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
}

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// 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

}

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