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Monday, 15 December 2025
Välkommen till del 9! I tidigare delar har vi byggt ett robust RAG-system som behandlar nedmarkerade blogginlägg och gör dem sökbara genom semantiska inbäddningar. Nu är det dags att utöka vår kapacitet med Dockning - ett kraftfullt dokumenthanteringsbibliotek som kan inta PDF-filer, DOCX och andra format, vilket gör vår Advokat GPT verkligt heltäckande.
OBS: Detta är en del av mina experiment med AI (assisterad skrivande) + min egen redigering. Samma röst, samma pragmatism; bara snabbare fingrar.
Inte för att jag behöver detta för bloggen (det är allt markdown), men för att slutföra jag tänkte att jag skulle visa hur man enkelt lägga till dokument intag kapacitet till din RAG rörledning. Detta är särskilt användbart om du bygger ett system som behöver för att behandla juridiska dokument, kontrakt, eller andra affärsdokument.
Moderna rättsliga förfaranden handlar om en mängd olika dokumentformat bortom bara text. Advokater måste hänvisa:
Med Docking kan vår advokat GPT bearbeta dessa format och göra dem sökbara, skapa en verkligt omfattande kunskapsbas som speglar hur moderna advokatbyråer använder AI.
Dockning är en verktygslåda för dokumentbehandling med öppen källkod från IBM som
Docking Serve är det enklaste sättet att köra Docking som en tjänst. Låt oss ställa in det:
# Using the official container image from Quay.io
docker run -p 5001:5001 quay.io/docling-project/docling-serve
# Or with the UI enabled for testing
docker run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=1 quay.io/docling-project/docling-serve
Tillgängliga containeravbildningar:
på bild och beskrivning på storlek på bilden
|-------|-------------|------|
| quay.io/docling-project/docling-serve Basavbildning (PyPI-paket) på ~8.7GB (amd64)
| quay.io/docling-project/docling-serve-cpu till CPU-enbart variant på ~4.4GB och
| quay.io/docling-project/docling-serve-cu126 CUDA 12.6 för GPU på ca 10 GB
| quay.io/docling-project/docling-serve-cu128 på CUDA 12,8 för GPU på ~11,4GB och
Slutpunkter:
http://localhost:5001http://localhost:5001/docshttp://localhost:5001/ui (om aktiverad)För produktion, lägg till Docking till din befintliga docker-compose.yml:
services:
docling:
image: quay.io/docling-project/docling-serve:latest
ports:
- "5001:5001"
environment:
- DOCLING_SERVE_ENABLE_UI=0
- DOCLING_SERVE_MAX_WORKERS=4
volumes:
- docling_cache:/root/.cache
restart: unless-stopped
volumes:
docling_cache:
Innan du integrerar med C#, låt oss testa API:
# Convert a PDF from URL
curl -X 'POST' \
'http://localhost:5001/v1/convert/source' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}],
"options": {
"to_formats": ["md"]
}
}'
# Convert a local file (upload)
curl -X 'POST' \
'http://localhost:5001/v1/convert/file' \
-H 'accept: application/json' \
-F '[email protected]'
Eftersom Docking är en Python-tjänst integrerar vi oss via HTTP. Låt oss bygga en robust C#-klient.
using System.Text.Json.Serialization;
namespace Mostlylucid.BlogLLM.Core.Models
{
/// <summary>
/// Request to convert documents from URLs or base64 content
/// </summary>
public class DoclingConvertRequest
{
[JsonPropertyName("sources")]
public List<DoclingSource> Sources { get; set; } = new();
[JsonPropertyName("options")]
public DoclingOptions? Options { get; set; }
}
public class DoclingSource
{
[JsonPropertyName("kind")]
public string Kind { get; set; } = "http"; // "http", "base64", "file"
[JsonPropertyName("url")]
public string? Url { get; set; }
[JsonPropertyName("base64")]
public string? Base64Content { get; set; }
[JsonPropertyName("filename")]
public string? Filename { get; set; }
}
public class DoclingOptions
{
[JsonPropertyName("to_formats")]
public List<string> ToFormats { get; set; } = new() { "md" }; // "md", "json", "text"
[JsonPropertyName("ocr")]
public bool Ocr { get; set; } = true;
[JsonPropertyName("table_mode")]
public string TableMode { get; set; } = "accurate"; // "fast", "accurate"
}
/// <summary>
/// Response from Docling conversion
/// </summary>
public class DoclingConvertResponse
{
[JsonPropertyName("document")]
public DoclingDocument? Document { get; set; }
[JsonPropertyName("status")]
public string Status { get; set; } = string.Empty;
[JsonPropertyName("errors")]
public List<string>? Errors { get; set; }
}
public class DoclingDocument
{
[JsonPropertyName("md_content")]
public string? MarkdownContent { get; set; }
[JsonPropertyName("json_content")]
public object? JsonContent { get; set; }
[JsonPropertyName("text_content")]
public string? TextContent { get; set; }
[JsonPropertyName("metadata")]
public DoclingMetadata? Metadata { get; set; }
}
public class DoclingMetadata
{
[JsonPropertyName("filename")]
public string? Filename { get; set; }
[JsonPropertyName("page_count")]
public int? PageCount { get; set; }
[JsonPropertyName("file_type")]
public string? FileType { get; set; }
}
/// <summary>
/// Our internal document model
/// </summary>
public class ProcessedDocument
{
public string DocumentId { get; set; } = Guid.NewGuid().ToString();
public string FileName { get; set; } = string.Empty;
public string OriginalFormat { get; set; } = string.Empty;
public string MarkdownContent { get; set; } = string.Empty;
public string? TextContent { get; set; }
public DateTime ProcessedDate { get; set; } = DateTime.UtcNow;
public string[] Categories { get; set; } = Array.Empty<string>();
public int? PageCount { get; set; }
public string ContentHash { get; set; } = string.Empty;
}
}
using Microsoft.Extensions.Logging;
using Microsoft.Extensions.Options;
using Mostlylucid.BlogLLM.Core.Models;
using System.Net.Http.Json;
using System.Security.Cryptography;
using System.Text;
using System.Text.Json;
namespace Mostlylucid.BlogLLM.Core.Services
{
public class DoclingClientOptions
{
public string BaseUrl { get; set; } = "http://localhost:5001";
public int TimeoutSeconds { get; set; } = 300; // 5 minutes for large documents
public bool EnableOcr { get; set; } = true;
public string TableMode { get; set; } = "accurate";
}
public class DoclingClient : IDisposable
{
private readonly HttpClient _httpClient;
private readonly ILogger<DoclingClient> _logger;
private readonly DoclingClientOptions _options;
public DoclingClient(
HttpClient httpClient,
ILogger<DoclingClient> logger,
IOptions<DoclingClientOptions> options)
{
_httpClient = httpClient;
_logger = logger;
_options = options.Value;
_httpClient.BaseAddress = new Uri(_options.BaseUrl);
_httpClient.Timeout = TimeSpan.FromSeconds(_options.TimeoutSeconds);
}
/// <summary>
/// Convert a document from a URL
/// </summary>
public async Task<ProcessedDocument?> ConvertFromUrlAsync(
string url,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
_logger.LogInformation("Converting document from URL: {Url}", url);
var request = new DoclingConvertRequest
{
Sources = new List<DoclingSource>
{
new() { Kind = "http", Url = url }
},
Options = new DoclingOptions
{
ToFormats = new List<string> { "md", "text" },
Ocr = _options.EnableOcr,
TableMode = _options.TableMode
}
};
return await SendConversionRequestAsync(request, categories, cancellationToken);
}
/// <summary>
/// Convert a local file
/// </summary>
public async Task<ProcessedDocument?> ConvertFileAsync(
string filePath,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
if (!File.Exists(filePath))
{
_logger.LogError("File not found: {FilePath}", filePath);
return null;
}
_logger.LogInformation("Converting local file: {FilePath}", filePath);
// Read file and convert to base64
var fileBytes = await File.ReadAllBytesAsync(filePath, cancellationToken);
var base64Content = Convert.ToBase64String(fileBytes);
var fileName = Path.GetFileName(filePath);
var request = new DoclingConvertRequest
{
Sources = new List<DoclingSource>
{
new()
{
Kind = "base64",
Base64Content = base64Content,
Filename = fileName
}
},
Options = new DoclingOptions
{
ToFormats = new List<string> { "md", "text" },
Ocr = _options.EnableOcr,
TableMode = _options.TableMode
}
};
return await SendConversionRequestAsync(request, categories, cancellationToken);
}
/// <summary>
/// Convert a file using multipart form upload (more efficient for large files)
/// </summary>
public async Task<ProcessedDocument?> ConvertFileUploadAsync(
string filePath,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
if (!File.Exists(filePath))
{
_logger.LogError("File not found: {FilePath}", filePath);
return null;
}
_logger.LogInformation("Uploading and converting file: {FilePath}", filePath);
try
{
using var fileStream = File.OpenRead(filePath);
using var content = new MultipartFormDataContent();
using var streamContent = new StreamContent(fileStream);
var fileName = Path.GetFileName(filePath);
content.Add(streamContent, "files", fileName);
var response = await _httpClient.PostAsync(
"/v1/convert/file",
content,
cancellationToken);
if (!response.IsSuccessStatusCode)
{
var errorContent = await response.Content.ReadAsStringAsync(cancellationToken);
_logger.LogError("Docling conversion failed: {StatusCode} - {Error}",
response.StatusCode, errorContent);
return null;
}
var result = await response.Content.ReadFromJsonAsync<DoclingConvertResponse>(
cancellationToken: cancellationToken);
return MapToProcessedDocument(result, fileName, categories);
}
catch (Exception ex)
{
_logger.LogError(ex, "Error uploading file to Docling: {FilePath}", filePath);
return null;
}
}
private async Task<ProcessedDocument?> SendConversionRequestAsync(
DoclingConvertRequest request,
string[]? categories,
CancellationToken cancellationToken)
{
try
{
var response = await _httpClient.PostAsJsonAsync(
"/v1/convert/source",
request,
cancellationToken);
if (!response.IsSuccessStatusCode)
{
var errorContent = await response.Content.ReadAsStringAsync(cancellationToken);
_logger.LogError("Docling conversion failed: {StatusCode} - {Error}",
response.StatusCode, errorContent);
return null;
}
var result = await response.Content.ReadFromJsonAsync<DoclingConvertResponse>(
cancellationToken: cancellationToken);
var filename = request.Sources.FirstOrDefault()?.Filename
?? request.Sources.FirstOrDefault()?.Url
?? "unknown";
return MapToProcessedDocument(result, filename, categories);
}
catch (HttpRequestException ex)
{
_logger.LogError(ex, "HTTP error calling Docling API");
return null;
}
catch (TaskCanceledException ex)
{
_logger.LogError(ex, "Docling conversion timed out");
return null;
}
catch (Exception ex)
{
_logger.LogError(ex, "Unexpected error calling Docling API");
return null;
}
}
private ProcessedDocument? MapToProcessedDocument(
DoclingConvertResponse? response,
string filename,
string[]? categories)
{
if (response?.Document == null)
{
_logger.LogWarning("Docling returned empty document");
return null;
}
var markdownContent = response.Document.MarkdownContent ?? string.Empty;
return new ProcessedDocument
{
DocumentId = Guid.NewGuid().ToString(),
FileName = Path.GetFileName(filename),
OriginalFormat = Path.GetExtension(filename).TrimStart('.').ToLower(),
MarkdownContent = markdownContent,
TextContent = response.Document.TextContent,
ProcessedDate = DateTime.UtcNow,
Categories = categories ?? Array.Empty<string>(),
PageCount = response.Document.Metadata?.PageCount,
ContentHash = ComputeHash(markdownContent)
};
}
private static string ComputeHash(string content)
{
using var sha256 = SHA256.Create();
var bytes = sha256.ComputeHash(Encoding.UTF8.GetBytes(content));
return Convert.ToBase64String(bytes);
}
public void Dispose()
{
_httpClient?.Dispose();
}
}
}
Låt oss nu integrera Docking med vår befintliga RAG rörledning:
using Microsoft.Extensions.Logging;
using Mostlylucid.BlogLLM.Core.Models;
namespace Mostlylucid.BlogLLM.Core.Services
{
public class DocumentIngestionService
{
private readonly ILogger<DocumentIngestionService> _logger;
private readonly DoclingClient _doclingClient;
private readonly MarkdownParserService _markdownParser;
private readonly ChunkingService _chunker;
private readonly BatchEmbeddingService _embedder;
private readonly QdrantVectorStore _vectorStore;
public DocumentIngestionService(
ILogger<DocumentIngestionService> logger,
DoclingClient doclingClient,
MarkdownParserService markdownParser,
ChunkingService chunker,
BatchEmbeddingService embedder,
QdrantVectorStore vectorStore)
{
_logger = logger;
_doclingClient = doclingClient;
_markdownParser = markdownParser;
_chunker = chunker;
_embedder = embedder;
_vectorStore = vectorStore;
}
/// <summary>
/// Process a document file and add to vector store
/// </summary>
public async Task<bool> ProcessDocumentAsync(
string filePath,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
try
{
_logger.LogInformation("Processing document: {FilePath}", filePath);
// Step 1: Convert with Docling
var document = await _doclingClient.ConvertFileUploadAsync(
filePath, categories, cancellationToken);
if (document == null)
{
_logger.LogError("Failed to convert document: {FilePath}", filePath);
return false;
}
return await ProcessConvertedDocumentAsync(document, cancellationToken);
}
catch (Exception ex)
{
_logger.LogError(ex, "Error processing document {FilePath}", filePath);
return false;
}
}
/// <summary>
/// Process a document from URL and add to vector store
/// </summary>
public async Task<bool> ProcessDocumentFromUrlAsync(
string url,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
try
{
_logger.LogInformation("Processing document from URL: {Url}", url);
// Step 1: Convert with Docling
var document = await _doclingClient.ConvertFromUrlAsync(
url, categories, cancellationToken);
if (document == null)
{
_logger.LogError("Failed to convert document from URL: {Url}", url);
return false;
}
return await ProcessConvertedDocumentAsync(document, cancellationToken);
}
catch (Exception ex)
{
_logger.LogError(ex, "Error processing document from URL {Url}", url);
return false;
}
}
private async Task<bool> ProcessConvertedDocumentAsync(
ProcessedDocument document,
CancellationToken cancellationToken)
{
_logger.LogInformation("Document converted: {FileName} ({PageCount} pages)",
document.FileName, document.PageCount ?? 0);
// Step 2: Parse the markdown content
var post = _markdownParser.ParseMarkdownFromContent(
document.MarkdownContent,
document.FileName);
post.Categories = document.Categories;
// Step 3: Chunk the content
var chunks = _chunker.ChunkBlogPost(post);
_logger.LogInformation("Created {ChunkCount} chunks from {FileName}",
chunks.Count, document.FileName);
if (chunks.Count == 0)
{
_logger.LogWarning("No chunks created for document: {FileName}", document.FileName);
return false;
}
// Step 4: Generate embeddings
var progress = new Progress<int>(processed =>
{
_logger.LogDebug("Embedded {Processed}/{Total} chunks",
processed, chunks.Count);
});
await _embedder.GenerateEmbeddingsAsync(chunks, progress, cancellationToken);
// Step 5: Store in vector database
await _vectorStore.UpsertChunksAsync(chunks);
_logger.LogInformation("Successfully processed document: {FileName} ({ChunkCount} chunks)",
document.FileName, chunks.Count);
return true;
}
/// <summary>
/// Batch process multiple documents
/// </summary>
public async Task<(int success, int failed)> ProcessDocumentBatchAsync(
IEnumerable<string> filePaths,
string[]? categories = null,
CancellationToken cancellationToken = default)
{
int success = 0;
int failed = 0;
foreach (var filePath in filePaths)
{
if (cancellationToken.IsCancellationRequested)
break;
var result = await ProcessDocumentAsync(filePath, categories, cancellationToken);
if (result)
success++;
else
failed++;
}
_logger.LogInformation("Batch processing complete: {Success} succeeded, {Failed} failed",
success, failed);
return (success, failed);
}
}
}
using Microsoft.Extensions.DependencyInjection;
using Mostlylucid.BlogLLM.Core.Services;
public static class ServiceCollectionExtensions
{
public static IServiceCollection AddDoclingServices(
this IServiceCollection services,
Action<DoclingClientOptions>? configureOptions = null)
{
// Configure options
if (configureOptions != null)
{
services.Configure(configureOptions);
}
else
{
services.Configure<DoclingClientOptions>(options =>
{
options.BaseUrl = "http://localhost:5001";
options.TimeoutSeconds = 300;
options.EnableOcr = true;
});
}
// Register HttpClient with configuration
services.AddHttpClient<DoclingClient>((serviceProvider, client) =>
{
var options = serviceProvider
.GetRequiredService<IOptions<DoclingClientOptions>>().Value;
client.BaseAddress = new Uri(options.BaseUrl);
client.Timeout = TimeSpan.FromSeconds(options.TimeoutSeconds);
});
// Register services
services.AddScoped<DocumentIngestionService>();
return services;
}
}
Lägg till i din appsettings.json:
{
"Docling": {
"BaseUrl": "http://localhost:5001",
"TimeoutSeconds": 300,
"EnableOcr": true,
"TableMode": "accurate"
}
}
// PDF Processing
await documentIngestionService.ProcessDocumentAsync(
"C:\\documents\\client_contract.pdf",
new[] { "legal", "contracts", "client-agreements" });
// DOCX Processing
await documentIngestionService.ProcessDocumentAsync(
"C:\\documents\\motion_to_dismiss.docx",
new[] { "legal", "briefs", "motions" });
// URL Processing (great for public documents)
await documentIngestionService.ProcessDocumentFromUrlAsync(
"https://arxiv.org/pdf/2501.17887",
new[] { "research", "ai", "docling" });
// Batch Processing
var files = Directory.GetFiles("C:\\documents\\legal", "*.pdf");
var (success, failed) = await documentIngestionService.ProcessDocumentBatchAsync(
files,
new[] { "legal", "batch-import" });
Console.WriteLine($"Processed {success} files, {failed} failures");
public class DocumentWatcherService : BackgroundService
{
private readonly IServiceProvider _serviceProvider;
private readonly ILogger<DocumentWatcherService> _logger;
private FileSystemWatcher? _watcher;
private readonly string _watchPath;
public DocumentWatcherService(
IServiceProvider serviceProvider,
ILogger<DocumentWatcherService> logger,
IConfiguration configuration)
{
_serviceProvider = serviceProvider;
_logger = logger;
_watchPath = configuration["DocumentWatch:Path"] ?? "C:\\documents\\incoming";
}
protected override Task ExecuteAsync(CancellationToken stoppingToken)
{
if (!Directory.Exists(_watchPath))
{
Directory.CreateDirectory(_watchPath);
}
_watcher = new FileSystemWatcher(_watchPath)
{
NotifyFilter = NotifyFilters.FileName | NotifyFilters.LastWrite,
IncludeSubdirectories = false
};
// Watch for common document types
_watcher.Filters.Add("*.pdf");
_watcher.Filters.Add("*.docx");
_watcher.Filters.Add("*.doc");
_watcher.Filters.Add("*.pptx");
_watcher.Created += OnFileCreated;
_watcher.EnableRaisingEvents = true;
_logger.LogInformation("Watching for documents in: {Path}", _watchPath);
return Task.CompletedTask;
}
private async void OnFileCreated(object sender, FileSystemEventArgs e)
{
_logger.LogInformation("New document detected: {FileName}", e.Name);
// Wait for file to be fully written
await Task.Delay(1000);
using var scope = _serviceProvider.CreateScope();
var ingestionService = scope.ServiceProvider
.GetRequiredService<DocumentIngestionService>();
await ingestionService.ProcessDocumentAsync(e.FullPath);
}
public override void Dispose()
{
_watcher?.Dispose();
base.Dispose();
}
}
på dokumenttyp på typisk storlek på dockning bearbetning på inbäddningstid på plats |--------------|-------------|-------------------|----------------| Enklare PDF (1-5 sidor) 100KB-500KB 2-5 sekunder 0.5-1 sekund En komplex PDF (20+ sidor) 1-5MB 10-30 sekunder 2-5 sekunder Skannad PDF med OCR 1-10MB 30-120 sekunder 2-5 sekunder DOCX-dokument 50KB-500KB 1-3 sekunder 0.3-0.8 sekunder PPTX-presentation 1-20MB 5-30 sekunder 1-3 sekunder
docling-serve-cu126 eller docling-serve-cu128)fast Tabellläge när bordsnoggrannheten inte är kritiskVi har framgångsrikt integrerat Docking i vårt Lawyer GPT-system, vilket möjliggör:
Detta utökar vår kunskapsbas utöver blogginlägg till att omfatta juridiska dokument, kontrakt, forskningspapper och annat viktigt material.
© 2026 Scott Galloway — Unlicense — All content and source code on this site is free to use, copy, modify, and sell.