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added Azure Document Intelligence example to semantic search PDF file
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‎samples/azure/document-intelligence/b59-azure-doc-intelligence/Program.cs

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using Azure;
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using Azure.AI.DocumentIntelligence;
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using System;
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using System.Text;
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using System.IO;
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using System.Threading.Tasks;
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using Build5Nines.SharpVector;
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// This sample demonstrates how to use the Document Intelligence client library to analyze a document using the prebuilt-read model.
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string endpoint = "https://<resource-name>.cognitiveservices.azure.com/";
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string apiKey = "<your-key>";
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string filePath = "document.pdf"; // Can be .pdf, .docx, .jpg, etc.
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// Create timers to measure how long it takes to run the code
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var overallTimer = new System.Diagnostics.Stopwatch();
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var stepTimer = new System.Diagnostics.Stopwatch();
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overallTimer.Start();
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// Create a DocumentIntelligenceClient
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var credential = new AzureKeyCredential(apiKey);
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var client = new DocumentIntelligenceClient(new Uri(endpoint), credential);
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var vdb = new BasicMemoryVectorDatabase();
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// Read the file into a BinaryData object
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Console.WriteLine("Reading file...");
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stepTimer.Start();
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using var stream = File.OpenRead(filePath);
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byte[] buffer = new byte[stream.Length];
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await stream.ReadAsync(buffer, 0, buffer.Length);
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var binaryData = BinaryData.FromBytes(buffer);
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stepTimer.Stop();
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Console.WriteLine($"File loaded into memory: {stepTimer.ElapsedMilliseconds} ms");
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Console.WriteLine("Analyzing document with Azure Document Intelligence...");
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stepTimer.Restart();
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// Analyze the document using the prebuilt-read model
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var operation = await client.AnalyzeDocumentAsync(
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WaitUntil.Completed,
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"prebuilt-read",
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binaryData);
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var docResult = operation.Value;
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stepTimer.Stop();
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Console.WriteLine($"Document analysis completed: {stepTimer.ElapsedMilliseconds} ms");
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stepTimer.Restart();
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Console.WriteLine("Loading SharpVector database...");
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foreach (var page in docResult.Pages)
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{
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var sb = new StringBuilder();
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foreach (var line in page.Lines)
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{
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sb.AppendLine(line.Content);
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}
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// Add the text to the vector database
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// Let's use the Page Number as the metadata
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// Note: In a real-world scenario, you might want to use more meaningful metadata
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var textMetadata = page.PageNumber.ToString();
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vdb.AddText(sb.ToString(), textMetadata);
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}
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stepTimer.Stop();
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Console.WriteLine($"SharpVector database loaded: {stepTimer.ElapsedMilliseconds} ms");
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// Console.WriteLine("");
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// Console.WriteLine("Loading PDF File into vector database...");
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// stepTimer.Restart();
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// // read pdf file with PdfPig locally
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// var vdb2 = new BasicMemoryVectorDatabase();
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// using (var pdfDocument = UglyToad.PdfPig.PdfDocument.Open(filePath))
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// {
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// foreach (var page in pdfDocument.GetPages())
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// {
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// // Add the text to the vector database
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// // Let's use the Page Number as the metadata
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// // Note: In a real-world scenario, you might want to use more meaningful metadata
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// var metadata = page.Number.ToString();
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// vdb.AddText(page.Text, metadata);
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// }
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// }
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// stepTimer.Stop();
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// Console.WriteLine($"Vector database loaded: {stepTimer.ElapsedMilliseconds} ms");
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Console.WriteLine("");
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Console.WriteLine("Searching in SharpVector database for \"Azure ML\" with similarity score > 0.5...");
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stepTimer.Restart();
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var query = "Azure ML";
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var semanticResults = vdb.Search(
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query,
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threshold: 0.5f // Set a threshold for the similarity score to only match results above this value
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);
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stepTimer.Stop();
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Console.WriteLine($"Search completed: {stepTimer.ElapsedMilliseconds} ms");
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Console.WriteLine("Top Matching Results:");
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foreach (var result in semanticResults.Texts)
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{
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//var text = result.Text;
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var metadata = result.Metadata;
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var similarity = result.VectorComparison;
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Console.WriteLine($" - Page: {metadata} - Similarity: {similarity}");
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}
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Console.WriteLine("");
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Console.WriteLine("Searching in SharpVector database for \"Why use a Cloud Adoption Framework strategy\", top 3 results...");
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stepTimer.Restart();
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query = "Why use a Cloud Adoption Framework strategy";
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semanticResults = vdb.Search(
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query,
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pageCount: 3 // Set the number of top results to return
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);
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stepTimer.Stop();
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Console.WriteLine($"Search completed: {stepTimer.ElapsedMilliseconds} ms");
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Console.WriteLine("Top Matching Results:");
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foreach (var result in semanticResults.Texts)
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{
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//var text = result.Text;
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var metadata = result.Metadata;
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var similarity = result.VectorComparison;
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Console.WriteLine($" - Page: {metadata} - Similarity: {similarity}");
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}
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overallTimer.Stop();
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Console.WriteLine("");
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Console.WriteLine($"Overall processing time: {overallTimer.ElapsedMilliseconds} ms");

‎samples/azure/document-intelligence/b59-azure-doc-intelligence/b59-azure-doc-intelligence.csproj

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFramework>net9.0</TargetFramework>
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<RootNamespace>b59_azure_doc_intelligence</RootNamespace>
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<ImplicitUsings>enable</ImplicitUsings>
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<Nullable>enable</Nullable>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.DocumentIntelligence" Version="1.0.0" />
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<PackageReference Include="Build5nines.sharpvector" Version="2.1.1" />
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<PackageReference Include="PdfPig" Version="0.1.10" />
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</ItemGroup>
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</Project>

‎samples/azure/document-intelligence/b59-azure-doc-intelligence/document.pdf

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