feat(Ollama): Updated to use Ollama SDK from NuGet.

examples/LangChain.Samples.Serve/Program.cs

@@ -1,10 +1,11 @@
 using LangChain.Memory;
-using LangChain.Providers;
 using LangChain.Providers.Ollama;
 using LangChain.Serve;
 using LangChain.Serve.Abstractions.Repository;
+using Ollama;
 using static LangChain.Chains.Chain;
 using Message = LangChain.Providers.Message;
+using MessageRole = LangChain.Providers.MessageRole;
 
 
 var builder = WebApplication.CreateBuilder();
@@ -15,7 +16,7 @@
 builder.Services.AddLangChainServe();
 
 // 2. Create a model
-var model = new OllamaChatModel(new OllamaProvider(options: new OllamaOptions
+var model = new OllamaChatModel(new OllamaProvider(options: new RequestOptions
 {
     Temperature = 0,
     Stop = ["User:"],

src/Meta/test/WikiTests.cs

@@ -1,5 +1,4 @@
 using LangChain.Chains.StackableChains.Agents.Tools.BuiltIn;
-using LangChain.Databases;
 using LangChain.Databases.Sqlite;
 using LangChain.Extensions;
 using LangChain.Memory;
@@ -9,7 +8,9 @@
 using LangChain.Providers.LLamaSharp;
 using LangChain.Providers.OpenAI.Predefined;
 using LangChain.DocumentLoaders;
+using LangChain.Providers.Ollama;
 using LangChain.Splitters.Text;
+using Ollama;
 using static LangChain.Chains.Chain;
 
 namespace LangChain.IntegrationTests;
@@ -21,15 +22,16 @@ public class WikiTests
     [Test]
     public async Task AgentWithOllama()
     {
-        var model = new OllamaLanguageModelInstruction("mistral:latest",
-            "http://localhost:11434",
-            options: new OllamaLanguageModelOptions
+        var provider = new OllamaProvider(
+            // "http://172.16.50.107:11434",
+            options: new RequestOptions
             {
                 Temperature = 0,
-            }).UseConsoleForDebug();
+            });
+        var model = new OllamaChatModel(provider, id: "llama3").UseConsoleForDebug();
 
         var chain =
-            Set("What is tryAGI/LangChain?")
+            Set("What is tryAGI/LangChain? In 5 words")
             | LLM(model);
 
         await chain.RunAsync();
@@ -38,13 +40,13 @@ public async Task AgentWithOllama()
     [Test]
     public async Task AgentWithOllamaReact()
     {
-        var model = new OllamaLanguageModelInstruction("mistral:latest",
-            "http://localhost:11434",
-            options: new OllamaLanguageModelOptions()
+        var provider = new OllamaProvider(
+            options: new RequestOptions
             {
                 Stop = new[] { "Observation", "[END]" }, // add injection word `Observation` and `[END]` to stop the model(just as additional safety feature)
                 Temperature = 0
-            }).UseConsoleForDebug();
+            });
+        var model = new OllamaChatModel(provider, id: "mistral:latest").UseConsoleForDebug();
 
         // create a google search tool
         var searchTool = new GoogleCustomSearchTool(key: "<your key>", cx: "<your cx>", resultsLimit: 1);
@@ -158,13 +160,13 @@ public async Task HowToUseOpenAiProviderSmaller()
     [Test]
     public async Task ImageGenerationWithOllamaAndStableDiffusion()
     {
-        var olmodel = new OllamaLanguageModelInstruction("mistral:latest",
-            "http://localhost:11434",
-            options: new OllamaLanguageModelOptions()
+        var provider = new OllamaProvider(
+            options: new RequestOptions
             {
                 Stop = new[] { "\n" },
                 Temperature = 0
-            }).UseConsoleForDebug();
+            });
+        var llm = new OllamaChatModel(provider, id: "mistral:latest").UseConsoleForDebug();
 
         var sdmodel = new Automatic1111Model
         {
@@ -201,7 +203,7 @@ public async Task ImageGenerationWithOllamaAndStableDiffusion()
 
         var chain = Set("a cute girl cosplaying a cat")                                     // describe a desired image in simple words
                     | Template(template, outputKey: "prompt")                               // insert our description into the template
-                    | LLM(olmodel, inputKey: "prompt", outputKey: "image_prompt")           // ask ollama to generate a prompt for stable diffusion
+                    | LLM(llm, inputKey: "prompt", outputKey: "image_prompt")           // ask ollama to generate a prompt for stable diffusion
                     | GenerateImage(sdmodel, inputKey: "image_prompt", outputKey: "image")  // generate an image using stable diffusion
                     | SaveIntoFile("image.png", inputKey: "image");                     // save the image into a file
 
@@ -217,11 +219,13 @@ public async Task RagWithOpenAiOllama()
         var embeddingModel = new TextEmbeddingV3SmallModel(apiKey);
 
         // prepare Ollama with mistral model
-        var model = new OllamaLanguageModelInstruction("mistral:latest", options: new OllamaLanguageModelOptions
-        {
-            Stop = ["\n"],
-            Temperature = 0.0f,
-        }).UseConsoleForDebug();
+        var provider = new OllamaProvider(
+            options: new RequestOptions
+            {
+                Stop = ["\n"],
+                Temperature = 0.0f,
+            });
+        var llm = new OllamaChatModel(provider, id: "mistral:latest").UseConsoleForDebug();
 
         using var vectorDatabase = new SqLiteVectorDatabase("vectors.db");
         var vectorCollection = await vectorDatabase.AddDocumentsFromAsync<PdfPigPdfLoader>(
@@ -247,7 +251,7 @@ public async Task RagWithOpenAiOllama()
             | RetrieveDocuments(vectorCollection, embeddingModel, inputKey: "question", outputKey: "documents", amount: 5) // take 5 most similar documents
             | StuffDocuments(inputKey: "documents", outputKey: "context")                       // combine documents together and put them into context
             | Template(promptText)                                                              // replace context and question in the prompt with their values
-            | LLM(model);                                                                       // send the result to the language model
+            | LLM(llm);                                                                       // send the result to the language model
 
         var result = await chain.RunAsync("text", CancellationToken.None);                                        // get chain result
 

src/Providers/Ollama/src/LangChain.Providers.Ollama.csproj

@@ -3,7 +3,7 @@
 	<PropertyGroup>
 		<TargetFrameworks>net4.6.2;netstandard2.0;net6.0;net8.0</TargetFrameworks>
 		<SignAssembly>false</SignAssembly>
-		<NoWarn>$(NoWarn);CA1003;CA1307;CA1054;CA1711;CA1819;CA2234</NoWarn>
+		<NoWarn>$(NoWarn);CA1003;CA1307;CA1054;CA1711;CA1819;CA2234;CS3001;CS3003</NoWarn>
 		<IsAotCompatible>false</IsAotCompatible>
 		<IsTrimmable>false</IsTrimmable>
 		<EnableTrimAnalyzer>false</EnableTrimAnalyzer>
@@ -27,6 +27,10 @@
 		<PackageTags>$(PackageTags);Ollama;api</PackageTags>
 	</PropertyGroup>
 
+	<ItemGroup>
+	  <PackageReference Include="Ollama" />
+	</ItemGroup>
+
 	<ItemGroup>
 		<ProjectReference Include="..\..\Abstractions\src\LangChain.Providers.Abstractions.csproj" />
 	</ItemGroup>

src/Providers/Ollama/src/OllamaChatModel.cs

@@ -1,4 +1,5 @@
 using System.Diagnostics;
+using Ollama;
 
 namespace LangChain.Providers.Ollama;
 
@@ -31,31 +32,31 @@ public override async Task<ChatResponse> GenerateAsync(
     {
         request = request ?? throw new ArgumentNullException(nameof(request));
 
-        var models = await Provider.Api.ListLocalModels().ConfigureAwait(false);
-        if (models.All(x => x.Name != Id))
+        var models = await Provider.Api.ListLocalModelsAsync(cancellationToken).ConfigureAwait(false);
+        if (models.All(x => x.Model != Id))
         {
-            await Provider.Api.PullModel(Id).ConfigureAwait(false);
+            await Provider.Api.PullModelAsync(Id, cancellationToken: cancellationToken).WaitAsync().ConfigureAwait(false);
         }
 
         var prompt = ToPrompt(request.Messages);
         var watch = Stopwatch.StartNew();
-        var response = Provider.Api.GenerateCompletion(new GenerateCompletionRequest()
+        var response = Provider.Api.GetCompletionAsync(new GenerateCompletionRequest
         {
             Prompt = prompt,
             Model = Id,
             Options = Provider.Options,
             Stream = true,
             Raw = true,
             Format = UseJson ? "json" : string.Empty,
-        });
+        }, cancellationToken);
 
         OnPromptSent(prompt);
 
         var buf = "";
         await foreach (var completion in response)
         {
             buf += completion.Response;
-            OnPartialResponseGenerated(completion.Response);
+            OnPartialResponseGenerated(completion.Response ?? string.Empty);
         }
 
         OnCompletedResponseGenerated(buf);

src/Providers/Ollama/src/OllamaEmbeddingModel.cs

@@ -1,4 +1,6 @@
-namespace LangChain.Providers.Ollama;
+using Ollama;
+
+namespace LangChain.Providers.Ollama;
 
 /// <summary>
 /// 
@@ -23,17 +25,17 @@ public async Task<EmbeddingResponse> CreateEmbeddingsAsync(
     {
         request = request ?? throw new ArgumentNullException(nameof(request));
 
-        var results = new List<double[]>(capacity: request.Strings.Count);
+        var results = new List<IList<double>>(capacity: request.Strings.Count);
         foreach (var prompt in request.Strings)
         {
-            var response = await Provider.Api.GenerateEmbeddings(new GenerateEmbeddingRequest
+            var response = await Provider.Api.GenerateEmbeddingsAsync(new GenerateEmbeddingRequest
             {
                 Prompt = prompt,
                 Model = Id,
                 Options = Provider.Options,
-            }).ConfigureAwait(false);
+            }, cancellationToken).ConfigureAwait(false);
 
-            results.Add(response.Embedding);
+            results.Add(response.Embedding ?? []);
         }
 
         return new EmbeddingResponse
@@ -42,7 +44,7 @@ public async Task<EmbeddingResponse> CreateEmbeddingsAsync(
                 .Select(x => x.Select(y => (float)y).ToArray())
                 .ToArray(),
             UsedSettings = EmbeddingSettings.Default,
-            Dimensions = results.FirstOrDefault()?.Length ?? 0,
+            Dimensions = results.FirstOrDefault()?.Count ?? 0,
         };
     }
 }

src/Providers/Ollama/src/OllamaProvider.cs

@@ -1,4 +1,6 @@
-namespace LangChain.Providers.Ollama;
+using Ollama;
+
+namespace LangChain.Providers.Ollama;
 
 /// <summary>
 /// 
@@ -7,7 +9,7 @@
 /// <param name="options"></param>
 public class OllamaProvider(
     string url = "http://localhost:11434",
-    OllamaOptions? options = null)
+    RequestOptions? options = null)
     : Provider(id: "ollama")
 {
     /// <summary>
@@ -18,5 +20,5 @@ public class OllamaProvider(
     /// <summary>
     /// 
     /// </summary>
-    public OllamaOptions Options { get; } = options ?? new OllamaOptions();
+    public RequestOptions Options { get; } = options ?? new RequestOptions();
 }