Change interface to support multiple images and add the capabitlity to render the image in the console

LLama.Examples/Examples/LlavaInteractiveModeExecute.cs

@@ -1,4 +1,7 @@
-using LLama.Common;
+using System.Text.RegularExpressions;
+using LLama.Batched;
+using LLama.Common;
+using Spectre.Console;
 
 namespace LLama.Examples.Examples
 {
@@ -8,15 +11,15 @@ namespace LLama.Examples.Examples
         {
             string multiModalProj = UserSettings.GetMMProjPath();
             string modelPath = UserSettings.GetModelPath();
-            string imagePath = UserSettings.GetImagePath();
+            string modelImage = UserSettings.GetImagePath();
+            const int maxTokens = 1024;
 
-            var prompt = (await File.ReadAllTextAsync("Assets/vicuna-llava-v16.txt")).Trim();
+            var prompt = $"{{{modelImage}}}\nUSER:\nProvide a full description of the image.\nASSISTANT:\n";
 
             var parameters = new ModelParams(modelPath)
             {
                 ContextSize = 4096,
                 Seed = 1337,
-                GpuLayerCount = 5
             };
             using var model = LLamaWeights.LoadFromFile(parameters);
             using var context = model.CreateContext(parameters);
@@ -26,26 +29,93 @@ namespace LLama.Examples.Examples
             
             var ex = new InteractiveExecutor(context, clipModel );
 
-            ex.ImagePath = imagePath;
-
             Console.ForegroundColor = ConsoleColor.Yellow;
-            Console.WriteLine("The executor has been enabled. In this example, the prompt is printed, the maximum tokens is set to 1024 and the context size is 4096. ");
-            Console.ForegroundColor = ConsoleColor.White;
-
-            Console.Write(prompt);
+            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> { "USER:" }, MaxTokens = 1024 };
+            var inferenceParams = new InferenceParams() { Temperature = 0.1f, AntiPrompts = new List<string> { "\nUSER:" }, MaxTokens = maxTokens };
 
-            while (true)
+            do
             {
+                
+                // Evaluate if we have images
+                //
+                var imageMatches = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);
+                var imageCount = imageMatches.Count();
+                var hasImages = imageCount > 0;
+                byte[][] imageBytes = null;
+
+                if (hasImages)
+                {
+                    var imagePathsWithCurlyBraces = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Value);
+                    var imagePaths = Regex.Matches(prompt, "{([^}]*)}").Select(m => m.Groups[1].Value);
+
+                    try
+                    {
+                        imageBytes = imagePaths.Select(File.ReadAllBytes).ToArray();
+                    }
+                    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;
+                    }
+
+
+                    int index = 0;
+                    foreach (var path in imagePathsWithCurlyBraces)
+                    {
+                        // First image replace to tag <image, the rest of the images delete the tag
+                        if (index++ == 0)
+                            prompt = prompt.Replace(path, "<image>");
+                        else
+                            prompt = prompt.Replace(path, "");
+                    }
+
+                  
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    Console.WriteLine($"Here are the images, that are sent to the chat model in addition to your message.");
+                    Console.WriteLine();
+
+                    foreach (var consoleImage in imageBytes?.Select(bytes => new CanvasImage(bytes)))
+                    {
+                        consoleImage.MaxWidth = 50;
+                        AnsiConsole.Write(consoleImage);
+                    }
+
+                    Console.WriteLine();
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    Console.WriteLine($"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();
+
+
+                    // Initilize Images in executor
+                    //
+                    ex.ImagePaths = imagePaths.ToList();
+                }
+
+                Console.ForegroundColor = Color.White;
                 await foreach (var text in ex.InferAsync(prompt, inferenceParams))
                 {
                     Console.Write(text);
                 }
+                Console.Write(" ");
                 Console.ForegroundColor = ConsoleColor.Green;
                 prompt = Console.ReadLine();
-                Console.ForegroundColor = ConsoleColor.White;
+                Console.WriteLine();
+                
+                // let the user finish with exit
+                //
+                if (prompt.Equals("/exit", StringComparison.OrdinalIgnoreCase))
+                    break;
+
             }
+            while(true);
         }
     }
 }

LLama.Examples/LLama.Examples.csproj

@@ -19,6 +19,7 @@
     <PackageReference Include="Microsoft.SemanticKernel" Version="1.6.2" />
     <PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.6.2-alpha" />
     <PackageReference Include="Spectre.Console" Version="0.48.0" />
+    <PackageReference Include="Spectre.Console.ImageSharp" Version="0.48.0" />
   </ItemGroup>
 
   <ItemGroup>

LLama/Abstractions/ILLamaExecutor.cs

@@ -25,9 +25,9 @@ namespace LLama.Abstractions
         public LLavaWeights? ClipModel { get;  }        
         
         /// <summary>
-        /// Image filename and path (jpeg images).
+        /// List of images: Image filename and path (jpeg images).
         /// </summary>
-        public string? ImagePath { get; set; }
+        public List<string> ImagePaths { get; set; }
         
         
         /// <summary>

LLama/LLamaExecutorBase.cs

@@ -71,7 +71,7 @@ namespace LLama
         {
             get
             {
-                return ClipModel != null && ImagePath != null;
+                return ClipModel != null;
             }
         }
         
@@ -79,7 +79,7 @@ namespace LLama
         public LLavaWeights? ClipModel { get;  }      
         
         /// <inheritdoc />
-        public string? ImagePath { get; set; }        
+        public List<string> ImagePaths { get; set; }        
         
         /// <summary>
         /// Current "mu" value for mirostat sampling
@@ -95,6 +95,7 @@ namespace LLama
         /// <param name="logger"></param>
         protected StatefulExecutorBase(LLamaContext context, ILogger? logger = null)
         {
+            ImagePaths = new List<string>();
             _logger = logger;
             Context = context;
             _pastTokensCount = 0;

LLama/LLamaInteractExecutor.cs

@@ -24,7 +24,7 @@ namespace LLama
         
         // LLava
         private int _EmbedImagePosition = -1;
-        private SafeLlavaImageEmbedHandle _imageEmbedHandle = null;
+        private List<SafeLlavaImageEmbedHandle> _imageEmbedHandles = new List<SafeLlavaImageEmbedHandle>();
         private bool _imageInPrompt = false;
 
         /// <summary>
@@ -125,30 +125,7 @@ namespace LLama
                 }
                 else
                 {
-                    // If the prompt contains the tag <image> extract this.
-                    _imageInPrompt = text.Contains("<image>");
-                    if (_imageInPrompt)
-                    {
-                        if (!string.IsNullOrEmpty(ImagePath))
-                        {
-                            _imageEmbedHandle = SafeLlavaImageEmbedHandle.CreateFromFileName( ClipModel.NativeHandle, Context, ImagePath);
-                        }
-                        
-                        int imageIndex = text.IndexOf("<image>");
-                        // Tokenize segment 1 (before <image> tag)
-                        string preImagePrompt = text.Substring(0, imageIndex);
-                        var segment1 = Context.Tokenize(preImagePrompt, true);
-                        // Remember the position to add the image embeddings
-                        _EmbedImagePosition = segment1.Length;
-                        string postImagePrompt = text.Substring(imageIndex + 7);
-                        var segment2 = Context.Tokenize(postImagePrompt, false);
-                        _embed_inps.AddRange(segment1);
-                        _embed_inps.AddRange(segment2);
-                    }
-                    else
-                    {
-                        _embed_inps = Context.Tokenize(text, true).ToList();
-                    }
+                    PreprocessLlava(text, args, true );
                 }
             }
             else
@@ -157,6 +134,7 @@ namespace LLama
                 {
                     text += "\n";
                 }
+
                 var line_inp = Context.Tokenize(text, false);
                 _embed_inps.AddRange(line_inp);
                 args.RemainedTokens -= line_inp.Length;
@@ -165,6 +143,37 @@ namespace LLama
             return Task.CompletedTask;
         }
 
+        private Task PreprocessLlava(string text, InferStateArgs args, bool addBos = true )
+        {
+            int usedTokens = 0;
+            // If the prompt contains the tag <image> extract this.
+            _imageInPrompt = text.Contains("<image>");
+            if (_imageInPrompt)
+            {
+                foreach (var image in ImagePaths)
+                {
+                    _imageEmbedHandles.Add(SafeLlavaImageEmbedHandle.CreateFromFileName( ClipModel.NativeHandle, Context, image ) );
+                }
+                        
+                int imageIndex = text.IndexOf("<image>");
+                // Tokenize segment 1 (before <image> tag)
+                string preImagePrompt = text.Substring(0, imageIndex);
+                var segment1 = Context.Tokenize(preImagePrompt, addBos );
+                // Remember the position to add the image embeddings
+                _EmbedImagePosition = segment1.Length;
+                string postImagePrompt = text.Substring(imageIndex + 7);
+                var segment2 = Context.Tokenize(postImagePrompt, false);
+                _embed_inps.AddRange(segment1);
+                _embed_inps.AddRange(segment2);
+                usedTokens += (segment1.Length + segment2.Length);
+            }
+            else
+            {
+                _embed_inps = Context.Tokenize(text, true).ToList();
+            }
+            return Task.CompletedTask;
+        }
+        
         /// <summary>
         /// Return whether to break the generation.
         /// </summary>
@@ -216,18 +225,19 @@ namespace LLama
                 (DecodeResult, int) header, end, result;
                 if (IsMultiModal &&  _EmbedImagePosition > 0)
                 {
-                    // Previous to Image
+                    // Tokens previous to the images
                     header = Context.NativeHandle.Decode(_embeds.GetRange(0, _EmbedImagePosition), LLamaSeqId.Zero, batch, ref _pastTokensCount);
                     if (header.Item1 != DecodeResult.Ok) throw new LLamaDecodeError(header.Item1);
                    
-                    // Image
-                    ClipModel.EvalImageEmbed(Context, _imageEmbedHandle, ref _pastTokensCount);
+                    // Images
+                    foreach( var image in _imageEmbedHandles )
+                        ClipModel.EvalImageEmbed(Context, image, ref _pastTokensCount);
                         
-                    // Post-image
+                    // Post-image Tokens
                     end = Context.NativeHandle.Decode(_embeds.GetRange(_EmbedImagePosition, _embeds.Count - _EmbedImagePosition), LLamaSeqId.Zero, batch, ref _pastTokensCount);
 
                     _EmbedImagePosition = -1;
-
+                    _imageEmbedHandles.Clear();
                 }
                 else
                 {

LLama/LLamaStatelessExecutor.cs

@@ -27,8 +27,8 @@ namespace LLama
         // LLava Section
         public bool IsMultiModal => false;
         public bool MultiModalProject { get;  }
-        public LLavaWeights ClipModel { get;  }        
-        public string ImagePath { get; set; } 
+        public LLavaWeights? ClipModel { get;  }        
+        public List<string> ImagePaths { get; set; } 
         
         /// <summary>
         /// The context used by the executor when running the inference.
@@ -43,6 +43,7 @@ namespace LLama
         /// <param name="logger"></param>
         public StatelessExecutor(LLamaWeights weights, IContextParams @params, ILogger? logger = null)
         {
+            ImagePaths = new List<string>();
             _weights = weights;
             _params = @params;
             _logger = logger;