Organize workspace: Frontend, Backend, and Tests in one repo

.vscode-server/data/User/History/b03096/XLsh.cs

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+using Seasoned.Backend.DTOs;
+using Mscc.GenerativeAI; // Add this!
+
+namespace Seasoned.Backend.Services;
+
+public class RecipeService : IRecipeService
+{
+    private readonly string _apiKey;
+
+    public RecipeService(IConfiguration config)
+    {
+        // Get the key from your user-secrets
+        _apiKey = config["GeminiApiKey"] ?? throw new ArgumentNullException("API Key missing");
+    }
+
+    public async Task<RecipeResponseDto> ParseRecipeImageAsync(IFormFile image)
+    {
+        // 1. Initialize Gemini
+        var googleAI = new GoogleAI(_apiKey);
+        var model = googleAI.GenerativeModel(Model.Gemini15Flash);
+
+        // 2. Convert the uploaded image to a format Gemini understands
+        using var ms = new MemoryStream();
+        await image.CopyToAsync(ms);
+        var base64Image = Convert.ToBase64String(ms.ToArray());
+
+        // 3. The "Magic" Prompt
+        var prompt = "Extract the recipe from this image. Return ONLY a JSON object with: title (string), description (string), ingredients (array of strings), and instructions (array of strings).";
+        
+        // 4. Call Gemini
+        var response = await model.GenerateContent(new List<Part> {
+            new TextPart { Text = prompt },
+            new InlineDataPart { MimeType = "image/jpeg", Data = base64Image }
+        });
+
+        // 5. Parse the AI's response (simplified for now)
+        var aiText = response.Text;
+        
+        // For now, let's return the AI text in our DTO
+        return new RecipeResponseDto
+        {
+            Title = "AI Decoded Recipe",
+            Description = aiText, // The raw AI response
+            Ingredients = new List<string> { "Check description for details" }
+        };
+    }
+}