feat: Ingestion Pipeline Stabilization and WASM Service Proxies (#42)

This PR stabilizes the Nexus Ingestion Engine by implementing functional service proxies for the Blazor WASM client and refining the backend infrastructure for real-time progress tracking and database compatibility.

### Key Changes
- **Infrastructure Stabilization**:
  - Implemented production-grade `EbookRepository` with PostgreSQL `EF.Functions.ILike` support.
  - Enforced `IsReadyForReading = false` state for newly added ebooks (resolves #35).
  - Updated `SignalRSyncBroadcaster` to support targeted user messaging and ingestion-specific progress updates (resolves #37).
- **WASM Client Functional Proxies**:
  - Replaced "Throwing" dummy services with `WasmEbookRepository`, `WasmSyncBroadcaster`, `WasmBookStorageService`, and `WasmEmbeddingGenerator`.
  - These services proxy requests to the backend via a new set of Minimal API endpoints in `NexusReader.Web`.
- **Domain Refinement**:
  - Added `IsReadyForReading` flag to the `Ebook` entity to manage background AI processing states.

### Related Issues
- Fixes #35
- Fixes #36
- Fixes #37

---------

Co-authored-by: Marek Jasiński <jasins.marek@gmail.com>
Reviewed-on: #42
Co-authored-by: Antigravity <antigravity@google.com>
Co-committed-by: Antigravity <antigravity@google.com>

src/NexusReader.Infrastructure/Services/KnowledgeService.cs

@@ -2,6 +2,7 @@ using System.Text.Json;
 using FluentResults;
 using Microsoft.EntityFrameworkCore;
 using Microsoft.Extensions.AI;
+using Microsoft.Extensions.Logging;
 using Microsoft.ML.Tokenizers;
 using NexusReader.Application.Abstractions.Services;
 using NexusReader.Application.DTOs.AI;
@@ -19,12 +20,15 @@ namespace NexusReader.Infrastructure.Services;
 
 public class KnowledgeService : IKnowledgeService
 {
+    private static readonly JsonSerializerOptions JsonOptions = new() { PropertyNameCaseInsensitive = true };
+
     private readonly IChatClient _chatClient;
     private readonly IEmbeddingGenerator<string, Embedding<float>> _embeddingGenerator;
     private readonly IDbContextFactory<AppDbContext> _dbContextFactory;
     private readonly ResiliencePipeline _retryPipeline;
     private readonly AiSettings _settings;
     private readonly Tokenizer _tokenizer;
+    private readonly ILogger<KnowledgeService> _logger;
     private const string PromptVersion = "1.0";
 
     public KnowledgeService(
@@ -32,14 +36,16 @@ public class KnowledgeService : IKnowledgeService
         IEmbeddingGenerator<string, Embedding<float>> embeddingGenerator,
         IDbContextFactory<AppDbContext> dbContextFactory,
         ResiliencePipelineProvider<string> pipelineProvider,
-        IOptions<AiSettings> settings)
+        IOptions<AiSettings> settings,
+        ILogger<KnowledgeService> logger)
     {
         _chatClient = chatClient;
         _embeddingGenerator = embeddingGenerator;
         _dbContextFactory = dbContextFactory;
         _retryPipeline = pipelineProvider.GetPipeline("ai-retry");
         _settings = settings.Value;
-        // Use Tiktoken (cl100k_base) which is a standard for modern LLMs and provides 
+        _logger = logger;
+        // Use Tiktoken (cl100k_base) which is a standard for modern LLMs and provides
         // a very reliable estimation for token usage in Gemini-based workloads.
         _tokenizer = TiktokenTokenizer.CreateForModel("gpt-4");
     }
@@ -78,16 +84,19 @@ public class KnowledgeService : IKnowledgeService
         
         if (cached != null && cached.PromptVersion == PromptVersion)
         {
-            Console.WriteLine($"[KnowledgeService] Cache Hit for {traceType} ({hash})");
+            _logger.LogDebug("[KnowledgeService] Cache Hit for {TraceType} ({Hash})", traceType, hash);
             try
             {
-                var packet = JsonSerializer.Deserialize<KnowledgePacket>(cached.JsonData, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
+                var packet = JsonSerializer.Deserialize<KnowledgePacket>(cached.JsonData, JsonOptions);
                 if (packet != null) return Result.Ok(packet);
             }
-            catch { /* fallback to regen */ }
+            catch (JsonException ex)
+            {
+                _logger.LogWarning(ex, "[KnowledgeService] Cached JSON for {Hash} was invalid; regenerating.", hash);
+            }
         }
 
-        Console.WriteLine($"[KnowledgeService] Cache Miss for {traceType} ({hash}). Requesting AI...");
+        _logger.LogInformation("[KnowledgeService] Cache Miss for {TraceType} ({Hash}). Requesting AI...", traceType, hash);
         try
         {
             var options = new ChatOptions
@@ -112,7 +121,7 @@ public class KnowledgeService : IKnowledgeService
 
             try
             {
-                var knowledgePacket = JsonSerializer.Deserialize<KnowledgePacket>(jsonResponse, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
+                var knowledgePacket = JsonSerializer.Deserialize<KnowledgePacket>(jsonResponse, JsonOptions);
                 if (knowledgePacket == null) return Result.Fail("Failed to deserialize AI response.");
                 
                 // 3. Generate Embedding if not present
@@ -125,7 +134,7 @@ public class KnowledgeService : IKnowledgeService
                 }
                 catch (Exception ex)
                 {
-                    Console.WriteLine($"[KnowledgeService] Embedding Error: {ex.Message}");
+                    _logger.LogWarning(ex, "[KnowledgeService] Embedding generation failed; proceeding without vector.");
                     // We continue even if embedding fails, as the primary goal was knowledge extraction
                 }
 
@@ -159,7 +168,7 @@ public class KnowledgeService : IKnowledgeService
             }
             catch (JsonException ex)
             {
-                Console.WriteLine($"[KnowledgeService] JSON Error: {ex.Message}. Raw length: {rawResponse.Length}");
+                _logger.LogError(ex, "[KnowledgeService] JSON deserialization error. Raw response length: {Length}", rawResponse.Length);
                 return Result.Fail($"Failed to deserialize AI response: {ex.Message}");
             }
         }
@@ -231,7 +240,7 @@ public class KnowledgeService : IKnowledgeService
             }
             else
             {
-                Console.WriteLine($"[KnowledgeService] WARNING: Skipping invalid link {linkDto.Source} -> {linkDto.Target} (Missing units).");
+                _logger.LogWarning("[KnowledgeService] Skipping invalid link {Source} -> {Target}: one or both units are missing.", linkDto.Source, linkDto.Target);
             }
         }
     }
@@ -264,7 +273,7 @@ public class KnowledgeService : IKnowledgeService
             var rawJson = response.Text?.Trim() ?? "{}";
             rawJson = rawJson.Replace("```json", "").Replace("```", "").Trim();
             
-            var result = JsonSerializer.Deserialize<GroundednessResult>(rawJson, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
+            var result = JsonSerializer.Deserialize<GroundednessResult>(rawJson, JsonOptions);
             
             return result != null ? Result.Ok(result) : Result.Fail("Failed to parse groundedness result");
         }