InteractiveExecutor(LLMcontext);
        LLMChatSession = new(LLMexecutor, chatHistory);
    }

    CleanExectuor = LLMexecutor.GetStateData();
    CleanChatSession = LLMChatSession.GetSessionState();
    CleanContext = LLMcontext.GetState();
    //_memoryStore
    //var field = MyMemoryStore.GetType().GetField("_storage", BindingFlags.NonPublic | BindingFlags.Instance);
    //var memoryStore = (Dictionary<string, string>)field.GetValue(MyMemoryStore);
    //var keys = memoryStore.Keys.ToList();

    using (var connection = new SqliteConnection("Data Source=" + LocalMemoryPath))
    {
        connection.Open();

        var command = connection.CreateCommand();

        command.CommandText = @"SELECT COUNT(1) from SKMemoryTable";

        Debug.WriteLine(command.ExecuteScalar());

        //collection, key, metadata, embedding, timestamp
        //metadata holds a json string of "is_reference", "external_source_name", "id" and "description", "text", "additional_metadata"
        command.CommandText = @"SELECT DISTINCT key FROM SKMemoryTable"; // Replace 'MemoryTable' with the actual table name

        using (var reader = command.ExecuteReader())
        {
            while (reader.Read())
            {
                //Console.WriteLine(reader.GetString(0));
            }
        }
    }

    //System.Diagnostics.Debugger.Break();
    //LLMsession.SaveSession();
}


if (false)
{
    await RunLLava();
    Console.ReadKey();
    return;
}


await LoadModule();

string CompleteAnswer = null;
Match Matches;

long TokensInMemory = 0;

IEnumerable<string> SplitToLines(string stringToSplit, int maximumLineLength)
{
    var words = stringToSplit.Split(' ').Concat(new[] { "" });
    return
        words
            .Skip(1)
            .Aggregate(
                words.Take(1).ToList(),
                (a, w) =>
                {
                    var last = a.Last();
                    while (last.Length > maximumLineLength)
                    {
                        a[a.Count() - 1] = last.Substring(0, maximumLineLength);
                        last = last.Substring(maximumLineLength);
                        a.Add(last);
                    }
                    var test = last + " " + w;
                    if (test.Length > maximumLineLength)
                    {
                        a.Add(w);
                    }
                    else
                    {
                        a[a.Count() - 1] = test;
                    }
                    return a;
                });
}

async Task IngestFile()
{
    long TotalParagraphsLoaded = 0;
    Console.WriteLine("===== INGESTING =====");

    IList<string> collections = await MyMemoryStore.GetCollectionsAsync();

    string folderPath = Path.GetFullPath(PathToFilesToIngest);
    string[] files = Directory.GetFiles(folderPath);

    if (collections.Contains(collectionName))
    {
        Console.WriteLine("Found database");
    }
    else
    {

        List<Task> tasks = new List<Task>();
        foreach (var item in files.Select((path, index) => new { path, index }))
        {
            Console.WriteLine($"Ingesting file #{item.index}");
            string text = File.ReadAllText(item.path);

            if (false)
            {
                var sentences = TextChunker.SplitPlainTextLines(text, 256);
                var paragraphs = TextChunker.SplitPlainTextParagraphs(sentences, 1024);

                foreach (var para in paragraphs.Select((text, index) => new { text, index }))
                    await MyMemoryStore.SaveInformationAsync(collectionName, para.text, $"Document {item.path}, Paragraph {para.index}");
            }
            else if (true)
            {
                string[] splitQuestions = Regex.Split(text, @"(?=Question\s\d+\.)");
                long ParaIndex = 1;
                foreach (string question in splitQuestions)
                {
                    if (!string.IsNullOrWhiteSpace(question))
                    {
                        try
                        {
                            //description is stored in the metadata column, same with additional_metadata. Remember, converting to weights takes about 6-7x times the space in total.
                            Debug.WriteLine("Importing: " + model.Tokenize(question.Trim(), true, false, Encoding.ASCII).Length + "\r\n");
                            if (model.Tokenize(question.Trim(), true, false, Encoding.ASCII).Length >= 512)
                            {
                                foreach (string DataToAdd in SplitToLines(question.Trim(), question.Trim().Length / 2 + 10)) //800
                                {
                                    Debug.WriteLine("Splitting into: " + model.Tokenize(DataToAdd, true, false, Encoding.ASCII).Length + "\r\n");
                                    await MyMemoryStore.SaveInformationAsync(collectionName, DataToAdd, ($"Document {item.path}, Paragraph {ParaIndex++}"));
                                }
                            }
                            else
                            {
                                await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), ($"Document {item.path}, Paragraph {ParaIndex++}"));
                            }
                        }
                        catch
                        {

                        }
                        //tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));
                        TotalParagraphsLoaded++;
                    }
                }
            }
            else if (false)
            {
                string[] splitQuestions = Regex.Split(text, @"(?<=[.!?])\s+|(?<=\.\.)\s*|\r\n|\n"); //each sentence
                long ParaIndex = 1;

                foreach (string question in splitQuestions)
                {
                    if (!string.IsNullOrWhiteSpace(question))
                    {
                        //await memory.SaveReferenceAsync()
                        await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}");
                        //tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));
                        TotalParagraphsLoaded++;
                    }
                }
            }
            //await Task.WhenAll(tasks);
        }

        Console.WriteLine("Generated database with " + TotalParagraphsLoaded + " items.");
    }
    Console.WriteLine("===== DONE INGESTING =====");
}

void ClearContext()
{
    return;
    LLMChatSession.LoadSession(CleanChatSession);
    Debug.WriteLine(LLMChatSession.HistoryTransform.HistoryToText(LLMChatSession.History));
    return;
    LLMcontext.Dispose();
    LLMexecutor = null;
    LLMChatSession = null;
    LLMcontext = LLMmodel.CreateContext(LLMparameters);
    LLMexecutor = new InteractiveExecutor(LLMcontext);
    LLMChatSession = new(LLMexecutor, chatHistory);
    return;
    chatHistory.Messages.Clear();
    LLMcontext.LoadState(CleanContext);
    LLMChatSession.LoadSession(CleanChatSession);
    LLMexecutor.LoadState(CleanExectuor);
    return;
    while (LLMChatSession.History.Messages.Count > 0)
    {
        LLMChatSession.RemoveLastMessage();
    }
    return;
}

string Keywords(string sentence)
{
    HashSet<string> StopWords = new HashSet<string>(new[]
    {
        "a", "an", "and", "the", "is", "in", "on", "at", "of", "for", "to", "with", "by", "from", "that", "this", "it",
        "as", "are", "was", "were", "be", "been", "has", "have", "had", "but", "or", "not", "so", "if", "then", "i",
        "me", "my", "myself", "we", "our", "ours", "ourselves", "you", "your", "yours", "yourself", "yourselves",
        "he", "him", "his", "himself", "she", "her", "hers", "herself", "its", "itself", "they", "them", "their",
        "theirs", "themselves", "what", "which", "who", "whom", "these", "those", "am", "being", "do", "does",
        "did", "doing", "because", "until", "while", "about", "against", "between", "into", "through", "during",
        "before", "after", "above", "below", "up", "down", "out", "off", "over", "under", "again", "further",
        "once", "here", "there", "when", "where", "why", "how", "all", "any", "both", "each", "few", "more",
        "most", "other", "some", "such", "no", "nor", "only", "own", "same", "than", "too", "very", "s", "t",
        "can", "will", "just", "don", "should", "now"
    });

    string cleanSentence = Regex.Replace(sentence.ToLower(), @"[^\w\s]", "");

    // Split sentence into words
    var words = cleanSentence.Split(new[] { ' ', '\t', '\n', '\r' }, StringSplitOptions.RemoveEmptyEntries);

    // Filter out stop words and return remaining words as keywords
    var keywords = words.Where(word => !StopWords.Contains(word)).ToList();

    // Join the keywords into a single string separated by spaces
    return string.Join(" ", keywords);
}

async void ProcessAIRequest(string userInput)
{
    Debug.WriteLine("ProcessAIRequest starting");
    TokensInMemory += model.Tokenize(userInput, true, false, Encoding.ASCII).Length;

    //executor.rag

    //RAG and context building: https://medium.com/@bruno.facco/rag-from-concept-to-application-using-gpt-llama-index-and-sql-retriever-cfb437da99eb
    //session.
    String ChatResponseToMeasure = null;
    if (MyStartupMethod == MyLoadedMethod.RAG)
    {
        StringBuilder ColoredStringBuilder = new();
        ColoredStringBuilder.Clear();

        List<string> sources = [];

        var resultsfound = false;
        double minRelevanceScoreValue = 0.8;

        Console.WriteLine("=== Extracting Keywords ===");

        /*
            string prompt = "System: Ensure that the results contain ALL of the words from the following user query. The words must appear at least once anywhere in the result, without exception.\r\n The results are in the following format, The question number, the question, possible answers then followed by the explanation. The user will give keywords and return the results if those keywords appear in any of the result, either in the question or the explanation.\r\n" +
            "Assistant: I will only return results that include every single keyword provided by the user. If even one keyword is missing, the result will not be returned, without exception.\r\n" +
            "User: " + userInput;
        */
        string prompt = userInput;

        string keywords = "";

        string StrchatHistory = "\r\nUser: What is Congresses Commerce Clause powers?\r\n" +
            "Assistant: Congress Commerce Clause\r\n" +
            "User: What time is it in new york?\r\n" +
            "Assistant: time new york\r\n" +
            "User: How do you fill up a car tire?\r\n" +
            "Assistant: fill up car tire\r\n" +
            "User: How fast can a car go on a freeway?\r\n" +
            "Assistant: fast car freeway\r\n" +
            "User: How do you make pancakes in an oven?\r\n" +
            "Assistant: make pancakes oven\r\n" +
            "User: How do you write a business plan?\r\n" +
            "Assistant: write business plan\r\n" +
            "User: What is the capital of Japan?\r\n" +
            "Assistant: capital Japan\r\n" +
            "User: How to set up a new email account?\r\n" +
            "Assistant: set up email account\r\n" +
            "User: What are the benefits of meditation?\r\n" +
            "Assistant: benefits meditation\r\n" +
            "User: How to make a website responsive?\r\n" +
            "Assistant: make website responsive\r\n" +
            "User: What is the difference between Python and Java?\r\n" +
            "Assistant: difference Python Java\r\n" +
            "User: How do I replace a car battery?\r\n" +
            "Assistant: replace car battery\r\n" +
            "User: What is the tallest mountain in the world?\r\n" +
            "Assistant: tallest mountain world\r\n" +
            "User: How can I improve my public speaking skills?\r\n" +
            "Assistant: improve public speaking skills\r\n" +
            "User: What is the population of Canada?\r\n" +
            "Assistant: population Canada\r\n" +
            "User: How to brew coffee using a French press?\r\n" +
            "Assistant: brew coffee French press\r\n" +
            "User: How does a blockchain work?\r\n" +
            "Assistant: blockchain work\r\n" +
            "User: What are the side effects of aspirin?\r\n" +
            "Assistant: side effects aspirin\r\n" +
            "User: How to start learning data science?\r\n" +
            "Assistant: start learning data science\r\n" +
            "User: What is the speed of light?\r\n" +
            "Assistant: speed of light\r\n" +
            "User: How do I bake a chocolate cake?\r\n" +
            "Assistant: bake chocolate cake\r\n" +
            "User: What are the causes of climate change?\r\n" +
            "Assistant: causes climate change\r\n" +
            "User: How to play the guitar for beginners?\r\n" +
            "Assistant: play guitar beginners\r\n" +
            "User: What are the symptoms of a common cold?\r\n" +
            "Assistant: symptoms common cold\r\n" +
            "User: How to create a budget plan?\r\n" +
            "Assistant: create budget plan\r\n";
        if (false)
        {
            if (true)
            {
                await foreach (var text in LLMStatelessExecutor.InferAsync("System: Return only the keywords from the following statement and do not provide anything else. Use spaces when outputing the keywords values and do not add anything futher." + StrchatHistory + "User: '" + userInput + "'", inferenceParams)) // Generate the response streamingly.
                {
                    Console.ForegroundColor = ConsoleColor.White;
                    Console.Write(text);

                    keywords += text;
                }
            }
            else
            {
                //chatHistory.Messages.Clear();
                chatHistory.AddMessage(AuthorRole.System, "I am a search engine assistant. I will only return back keywords from any statement you make and nothing else with no exceptions.\r\n");
                chatHistory.AddMessage(AuthorRole.User, "What is Congresses Commerce Clause powers?");
                chatHistory.AddMessage(AuthorRole.Assistant, "Congress Commerce Clause");
                chatHistory.AddMessage(AuthorRole.User, "What time is it in new york?");
                chatHistory.AddMessage(AuthorRole.Assistant, "time new york");
                chatHistory.AddMessage(AuthorRole.User, "How do you fill up a car tire?");
                chatHistory.AddMessage(AuthorRole.Assistant, "fill up car tire");
                chatHistory.AddMessage(AuthorRole.User, "How fast can a car go on a freeway?");
                chatHistory.AddMessage(AuthorRole.Assistant, "fast car freeway");
                chatHistory.AddMessage(AuthorRole.User, "How do you make pancakes in an oven?");
                chatHistory.AddMessage(AuthorRole.Assistant, "make pancakes oven");
                chatHistory.AddMessage(AuthorRole.User, "How do you write a business plan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "write business plan");
                chatHistory.AddMessage(AuthorRole.User, "What is the capital of Japan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "capital Japan");
                chatHistory.AddMessage(AuthorRole.User, "How to set up a new email account?");
                chatHistory.AddMessage(AuthorRole.Assistant, "set up email account");
                chatHistory.AddMessage(AuthorRole.User, "What are the benefits of meditation?");
                chatHistory.AddMessage(AuthorRole.Assistant, "benefits meditation");
                chatHistory.AddMessage(AuthorRole.User, "How to make a website responsive?");
                chatHistory.AddMessage(AuthorRole.Assistant, "make website responsive");
                chatHistory.AddMessage(AuthorRole.User, "What is the difference between Python and Java?");
                chatHistory.AddMessage(AuthorRole.Assistant, "difference Python Java");
                chatHistory.AddMessage(AuthorRole.User, "How do I replace a car battery?");
                chatHistory.AddMessage(AuthorRole.Assistant, "replace car battery");
                chatHistory.AddMessage(AuthorRole.User, "What is the tallest mountain in the world?");
                chatHistory.AddMessage(AuthorRole.Assistant, "tallest mountain world");
                chatHistory.AddMessage(AuthorRole.User, "How can I improve my public speaking skills?");
                chatHistory.AddMessage(AuthorRole.Assistant, "improve public speaking skills");
                chatHistory.AddMessage(AuthorRole.User, "What is the population of Canada?");
                chatHistory.AddMessage(AuthorRole.Assistant, "population Canada");
                chatHistory.AddMessage(AuthorRole.User, "How to brew coffee using a French press?");
                chatHistory.AddMessage(AuthorRole.Assistant, "brew coffee French press");
                chatHistory.AddMessage(AuthorRole.User, "How does a blockchain work?");
                chatHistory.AddMessage(AuthorRole.Assistant, "blockchain work");
                chatHistory.AddMessage(AuthorRole.User, "What are the side effects of aspirin?");
                chatHistory.AddMessage(AuthorRole.Assistant, "side effects aspirin");
                chatHistory.AddMessage(AuthorRole.User, "How to start learning data science?");
                chatHistory.AddMessage(AuthorRole.Assistant, "start learning data science");
                chatHistory.AddMessage(AuthorRole.User, "What is the speed of light?");
                chatHistory.AddMessage(AuthorRole.Assistant, "speed of light");
                chatHistory.AddMessage(AuthorRole.User, "How do I bake a chocolate cake?");
                chatHistory.AddMessage(AuthorRole.Assistant, "bake chocolate cake");
                chatHistory.AddMessage(AuthorRole.User, "What are the causes of climate change?");
                chatHistory.AddMessage(AuthorRole.Assistant, "causes climate change");
                chatHistory.AddMessage(AuthorRole.User, "How to play the guitar for beginners?");
                chatHistory.AddMessage(AuthorRole.Assistant, "play guitar beginners");
                chatHistory.AddMessage(AuthorRole.User, "What are the symptoms of a common cold?");
                chatHistory.AddMessage(AuthorRole.Assistant, "symptoms common cold");
                chatHistory.AddMessage(AuthorRole.User, "How to create a budget plan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "create budget plan");

                await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
                {
                    Console.ForegroundColor = ConsoleColor.White;
                    Console.Write(text);

                    keywords += text;
                }
            }
        }

        keywords = Keywords(userInput);
        Console.WriteLine(keywords);

        while (!resultsfound)
        {
            Console.WriteLine("=== RETRIEVING [" + minRelevanceScoreValue + "]===");
            //"Instruct:Given the query, find all relevant text.\r\nQuery: " + keywords + "\r\n"
            //"Assistant: " + keywords + "\r\nUser:"
            //await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Query: " + keywords + "\r\n", limit: 10, minRelevanceScore: minRelevanceScoreValue))
            await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Assistant: " + keywords + "\r\nUser:", limit: 10, minRelevanceScore: minRelevanceScoreValue))
            {
                resultsfound = true;
                //builder.AppendLine(result.Metadata.Text + "\r\n\r\n" + result.Relevance + "\r\n\r\n");
                //CompleteAnswer += result.Metadata.Text;
                string highlightedText = result.Metadata.Text;
                foreach (var word in keywords.Split(' ', StringSplitOptions.RemoveEmptyEntries))
                {
                    highlightedText = Regex.Replace(highlightedText, " " + word, match => $"\x1b[31m{match.Value}\x1b[0m", RegexOptions.IgnoreCase);
                }

                CompleteAnswer += result.Metadata.Text + "\r\n";
                ColoredStringBuilder.AppendLine(highlightedText + "\r\n\r\n" + result.Relevance + "\r\n\r\n");

                sources.Add(result.Metadata.Id);
            }
            minRelevanceScoreValue -= .05d;
            if (minRelevanceScoreValue < .2d)
            {
                Console.WriteLine("Unable to find any subject using your keywords");
                return;
            }
        }

        ColoredStringBuilder.AppendLine("""

        Sources:
        """);

        CompleteAnswer += ("\r\n\r\nSources:\r\n");


        foreach (string source in sources)
        {
            ColoredStringBuilder.AppendLine($"    {source}");
            CompleteAnswer += $"    {source}\r\n";
        }
        CompleteAnswer += "\r\n";
        Console.WriteLine("=== DONE RETRIEVING ===");

        Console.WriteLine(ColoredStringBuilder.ToString());
        CompleteAnswer += "\r\n";
        //CompleteAnswer = builder.ToString();

        ClearContext();

        if (false)
        {
            //string InferPrompt = "System: I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\nUser: " + userInput;
            //<|begin_of_text|>
            string InferPrompt = "<|start_header_id|>system<|end_header_id|>\r\n" +
                                    "Cutting Knowledge Date: December 2023\r\n" +
                                    "Today Date: 26 Jul 2024\r\n\r\n" +
                                    "I am a law professor at a law school. I will answer your legal questions with the help of using ONLY the following information within the context of the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any further information or ask anything in return after giving you the direct answer to your question.\r\n" +
                                    "<|eot_id|><|start_header_id|>user<|end_header_id|>\r\n\r\n" +
                                    userInput + "\r\n" +
                                    "<|eot_id|><|start_header_id|>assistant<|end_header_id|>\r\n\r\n" +
                                    "### Start of Documentation:\r\n" +
                                    CompleteAnswer.Replace("'", "`") +
                                    "\r\n### End of Documentation\r\n";
            await foreach (var text in LLMStatelessExecutor.InferAsync(InferPrompt, inferenceParams)) // Generate the response streamingly.
            {
                Console.ForegroundColor = ConsoleColor.White;
                Console.Write(text);

                CompleteAnswer += text;
                ChatResponseToMeasure += text;
            }
            
        }
        else
        {
            chatHistory.AddMessage(AuthorRole.System, "I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\n\r\nIf I cannot answer I will say 'I am not sure'.\r\n");
            chatHistory.AddMessage(AuthorRole.Assistant, "I will answer all your legal questions in context of the law. I will answer your question and will not add anything else to the end of the answer. What legal question may I answer for you?");
            await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
            {
                Console.ForegroundColor = ConsoleColor.White;
                Console.Write(text);

                CompleteAnswer += text;
                ChatResponseToMeasure += text;
            }

        }

        ClearContext();
    }
    else
    {
        await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
        {
            Console.ForegroundColor = ConsoleColor.White;
            Console.Write(text);

            CompleteAnswer += text;
            ChatResponseToMeasure += text;
        }
    }

    long TokensInResponse = model.Tokenize(ChatResponseToMeasure, true, false, Encoding.ASCII).Length;
    Debug.WriteLine("Response Length: " + TokensInResponse);

    if (!ChatResponseToMeasure.EndsWith("User:") || TokensInResponse > inferenceParams.MaxTokens)
    {
        Console.Write("\r\nUser:");
    }

    if (CompleteAnswer != null)
    {
        TokensInMemory += model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length;

        Debug.WriteLine("User added " + model.Tokenize(userInput, true, false, Encoding.ASCII).Length + " Response added: " + model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length + " tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

        if (webSocketContext != null)
        {
            if (webSocketContext.WebSocket.State == WebSocketState.Open)
            {
                //HttpUtility.HtmlEncode(
                foreach (var MyString in CompleteAnswer.Split("\r\n"))
                {
                    webSocketContext.WebSocket.SendAsync(Encoding.UTF8.GetBytes(MyString), WebSocketMessageType.Text, true, CancellationToken.None);
                }
            }
        }

        Matches = Regex.Match(CompleteAnswer, @"myArray = \[.*?\];");
        if (Matches.Success)
        {
            Debug.WriteLine(Matches.Value);
        }
    }

    CompleteAnswer = null;
    Debug.WriteLine("ProcessAIRequest Finished");
}
async void StartWebSocketServer()
{
    HttpListener httpListener = new HttpListener();
    httpListener.Prefixes.Add("http://localhost:5000/ws/");
    httpListener.Start();
    Console.WriteLine("WebSocket server started at ws://localhost:5000/ws/");

    while (true)
    {
        HttpListenerContext httpContext = await httpListener.GetContextAsync();

        if (httpContext.Request.IsWebSocketRequest)
        {
            webSocketContext = await httpContext.AcceptWebSocketAsync(subProtocol: null);
            Console.WriteLine("WebSocket connection established.");

            await ProcessWebSocketMessages(webSocketContext.WebSocket);
        }
        else
        {
            httpContext.Response.StatusCode = 400;
            httpContext.Response.Close();
            Console.WriteLine("Non-WebSocket request received and rejected.");
        }
    }
}

async Task ProcessWebSocketMessages(WebSocket webSocket)
{
    var buffer = new byte[1024 * 4];

    while (webSocket.State == WebSocketState.Open)
    {
        WebSocketReceiveResult result = await webSocket.ReceiveAsync(new ArraySegment<byte>(buffer), CancellationToken.None);

        if (result.MessageType == WebSocketMessageType.Close)
        {
            await webSocket.CloseAsync(WebSocketCloseStatus.NormalClosure, "Closing", CancellationToken.None);
            Console.WriteLine("WebSocket connection closed.");
        }
        else
        {
            string message = Encoding.UTF8.GetString(buffer, 0, result.Count);
            Console.WriteLine($"{message}");
            ProcessAIRequest(message);
        }
    }
}

if (true)
{

}
else
{
    chatHistory.AddMessage(AuthorRole.System, "Transcript of a dialog, where the User interacts with an Assistant named Bob. Bob is Lawyer and is helpful, kind, honest, good at writing, and never fails to answer the User's requests immediately and with precision. Bob will only answer from information provided by Users input and will answer questions as short and precise as possible. After each answer I will cite the exact text that I pulled the inforamtion from word for word.");
    var Input = File.ReadAllText("D:\\Output-WC 25896.txt");
    Console.WriteLine("Console writeline length: " + Input.Length);
    chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000
    chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");
    //chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000
    //chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");
}

static void FocusProcess()
{
    IntPtr hWnd; //change this to IntPtr
    Process[] processRunning = Process.GetProcesses();
    foreach (Process pr in processRunning)
    {
        if (pr.ProcessName == "notepad")
        {
            hWnd = pr.MainWindowHandle; //use it as IntPtr not int
            ShowWindow(hWnd, 3);
            SetForegroundWindow(hWnd); //set to topmost
        }
    }
}

StartWebSocketServer();
FocusProcess();
Console.ForegroundColor = ConsoleColor.Yellow;
Console.Write("The chat session has started.\nUser: ");
Console.ForegroundColor = ConsoleColor.White;

void MeasureChatHistoryTokens()
{
    foreach (ChatHistory.Message Value in LLMChatSession.History.Messages.ToArray())
    {
        TokensInMemory += model.Tokenize(Value.Content, true, false, Encoding.ASCII).Length;
    }

}
Debug.WriteLine("Starting with tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

string userInput = "";
while (userInput != "exit")
{
    userInput = Console.ReadLine() ?? "";
    ProcessAIRequest(userInput);
}

async Task RunLLava()
{
    string MultiModel = @"D:\llava-v1.6-mistral-7b.Q4_K_M.gguf";
    
    //string multiModalProj = @"D:\mmproj-mistral7b-f16-q6_k.gguf";
    string multiModalProj = @"D:\mmproj-mistral7b-f16.gguf";
    string modelImage = @"D:\Ticket4.jpeg";
    const int maxTokens = 2048;

    var prompt = $"{{{modelImage}}}\nUSER:\nProvide a full description of the image, its fields and the values in each field.\nASSISTANT:\n";

    var parameters = new ModelParams(MultiModel);

    using var model = LLamaWeights.LoadFromFile(parameters);
    using var context = model.CreateContext(parameters);

    //https://platform.mindee.com/keld/traffic_ticket/live-interface#tab=%22extractedFields%22
    //https://www.cnblogs.com/gmmy/p/18146496
    //Multimodal model: llava-v1.6-mistral-7b.Q4_K_M.gguf Download address: https://huggingface.co/mradermacher/llava-v1.6-mistral-7b-GGUF/resolve/main/llava-v1.6-mistral-7b.Q4_K_M.gguf
    //Llava CLIP model: mmproj-mistral7b-f16-q6_k.gguf Download address: https://huggingface.co/cmp-nct/llava-1.6-gguf/resolve/main/mmproj-mistral7b-f16-q6_k.gguf?download=true
    // Llava Init
    using var clipModel = LLavaWeights.LoadFromFile(multiModalProj);

    var ex = new InteractiveExecutor(context, clipModel);

    Console.ForegroundColor = ConsoleColor.Yellow;
    Console.WriteLine("The executor has been enabled. In this example, the prompt is printed, the maximum tokens is set to {0} and the context size is {1}.", maxTokens, parameters.ContextSize);
    Console.WriteLine("To send an image, enter its filename in curly braces, like this {c:/image.jpg}.");

    var inferenceParams = new InferenceParams() { Temperature = 0.1f, AntiPrompts = new List<string> { "\nUSER:" }, MaxTokens = maxTokens };

    do
    {

        // Evaluate if we have images
        //
        var imageMatches = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);
        var imageCount = imageMatches.Count();
        var hasImages = imageCount > 0;

        if (hasImages)
        {
            var imagePathsWithCurlyBraces = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);
            var imagePaths = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Groups[1].Value).ToList();

            List<byte[]> imageBytes;
            try
            {
                imageBytes = imagePaths.Select(File.ReadAllBytes).ToList();
            }
            catch (IOException exception)
            {
                Console.ForegroundColor = ConsoleColor.Red;
                Console.Write($"Could not load your {(imageCount == 1 ? "image" : "images")}:");
                Console.Write($"{exception.Message}");
                Console.ForegroundColor = ConsoleColor.Yellow;
                Console.WriteLine("Please try again.");
                break;
            }

            // Each prompt with images we clear cache
            // When the prompt contains images we clear KV_CACHE to restart conversation
            // See:
            // https://github.com/ggerganov/llama.cpp/discussions/3620
            ex.Context.NativeHandle.KvCacheRemove(LLamaSeqId.Zero, -1, -1);

            int index = 0;
            foreach (var path in imagePathsWithCurlyBraces)
            {
                // First image replace to tag <image, the rest of the images delete the tag
                prompt = prompt.Replace(path, index++ == 0 ? "<image>" : "");
            }


            Console.ForegroundColor = ConsoleColor.Yellow;
            Console.WriteLine($"Here are the images, that are sent to the chat model in addition to your message.");
            Console.WriteLine();

            /*
            foreach (var consoleImage in imageBytes?.Select(bytes => new CanvasImage(bytes)))
            {
                consoleImage.MaxWidth = 50;
                Spectre.Console.AnsiConsole.Write(consoleImage);
            }
            */

            Console.WriteLine();
            Console.ForegroundColor = ConsoleColor.Yellow;
            Console.WriteLine($"The images were scaled down for the console only, the model gets full versions.");
            Console.WriteLine($"Write /exit or press Ctrl+c to return to main menu.");
            Console.WriteLine();


            // Initialize Images in executor
            //
            foreach (var image in imagePaths)
            {
                ex.Images.Add(await File.ReadAllBytesAsync(image));
            }
        }

        Console.ForegroundColor = ConsoleColor.White;
        await foreach (var text in ex.InferAsync(prompt, inferenceParams))
        {
            Console.Write(text);
        }
        Console.Write(" ");
        Console.ForegroundColor = ConsoleColor.Green;
        prompt = Console.ReadLine();
        Console.WriteLine();

        // let the user finish with exit
        //
        if (prompt != null && prompt.Equals("/exit", StringComparison.OrdinalIgnoreCase))
            break;

    }
    while (true);
}

//Unable to use to do "Top level statements must procede namespace and type declerations.
[Flags]
enum MyLoadedMethod : ushort
{
    Plain = 0,
    RAG = 1
}

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

585

586

587

588

589

590

591

592

593

594

595

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

646

647

648

649

650

651

652

653

654

655

656

657

658

659

660

661

662

663

664

665

666

667

668

669

670

671

672

673

674

675

676

677

678

679

680

681

682

683

684

685

686

687

688

689

690

691

692

693

694

695

696

697

698

699

700

701

702

703

704

705

706

707

708

709

710

711

712

713

714

715

716

717

718

719

720

721

722

723

724

725

726

727

728

729

730

731

732

733

734

735

736

737

738

739

740

741

742

743

744

745

746

747

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

773

774

775

776

777

778

779

780

781

782

783

784

785

786

787

788

789

790

791

792

793

794

795

796

797

798

799

800

801

802

803

804

805

806

807

808

809

810

811

812

813

814

815

816

817

818

819

820

821

822

823

824

825

826

827

828

829

830

831

832

833

834

835

836

837

838

839

840

841

842

843

844

845

846

847

848

849

850

851

852

853

854

855

856

857

858

859

860

861

862

863

864

865

866

867

868

869

870

871

872

873

874

875

876

877

878

879

880

881

882

883

884

885

886

887

888

889

890

891

892

893

894

895

896

897

898

899

900

901

902

903

904

905

906

907

908

909

910

911

912

913

914

915

916

917

918

919

920

921

922

923

924

925

926

927

928

929

930

931

932

933

934

935

936

937

938

939

940

941

942

943

944

945

946

947

948

949

950

951

952

953

954

955

956

957

958

959

960

961

962

963

964

965

966

967

968

969

970

971

972

973

974

975

976

977

978

979

980

981

982

983

984

985

986

// See https://aka.ms/new-console-template for more information

//leaderboards

//https://huggingface.co/spaces/mteb/leaderboard

//Implement with Python

//https://www.llamaindex.ai/

//https://docs.llamaindex.ai/en/stable/getting_started/discover_llamaindex/

//Install-Package LLamaSharp

//Install-Package LLamaSharp.Backend.Cuda11

//https://dotnet.microsoft.com/en-us/download/dotnet/8.0

//https://dotnet.microsoft.com/en-us/download/dotnet

//The top line returns waaayy better results then the bottom

//Assistant: discovery\r\nUser:

//discovery

using LLama.Common;

using LLama;

#pragma warning disable SKEXP0050, SKEXP0001, SKEXP0020

//RAG

//Install-Package LLamaSharp.Semantic-Kernel

//https://github.com/SciSharp/LLamaSharp/issues/648

using LLamaSharp.SemanticKernel.TextEmbedding;

//Install-Package Microsoft.SemanticKernel

using Microsoft.SemanticKernel.Connectors;

using Microsoft.SemanticKernel.Memory;

using Microsoft.SemanticKernel.Text;

//Install-Package Microsoft.SemanticKernel.Connectors.Sqlite -Version 1.18.0-alpha

using Microsoft.SemanticKernel.Connectors.Sqlite;

using System.IO;

using System.Text.RegularExpressions;

using System.Diagnostics;

using System.Net.WebSockets;

using System.Text;

using System.Net;

using System.Management;

using SQLitePCL;

using System;

using System.Collections;

using System.Windows.Documents;

using System.Runtime.InteropServices;

using static System.Net.Mime.MediaTypeNames;

using System.CodeDom.Compiler;

using System.Reflection;

using Microsoft.Data.Sqlite;

using static System.Collections.Specialized.BitVector32;

using LLama.Native;

//LLava

//Install-package spectre.console

[DllImport("user32.dll")]

static extern IntPtr SetForegroundWindow(IntPtr hWnd);

[DllImport("user32.dll")]

static extern bool ShowWindow(IntPtr hWnd, int nCmdShow); //ShowWindow needs an IntPtr

Console.ForegroundColor = ConsoleColor.White;

Console.WriteLine("Starting ISPortal AI!");

HttpListenerWebSocketContext webSocketContext = null;

//https://huggingface.co/mradermacher/llava-v1.6-mistral-7b-GGUF/tree/main

string RagModelPath = @"D:\LLM\bge-large-en-v1.5-q8_0.gguf";

//string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q6_K.gguf";

string modelPath = @"D:\LLM\Saul-Instruct-v1.Q8_0.gguf";

//string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q8_0.gguf"; // change it to your own model path.

//string modelPath = @"D:\Meta-Llama-3.1-70B-Instruct-Q6_K-00001-of-00002.gguf"; // Way too large for my computer

//var embeddingModelPath = Path.GetFullPath("<path to embed model>/nomic-embed.gguf");

string LocalMemoryPath = @"C:\Users\User\Desktop\MyMemory.db";

string PathToFilesToIngest = "D:\\Embeddings";

ManagementObjectSearcher searcher = new ManagementObjectSearcher("SELECT * FROM Win32_Processor");

List<int> coresCPUs = new List<int>();

foreach (ManagementObject mo in searcher.Get())

{

coresCPUs.Add(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));

Debug.WriteLine(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));

}

//RAG variables

ModelParams RAGparameters = null;

ISemanticTextMemory MyMemoryStore = null;

//All operations

LLamaWeights model = null;

LLamaContext context = null;

InteractiveExecutor executor = null;

var MyStartupMethod = MyLoadedMethod.RAG;

string collectionName = "TestCollection";

// Add chat histories as prompt to tell AI how to act.

var chatHistory = new ChatHistory();

var chatHistory2 = new ChatHistory();

string Str = null;

switch ("rag")

{

case "train":

chatHistory.AddMessage(AuthorRole.System, "Generate new examples based on user input examples, once asked to write additional samples, take the previous request and continue to generate addtional samples. All answers need to strictly be formed into a statement and then answered as a JSON array of strings, always add a semicolon after each string array to close the statement properly. All commands should be for use by the windows operating system. Do not explain, add notes or say anything else unless specifically asked to for any reason.");

chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate to program files in windows, find a folder with the word steam in it then create a subfolder inside with two text files and populate a random string in each text file. Write the commands using a json array of strings to be processed by an interrupter."); //10000

Str = "myArray = [\"CD \\\\\", \"CD C:\\\\Program Files\\\\\", \"DIR /OD \\\"*steam*\\\"\", \"MKDIR \\\"SteamFolder\\\"\", \"MD \\\"SteamFolder\\\\subfolder\\\", \\\"ECHO New content 1 > \\\"SteamFolder\\\\subfolder\\\\file1.txt\", \"COPY \\\"asdawdafag\\\" > \\\"SteamFolder\\\\subfolder\\\\file2.txt\\\"\"];";

chatHistory.AddMessage(AuthorRole.Assistant, Str);

chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000

Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";

chatHistory.AddMessage(AuthorRole.Assistant, Str);

chatHistory.AddMessage(AuthorRole.User, "Great, now continue to write addtional samples, remember to keep the format as a statement, then followed by a JSON answer with a semicolon at the end of each JSON answer. I will ask for over 100 samples."); //10000

chatHistory.AddMessage(AuthorRole.Assistant, "Ping google.com and write the the results to a text file then open the program files folder using explorer. myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];"); //10000

chatHistory.AddMessage(AuthorRole.User, "y"); //10000

chatHistory.AddMessage(AuthorRole.Assistant, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside. myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];"); //10000

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Use Moveit.exe to move a file named NTFS.mbr localy, then zip the moved file and display its size. myArray = [\"Moveit \\\"NTFS.mbr\\\" C:\", \"7z a ntfs.zip ntfs.mbr\", \"7z l ntfs.zip\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to direct a LAN IP to a temp directory, download a single file using curl and extract the extracted content into a subfolder named debug. myArray = [\"MKDIR C:\\\\tmp\\\", \"curl \\\"http://192.168.1.100/somefile.zip\\\" -o C:\\\\tmp\", \"7z e C:\\\\tmp\\\\somefile.zip -od C:\\\\tmp\\\\debug\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Create a random 32 character hexadecimal color code, then use the color picker tool in Windows to open up a default browser using this new color as its background. myArray = [\"wmic os get version > C:\\versions.txt\", \"color cc233330cc2233c2\", \"explorer https://www.google.com\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to create an Ecrypted zip archive and store it in the users desktop directory, than extract this zip file with AES encryption using 7z. myArray = [\"cipher /E /S:C:\\\\Users\\\\username\\\\Documents\" > C:\\UserEnv, \"cipher /D /S:C:\\\\Users\\\\username\\\\Documents\", \"CIPHER /P\"aVeryStrongPassword123\\* \\\"C:\\\\Users\\\\username\\\\Desktop\\\\enc.zip\\\"\", \"7z e -hp\"aVeryStrongPassword123 \\*.zip\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Display user accounts with administrative privileges, and list the user object properties in Windows registry. myArray = [\"wmic useraccount where Enabled=TRUE and Administrator=TRUE get *\", \"reg query HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\\\Winlogon /v DefaultUserName\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Change password for a service called misconfigure-MDViewer, change priority of CpuGroup1; write a list of commands to accomplish these tasks. myArray = [\"net user \\\"misconfigure-MDViewer\\\" changesPassword!!\"], \"wmic cpu Get Name\", \"wmic process where ProcessID=1234 set Priority=5\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Use the Windows Task Scheduler to create a scheduled task to download a simple text file from a remote server every 10 minutes. myArray = [\"schtasks /create /tn \"MyTask\" /tr \"curl http://192.168.1.100/textfile.txt -o C:\\tmp\\mytext.txt\\\"\", \"schtasks /change /tn \"MyTask\\\" /st 00:00 /ri 10\"];");

chatHistory.AddMessage(AuthorRole.User, "y");

chatHistory.AddMessage(AuthorRole.Assistant, "Write a batch file that opens up Internet Explorer with two tabs one with the url google.com and another with bing.com. myArray = [\"start iexplore.exe \\\"http://www.google.com\\\", start iexplore.exe \\\"http://www.bing.com\\\"\"];");

break;

case "production":

chatHistory.AddMessage(AuthorRole.System, "Transcribe request from the user into an array of JSON strings labeled 'myArray' to be processed by an interpreter that will parse an array of strings and execute them on a system. All answers need to strictly be formed into a JSON array of strings for the windows operating system. Only give the results in JSON format and do not explain or say anything else unless asked specifically.");

chatHistory.AddMessage(AuthorRole.Assistant, Str);

chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000

Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";

chatHistory.AddMessage(AuthorRole.Assistant, Str);

chatHistory.AddMessage(AuthorRole.User, "Ping google.com and write the the results to a text file then open the program files folder using explorer."); //10000

Str = "myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];";

chatHistory.AddMessage(AuthorRole.Assistant, Str);

chatHistory.AddMessage(AuthorRole.User, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside."); //10000

Str = "myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];";

chatHistory.AddMessage(AuthorRole.Assistant, Str);

break;

case "rag":

//chatHistory.AddMessage(AuthorRole.System, "You are a legal assistance. You will be provided context to some data and will answer any questions you receive the best you can with the context provided and do not include information outside of the information provided.");

break;

default:

Console.WriteLine("Number is not between 1 and 4");

break;

}

//LLM variables

var LLMparameters = new ModelParams(modelPath)

{

ContextSize = 13107, // Does not require alot of memory

//ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl

//If commented out, swaps to CPU

//GpuLayerCount = 0

GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.

};

LLamaWeights LLMmodel = null;

LLamaContext LLMcontext = null;

LLamaContext.State CleanContext = null;

InteractiveExecutor LLMexecutor = null;

StatelessExecutor LLMStatelessExecutor = null; //Not currently in use. Results were bad.

StatefulExecutorBase.ExecutorBaseState CleanExectuor = null;

ChatSession LLMChatSession = null;

SessionState CleanChatSession = null;

InferenceParams inferenceParams = new InferenceParams()

{

Temperature = 0.4f,

MaxTokens = 512, // No more than 256 tokens should appear in answer. Remove it if antiprompt is enough for control.

AntiPrompts = new List<string> { "\nUser:" } // Stop generation once antiprompts appear.

};

async Task LoadModule()

{

if (MyStartupMethod == MyLoadedMethod.RAG) //RAG //Checks for enum need to be wrapped in a function to be valid.

{

RAGparameters = new ModelParams(RagModelPath)

{

ContextSize = 32000, // Does not require alot of memory

//ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl

Embeddings = true,

//GpuLayerCount = 0 //If commented out, swaps to CPU

GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.

};

model = LLamaWeights.LoadFromFile(RAGparameters);

context = model.CreateContext(RAGparameters);

executor = new InteractiveExecutor(context);

var embedder = new LLamaEmbedder(model, RAGparameters);

var service = new LLamaSharpEmbeddingGeneration(embedder);

MyMemoryStore = new MemoryBuilder().WithMemoryStore(await SqliteMemoryStore.ConnectAsync(LocalMemoryPath)).WithTextEmbeddingGeneration(service).Build();

await IngestFile();

LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);

LLMStatelessExecutor = new StatelessExecutor(LLMmodel, LLMparameters);

LLMcontext = LLMmodel.CreateContext(LLMparameters);

LLMexecutor = new InteractiveExecutor(LLMcontext);

LLMChatSession = new(LLMexecutor, chatHistory);

}

else

{

LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);

LLMcontext = LLMmodel.CreateContext(LLMparameters);

LLMexecutor = new InteractiveExecutor(LLMcontext);

LLMChatSession = new(LLMexecutor, chatHistory);

}

CleanExectuor = LLMexecutor.GetStateData();

CleanChatSession = LLMChatSession.GetSessionState();

CleanContext = LLMcontext.GetState();

//_memoryStore

//var field = MyMemoryStore.GetType().GetField("_storage", BindingFlags.NonPublic | BindingFlags.Instance);

//var memoryStore = (Dictionary<string, string>)field.GetValue(MyMemoryStore);

//var keys = memoryStore.Keys.ToList();

using (var connection = new SqliteConnection("Data Source=" + LocalMemoryPath))

{

connection.Open();

var command = connection.CreateCommand();

command.CommandText = @"SELECT COUNT(1) from SKMemoryTable";

Debug.WriteLine(command.ExecuteScalar());

//collection, key, metadata, embedding, timestamp

//metadata holds a json string of "is_reference", "external_source_name", "id" and "description", "text", "additional_metadata"

command.CommandText = @"SELECT DISTINCT key FROM SKMemoryTable"; // Replace 'MemoryTable' with the actual table name

using (var reader = command.ExecuteReader())

{

while (reader.Read())

{

//Console.WriteLine(reader.GetString(0));

}

//System.Diagnostics.Debugger.Break();

//LLMsession.SaveSession();

}

if (false)

{

await RunLLava();

Console.ReadKey();

return;

}

await LoadModule();

string CompleteAnswer = null;

Match Matches;

long TokensInMemory = 0;

IEnumerable<string> SplitToLines(string stringToSplit, int maximumLineLength)

{

var words = stringToSplit.Split(' ').Concat(new[] { "" });

return

words

.Skip(1)

.Aggregate(

words.Take(1).ToList(),

(a, w) =>

{

var last = a.Last();

while (last.Length > maximumLineLength)

{

a[a.Count() - 1] = last.Substring(0, maximumLineLength);

last = last.Substring(maximumLineLength);

a.Add(last);

}

var test = last + " " + w;

if (test.Length > maximumLineLength)

{

a.Add(w);

}

else

{

a[a.Count() - 1] = test;

}

return a;

});

}

async Task IngestFile()

{

long TotalParagraphsLoaded = 0;

Console.WriteLine("===== INGESTING =====");

IList<string> collections = await MyMemoryStore.GetCollectionsAsync();

string folderPath = Path.GetFullPath(PathToFilesToIngest);

string[] files = Directory.GetFiles(folderPath);

if (collections.Contains(collectionName))

{

Console.WriteLine("Found database");

}

else

{

List<Task> tasks = new List<Task>();

foreach (var item in files.Select((path, index) => new { path, index }))

{

Console.WriteLine($"Ingesting file #{item.index}");

string text = File.ReadAllText(item.path);

if (false)

{

var sentences = TextChunker.SplitPlainTextLines(text, 256);

var paragraphs = TextChunker.SplitPlainTextParagraphs(sentences, 1024);

foreach (var para in paragraphs.Select((text, index) => new { text, index }))

await MyMemoryStore.SaveInformationAsync(collectionName, para.text, $"Document {item.path}, Paragraph {para.index}");

}

else if (true)

{

string[] splitQuestions = Regex.Split(text, @"(?=Question\s\d+\.)");

long ParaIndex = 1;

foreach (string question in splitQuestions)

{

if (!string.IsNullOrWhiteSpace(question))

{

try

{

//description is stored in the metadata column, same with additional_metadata. Remember, converting to weights takes about 6-7x times the space in total.

Debug.WriteLine("Importing: " + model.Tokenize(question.Trim(), true, false, Encoding.ASCII).Length + "\r\n");

if (model.Tokenize(question.Trim(), true, false, Encoding.ASCII).Length >= 512)

{

foreach (string DataToAdd in SplitToLines(question.Trim(), question.Trim().Length / 2 + 10)) //800

{

Debug.WriteLine("Splitting into: " + model.Tokenize(DataToAdd, true, false, Encoding.ASCII).Length + "\r\n");

await MyMemoryStore.SaveInformationAsync(collectionName, DataToAdd, ($"Document {item.path}, Paragraph {ParaIndex++}"));

}

else

{

await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), ($"Document {item.path}, Paragraph {ParaIndex++}"));

}

catch

{

}

//tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));

TotalParagraphsLoaded++;

}

else if (false)

{

string[] splitQuestions = Regex.Split(text, @"(?<=[.!?])\s+|(?<=\.\.)\s*|\r\n|\n"); //each sentence

long ParaIndex = 1;

foreach (string question in splitQuestions)

{

if (!string.IsNullOrWhiteSpace(question))

{

//await memory.SaveReferenceAsync()

await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}");

//tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));

TotalParagraphsLoaded++;

}

//await Task.WhenAll(tasks);

}

Console.WriteLine("Generated database with " + TotalParagraphsLoaded + " items.");

}

Console.WriteLine("===== DONE INGESTING =====");

}

void ClearContext()

{

return;

LLMChatSession.LoadSession(CleanChatSession);

Debug.WriteLine(LLMChatSession.HistoryTransform.HistoryToText(LLMChatSession.History));

return;

LLMcontext.Dispose();

LLMexecutor = null;

LLMChatSession = null;

LLMcontext = LLMmodel.CreateContext(LLMparameters);

LLMexecutor = new InteractiveExecutor(LLMcontext);

LLMChatSession = new(LLMexecutor, chatHistory);

return;

chatHistory.Messages.Clear();

LLMcontext.LoadState(CleanContext);

LLMChatSession.LoadSession(CleanChatSession);

LLMexecutor.LoadState(CleanExectuor);

return;

while (LLMChatSession.History.Messages.Count > 0)

{

LLMChatSession.RemoveLastMessage();

}

return;

}

string Keywords(string sentence)

{

HashSet<string> StopWords = new HashSet<string>(new[]

{

"a", "an", "and", "the", "is", "in", "on", "at", "of", "for", "to", "with", "by", "from", "that", "this", "it",

"as", "are", "was", "were", "be", "been", "has", "have", "had", "but", "or", "not", "so", "if", "then", "i",

"me", "my", "myself", "we", "our", "ours", "ourselves", "you", "your", "yours", "yourself", "yourselves",

"he", "him", "his", "himself", "she", "her", "hers", "herself", "its", "itself", "they", "them", "their",

"theirs", "themselves", "what", "which", "who", "whom", "these", "those", "am", "being", "do", "does",

"did", "doing", "because", "until", "while", "about", "against", "between", "into", "through", "during",

"before", "after", "above", "below", "up", "down", "out", "off", "over", "under", "again", "further",

"once", "here", "there", "when", "where", "why", "how", "all", "any", "both", "each", "few", "more",

"most", "other", "some", "such", "no", "nor", "only", "own", "same", "than", "too", "very", "s", "t",

"can", "will", "just", "don", "should", "now"

});

string cleanSentence = Regex.Replace(sentence.ToLower(), @"[^\w\s]", "");

// Split sentence into words

var words = cleanSentence.Split(new[] { ' ', '\t', '\n', '\r' }, StringSplitOptions.RemoveEmptyEntries);

// Filter out stop words and return remaining words as keywords

var keywords = words.Where(word => !StopWords.Contains(word)).ToList();

// Join the keywords into a single string separated by spaces

return string.Join(" ", keywords);

}

async void ProcessAIRequest(string userInput)

{

Debug.WriteLine("ProcessAIRequest starting");

TokensInMemory += model.Tokenize(userInput, true, false, Encoding.ASCII).Length;

//executor.rag

//RAG and context building: https://medium.com/@bruno.facco/rag-from-concept-to-application-using-gpt-llama-index-and-sql-retriever-cfb437da99eb

//session.

String ChatResponseToMeasure = null;

if (MyStartupMethod == MyLoadedMethod.RAG)

{

StringBuilder ColoredStringBuilder = new();

ColoredStringBuilder.Clear();

List<string> sources = [];

var resultsfound = false;

double minRelevanceScoreValue = 0.8;

Console.WriteLine("=== Extracting Keywords ===");

string prompt = "System: Ensure that the results contain ALL of the words from the following user query. The words must appear at least once anywhere in the result, without exception.\r\n The results are in the following format, The question number, the question, possible answers then followed by the explanation. The user will give keywords and return the results if those keywords appear in any of the result, either in the question or the explanation.\r\n" +

"Assistant: I will only return results that include every single keyword provided by the user. If even one keyword is missing, the result will not be returned, without exception.\r\n" +

"User: " + userInput;

string prompt = userInput;

string keywords = "";

string StrchatHistory = "\r\nUser: What is Congresses Commerce Clause powers?\r\n" +

"Assistant: Congress Commerce Clause\r\n" +

"User: What time is it in new york?\r\n" +

"Assistant: time new york\r\n" +

"User: How do you fill up a car tire?\r\n" +

"Assistant: fill up car tire\r\n" +

"User: How fast can a car go on a freeway?\r\n" +

"Assistant: fast car freeway\r\n" +

"User: How do you make pancakes in an oven?\r\n" +

"Assistant: make pancakes oven\r\n" +

"User: How do you write a business plan?\r\n" +

"Assistant: write business plan\r\n" +

"User: What is the capital of Japan?\r\n" +

"Assistant: capital Japan\r\n" +

"User: How to set up a new email account?\r\n" +

"Assistant: set up email account\r\n" +

"User: What are the benefits of meditation?\r\n" +

"Assistant: benefits meditation\r\n" +

"User: How to make a website responsive?\r\n" +

"Assistant: make website responsive\r\n" +

"User: What is the difference between Python and Java?\r\n" +

"Assistant: difference Python Java\r\n" +

"User: How do I replace a car battery?\r\n" +

"Assistant: replace car battery\r\n" +

"User: What is the tallest mountain in the world?\r\n" +

"Assistant: tallest mountain world\r\n" +

"User: How can I improve my public speaking skills?\r\n" +

"Assistant: improve public speaking skills\r\n" +

"User: What is the population of Canada?\r\n" +

"Assistant: population Canada\r\n" +

"User: How to brew coffee using a French press?\r\n" +

"Assistant: brew coffee French press\r\n" +

"User: How does a blockchain work?\r\n" +

"Assistant: blockchain work\r\n" +

"User: What are the side effects of aspirin?\r\n" +

"Assistant: side effects aspirin\r\n" +

"User: How to start learning data science?\r\n" +

"Assistant: start learning data science\r\n" +

"User: What is the speed of light?\r\n" +

"Assistant: speed of light\r\n" +

"User: How do I bake a chocolate cake?\r\n" +

"Assistant: bake chocolate cake\r\n" +

"User: What are the causes of climate change?\r\n" +

"Assistant: causes climate change\r\n" +

"User: How to play the guitar for beginners?\r\n" +

"Assistant: play guitar beginners\r\n" +

"User: What are the symptoms of a common cold?\r\n" +

"Assistant: symptoms common cold\r\n" +

"User: How to create a budget plan?\r\n" +

"Assistant: create budget plan\r\n";

if (false)

{

if (true)

{

await foreach (var text in LLMStatelessExecutor.InferAsync("System: Return only the keywords from the following statement and do not provide anything else. Use spaces when outputing the keywords values and do not add anything futher." + StrchatHistory + "User: '" + userInput + "'", inferenceParams)) // Generate the response streamingly.

{

Console.ForegroundColor = ConsoleColor.White;

Console.Write(text);

keywords += text;

}

else

{

//chatHistory.Messages.Clear();

chatHistory.AddMessage(AuthorRole.System, "I am a search engine assistant. I will only return back keywords from any statement you make and nothing else with no exceptions.\r\n");

chatHistory.AddMessage(AuthorRole.User, "What is Congresses Commerce Clause powers?");

chatHistory.AddMessage(AuthorRole.Assistant, "Congress Commerce Clause");

chatHistory.AddMessage(AuthorRole.User, "What time is it in new york?");

chatHistory.AddMessage(AuthorRole.Assistant, "time new york");

chatHistory.AddMessage(AuthorRole.User, "How do you fill up a car tire?");

chatHistory.AddMessage(AuthorRole.Assistant, "fill up car tire");

chatHistory.AddMessage(AuthorRole.User, "How fast can a car go on a freeway?");

chatHistory.AddMessage(AuthorRole.Assistant, "fast car freeway");

chatHistory.AddMessage(AuthorRole.User, "How do you make pancakes in an oven?");

chatHistory.AddMessage(AuthorRole.Assistant, "make pancakes oven");

chatHistory.AddMessage(AuthorRole.User, "How do you write a business plan?");

chatHistory.AddMessage(AuthorRole.Assistant, "write business plan");

chatHistory.AddMessage(AuthorRole.User, "What is the capital of Japan?");

chatHistory.AddMessage(AuthorRole.Assistant, "capital Japan");

chatHistory.AddMessage(AuthorRole.User, "How to set up a new email account?");

chatHistory.AddMessage(AuthorRole.Assistant, "set up email account");

chatHistory.AddMessage(AuthorRole.User, "What are the benefits of meditation?");

chatHistory.AddMessage(AuthorRole.Assistant, "benefits meditation");

chatHistory.AddMessage(AuthorRole.User, "How to make a website responsive?");

chatHistory.AddMessage(AuthorRole.Assistant, "make website responsive");

chatHistory.AddMessage(AuthorRole.User, "What is the difference between Python and Java?");

chatHistory.AddMessage(AuthorRole.Assistant, "difference Python Java");

chatHistory.AddMessage(AuthorRole.User, "How do I replace a car battery?");

chatHistory.AddMessage(AuthorRole.Assistant, "replace car battery");

chatHistory.AddMessage(AuthorRole.User, "What is the tallest mountain in the world?");

chatHistory.AddMessage(AuthorRole.Assistant, "tallest mountain world");

chatHistory.AddMessage(AuthorRole.User, "How can I improve my public speaking skills?");

chatHistory.AddMessage(AuthorRole.Assistant, "improve public speaking skills");

chatHistory.AddMessage(AuthorRole.User, "What is the population of Canada?");

chatHistory.AddMessage(AuthorRole.Assistant, "population Canada");

chatHistory.AddMessage(AuthorRole.User, "How to brew coffee using a French press?");

chatHistory.AddMessage(AuthorRole.Assistant, "brew coffee French press");

chatHistory.AddMessage(AuthorRole.User, "How does a blockchain work?");

chatHistory.AddMessage(AuthorRole.Assistant, "blockchain work");

chatHistory.AddMessage(AuthorRole.User, "What are the side effects of aspirin?");

chatHistory.AddMessage(AuthorRole.Assistant, "side effects aspirin");

chatHistory.AddMessage(AuthorRole.User, "How to start learning data science?");

chatHistory.AddMessage(AuthorRole.Assistant, "start learning data science");

chatHistory.AddMessage(AuthorRole.User, "What is the speed of light?");

chatHistory.AddMessage(AuthorRole.Assistant, "speed of light");

chatHistory.AddMessage(AuthorRole.User, "How do I bake a chocolate cake?");

chatHistory.AddMessage(AuthorRole.Assistant, "bake chocolate cake");

chatHistory.AddMessage(AuthorRole.User, "What are the causes of climate change?");

chatHistory.AddMessage(AuthorRole.Assistant, "causes climate change");

chatHistory.AddMessage(AuthorRole.User, "How to play the guitar for beginners?");

chatHistory.AddMessage(AuthorRole.Assistant, "play guitar beginners");

chatHistory.AddMessage(AuthorRole.User, "What are the symptoms of a common cold?");

chatHistory.AddMessage(AuthorRole.Assistant, "symptoms common cold");

chatHistory.AddMessage(AuthorRole.User, "How to create a budget plan?");

chatHistory.AddMessage(AuthorRole.Assistant, "create budget plan");

await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.

{

Console.ForegroundColor = ConsoleColor.White;

Console.Write(text);

keywords += text;

}

keywords = Keywords(userInput);

Console.WriteLine(keywords);

while (!resultsfound)

{

Console.WriteLine("=== RETRIEVING [" + minRelevanceScoreValue + "]===");

//"Instruct:Given the query, find all relevant text.\r\nQuery: " + keywords + "\r\n"

//"Assistant: " + keywords + "\r\nUser:"

//await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Query: " + keywords + "\r\n", limit: 10, minRelevanceScore: minRelevanceScoreValue))

await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Assistant: " + keywords + "\r\nUser:", limit: 10, minRelevanceScore: minRelevanceScoreValue))

{

resultsfound = true;

//builder.AppendLine(result.Metadata.Text + "\r\n\r\n" + result.Relevance + "\r\n\r\n");

//CompleteAnswer += result.Metadata.Text;

string highlightedText = result.Metadata.Text;

foreach (var word in keywords.Split(' ', StringSplitOptions.RemoveEmptyEntries))

{

highlightedText = Regex.Replace(highlightedText, " " + word, match => $"\x1b[31m{match.Value}\x1b[0m", RegexOptions.IgnoreCase);

}

CompleteAnswer += result.Metadata.Text + "\r\n";

ColoredStringBuilder.AppendLine(highlightedText + "\r\n\r\n" + result.Relevance + "\r\n\r\n");

sources.Add(result.Metadata.Id);

}

minRelevanceScoreValue -= .05d;

if (minRelevanceScoreValue < .2d)

{

Console.WriteLine("Unable to find any subject using your keywords");

return;

}

ColoredStringBuilder.AppendLine("""

Sources:

""");

CompleteAnswer += ("\r\n\r\nSources:\r\n");

foreach (string source in sources)

{

ColoredStringBuilder.AppendLine($" {source}");

CompleteAnswer += $" {source}\r\n";

}

CompleteAnswer += "\r\n";

Console.WriteLine("=== DONE RETRIEVING ===");

Console.WriteLine(ColoredStringBuilder.ToString());

CompleteAnswer += "\r\n";

//CompleteAnswer = builder.ToString();

ClearContext();

if (false)

{

//string InferPrompt = "System: I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\nUser: " + userInput;

//<|begin_of_text|>

string InferPrompt = "<|start_header_id|>system<|end_header_id|>\r\n" +

"Cutting Knowledge Date: December 2023\r\n" +

"Today Date: 26 Jul 2024\r\n\r\n" +

"I am a law professor at a law school. I will answer your legal questions with the help of using ONLY the following information within the context of the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any further information or ask anything in return after giving you the direct answer to your question.\r\n" +

userInput + "\r\n" +

"### Start of Documentation:\r\n" +

CompleteAnswer.Replace("'", "`") +

"\r\n### End of Documentation\r\n";

await foreach (var text in LLMStatelessExecutor.InferAsync(InferPrompt, inferenceParams)) // Generate the response streamingly.

{

Console.ForegroundColor = ConsoleColor.White;

Console.Write(text);

CompleteAnswer += text;

ChatResponseToMeasure += text;

}

else

{

chatHistory.AddMessage(AuthorRole.System, "I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\n\r\nIf I cannot answer I will say 'I am not sure'.\r\n");

chatHistory.AddMessage(AuthorRole.Assistant, "I will answer all your legal questions in context of the law. I will answer your question and will not add anything else to the end of the answer. What legal question may I answer for you?");

await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.

{

Console.ForegroundColor = ConsoleColor.White;

Console.Write(text);

CompleteAnswer += text;

ChatResponseToMeasure += text;

}

ClearContext();

}

else

{

await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.

{

Console.ForegroundColor = ConsoleColor.White;

Console.Write(text);

CompleteAnswer += text;

ChatResponseToMeasure += text;

}

long TokensInResponse = model.Tokenize(ChatResponseToMeasure, true, false, Encoding.ASCII).Length;

Debug.WriteLine("Response Length: " + TokensInResponse);

if (!ChatResponseToMeasure.EndsWith("User:") || TokensInResponse > inferenceParams.MaxTokens)

{

Console.Write("\r\nUser:");

}

if (CompleteAnswer != null)

{

TokensInMemory += model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length;

Debug.WriteLine("User added " + model.Tokenize(userInput, true, false, Encoding.ASCII).Length + " Response added: " + model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length + " tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

if (webSocketContext != null)

{

if (webSocketContext.WebSocket.State == WebSocketState.Open)

{

//HttpUtility.HtmlEncode(

foreach (var MyString in CompleteAnswer.Split("\r\n"))

{

webSocketContext.WebSocket.SendAsync(Encoding.UTF8.GetBytes(MyString), WebSocketMessageType.Text, true, CancellationToken.None);

}

Matches = Regex.Match(CompleteAnswer, @"myArray = \[.*?\];");

if (Matches.Success)

{

Debug.WriteLine(Matches.Value);

}

CompleteAnswer = null;

Debug.WriteLine("ProcessAIRequest Finished");

}

async void StartWebSocketServer()

{

HttpListener httpListener = new HttpListener();

httpListener.Prefixes.Add("http://localhost:5000/ws/");

httpListener.Start();

Console.WriteLine("WebSocket server started at ws://localhost:5000/ws/");

while (true)

{

HttpListenerContext httpContext = await httpListener.GetContextAsync();

if (httpContext.Request.IsWebSocketRequest)

{

webSocketContext = await httpContext.AcceptWebSocketAsync(subProtocol: null);

Console.WriteLine("WebSocket connection established.");

await ProcessWebSocketMessages(webSocketContext.WebSocket);

}

else

{

httpContext.Response.StatusCode = 400;

httpContext.Response.Close();

Console.WriteLine("Non-WebSocket request received and rejected.");

}

async Task ProcessWebSocketMessages(WebSocket webSocket)

{

var buffer = new byte[1024 * 4];

while (webSocket.State == WebSocketState.Open)

{

WebSocketReceiveResult result = await webSocket.ReceiveAsync(new ArraySegment<byte>(buffer), CancellationToken.None);

if (result.MessageType == WebSocketMessageType.Close)

{

await webSocket.CloseAsync(WebSocketCloseStatus.NormalClosure, "Closing", CancellationToken.None);

Console.WriteLine("WebSocket connection closed.");

}

else

{

string message = Encoding.UTF8.GetString(buffer, 0, result.Count);

Console.WriteLine($"{message}");

ProcessAIRequest(message);

}

if (true)

{

}

else

{

chatHistory.AddMessage(AuthorRole.System, "Transcript of a dialog, where the User interacts with an Assistant named Bob. Bob is Lawyer and is helpful, kind, honest, good at writing, and never fails to answer the User's requests immediately and with precision. Bob will only answer from information provided by Users input and will answer questions as short and precise as possible. After each answer I will cite the exact text that I pulled the inforamtion from word for word.");

var Input = File.ReadAllText("D:\\Output-WC 25896.txt");

Console.WriteLine("Console writeline length: " + Input.Length);

chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000

chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");

//chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000

//chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");

}

static void FocusProcess()

{

IntPtr hWnd; //change this to IntPtr

Process[] processRunning = Process.GetProcesses();

foreach (Process pr in processRunning)

{

if (pr.ProcessName == "notepad")

{

hWnd = pr.MainWindowHandle; //use it as IntPtr not int

ShowWindow(hWnd, 3);

SetForegroundWindow(hWnd); //set to topmost

}

StartWebSocketServer();

FocusProcess();

Console.ForegroundColor = ConsoleColor.Yellow;

Console.Write("The chat session has started.\nUser: ");

Console.ForegroundColor = ConsoleColor.White;

void MeasureChatHistoryTokens()

{

foreach (ChatHistory.Message Value in LLMChatSession.History.Messages.ToArray())

{

TokensInMemory += model.Tokenize(Value.Content, true, false, Encoding.ASCII).Length;

}

Debug.WriteLine("Starting with tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

string userInput = "";

while (userInput != "exit")

{

userInput = Console.ReadLine() ?? "";

ProcessAIRequest(userInput);

}

async Task RunLLava()

{

string MultiModel = @"D:\llava-v1.6-mistral-7b.Q4_K_M.gguf";

//string multiModalProj = @"D:\mmproj-mistral7b-f16-q6_k.gguf";

string multiModalProj = @"D:\mmproj-mistral7b-f16.gguf";

string modelImage = @"D:\Ticket4.jpeg";

const int maxTokens = 2048;

var prompt = $"{{{modelImage}}}\nUSER:\nProvide a full description of the image, its fields and the values in each field.\nASSISTANT:\n";

var parameters = new ModelParams(MultiModel);

using var model = LLamaWeights.LoadFromFile(parameters);

using var context = model.CreateContext(parameters);

//https://platform.mindee.com/keld/traffic_ticket/live-interface#tab=%22extractedFields%22

//https://www.cnblogs.com/gmmy/p/18146496

//Multimodal model: llava-v1.6-mistral-7b.Q4_K_M.gguf Download address: https://huggingface.co/mradermacher/llava-v1.6-mistral-7b-GGUF/resolve/main/llava-v1.6-mistral-7b.Q4_K_M.gguf

//Llava CLIP model: mmproj-mistral7b-f16-q6_k.gguf Download address: https://huggingface.co/cmp-nct/llava-1.6-gguf/resolve/main/mmproj-mistral7b-f16-q6_k.gguf?download=true

// Llava Init

using var clipModel = LLavaWeights.LoadFromFile(multiModalProj);

var ex = new InteractiveExecutor(context, clipModel);

Console.ForegroundColor = ConsoleColor.Yellow;

Console.WriteLine("The executor has been enabled. In this example, the prompt is printed, the maximum tokens is set to {0} and the context size is {1}.", maxTokens, parameters.ContextSize);

Console.WriteLine("To send an image, enter its filename in curly braces, like this {c:/image.jpg}.");

var inferenceParams = new InferenceParams() { Temperature = 0.1f, AntiPrompts = new List<string> { "\nUSER:" }, MaxTokens = maxTokens };

{

// Evaluate if we have images

var imageMatches = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);

var imageCount = imageMatches.Count();

var hasImages = imageCount > 0;

if (hasImages)

{

var imagePathsWithCurlyBraces = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);

var imagePaths = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Groups[1].Value).ToList();

List<byte[]> imageBytes;

try

{

imageBytes = imagePaths.Select(File.ReadAllBytes).ToList();

}

catch (IOException exception)

{

Console.ForegroundColor = ConsoleColor.Red;

Console.Write($"Could not load your {(imageCount == 1 ? "image" : "images")}:");

Console.Write($"{exception.Message}");

Console.ForegroundColor = ConsoleColor.Yellow;

Console.WriteLine("Please try again.");

break;

}

// Each prompt with images we clear cache

// When the prompt contains images we clear KV_CACHE to restart conversation

// See:

// https://github.com/ggerganov/llama.cpp/discussions/3620

ex.Context.NativeHandle.KvCacheRemove(LLamaSeqId.Zero, -1, -1);

int index = 0;

foreach (var path in imagePathsWithCurlyBraces)

{

// First image replace to tag <image, the rest of the images delete the tag

prompt = prompt.Replace(path, index++ == 0 ? "<image>" : "");

}

Console.ForegroundColor = ConsoleColor.Yellow;

Console.WriteLine($"Here are the images, that are sent to the chat model in addition to your message.");

Console.WriteLine();

foreach (var consoleImage in imageBytes?.Select(bytes => new CanvasImage(bytes)))

{

consoleImage.MaxWidth = 50;

Spectre.Console.AnsiConsole.Write(consoleImage);

}

Console.WriteLine();

Console.ForegroundColor = ConsoleColor.Yellow;

Console.WriteLine($"The images were scaled down for the console only, the model gets full versions.");

Console.WriteLine($"Write /exit or press Ctrl+c to return to main menu.");

Console.WriteLine();

// Initialize Images in executor

foreach (var image in imagePaths)

{

ex.Images.Add(await File.ReadAllBytesAsync(image));

}

Console.ForegroundColor = ConsoleColor.White;

await foreach (var text in ex.InferAsync(prompt, inferenceParams))

{

Console.Write(text);

}

Console.Write(" ");

Console.ForegroundColor = ConsoleColor.Green;

prompt = Console.ReadLine();

Console.WriteLine();

// let the user finish with exit

if (prompt != null && prompt.Equals("/exit", StringComparison.OrdinalIgnoreCase))

break;

}

while (true);

}

//Unable to use to do "Top level statements must procede namespace and type declerations.

[Flags]

enum MyLoadedMethod : ushort

{

Plain = 0,

RAG = 1

}

Getting IIS Express to listen on a network LAN IP with visual studio.

Normally my post arnt so short but this burned 45 minutes of my time as I struggled to get a native IIS express deployment from VS2022 to use a lan port for debugging remote connections.

Navigate to \RootProjectDirectory\.vs\{ProjectName}\config\applicationhost.config

Run Visual Studio as Administrator, this is critical.
Delete the file after backing it up, then while in Visual studio click Create Virtual Directory using a different port on HTTP then the one you wish to open on lan
Start the project, then Stop debugging. Once Stopped, confirm IIS is no longer running on the taskbar.

Open the newly generated applicationhost.config file within the config directory and add the new binding, mine existed on line 168.

An example of the config will look like this

<sites>
<site name=”WebSite1″ id=”1″ serverAutoStart=”true”>
<application path=”/”>
<virtualDirectory path=”/” physicalPath=”%IIS_SITES_HOME%\WebSite1″ />
</application>
<bindings>
<binding protocol=”http” bindingInformation=”:8080:localhost” />
</bindings>
</site>
<site name=”ProjectName” id=”2″>
<application path=”/” applicationPool=”Clr4IntegratedAppPool”>
<virtualDirectory path=”/” physicalPath=”C:\Users\User\source\repos\ProjectName\ProjectName” />
</application>
<bindings>
<binding protocol=”http” bindingInformation=”*:44391:localhost” />
<binding protocol=”http” bindingInformation=”*:44392:192.168.0.199″ />
</bindings>
</site>
<siteDefaults>
<!– To enable logging, please change the below attribute “enabled” to “true” –>
<logFile logFormat=”W3C” directory=”%AppData%\Microsoft\IISExpressLogs” enabled=”false” />
<traceFailedRequestsLogging directory=”%AppData%\Microsoft” enabled=”false” maxLogFileSizeKB=”1024″ />
</siteDefaults>
<applicationDefaults applicationPool=”Clr4IntegratedAppPool” />
<virtualDirectoryDefaults allowSubDirConfig=”true” />
</sites>

Save, then click Start debug within VS. You may now HTTP from your other machine using the newly added port.

Using LLamaSharp with RAG.

So, The data appears to take 6x-7x the amount of space to archive into the SQLlite memory storage.

Clearing history with a Chatsession does not appear to work correctly so I swapped over to a stateless built which helped so long that the RAG only needs to be called once per question. If additional questions need to be asked on the same data then optimization can be added to speed things up.

I will node that the prompt I’m using to search on provided much better results then the format documented on hugging face oddly enough. “Assistant:” {Query} “User:” instead of “instruct”, “query”.

I also used a function to pull filler words to speed up and create a more reliable keyword function, but the LLM itself wasn’t too bad.

Ultimately, Ill have to stick with the statelessexecutor until I can validate that the ChatSession operates correctly. Once I call LLMSession.load(CleanSession), readding in the prompts appears to not work correctly. During debugging, upon the second add, the count of the ChatSession remained zero.

// See https://aka.ms/new-console-template for more information

//leaderboards
//https://huggingface.co/spaces/mteb/leaderboard

//Implement with Python
//https://www.llamaindex.ai/
//https://docs.llamaindex.ai/en/stable/getting_started/discover_llamaindex/

//Install-Package LLamaSharp
//Install-Package LLamaSharp.Backend.Cuda11
//https://dotnet.microsoft.com/en-us/download/dotnet/8.0
//https://dotnet.microsoft.com/en-us/download/dotnet

//The top line returns waaayy better results then the bottom
//Assistant: discovery\r\nUser:
//discovery

using LLama.Common;
using LLama;
#pragma warning disable SKEXP0050, SKEXP0001, SKEXP0020
//RAG
//Install-Package LLamaSharp.Semantic-Kernel
//https://github.com/SciSharp/LLamaSharp/issues/648
using LLamaSharp.SemanticKernel.TextEmbedding;
//Install-Package Microsoft.SemanticKernel
using Microsoft.SemanticKernel.Connectors;
using Microsoft.SemanticKernel.Memory;
using Microsoft.SemanticKernel.Text;
//Install-Package Microsoft.SemanticKernel.Connectors.Sqlite -Version 1.18.0-alpha
using Microsoft.SemanticKernel.Connectors.Sqlite;
//
using System.IO;
using System.Text.RegularExpressions;
using System.Diagnostics;
using System.Net.WebSockets;
using System.Text;
using System.Net;
using System.Management;
using SQLitePCL;
using System;
using System.Collections;
using System.Windows.Documents;
using System.Runtime.InteropServices;
using static System.Net.Mime.MediaTypeNames;
using System.CodeDom.Compiler;
using System.Reflection;
using Microsoft.Data.Sqlite;
using static System.Collections.Specialized.BitVector32;

[DllImport("user32.dll")]
static extern IntPtr SetForegroundWindow(IntPtr hWnd);

[DllImport("user32.dll")]
static extern bool ShowWindow(IntPtr hWnd, int nCmdShow); //ShowWindow needs an IntPtr


Console.ForegroundColor = ConsoleColor.White;

HttpListenerWebSocketContext webSocketContext = null;

string RagModelPath = @"D:\bge-large-en-v1.5-q8_0.gguf";
string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q6_K.gguf";
//string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q8_0.gguf"; // change it to your own model path.
//string modelPath = @"D:\Meta-Llama-3.1-70B-Instruct-Q6_K-00001-of-00002.gguf"; // Way too large for my computer
//var embeddingModelPath = Path.GetFullPath("<path to embed model>/nomic-embed.gguf");
string LocalMemoryPath = @"C:\Users\User\Desktop\MyMemory.db";
string PathToFilesToIngest = "D:\\Embeddings";

ManagementObjectSearcher searcher = new ManagementObjectSearcher("SELECT * FROM Win32_Processor");
List<int> coresCPUs = new List<int>();
foreach (ManagementObject mo in searcher.Get())
{
    coresCPUs.Add(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));
    Debug.WriteLine(Convert.ToInt32(mo.Properties["NumberOfCores"].Value));
}

//RAG variables
ModelParams RAGparameters = null;
ISemanticTextMemory MyMemoryStore = null;
//All operations
LLamaWeights model = null;
LLamaContext context = null;
InteractiveExecutor executor = null;

var MyStartupMethod = MyLoadedMethod.RAG;
string collectionName = "TestCollection";

// Add chat histories as prompt to tell AI how to act.
var chatHistory = new ChatHistory();
var chatHistory2 = new ChatHistory();
string Str = null;

switch ("rag")
{
    case "train":
        chatHistory.AddMessage(AuthorRole.System, "Generate new examples based on user input examples, once asked to write additional samples, take the previous request and continue to generate addtional samples. All answers need to strictly be formed into a statement and then answered as a JSON array of strings, always add a semicolon after each string array to close the statement properly. All commands should be for use by the windows operating system. Do not explain, add notes or say anything else unless specifically asked to for any reason.");
        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate to program files in windows, find a folder with the word steam in it then create a subfolder inside with two text files and populate a random string in each text file. Write the commands using a json array of strings to be processed by an interrupter."); //10000
        Str = "myArray = [\"CD \\\\\", \"CD C:\\\\Program Files\\\\\", \"DIR /OD \\\"*steam*\\\"\", \"MKDIR \\\"SteamFolder\\\"\", \"MD \\\"SteamFolder\\\\subfolder\\\", \\\"ECHO New content 1 > \\\"SteamFolder\\\\subfolder\\\\file1.txt\", \"COPY \\\"asdawdafag\\\" > \\\"SteamFolder\\\\subfolder\\\\file2.txt\\\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000
        Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "Great, now continue to write addtional samples, remember to keep the format as a statement, then followed by a JSON answer with a semicolon at the end of each JSON answer. I will ask for over 100 samples."); //10000

        chatHistory.AddMessage(AuthorRole.Assistant, "Ping google.com and write the the results to a text file then open the program files folder using explorer. myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];"); //10000
        chatHistory.AddMessage(AuthorRole.User, "y"); //10000
        chatHistory.AddMessage(AuthorRole.Assistant, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside. myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];"); //10000
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Use Moveit.exe to move a file named NTFS.mbr localy, then zip the moved file and display its size. myArray = [\"Moveit \\\"NTFS.mbr\\\" C:\", \"7z a ntfs.zip ntfs.mbr\", \"7z l ntfs.zip\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to direct a LAN IP to a temp directory, download a single file using curl and extract the extracted content into a subfolder named debug. myArray = [\"MKDIR C:\\\\tmp\\\", \"curl \\\"http://192.168.1.100/somefile.zip\\\" -o C:\\\\tmp\", \"7z e C:\\\\tmp\\\\somefile.zip -od C:\\\\tmp\\\\debug\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Create a random 32 character hexadecimal color code, then use the color picker tool in Windows to open up a default browser using this new color as its background. myArray = [\"wmic os get version > C:\\versions.txt\", \"color cc233330cc2233c2\", \"explorer https://www.google.com\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a list of commands to create an Ecrypted zip archive and store it in the users desktop directory, than extract this zip file with AES encryption using 7z. myArray = [\"cipher /E /S:C:\\\\Users\\\\username\\\\Documents\" > C:\\UserEnv, \"cipher /D /S:C:\\\\Users\\\\username\\\\Documents\", \"CIPHER /P\"aVeryStrongPassword123\\* \\\"C:\\\\Users\\\\username\\\\Desktop\\\\enc.zip\\\"\", \"7z e -hp\"aVeryStrongPassword123 \\*.zip\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Display user accounts with administrative privileges, and list the user object properties in Windows registry. myArray = [\"wmic useraccount where Enabled=TRUE and Administrator=TRUE get *\", \"reg query HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\\\Winlogon /v DefaultUserName\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Change password for a service called misconfigure-MDViewer, change priority of CpuGroup1; write a list of commands to accomplish these tasks. myArray = [\"net user \\\"misconfigure-MDViewer\\\" changesPassword!!\"], \"wmic cpu Get Name\", \"wmic process where ProcessID=1234 set Priority=5\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Use the Windows Task Scheduler to create a scheduled task to download a simple text file from a remote server every 10 minutes. myArray = [\"schtasks /create /tn \"MyTask\" /tr \"curl http://192.168.1.100/textfile.txt -o C:\\tmp\\mytext.txt\\\"\", \"schtasks /change /tn \"MyTask\\\" /st 00:00 /ri 10\"];");
        chatHistory.AddMessage(AuthorRole.User, "y");
        chatHistory.AddMessage(AuthorRole.Assistant, "Write a batch file that opens up Internet Explorer with two tabs one with the url google.com and another with bing.com. myArray = [\"start iexplore.exe \\\"http://www.google.com\\\", start iexplore.exe \\\"http://www.bing.com\\\"\"];");
        break;
    case "production":
        chatHistory.AddMessage(AuthorRole.System, "Transcribe request from the user into an array of JSON strings labeled 'myArray' to be processed by an interpreter that will parse an array of strings and execute them on a system. All answers need to strictly be formed into a JSON array of strings for the windows operating system. Only give the results in JSON format and do not explain or say anything else unless asked specifically.");
        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate to program files in windows, find a folder with the word steam in it then create a subfolder inside with two text files and populate a random string in each text file. Write the commands using a json array of strings to be processed by an interrupter."); //10000
        Str = "myArray = [\"CD \\\\\", \"CD C:\\\\Program Files\\\\\", \"DIR /OD \\\"*steam*\\\"\", \"MKDIR \\\"SteamFolder\\\"\", \"MD \\\"SteamFolder\\\\subfolder\\\", \\\"ECHO New content 1 > \\\"SteamFolder\\\\subfolder\\\\file1.txt\", \"COPY \\\"asdawdafag\\\" > \\\"SteamFolder\\\\subfolder\\\\file2.txt\\\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that will navigate list the files and folders in the C: drive, the shutdown the computer in 60 seconds."); //10000
        Str = "myArray = [\"DIR C:\\\", \"shutdown -s -t 60\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "Ping google.com and write the the results to a text file then open the program files folder using explorer."); //10000
        Str = "myArray = [\"ping google > c:\\Output.txt\", \"Explorer \"%programfiles%\"\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);

        chatHistory.AddMessage(AuthorRole.User, "write a list of commands that searches for files in the D: Drive that start with the name \"test\" and then copy those files to the c: drive if they contain a word \"echo\" inside."); //10000
        Str = "myArray = [\"DIR /S /B /A:-D D:\\test*.txt\", \"COPY \\\"D:\\\\test*.txt\\\" C:\\\" /Y\", \"FINDSTR /C:\"\"echo\"\" D:\\\\test*.txt > E:\\\\log.txt\"];";
        chatHistory.AddMessage(AuthorRole.Assistant, Str);
        break;
    case "rag":
        //chatHistory.AddMessage(AuthorRole.System, "You are a legal assistance. You will be provided context to some data and will answer any questions you receive the best you can with the context provided and do not include information outside of the information provided.");
        break;
    default:
        Console.WriteLine("Number is not between 1 and 4");
        break;
}
//LLM variables
var LLMparameters = new ModelParams(modelPath)
{
    ContextSize = 13107, // Does not require alot of memory
                         //ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl
                         //If commented out, swaps to CPU
                         //GpuLayerCount = 0
    GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.
};
LLamaWeights LLMmodel = null;

LLamaContext LLMcontext = null;
LLamaContext.State CleanContext = null;

InteractiveExecutor LLMexecutor = null;
StatelessExecutor LLMStatelessExecutor = null; //Not currently in use. Results were bad.
StatefulExecutorBase.ExecutorBaseState CleanExectuor = null;

ChatSession LLMChatSession = null;
SessionState CleanChatSession = null;

InferenceParams inferenceParams = new InferenceParams()
{
    Temperature = 0.4f,
    MaxTokens = 512, // No more than 256 tokens should appear in answer. Remove it if antiprompt is enough for control.
    AntiPrompts = new List<string> { "\nUser:" } // Stop generation once antiprompts appear.
};

async Task LoadModule()
{
    if (MyStartupMethod == MyLoadedMethod.RAG) //RAG //Checks for enum need to be wrapped in a function to be valid.
    {
        RAGparameters = new ModelParams(RagModelPath)
        {
            ContextSize = 32000, // Does not require alot of memory
                                 //ContextSize = 131072, // The longest length of chat as memory. This can bring the computer to a crawl
            Embeddings = true,
            //GpuLayerCount = 0 //If commented out, swaps to CPU
            GpuLayerCount = 33 // How many layers to offload to GPU. Please adjust it according to your GPU memory.
        };

        model = LLamaWeights.LoadFromFile(RAGparameters);
        context = model.CreateContext(RAGparameters);
        executor = new InteractiveExecutor(context);

        var embedder = new LLamaEmbedder(model, RAGparameters);
        var service = new LLamaSharpEmbeddingGeneration(embedder);

        MyMemoryStore = new MemoryBuilder().WithMemoryStore(await SqliteMemoryStore.ConnectAsync(LocalMemoryPath)).WithTextEmbeddingGeneration(service).Build();

        await IngestFile();

        LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);

        LLMStatelessExecutor = new StatelessExecutor(LLMmodel, LLMparameters);

        LLMcontext = LLMmodel.CreateContext(LLMparameters);
        LLMexecutor = new InteractiveExecutor(LLMcontext);
        LLMChatSession = new(LLMexecutor, chatHistory);
    }
    else
    {
        LLMmodel = LLamaWeights.LoadFromFile(LLMparameters);
        LLMcontext = LLMmodel.CreateContext(LLMparameters);
        LLMexecutor = new InteractiveExecutor(LLMcontext);
        LLMChatSession = new(LLMexecutor, chatHistory);
    }

    CleanExectuor = LLMexecutor.GetStateData();
    CleanChatSession = LLMChatSession.GetSessionState();
    CleanContext = LLMcontext.GetState();
    //_memoryStore
    //var field = MyMemoryStore.GetType().GetField("_storage", BindingFlags.NonPublic | BindingFlags.Instance);
    //var memoryStore = (Dictionary<string, string>)field.GetValue(MyMemoryStore);
    //var keys = memoryStore.Keys.ToList();

    using (var connection = new SqliteConnection("Data Source=" + LocalMemoryPath))
    {
        connection.Open();

        var command = connection.CreateCommand();

        command.CommandText = @"SELECT COUNT(1) from SKMemoryTable";

        Debug.WriteLine(command.ExecuteScalar());

        //collection, key, metadata, embedding, timestamp
        //metadata holds a json string of "is_reference", "external_source_name", "id" and "description", "text", "additional_metadata"
        command.CommandText = @"SELECT DISTINCT key FROM SKMemoryTable"; // Replace 'MemoryTable' with the actual table name

        using (var reader = command.ExecuteReader())
        {
            while (reader.Read())
            {
                //Console.WriteLine(reader.GetString(0));
            }
        }
    }

    //System.Diagnostics.Debugger.Break();
    //LLMsession.SaveSession();
}

await LoadModule();

string CompleteAnswer = null;
Match Matches;

long TokensInMemory = 0;

async Task IngestFile()
{
    long TotalParagraphsLoaded = 0;
    Console.WriteLine("===== INGESTING =====");

    IList<string> collections = await MyMemoryStore.GetCollectionsAsync();

    string folderPath = Path.GetFullPath(PathToFilesToIngest);
    string[] files = Directory.GetFiles(folderPath);

    if (collections.Contains(collectionName))
    {
        Console.WriteLine("Found database");
    }
    else
    {

        List<Task> tasks = new List<Task>();
        foreach (var item in files.Select((path, index) => new { path, index }))
        {
            Console.WriteLine($"Ingesting file #{item.index}");
            string text = File.ReadAllText(item.path);

            if (false)
            {
                var sentences = TextChunker.SplitPlainTextLines(text, 256);
                var paragraphs = TextChunker.SplitPlainTextParagraphs(sentences, 1024);

                foreach (var para in paragraphs.Select((text, index) => new { text, index }))
                    await MyMemoryStore.SaveInformationAsync(collectionName, para.text, $"Document {item.path}, Paragraph {para.index}");
            }
            else if (true)
            {
                string[] splitQuestions = Regex.Split(text, @"(?=Question\s\d+\.)");
                long ParaIndex = 1;
                foreach (string question in splitQuestions)
                {
                    if (!string.IsNullOrWhiteSpace(question))
                    {
                        try
                        {
                            //description is stored in the metadata column, same with additional_metadata. Remember, converting to weights takes about 6-7x times the space in total.
                            await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), ($"Document {item.path}, Paragraph {ParaIndex++}"));
                        }
                        catch
                        {

                        }

                        //tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));
                        TotalParagraphsLoaded++;
                    }
                }
            }
            else if (false)
            {
                string[] splitQuestions = Regex.Split(text, @"(?<=[.!?])\s+|(?<=\.\.)\s*|\r\n|\n"); //each sentence
                long ParaIndex = 1;

                foreach (string question in splitQuestions)
                {
                    if (!string.IsNullOrWhiteSpace(question))
                    {
                        //await memory.SaveReferenceAsync()
                        await MyMemoryStore.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}");
                        //tasks.Add(Task.Run(() => memory.SaveInformationAsync(collectionName, question.Trim(), $"Document {item.path}, Paragraph {ParaIndex++}")));
                        TotalParagraphsLoaded++;
                    }
                }
            }
            //await Task.WhenAll(tasks);
        }

        Console.WriteLine("Generated database with " + TotalParagraphsLoaded + " items.");
    }
    Console.WriteLine("===== DONE INGESTING =====");
}

void ClearContext()
{
    return;
    LLMChatSession.LoadSession(CleanChatSession);
    Debug.WriteLine(LLMChatSession.HistoryTransform.HistoryToText(LLMChatSession.History));
    return;
    LLMcontext.Dispose();
    LLMexecutor = null;
    LLMChatSession = null;
    LLMcontext = LLMmodel.CreateContext(LLMparameters);
    LLMexecutor = new InteractiveExecutor(LLMcontext);
    LLMChatSession = new(LLMexecutor, chatHistory);
    return;
    chatHistory.Messages.Clear();
    LLMcontext.LoadState(CleanContext);
    LLMChatSession.LoadSession(CleanChatSession);
    LLMexecutor.LoadState(CleanExectuor);
    return;
    while (LLMChatSession.History.Messages.Count > 0)
    {
        LLMChatSession.RemoveLastMessage();
    }
    return;
}

string Keywords(string sentence)
{
    HashSet<string> StopWords = new HashSet<string>(new[]
    {
        "a", "an", "and", "the", "is", "in", "on", "at", "of", "for", "to", "with", "by", "from", "that", "this", "it",
        "as", "are", "was", "were", "be", "been", "has", "have", "had", "but", "or", "not", "so", "if", "then", "i",
        "me", "my", "myself", "we", "our", "ours", "ourselves", "you", "your", "yours", "yourself", "yourselves",
        "he", "him", "his", "himself", "she", "her", "hers", "herself", "its", "itself", "they", "them", "their",
        "theirs", "themselves", "what", "which", "who", "whom", "these", "those", "am", "being", "do", "does",
        "did", "doing", "because", "until", "while", "about", "against", "between", "into", "through", "during",
        "before", "after", "above", "below", "up", "down", "out", "off", "over", "under", "again", "further",
        "once", "here", "there", "when", "where", "why", "how", "all", "any", "both", "each", "few", "more",
        "most", "other", "some", "such", "no", "nor", "only", "own", "same", "than", "too", "very", "s", "t",
        "can", "will", "just", "don", "should", "now"
    });

    string cleanSentence = Regex.Replace(sentence.ToLower(), @"[^\w\s]", "");

    // Split sentence into words
    var words = cleanSentence.Split(new[] { ' ', '\t', '\n', '\r' }, StringSplitOptions.RemoveEmptyEntries);

    // Filter out stop words and return remaining words as keywords
    var keywords = words.Where(word => !StopWords.Contains(word)).ToList();

    // Join the keywords into a single string separated by spaces
    return string.Join(" ", keywords);
}

async void ProcessAIRequest(string userInput)
{
    Debug.WriteLine("ProcessAIRequest starting");
    TokensInMemory += model.Tokenize(userInput, true, false, Encoding.ASCII).Length;

    //executor.rag

    //RAG and context building: https://medium.com/@bruno.facco/rag-from-concept-to-application-using-gpt-llama-index-and-sql-retriever-cfb437da99eb
    //session.
    String ChatResponseToMeasure = null;
    if (MyStartupMethod == MyLoadedMethod.RAG)
    {
        StringBuilder ColoredStringBuilder = new();
        ColoredStringBuilder.Clear();

        List<string> sources = [];

        var resultsfound = false;
        double minRelevanceScoreValue = 0.8;

        Console.WriteLine("=== Extracting Keywords ===");

        /*
            string prompt = "System: Ensure that the results contain ALL of the words from the following user query. The words must appear at least once anywhere in the result, without exception.\r\n The results are in the following format, The question number, the question, possible answers then followed by the explanation. The user will give keywords and return the results if those keywords appear in any of the result, either in the question or the explanation.\r\n" +
            "Assistant: I will only return results that include every single keyword provided by the user. If even one keyword is missing, the result will not be returned, without exception.\r\n" +
            "User: " + userInput;
        */
        string prompt = userInput;

        string keywords = "";

        string StrchatHistory = "\r\nUser: What is Congresses Commerce Clause powers?\r\n" +
            "Assistant: Congress Commerce Clause\r\n" +
            "User: What time is it in new york?\r\n" +
            "Assistant: time new york\r\n" +
            "User: How do you fill up a car tire?\r\n" +
            "Assistant: fill up car tire\r\n" +
            "User: How fast can a car go on a freeway?\r\n" +
            "Assistant: fast car freeway\r\n" +
            "User: How do you make pancakes in an oven?\r\n" +
            "Assistant: make pancakes oven\r\n" +
            "User: How do you write a business plan?\r\n" +
            "Assistant: write business plan\r\n" +
            "User: What is the capital of Japan?\r\n" +
            "Assistant: capital Japan\r\n" +
            "User: How to set up a new email account?\r\n" +
            "Assistant: set up email account\r\n" +
            "User: What are the benefits of meditation?\r\n" +
            "Assistant: benefits meditation\r\n" +
            "User: How to make a website responsive?\r\n" +
            "Assistant: make website responsive\r\n" +
            "User: What is the difference between Python and Java?\r\n" +
            "Assistant: difference Python Java\r\n" +
            "User: How do I replace a car battery?\r\n" +
            "Assistant: replace car battery\r\n" +
            "User: What is the tallest mountain in the world?\r\n" +
            "Assistant: tallest mountain world\r\n" +
            "User: How can I improve my public speaking skills?\r\n" +
            "Assistant: improve public speaking skills\r\n" +
            "User: What is the population of Canada?\r\n" +
            "Assistant: population Canada\r\n" +
            "User: How to brew coffee using a French press?\r\n" +
            "Assistant: brew coffee French press\r\n" +
            "User: How does a blockchain work?\r\n" +
            "Assistant: blockchain work\r\n" +
            "User: What are the side effects of aspirin?\r\n" +
            "Assistant: side effects aspirin\r\n" +
            "User: How to start learning data science?\r\n" +
            "Assistant: start learning data science\r\n" +
            "User: What is the speed of light?\r\n" +
            "Assistant: speed of light\r\n" +
            "User: How do I bake a chocolate cake?\r\n" +
            "Assistant: bake chocolate cake\r\n" +
            "User: What are the causes of climate change?\r\n" +
            "Assistant: causes climate change\r\n" +
            "User: How to play the guitar for beginners?\r\n" +
            "Assistant: play guitar beginners\r\n" +
            "User: What are the symptoms of a common cold?\r\n" +
            "Assistant: symptoms common cold\r\n" +
            "User: How to create a budget plan?\r\n" +
            "Assistant: create budget plan\r\n";
        if (false)
        {
            if (true)
            {
                await foreach (var text in LLMStatelessExecutor.InferAsync("System: Return only the keywords from the following statement and do not provide anything else. Use spaces when outputing the keywords values and do not add anything futher." + StrchatHistory + "User: '" + userInput + "'", inferenceParams)) // Generate the response streamingly.
                {
                    Console.ForegroundColor = ConsoleColor.White;
                    Console.Write(text);

                    keywords += text;
                }
            }
            else
            {
                //chatHistory.Messages.Clear();
                chatHistory.AddMessage(AuthorRole.System, "I am a search engine assistant. I will only return back keywords from any statement you make and nothing else with no exceptions.\r\n");
                chatHistory.AddMessage(AuthorRole.User, "What is Congresses Commerce Clause powers?");
                chatHistory.AddMessage(AuthorRole.Assistant, "Congress Commerce Clause");
                chatHistory.AddMessage(AuthorRole.User, "What time is it in new york?");
                chatHistory.AddMessage(AuthorRole.Assistant, "time new york");
                chatHistory.AddMessage(AuthorRole.User, "How do you fill up a car tire?");
                chatHistory.AddMessage(AuthorRole.Assistant, "fill up car tire");
                chatHistory.AddMessage(AuthorRole.User, "How fast can a car go on a freeway?");
                chatHistory.AddMessage(AuthorRole.Assistant, "fast car freeway");
                chatHistory.AddMessage(AuthorRole.User, "How do you make pancakes in an oven?");
                chatHistory.AddMessage(AuthorRole.Assistant, "make pancakes oven");
                chatHistory.AddMessage(AuthorRole.User, "How do you write a business plan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "write business plan");
                chatHistory.AddMessage(AuthorRole.User, "What is the capital of Japan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "capital Japan");
                chatHistory.AddMessage(AuthorRole.User, "How to set up a new email account?");
                chatHistory.AddMessage(AuthorRole.Assistant, "set up email account");
                chatHistory.AddMessage(AuthorRole.User, "What are the benefits of meditation?");
                chatHistory.AddMessage(AuthorRole.Assistant, "benefits meditation");
                chatHistory.AddMessage(AuthorRole.User, "How to make a website responsive?");
                chatHistory.AddMessage(AuthorRole.Assistant, "make website responsive");
                chatHistory.AddMessage(AuthorRole.User, "What is the difference between Python and Java?");
                chatHistory.AddMessage(AuthorRole.Assistant, "difference Python Java");
                chatHistory.AddMessage(AuthorRole.User, "How do I replace a car battery?");
                chatHistory.AddMessage(AuthorRole.Assistant, "replace car battery");
                chatHistory.AddMessage(AuthorRole.User, "What is the tallest mountain in the world?");
                chatHistory.AddMessage(AuthorRole.Assistant, "tallest mountain world");
                chatHistory.AddMessage(AuthorRole.User, "How can I improve my public speaking skills?");
                chatHistory.AddMessage(AuthorRole.Assistant, "improve public speaking skills");
                chatHistory.AddMessage(AuthorRole.User, "What is the population of Canada?");
                chatHistory.AddMessage(AuthorRole.Assistant, "population Canada");
                chatHistory.AddMessage(AuthorRole.User, "How to brew coffee using a French press?");
                chatHistory.AddMessage(AuthorRole.Assistant, "brew coffee French press");
                chatHistory.AddMessage(AuthorRole.User, "How does a blockchain work?");
                chatHistory.AddMessage(AuthorRole.Assistant, "blockchain work");
                chatHistory.AddMessage(AuthorRole.User, "What are the side effects of aspirin?");
                chatHistory.AddMessage(AuthorRole.Assistant, "side effects aspirin");
                chatHistory.AddMessage(AuthorRole.User, "How to start learning data science?");
                chatHistory.AddMessage(AuthorRole.Assistant, "start learning data science");
                chatHistory.AddMessage(AuthorRole.User, "What is the speed of light?");
                chatHistory.AddMessage(AuthorRole.Assistant, "speed of light");
                chatHistory.AddMessage(AuthorRole.User, "How do I bake a chocolate cake?");
                chatHistory.AddMessage(AuthorRole.Assistant, "bake chocolate cake");
                chatHistory.AddMessage(AuthorRole.User, "What are the causes of climate change?");
                chatHistory.AddMessage(AuthorRole.Assistant, "causes climate change");
                chatHistory.AddMessage(AuthorRole.User, "How to play the guitar for beginners?");
                chatHistory.AddMessage(AuthorRole.Assistant, "play guitar beginners");
                chatHistory.AddMessage(AuthorRole.User, "What are the symptoms of a common cold?");
                chatHistory.AddMessage(AuthorRole.Assistant, "symptoms common cold");
                chatHistory.AddMessage(AuthorRole.User, "How to create a budget plan?");
                chatHistory.AddMessage(AuthorRole.Assistant, "create budget plan");

                await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
                {
                    Console.ForegroundColor = ConsoleColor.White;
                    Console.Write(text);

                    keywords += text;
                }
            }
        }

        keywords = Keywords(userInput);
        Console.WriteLine(keywords);

        while (!resultsfound)
        {
            Console.WriteLine("=== RETRIEVING [" + minRelevanceScoreValue + "]===");
            //"Instruct:Given the query, find all relevant text.\r\nQuery: " + keywords + "\r\n"
            //"Assistant: " + keywords + "\r\nUser:"
            //await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Query: " + keywords + "\r\n", limit: 10, minRelevanceScore: minRelevanceScoreValue))
            await foreach (var result in MyMemoryStore.SearchAsync(collectionName, "Assistant: " + keywords + "\r\nUser:", limit: 10, minRelevanceScore: minRelevanceScoreValue))
            {
                resultsfound = true;
                //builder.AppendLine(result.Metadata.Text + "\r\n\r\n" + result.Relevance + "\r\n\r\n");
                //CompleteAnswer += result.Metadata.Text;
                string highlightedText = result.Metadata.Text;
                foreach (var word in keywords.Split(' ', StringSplitOptions.RemoveEmptyEntries))
                {
                    highlightedText = Regex.Replace(highlightedText, " " + word, match => $"\x1b[31m{match.Value}\x1b[0m", RegexOptions.IgnoreCase);
                }

                CompleteAnswer += result.Metadata.Text + "\r\n";
                ColoredStringBuilder.AppendLine(highlightedText + "\r\n\r\n" + result.Relevance + "\r\n\r\n");

                sources.Add(result.Metadata.Id);
            }
            minRelevanceScoreValue -= .05d;
            if (minRelevanceScoreValue < .2d)
            {
                Console.WriteLine("Unable to find any subject using your keywords");
                return;
            }
        }

        ColoredStringBuilder.AppendLine("""

        Sources:
        """);

        CompleteAnswer += ("\r\n\r\nSources:\r\n");


        foreach (string source in sources)
        {
            ColoredStringBuilder.AppendLine($"    {source}");
            CompleteAnswer += $"    {source}\r\n";
        }
        CompleteAnswer += "\r\n";
        Console.WriteLine("=== DONE RETRIEVING ===");

        Console.WriteLine(ColoredStringBuilder.ToString());
        CompleteAnswer += "\r\n";
        //CompleteAnswer = builder.ToString();

        ClearContext();

        if (true)
        {
            //string InferPrompt = "System: I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\nUser: " + userInput;
            //<|begin_of_text|>
            string InferPrompt = "<|start_header_id|>system<|end_header_id|>\r\n" +
                                    "Cutting Knowledge Date: December 2023\r\n" +
                                    "Today Date: 26 Jul 2024\r\n\r\n" +
                                    "I am a law professor at a law school. I will answer your legal questions with the help of using ONLY the following information within the context of the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any further information or ask anything in return after giving you the direct answer to your question.\r\n" +
                                    "<|eot_id|><|start_header_id|>user<|end_header_id|>\r\n\r\n" +
                                    userInput + "\r\n" +
                                    "<|eot_id|><|start_header_id|>assistant<|end_header_id|>\r\n\r\n" +
                                    "### Start of Documentation:\r\n" +
                                    CompleteAnswer.Replace("'", "`") +
                                    "\r\n### End of Documentation\r\n";
            await foreach (var text in LLMStatelessExecutor.InferAsync(InferPrompt, inferenceParams)) // Generate the response streamingly.
            {
                Console.ForegroundColor = ConsoleColor.White;
                Console.Write(text);

                CompleteAnswer += text;
                ChatResponseToMeasure += text;
            }
            
        }
        else
        {
            chatHistory.AddMessage(AuthorRole.System, "I am a law professor at a law school. I will answer your legal questions with the help of using the ONLY the following information within the context the provided documentation. I will only answer with facts grounded in the provided documentation and try to do so in three paragraphs or less. I will only answer your question and will not add any futher information or ask anything in return after giving you the direct answer to your question.\r\n\r\n### Start of Documentation:\r\n" + CompleteAnswer.Replace("'", "`") + "\r\n### End of Documentation\r\n\r\nIf I cannot answer I will say 'I am not sure'.\r\n");
            chatHistory.AddMessage(AuthorRole.Assistant, "I will answer all your legal questions in context of the law. I will answer your question and will not add anything else to the end of the answer. What legal question may I answer for you?");
            await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
            {
                Console.ForegroundColor = ConsoleColor.White;
                Console.Write(text);

                CompleteAnswer += text;
                ChatResponseToMeasure += text;
            }

        }

        ClearContext();
    }
    else
    {
        await foreach (var text in LLMChatSession.ChatAsync(new ChatHistory.Message(AuthorRole.User, userInput), inferenceParams)) // Generate the response streamingly.
        {
            Console.ForegroundColor = ConsoleColor.White;
            Console.Write(text);

            CompleteAnswer += text;
            ChatResponseToMeasure += text;
        }
    }

    long TokensInResponse = model.Tokenize(ChatResponseToMeasure, true, false, Encoding.ASCII).Length;
    Debug.WriteLine("Response Length: " + TokensInResponse);

    if (!ChatResponseToMeasure.EndsWith("User:") || TokensInResponse > inferenceParams.MaxTokens)
    {
        Console.Write("\r\nUser:");
    }

    if (CompleteAnswer != null)
    {
        TokensInMemory += model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length;

        Debug.WriteLine("User added " + model.Tokenize(userInput, true, false, Encoding.ASCII).Length + " Response added: " + model.Tokenize(CompleteAnswer, true, false, Encoding.ASCII).Length + " tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

        if (webSocketContext != null)
        {
            if (webSocketContext.WebSocket.State == WebSocketState.Open)
            {
                //HttpUtility.HtmlEncode(
                foreach (var MyString in CompleteAnswer.Split("\r\n"))
                {
                    webSocketContext.WebSocket.SendAsync(Encoding.UTF8.GetBytes(MyString), WebSocketMessageType.Text, true, CancellationToken.None);
                }
            }
        }

        Matches = Regex.Match(CompleteAnswer, @"myArray = \[.*?\];");
        if (Matches.Success)
        {
            Debug.WriteLine(Matches.Value);
        }
    }

    CompleteAnswer = null;
    Debug.WriteLine("ProcessAIRequest Finished");
}
async void StartWebSocketServer()
{
    HttpListener httpListener = new HttpListener();
    httpListener.Prefixes.Add("http://localhost:5000/ws/");
    httpListener.Start();
    Console.WriteLine("WebSocket server started at ws://localhost:5000/ws/");

    while (true)
    {
        HttpListenerContext httpContext = await httpListener.GetContextAsync();

        if (httpContext.Request.IsWebSocketRequest)
        {
            webSocketContext = await httpContext.AcceptWebSocketAsync(subProtocol: null);
            Console.WriteLine("WebSocket connection established.");

            await ProcessWebSocketMessages(webSocketContext.WebSocket);
        }
        else
        {
            httpContext.Response.StatusCode = 400;
            httpContext.Response.Close();
            Console.WriteLine("Non-WebSocket request received and rejected.");
        }
    }
}

async Task ProcessWebSocketMessages(WebSocket webSocket)
{
    var buffer = new byte[1024 * 4];

    while (webSocket.State == WebSocketState.Open)
    {
        WebSocketReceiveResult result = await webSocket.ReceiveAsync(new ArraySegment<byte>(buffer), CancellationToken.None);

        if (result.MessageType == WebSocketMessageType.Close)
        {
            await webSocket.CloseAsync(WebSocketCloseStatus.NormalClosure, "Closing", CancellationToken.None);
            Console.WriteLine("WebSocket connection closed.");
        }
        else
        {
            string message = Encoding.UTF8.GetString(buffer, 0, result.Count);
            Console.WriteLine($"{message}");
            ProcessAIRequest(message);
        }
    }
}

if (true)
{

}
else
{
    chatHistory.AddMessage(AuthorRole.System, "Transcript of a dialog, where the User interacts with an Assistant named Bob. Bob is Lawyer and is helpful, kind, honest, good at writing, and never fails to answer the User's requests immediately and with precision. Bob will only answer from information provided by Users input and will answer questions as short and precise as possible. After each answer I will cite the exact text that I pulled the inforamtion from word for word.");
    var Input = File.ReadAllText("D:\\Output-WC 25896.txt");
    Console.WriteLine("Console writeline length: " + Input.Length);
    chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000
    chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");
    //chatHistory.AddMessage(AuthorRole.User, Input.Substring(0, 10000)); //10000
    //chatHistory.AddMessage(AuthorRole.Assistant, "Thank you, I will answer your questions only using the text given from User's input.");
}

static void FocusProcess()
{
    IntPtr hWnd; //change this to IntPtr
    Process[] processRunning = Process.GetProcesses();
    foreach (Process pr in processRunning)
    {
        if (pr.ProcessName == "notepad")
        {
            hWnd = pr.MainWindowHandle; //use it as IntPtr not int
            ShowWindow(hWnd, 3);
            SetForegroundWindow(hWnd); //set to topmost
        }
    }
}

StartWebSocketServer();
FocusProcess();
Console.ForegroundColor = ConsoleColor.Yellow;
Console.Write("The chat session has started.\nUser: ");
Console.ForegroundColor = ConsoleColor.White;

void MeasureChatHistoryTokens()
{
    foreach (ChatHistory.Message Value in LLMChatSession.History.Messages.ToArray())
    {
        TokensInMemory += model.Tokenize(Value.Content, true, false, Encoding.ASCII).Length;
    }

}
Debug.WriteLine("Starting with tokens" + "\r\nTokensInMemory: " + TokensInMemory + "/" + context.ContextSize + "/" + model.ContextSize);

string userInput = "";
while (userInput != "exit")
{
    userInput = Console.ReadLine() ?? "";
    ProcessAIRequest(userInput);
}

//Unable to use to do "Top level statements must procede namespace and type declerations.
[Flags]
enum MyLoadedMethod : ushort
{
    Plain = 0,
    RAG = 1
}

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

585

586

587

588

589

590

591

592

593

594

595

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

646

647

648

649

650

651

652

653

654

655

656

657

658

659

660

661

662

663

664

665

666

667

668

669

670

671

672

673

674

675

676

677

678

679

680

681

682

683

684

685

686

687

688

689

690

691

692

693

694

695

696

697

698

699

700

701

702

703

704

705

706

707

708

709

710

711

712

713

714

715

716

717

718

719

720

721

722

723

724

725

726

727

728

729

730

731

732

733

734

735

736

737

738

739

740

741

742

743

744

745

746

747

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

773

774

775

776

777

778

779

780

781

782

783

784

785

786

787

788

789

790

791

792

793

794

795

796

797

798

799

800

801

802

803

804

// See https://aka.ms/new-console-template for more information

//leaderboards

//https://huggingface.co/spaces/mteb/leaderboard

//Implement with Python

//https://www.llamaindex.ai/

//https://docs.llamaindex.ai/en/stable/getting_started/discover_llamaindex/

//Install-Package LLamaSharp

//Install-Package LLamaSharp.Backend.Cuda11

//https://dotnet.microsoft.com/en-us/download/dotnet/8.0

//https://dotnet.microsoft.com/en-us/download/dotnet

//The top line returns waaayy better results then the bottom

//Assistant: discovery\r\nUser:

//discovery

using LLama.Common;

using LLama;

#pragma warning disable SKEXP0050, SKEXP0001, SKEXP0020

//RAG

//Install-Package LLamaSharp.Semantic-Kernel

//https://github.com/SciSharp/LLamaSharp/issues/648

using LLamaSharp.SemanticKernel.TextEmbedding;

//Install-Package Microsoft.SemanticKernel

using Microsoft.SemanticKernel.Connectors;

using Microsoft.SemanticKernel.Memory;

using Microsoft.SemanticKernel.Text;

//Install-Package Microsoft.SemanticKernel.Connectors.Sqlite -Version 1.18.0-alpha

using Microsoft.SemanticKernel.Connectors.Sqlite;

using System.IO;

using System.Text.RegularExpressions;

using System.Diagnostics;

using System.Net.WebSockets;

using System.Text;

using System.Net;

using System.Management;

using SQLitePCL;

using System;

using System.Collections;

using System.Windows.Documents;

using System.Runtime.InteropServices;

using static System.Net.Mime.MediaTypeNames;

using System.CodeDom.Compiler;

using System.Reflection;

using Microsoft.Data.Sqlite;

using static System.Collections.Specialized.BitVector32;

[DllImport("user32.dll")]

static extern IntPtr SetForegroundWindow(IntPtr hWnd);

[DllImport("user32.dll")]

static extern bool ShowWindow(IntPtr hWnd, int nCmdShow); //ShowWindow needs an IntPtr

Console.ForegroundColor = ConsoleColor.White;

HttpListenerWebSocketContext webSocketContext = null;

string RagModelPath = @"D:\bge-large-en-v1.5-q8_0.gguf";

string modelPath = @"D:\Meta-Llama-3.1-8B-Instruct-Q6_K.gguf";