fix: VLM 参数优化 - temperature 0.7, top_p 0.8, 指令放 system+user

- VisionAsync 新增 Temperature=0.7, TopP=0.8
- system prompt 用专业营养识别指令
- userText 用简短"请看图识别食物"配合图片
- 修复重复 prompt 导致 VLM 误读文本的 bug

backend/src/Health.Infrastructure/AI/ai_clients.cs

@@ -124,6 +124,7 @@ public sealed class VisionClient(HttpClient http, IConfiguration config)
         var request = new ChatCompletionRequest
         {
             Model = _model, Messages = messages, MaxTokens = maxTokens, Stream = false,
+            Temperature = 0.7f, TopP = 0.8f,
         };
 
         var json = JsonSerializer.Serialize(request, _jsonOptions);

backend/src/Health.Infrastructure/AI/open_ai_compatible_client.cs

@@ -164,6 +164,7 @@ public sealed class ChatCompletionRequest
     public bool Stream { get; set; }
     public int MaxTokens { get; set; } = 2048;
     public float Temperature { get; set; } = 0.7f;
+    public float? TopP { get; set; }
     public List<ToolDefinition>? Tools { get; set; }
     public string? ToolChoice { get; set; }
 }

backend/src/Health.WebApi/Endpoints/ai_chat_endpoints.cs

@@ -267,22 +267,17 @@ public static class AiChatEndpoints
 
                 // 压缩图片后转 base64（VLM API 有请求体大小限制）
                 var compressedPath = Path.Combine(uploadsDir, $"compressed_{safeName}");
-                CompressImage(filePath, compressedPath, maxWidth: 2048, quality: 92L);
+                CompressImage(filePath, compressedPath, maxWidth: 1280, quality: 75L);
                 var compressedBytes = await File.ReadAllBytesAsync(compressedPath, ct);
                 var base64 = Convert.ToBase64String(compressedBytes);
                 imageUrls.Add($"data:image/jpeg;base64,{base64}");
             }
 
-            var prompt = """
-                识别图片中所有食物，用中文名称，只返回JSON：
-                {
-                  "foods": [{"name":"食物名","portion":"份量","calories":整数}]
-                }
-                """;
+            var prompt = "精准识别用户提供的食物图片，提取并返回详细信息，包括但不限于食物名称、具体份量及对应热量值。系统应确保识别结果的准确性和清晰度，以便为病人的饮食管理提供可靠数据支持。";
 
             try
             {
-                var response = await visionClient.VisionAsync(prompt, imageUrls, ct: ct);
+                var response = await visionClient.VisionAsync(prompt, imageUrls, userText: "请看图识别食物", ct: ct);
                 var result = response.Choices?.FirstOrDefault()?.Message?.Content ?? "{}";
                 return Results.Ok(new { code = 0, data = result, message = (string?)null });
             }