refactor(services): split services into separate folders and update namespaces

Services/AI/AiService.cs

@@ -0,0 +1,433 @@
+using System.Net.Http.Headers;
+using System.Text.Json.Serialization;
+using Foxel.Services.Configuration;
+using Foxel.Utils;
+
+namespace Foxel.Services.AI;
+
+public class AiService : IAiService
+{
+    private readonly HttpClient _httpClient;
+    private readonly IConfigService _configService;
+
+    public AiService(HttpClient httpClient, IConfigService configService)
+    {
+        _httpClient = httpClient;
+        _configService = configService;
+        string apiKey = _configService["AI:ApiKey"];
+        string baseUrl = _configService["AI:ApiEndpoint"];
+        _httpClient.BaseAddress = new Uri(baseUrl);
+        _httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);
+    }
+
+    public async Task<(string title, string description)> AnalyzeImageAsync(string base64Image)
+    {
+        try
+        {
+            string model = _configService["AI:Model"];
+            var imageUrl = new ImageUrl
+            {
+                Url = $"data:image/jpeg;base64,{base64Image}"
+            };
+
+            var imageContent = new ImageUrlContent
+            {
+                Type = "image_url",
+                ImageUrl = imageUrl
+            };
+
+            var textContent = new TextContent
+            {
+                Type = "text",
+                Text =
+                    "请详细分析这张图片，并提供全面的描述，以便用于向量嵌入和基于文本的图像搜索。描述需要包含：主体对象、场景环境、色彩特点、构图布局、风格特征、情绪氛围、细节特征等关键元素。请提供一个简短有力的标题，然后提供详细描述。\n\n请以JSON格式返回，格式如下：\n{\"title\": \"简短概括图片的核心内容\", \"description\": \"全面详细的描述，包含上述所有元素，使用丰富精确的词汇，避免笼统表达\"}\n\n请确保返回有效的JSON格式。"
+            };
+
+            var message = new ChatMessage
+            {
+                Role = "user",
+                Content = new MessageContent[] { imageContent, textContent }
+            };
+
+            var requestContent = new ChatCompletionRequest
+            {
+                Model = model,
+                Messages = [message],
+                Stream = false,
+                MaxTokens = 800,
+                Temperature = 0.5,
+                TopP = 0.8,
+                TopK = 50
+            };
+
+            var response = await _httpClient.PostAsJsonAsync("/v1/chat/completions", requestContent);
+            response.EnsureSuccessStatusCode();
+
+            var responseContent = await response.Content.ReadFromJsonAsync<AiResponse>();
+            if (responseContent?.Choices == null || responseContent.Choices.Length == 0)
+            {
+                return ("未能获取标题", "未能获取描述");
+            }
+
+            var aiMessage = responseContent.Choices[0].Message.Content;
+            return AiHelper.ExtractTitleAndDescription(aiMessage);
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"AI分析图片时出错: {ex.Message}");
+            return ("处理失败", $"AI分析过程中发生错误: {ex.Message}");
+        }
+    }
+
+    public async Task<List<string>> MatchTagsAsync(string description, List<string> availableTags)
+    {
+        try
+        {
+            if (availableTags.Count == 0)
+                return new List<string>();
+
+            string model = _configService["AI:Model"]; 
+            var tagsText = string.Join(", ", availableTags);
+            var textContent = new TextContent
+            {
+                Type = "text",
+                Text =
+                    $"以下是一组标签：[{tagsText}]。\n\n请从这些标签中严格选择与下面描述内容高度相关的标签（最多选择5个）。只选择确实匹配的标签，如果找不到完全匹配或高度相关的标签，宁可返回空数组也不要选择不太相关的标签。\n\n描述内容：{description}\n\n请以JSON格式返回，格式如下：\n{{\"tags\": [\"标签1\", \"标签2\", \"标签3\"]}}\n\n请确保返回有效的JSON格式前面不要加```，并且只包含确实匹配的标签名称。"
+            };
+
+            var message = new ChatMessage
+            {
+                Role = "user",
+                Content = new MessageContent[] { textContent }
+            };
+
+            var requestContent = new ChatCompletionRequest
+            {
+                Model = model,
+                Messages = [message],
+                Stream = false,
+                MaxTokens = 200,
+                Temperature = 0.1, // 降低温度使结果更确定性
+                TopP = 0.95,
+                TopK = 50
+            };
+
+            var response = await _httpClient.PostAsJsonAsync("/v1/chat/completions", requestContent);
+            response.EnsureSuccessStatusCode();
+
+            var responseContent = await response.Content.ReadFromJsonAsync<AiResponse>();
+            if (responseContent?.Choices == null || responseContent.Choices.Length == 0)
+            {
+                return new List<string>();
+            }
+
+            var aiMessage = responseContent.Choices[0].Message.Content;
+
+            if (string.IsNullOrEmpty(aiMessage))
+                return new List<string>();
+
+            if (aiMessage.Contains("{") && aiMessage.Contains("}"))
+            {
+                try
+                {
+                    int jsonStartIndex = aiMessage.IndexOf('{');
+                    int jsonEndIndex = aiMessage.LastIndexOf('}') + 1;
+
+                    if (jsonStartIndex >= 0 && jsonEndIndex > jsonStartIndex)
+                    {
+                        string jsonPart = aiMessage[jsonStartIndex..jsonEndIndex];
+                        var options = new System.Text.Json.JsonSerializerOptions
+                        {
+                            PropertyNameCaseInsensitive = true
+                        };
+
+                        var result =
+                            System.Text.Json.JsonSerializer.Deserialize<AiHelper.TagsResult>(jsonPart, options);
+                        if (result is { Tags.Length: > 0 })
+                        {
+                            // 确保返回的标签真的在可用标签列表中
+                            var matchedTags = new List<string>();
+
+                            foreach (var tagName in result.Tags)
+                            {
+                                if (string.IsNullOrWhiteSpace(tagName))
+                                    continue;
+
+                                // 找到大小写完全匹配的标签
+                                var exactMatch = availableTags.FirstOrDefault(t =>
+                                    string.Equals(t, tagName, StringComparison.OrdinalIgnoreCase));
+
+                                if (exactMatch != null)
+                                {
+                                    matchedTags.Add(exactMatch);
+                                }
+                            }
+
+                            return matchedTags.Distinct().ToList();
+                        }
+                    }
+                }
+                catch (System.Text.Json.JsonException)
+                {
+                    // JSON解析失败，返回空列表
+                    return new List<string>();
+                }
+            }
+
+            // 解析失败或没有找到匹配标签，返回空列表
+            return new List<string>();
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"AI匹配标签时出错: {ex.Message}");
+            return new List<string>();
+        }
+    }
+
+    public async Task<List<string>> GenerateTagsFromImageAsync(string base64Image, List<string> availableTags,
+        bool allowNewTags = false)
+    {
+        try
+        {
+
+            string model = _configService["AI:Model"]; 
+
+            var imageUrl = new ImageUrl
+            {
+                Url = $"data:image/jpeg;base64,{base64Image}"
+            };
+
+            var imageContent = new ImageUrlContent
+            {
+                Type = "image_url",
+                ImageUrl = imageUrl
+            };
+
+            string promptText;
+
+            if (allowNewTags)
+            {
+                // 如果允许新标签，则提供现有标签作为参考，但允许生成新标签
+                promptText = availableTags.Count > 0
+                    ? $"可以参考这些现有标签：[{string.Join(", ", availableTags)}]，但也可以生成其他与图片内容相关的新标签。\n\n请为图片生成5个最相关的标签，优先使用已有标签，但如果有更恰当的新标签也可以使用。\n\n请以JSON格式返回，格式如下：\n{{\"tags\": [\"标签1\", \"标签2\", \"标签3\", \"标签4\", \"标签5\"]}}\n\n请确保返回有效的JSON格式。"
+                    : "请为图片生成5个最相关的标签，每个标签应该是简短且描述性的词语或短语。\n\n请以JSON格式返回，格式如下：\n{\"tags\": [\"标签1\", \"标签2\", \"标签3\", \"标签4\", \"标签5\"]}\n\n请确保返回有效的JSON格式。";
+            }
+            else
+            {
+                // 如果不允许新标签，则只能从已有标签中选择
+                if (availableTags.Count == 0)
+                    return new List<string>();
+
+                var tagsText = string.Join(", ", availableTags);
+                promptText =
+                    $"以下是一组标签：[{tagsText}]。\n\n请从这些标签中严格选择与图片内容高度相关的标签（最多选择5个）。只选择确实匹配的标签，如果找不到完全匹配或高度相关的标签，宁可返回空数组也不要选择不太相关的标签。\n\n请以JSON格式返回，格式如下：\n{{\"tags\": [\"标签1\", \"标签2\", \"标签3\"]}}\n\n请确保返回有效的JSON格式，并且只包含上述列表中的标签名称。";
+            }
+
+            var textContent = new TextContent
+            {
+                Type = "text",
+                Text = promptText
+            };
+
+            var message = new ChatMessage
+            {
+                Role = "user",
+                Content = new MessageContent[] { imageContent, textContent }
+            };
+
+            var requestContent = new ChatCompletionRequest
+            {
+                Model = model,
+                Messages = [message],
+                Stream = false,
+                MaxTokens = 200,
+                Temperature = 0.1, // 降低温度使结果更确定性
+                TopP = 0.95,
+                TopK = 50
+            };
+
+            var response = await _httpClient.PostAsJsonAsync("/v1/chat/completions", requestContent);
+            response.EnsureSuccessStatusCode();
+
+            var responseContent = await response.Content.ReadFromJsonAsync<AiResponse>();
+            if (responseContent?.Choices == null || responseContent.Choices.Length == 0)
+            {
+                return new List<string>();
+            }
+
+            var aiMessage = responseContent.Choices[0].Message.Content;
+
+            if (string.IsNullOrEmpty(aiMessage))
+                return new List<string>();
+
+            if (aiMessage.Contains("{") && aiMessage.Contains("}"))
+            {
+                try
+                {
+                    int jsonStartIndex = aiMessage.IndexOf('{');
+                    int jsonEndIndex = aiMessage.LastIndexOf('}') + 1;
+
+                    if (jsonStartIndex >= 0 && jsonEndIndex > jsonStartIndex)
+                    {
+                        string jsonPart = aiMessage[jsonStartIndex..jsonEndIndex];
+                        var options = new System.Text.Json.JsonSerializerOptions
+                        {
+                            PropertyNameCaseInsensitive = true
+                        };
+
+                        var result =
+                            System.Text.Json.JsonSerializer.Deserialize<AiHelper.TagsResult>(jsonPart, options);
+                        if (result is { Tags.Length: > 0 })
+                        {
+                            var matchedTags = new List<string>();
+
+                            foreach (var tagName in result.Tags)
+                            {
+                                if (string.IsNullOrWhiteSpace(tagName))
+                                    continue;
+
+                                // 如果允许新标签，直接添加
+                                if (allowNewTags)
+                                {
+                                    matchedTags.Add(tagName.Trim());
+                                }
+                                else
+                                {
+                                    // 否则只添加已有标签列表中的标签
+                                    var exactMatch = availableTags.FirstOrDefault(t =>
+                                        string.Equals(t, tagName, StringComparison.OrdinalIgnoreCase));
+
+                                    if (exactMatch != null)
+                                    {
+                                        matchedTags.Add(exactMatch);
+                                    }
+                                }
+                            }
+
+                            return matchedTags.Distinct().ToList();
+                        }
+                    }
+                }
+                catch (System.Text.Json.JsonException)
+                {
+                    // JSON解析失败，返回空列表
+                    return new List<string>();
+                }
+            }
+
+            // 解析失败或没有找到匹配标签，返回空列表
+            return new List<string>();
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"AI从图片生成标签时出错: {ex.Message}");
+            return new List<string>();
+        }
+    }
+
+    public async Task<float[]> GetEmbeddingAsync(string text)
+    {
+        try
+        {
+
+            string model = _configService["AI:EmbeddingModel"];
+
+            var requestContent = new
+            {
+                model,
+                input = text,
+                encoding_format = "float"
+            };
+
+            var response = await _httpClient.PostAsJsonAsync("/v1/embeddings", requestContent);
+            response.EnsureSuccessStatusCode();
+
+            var embedResult = await response.Content.ReadFromJsonAsync<EmbeddingResponse>();
+            if (embedResult?.Data == null || embedResult.Data.Length == 0)
+            {
+                Console.WriteLine("嵌入向量API返回空结果");
+                return Array.Empty<float>();
+            }
+
+            return embedResult.Data[0].Embedding;
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"获取嵌入向量时出错: {ex.Message}");
+            return Array.Empty<float>();
+        }
+    }
+
+    // 从EmbeddingService移植的私有记录类
+    private record EmbeddingResponse
+    {
+        [JsonPropertyName("data")] public EmbeddingData[] Data { get; set; } = Array.Empty<EmbeddingData>();
+    }
+
+    private record EmbeddingData
+    {
+        [JsonPropertyName("embedding")] public float[] Embedding { get; set; } = Array.Empty<float>();
+    }
+
+    private class AiResponse
+    {
+        [JsonPropertyName("choices")] public Choice[] Choices { get; set; } = Array.Empty<Choice>();
+    }
+
+    private class Choice
+    {
+        [JsonPropertyName("message")] public Message Message { get; set; } = new Message();
+    }
+
+    private class Message
+    {
+        [JsonPropertyName("content")] public string Content { get; set; } = string.Empty;
+    }
+}
+
+public class ChatCompletionRequest
+{
+    [JsonPropertyName("model")] public string Model { get; set; } = string.Empty;
+
+    [JsonPropertyName("messages")] public ChatMessage[] Messages { get; set; } = Array.Empty<ChatMessage>();
+
+    [JsonPropertyName("stream")] public bool Stream { get; set; }
+
+    [JsonPropertyName("max_tokens")] public int MaxTokens { get; set; }
+
+    [JsonPropertyName("temperature")] public double Temperature { get; set; }
+
+    [JsonPropertyName("top_p")] public double TopP { get; set; }
+
+    [JsonPropertyName("top_k")] public int TopK { get; set; }
+}
+
+public class ChatMessage
+{
+    [JsonPropertyName("role")] public string Role { get; set; } = string.Empty;
+
+    [JsonPropertyName("content")] public MessageContent[] Content { get; set; } = Array.Empty<MessageContent>();
+}
+
+[JsonPolymorphic(TypeDiscriminatorPropertyName = "type")]
+[JsonDerivedType(typeof(TextContent), typeDiscriminator: "text")]
+[JsonDerivedType(typeof(ImageUrlContent), typeDiscriminator: "image_url")]
+public abstract class MessageContent
+{
+    [JsonPropertyName("type")] public string Type { get; set; } = string.Empty;
+}
+
+public class TextContent : MessageContent
+{
+    [JsonPropertyName("text")] public string Text { get; set; } = string.Empty;
+}
+
+public class ImageUrlContent : MessageContent
+{
+    [JsonPropertyName("image_url")] public ImageUrl ImageUrl { get; set; } = new();
+}
+
+public class ImageUrl
+{
+    [JsonPropertyName("url")] public string Url { get; set; } = string.Empty;
+}

Services/AI/IAiService.cs

@@ -0,0 +1,35 @@
+namespace Foxel.Services.AI;
+
+public interface IAiService
+{
+    /// <summary>
+    /// 分析图像并返回标题和描述
+    /// </summary>
+    /// <param name="base64Image">Base64格式的图像数据</param>
+    /// <returns>图像的标题和描述</returns>
+    Task<(string title, string description)> AnalyzeImageAsync(string base64Image);
+    
+    /// <summary>
+    /// 基于描述匹配标签
+    /// </summary>
+    /// <param name="description">图片描述</param>
+    /// <param name="availableTags">可用标签列表</param>
+    /// <returns>匹配的标签名称列表</returns>
+    Task<List<string>> MatchTagsAsync(string description, List<string> availableTags);
+    
+    /// <summary>
+    /// 直接从图像生成标签
+    /// </summary>
+    /// <param name="base64Image">Base64格式的图像数据</param>
+    /// <param name="availableTags">可用标签列表</param>
+    /// <param name="allowNewTags">是否允许生成新标签(不在availableTags中的标签)</param>
+    /// <returns>匹配的标签名称列表</returns>
+    Task<List<string>> GenerateTagsFromImageAsync(string base64Image, List<string> availableTags, bool allowNewTags = false);
+
+    /// <summary>
+    /// 获取文本的嵌入向量
+    /// </summary>
+    /// <param name="text">需要进行嵌入的文本</param>
+    /// <returns>表示文本语义的浮点数组向量</returns>
+    Task<float[]> GetEmbeddingAsync(string text);
+}