更新

OllamaStudy.UseExtensionsAI/OpenAISdkTest.cs

@@ -465,15 +465,23 @@ public class OpenAISdkTest
     }
     #endregion
 
-    [Fact]
     #region 如何将响应与文件搜索一起使用
+    //[Fact]
+    [Fact(Skip = "因本地Ollama测试环境不支持，忽略测试")]
     public async Task Respones_With_FileSearch_Test()
     {
 #pragma warning disable OPENAI001
-        OpenAIResponseClient client = new(
-        model: "gpt-4o-mini",
-        apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY"));
+        OpenAIResponseClient client = new
+        (
+            "gpt-4o-mini",
+            new ApiKeyCredential("sk-4azuOUkbzNGP22pQkND8ad1vZl7ladwBQyqGKlWWZyxYgX1L"),
+            new OpenAIClientOptions()
+            {
+                Endpoint = new Uri("https://sg.uiuiapi.com/v1")
+            }
+        );
 
+        //已经存在的文件向量IDS(提前将文件向量化)
         ResponseTool fileSearchTool = ResponseTool.CreateFileSearchTool(vectorStoreIds: ["sssssssss"]);
         OpenAIResponse response = await client.CreateResponseAsync
         (
@@ -504,11 +512,21 @@ public class OpenAISdkTest
     #endregion
 
     #region 如何将响应与网络搜索结合使用
-    [Fact]
+
+    [Fact(Skip = "因本地Ollama测试环境不支持，忽略测试")]
+    //[Fact]
     public async Task WebSearch_ChatClient_Test()
     {
 #pragma warning disable OPENAI001
-        OpenAIResponseClient client = _defaultOpenAIClient.GetOpenAIResponseClient(ModelSelecter.ModelWithRawmodel);
+        OpenAIResponseClient client = new
+        (
+            "gpt-4o-mini",
+            new ApiKeyCredential("sk-4azuOUkbzNGP22pQkND8ad1vZl7ladwBQyqGKlWWZyxYgX1L"),
+            new OpenAIClientOptions()
+            {
+                Endpoint = new Uri("https://sg.uiuiapi.com/v1")
+            }
+       );
 
         OpenAIResponse response = await client.CreateResponseAsync
         (
@@ -535,15 +553,274 @@ public class OpenAISdkTest
     #endregion
 
     #region 如何生成文本嵌入
+    [Fact]
+    public void Embedding_ChatClient_Test()
+    {
+        EmbeddingClient embeddingClient = _defaultOpenAIClient.GetEmbeddingClient(ModelSelecter.ModelWithEmbedding);
+
+        string description = "Best hotel in town if you like luxury hotels. They have an amazing infinity pool, a spa,"
+            + " and a really helpful concierge. The location is perfect -- right downtown, close to all the tourist"
+            + " attractions. We highly recommend this hotel.";
+
+        OpenAIEmbedding embedding = embeddingClient.GenerateEmbedding(description);
+        ReadOnlyMemory<float> vector = embedding.ToFloats();
+
+        Assert.True(vector.Length>0);
+    }
     #endregion
 
     #region 如何生成图像
+    [Fact(Skip = "因本地Ollama测试环境不支持，忽略测试")]
+    //[Fact]
+    public void Image_ChatClient_Test()
+    {
+        ImageClient imageClient = new
+        (
+            "dall-e-3",
+            new ApiKeyCredential("sk-4azuOUkbzNGP22pQkND8ad1vZl7ladwBQyqGKlWWZyxYgX1L"),
+            new OpenAIClientOptions()
+            {
+                Endpoint = new Uri("https://sg.uiuiapi.com/v1")
+            }
+        );
+
+        string prompt = """
+            The concept for a living room that blends Scandinavian simplicity with Japanese minimalism for a serene and cozy atmosphere. 
+            It's a space that invites relaxation and mindfulness, with natural light and fresh air. 
+            Using neutral tones, including colors like white, beige, gray, and black, that create a sense of harmony. 
+            Featuring sleek wood furniture with clean lines and subtle curves to add warmth and elegance. Plants and flowers in ceramic pots adding color and life to a space. 
+            They can serve as focal points, creating a connection with nature. Soft textiles and cushions in organic fabrics adding comfort and softness to a space. 
+            They can serve as accents, adding contrast and texture.
+            """;
+        prompt = """
+            画一个中国古代的将军。身披铠甲，手持长剑，眼神坚定，表情严肃，看起来很威严。国字脸，在战场上指挥作战！
+            """;
+
+        ImageGenerationOptions options = new()
+        {
+            Quality = GeneratedImageQuality.High,
+            Size = GeneratedImageSize.W1792xH1024,
+            Style = GeneratedImageStyle.Vivid,
+            ResponseFormat = GeneratedImageFormat.Bytes
+        };
+
+        GeneratedImage image = imageClient.GenerateImage(prompt, options);
+        BinaryData bytes = image.ImageBytes;
+
+        using FileStream stream = File.OpenWrite($"{Guid.NewGuid()}.png");
+        bytes.ToStream().CopyTo(stream);
+    }
     #endregion
 
     #region 如何转录音频
+    [Fact(Skip = "因本地Ollama测试环境不支持，忽略测试")]
+    //[Fact]
+    public void Tranacribe_Audio_AudioClient_Test()
+    {
+        AudioClient client = new
+        (
+            "whisper-1",
+            new ApiKeyCredential("sk-4azuOUkbzNGP22pQkND8ad1vZl7ladwBQyqGKlWWZyxYgX1L"),
+            new OpenAIClientOptions()
+            {
+                Endpoint = new Uri("https://sg.uiuiapi.com/v1")
+            }
+        );
+
+        string audioFilePath = Path.Combine("Assets", "dongdong.mp3");
+
+        AudioTranscriptionOptions options = new()
+        {
+            ResponseFormat = AudioTranscriptionFormat.Verbose,
+            TimestampGranularities = AudioTimestampGranularities.Word | AudioTimestampGranularities.Segment,
+        };
+
+        AudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);
+
+        _output.WriteLine("Transcription:");
+        _output.WriteLine($"{transcription.Text}");
+
+        _output.WriteLine("");
+        _output.WriteLine($"Words:");
+        foreach (TranscribedWord word in transcription.Words)
+        {
+            _output.WriteLine($"  {word.Word,15} : {word.StartTime.TotalMilliseconds,5:0} - {word.EndTime.TotalMilliseconds,5:0}");
+        }
+
+        _output.WriteLine("");
+        _output.WriteLine($"Segments:");
+        foreach (TranscribedSegment segment in transcription.Segments)
+        {
+            _output.WriteLine($"  {segment.Text,90} : {segment.StartTime.TotalMilliseconds,5:0} - {segment.EndTime.TotalMilliseconds,5:0}");
+        }
+    }
     #endregion
 
-    #region 如何将助手与检索增强生成 （RAG） 结合使用。
+    #region 如何将助手与检索增强生成 （RAG） 结合使用
+    /// <summary>
+    /// 在此示例中，您有一个包含不同产品每月销售信息的 JSON 文档，并且您希望构建一个能够分析它并回答有关它的问题的助手
+    /// 请同时使用 OpenAI.Files 命名空间中的 OpenAIFileClient 和 OpenAI.Assistants 命名空间中的 AssistantClient
+    /// </summary>
+    [Fact]
+    public void RAG_Assistant_ChatClient_Test()
+    {
+#pragma warning disable OPENAI001
+
+        OpenAIClientOptions clientOptions = new()
+        {
+            Endpoint = new Uri("https://sg.uiuiapi.com/v1"),
+        };
+
+        OpenAIClient openAIClient = new(new ApiKeyCredential("sk-4azuOUkbzNGP22pQkND8ad1vZl7ladwBQyqGKlWWZyxYgX1L"));
+        OpenAIFileClient fileClient = openAIClient.GetOpenAIFileClient();
+        AssistantClient assistantClient = openAIClient.GetAssistantClient();
+
+        using Stream document = BinaryData.FromBytes("""
+        {
+            "description": "This document contains the sale history data for Contoso products.",
+            "sales": [
+                {
+                    "month": "January",
+                    "by_product": {
+                        "113043": 15,
+                        "113045": 12,
+                        "113049": 2
+                    }
+                },
+                {
+                    "month": "February",
+                    "by_product": {
+                        "113045": 22
+                    }
+                },
+                {
+                    "month": "March",
+                    "by_product": {
+                        "113045": 16,
+                        "113055": 5
+                    }
+                }
+            ]
+        }
+        """u8.ToArray()).ToStream();
+        //使用 OpenAIFileClient 的 UploadFile 方法将此文档上传到 OpenAI，确保使用 FileUploadPurpose.Assistants 以允许助手稍后访问它
+        OpenAIFile salesFile = fileClient.UploadFile
+        (
+            document,
+            "monthly_sales.json",
+            FileUploadPurpose.Assistants
+        );
+
+        //使用 AssistantCreationOptions 类的实例创建新助手以对其进行自定义。
+        AssistantCreationOptions assistantOptions = new()
+        {
+            Name = "Example: Contoso sales RAG",
+            Instructions ="You are an assistant that looks up sales data and helps visualize the information based on user queries. When asked to generate a graph, chart, or other visualization, use the code interpreter tool to do so.",
+            Tools =
+            {
+                new FileSearchToolDefinition(),
+                new CodeInterpreterToolDefinition(),
+            },
+            ToolResources = new()
+            {
+                FileSearch = new()
+                {
+                    NewVectorStores =
+                    {
+                        new VectorStoreCreationHelper([salesFile.Id]),
+                    }
+                }
+            },
+        };
+
+        Assistant assistant = assistantClient.CreateAssistant("gpt-4o", assistantOptions);
+
+        //接下来，创建一个新线程。出于说明目的，可以包含询问给定产品的销售信息的初始用户消息，然后使用 AssistantClient 的 CreateThreadAndRun 方法启动它：
+        ThreadCreationOptions threadOptions = new()
+        {
+            InitialMessages = { "How well did product 113045 sell in February? Graph its trend over time." }
+        };
+
+        ThreadRun threadRun = assistantClient.CreateThreadAndRun(assistant.Id, threadOptions);
+
+        //轮询运行的状态，直到它不再排队或正在进行：
+        do
+        {
+            Thread.Sleep(TimeSpan.FromSeconds(1));
+            threadRun = assistantClient.GetRun(threadRun.ThreadId, threadRun.Id);
+        } while (!threadRun.Status.IsTerminal);
+
+        //如果一切顺利，运行的终端状态将为 RunStatus.Completed
+        //最后，可以使用 AssistantClient 的 GetMessages 方法检索与此线程关联的消息，这些消息现在包括助手对初始用户消息的响应。
+        //出于说明目的，您可以将消息打印到控制台，并将助手生成的任何图像保存到本地存储：
+
+        CollectionResult<ThreadMessage> messages = assistantClient.GetMessages(threadRun.ThreadId, new MessageCollectionOptions() { Order = MessageCollectionOrder.Ascending });
+
+        foreach (ThreadMessage message in messages)
+        {
+            Console.Write($"[{message.Role.ToString().ToUpper()}]: ");
+            foreach (MessageContent contentItem in message.Content)
+            {
+                if (!string.IsNullOrEmpty(contentItem.Text))
+                {
+                    Console.WriteLine($"{contentItem.Text}");
+
+                    if (contentItem.TextAnnotations.Count > 0)
+                    {
+                        Console.WriteLine();
+                    }
+
+                    // Include annotations, if any.
+                    foreach (TextAnnotation annotation in contentItem.TextAnnotations)
+                    {
+                        if (!string.IsNullOrEmpty(annotation.InputFileId))
+                        {
+                            Console.WriteLine($"* File citation, file ID: {annotation.InputFileId}");
+                        }
+                        if (!string.IsNullOrEmpty(annotation.OutputFileId))
+                        {
+                            Console.WriteLine($"* File output, new file ID: {annotation.OutputFileId}");
+                        }
+                    }
+                }
+                if (!string.IsNullOrEmpty(contentItem.ImageFileId))
+                {
+                    OpenAIFile imageInfo = fileClient.GetFile(contentItem.ImageFileId);
+                    BinaryData imageBytes = fileClient.DownloadFile(contentItem.ImageFileId);
+                    using FileStream stream = File.OpenWrite($"{imageInfo.Filename}.png");
+                    imageBytes.ToStream().CopyTo(stream);
+
+                    Console.WriteLine($"<image: {imageInfo.Filename}.png>");
+                }
+            }
+            Console.WriteLine();
+
+        }
+
+        //它会产生这样的结果
+        var output =
+        """
+            [USER]: How well did product 113045 sell in February? Graph its trend over time.
+            
+
+            [ASSISTANT]: Product 113045 sold 22 units in February【4:0†monthly_sales.json】.
+
+            Now, I will generate a graph to show its sales trend over time.
+
+            * File citation, file ID: file-hGOiwGNftMgOsjbynBpMCPFn
+
+            [ASSISTANT]: <image: 015d8e43-17fe-47de-af40-280f25452280.png>
+            The sales trend for Product 113045 over the past three months shows that:
+
+            - In January, 12 units were sold.
+            - In February, 22 units were sold, indicating significant growth.
+            - In March, sales dropped slightly to 16 units.
+
+            The graph above visualizes this trend, showing a peak in sales during February.
+        """;
+
+        #pragma warning restore OPENAI001
+    }
     #endregion
 
     #region 如何将助手与流媒体和视觉结合使用

OllamaStudy.UseHttpClientTest/OllamaApiTest.cs

@@ -350,10 +350,10 @@ public class OllamaApiTest
         var requetData = new
         {
             model = defaultOllamaOption.Model,
-            prompt = """Why is the sky blue?""",
+            prompt = """列出世界四大洋""",
             stream = false,
             think = false,
-            options = new { seed = 123 },
+            options = new { seed = 123, temperature = 0 },
         };
 
         //第一次请求
@@ -595,12 +595,12 @@ public class OllamaApiTest
             model = defaultOllamaOption.Model,
             messages = new[]
             {
-            new
-            {
-                role = "user",
-                content = "你好",
-            }
-        },
+                new
+                {
+                    role = "user",
+                    content = "你好",
+                }
+            },
             think = false,
             stream = false,
             options = new { seed = 123, temperature = 0 },

OllamaStudy.UseOllamaSharp/OllamaApiTest.cs

@@ -269,13 +269,14 @@ namespace OllamaStudy.UseOllamaSharp
             //第一次请求
             var generateRequest1 = new GenerateRequest()
             {
-                Prompt = """天空为什么是蓝色的? """,
+                Prompt = """中华人民共和国的首都是不是北京？回答是或否""",
                 Stream = false,
                 Options = new RequestOptions()
                 {
                     Seed = 999999999,
                     Temperature = 0,
-                }
+                },
+                
             };
 
             //处理响应
@@ -287,7 +288,7 @@ namespace OllamaStudy.UseOllamaSharp
             //第二次请求
             var generateRequest2 = new GenerateRequest()
             {
-                Prompt = """天空为什么是蓝色的? """,
+                Prompt = """中华人民共和国的首都是不是北京？回答是或否""",
                 Stream = false,
                 Options = new RequestOptions()
                 {