Nomad changes

docs/snippets/csharp/advanced/chunking_rag.md

@@ -0,0 +1,85 @@
+```csharp title="C#"
+using Kreuzberg;
+using System.Collections.Generic;
+using System.Linq;
+
+class RagPipelineExample
+{
+    static async Task Main()
+    {
+        var config = new ExtractionConfig
+        {
+            Chunking = new ChunkingConfig
+            {
+                MaxChars = 500,
+                MaxOverlap = 50,
+                Embedding = new EmbeddingConfig
+                {
+                    Model = EmbeddingModelType.Preset("all-mpnet-base-v2"),
+                    Normalize = true,
+                    BatchSize = 16
+                }
+            }
+        };
+
+        try
+        {
+            var result = await KreuzbergLib.ExtractFileAsync(
+                "research_paper.pdf",
+                config
+            ).ConfigureAwait(false);
+
+            var vectorStore = await BuildVectorStoreAsync(result.Chunks)
+                .ConfigureAwait(false);
+
+            var query = "machine learning optimization";
+            var relevantChunks = await SearchAsync(vectorStore, query)
+                .ConfigureAwait(false);
+
+            Console.WriteLine($"Found {relevantChunks.Count} relevant chunks");
+            foreach (var chunk in relevantChunks.Take(3))
+            {
+                Console.WriteLine($"Content: {chunk.Content[..80]}...");
+                Console.WriteLine($"Similarity: {chunk.Similarity:F3}\n");
+            }
+        }
+        catch (KreuzbergException ex)
+        {
+            Console.WriteLine($"Error: {ex.Message}");
+        }
+    }
+
+    static async Task<List<VectorEntry>> BuildVectorStoreAsync(
+        IEnumerable<Chunk> chunks)
+    {
+        return await Task.Run(() =>
+        {
+            return chunks.Select(c => new VectorEntry
+            {
+                Content = c.Content,
+                Embedding = c.Embedding?.ToArray() ?? Array.Empty<float>(),
+                Similarity = 0f
+            }).ToList();
+        }).ConfigureAwait(false);
+    }
+
+    static async Task<List<VectorEntry>> SearchAsync(
+        List<VectorEntry> store,
+        string query)
+    {
+        return await Task.Run(() =>
+        {
+            return store
+                .OrderByDescending(e => e.Similarity)
+                .ToList();
+        }).ConfigureAwait(false);
+    }
+
+    class VectorEntry
+    {
+        public string Content { get; set; } = string.Empty;
+        public float[] Embedding { get; set; } = Array.Empty<float>();
+        public float Similarity { get; set; }
+    }
+}
+```