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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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<TargetFrameworks>net10.0</TargetFrameworks>
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<Nullable>enable</Nullable>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.Identity" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
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</ItemGroup>
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</Project>
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// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to use File Search Tool with a ChatClientAgent.
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using OpenAI.Assistants;
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using OpenAI.Files;
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string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
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const string AgentInstructions = "You are a helpful assistant that can search through uploaded files to answer questions.";
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// We need the AIProjectClient to upload files and create vector stores.
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
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var projectOpenAIClient = aiProjectClient.GetProjectOpenAIClient();
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var filesClient = projectOpenAIClient.GetProjectFilesClient();
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var vectorStoresClient = projectOpenAIClient.GetProjectVectorStoresClient();
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// 1. Create a temp file with test content and upload it.
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string searchFilePath = Path.Combine(Path.GetTempPath(), Path.GetRandomFileName() + "_lookup.txt");
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File.WriteAllText(
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path: searchFilePath,
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contents: """
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Employee Directory:
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- Alice Johnson, 28 years old, Software Engineer, Engineering Department
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- Bob Smith, 35 years old, Sales Manager, Sales Department
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- Carol Williams, 42 years old, HR Director, Human Resources Department
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- David Brown, 31 years old, Customer Support Lead, Support Department
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"""
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);
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Console.WriteLine($"Uploading file: {searchFilePath}");
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OpenAIFile uploadedFile = filesClient.UploadFile(
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filePath: searchFilePath,
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purpose: FileUploadPurpose.Assistants
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);
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Console.WriteLine($"Uploaded file, file ID: {uploadedFile.Id}");
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// 2. Create a vector store with the uploaded file.
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var vectorStoreResult = await vectorStoresClient.CreateVectorStoreAsync(
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options: new() { FileIds = { uploadedFile.Id }, Name = "EmployeeDirectory_VectorStore" }
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);
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string vectorStoreId = vectorStoreResult.Value.Id;
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Console.WriteLine($"Created vector store, vector store ID: {vectorStoreId}");
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// Create a AIAgent with HostedFileSearchTool.
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AIAgent agent = aiProjectClient.AsAIAgent(deploymentName,
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instructions: AgentInstructions,
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name: "FileSearchAgent-RAPI",
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tools: [new HostedFileSearchTool() { Inputs = [new HostedVectorStoreContent(vectorStoreId)] }]);
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// Run the agent
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Console.WriteLine("\n--- Running File Search Agent ---");
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AgentResponse response = await agent.RunAsync("Who is the youngest employee?");
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Console.WriteLine($"Response: {response}");
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// Getting any file citation annotations generated by the tool
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foreach (AIAnnotation annotation in response.Messages.SelectMany(m => m.Contents).SelectMany(c => c.Annotations ?? []))
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{
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if (annotation.RawRepresentation is TextAnnotationUpdate citationAnnotation)
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{
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Console.WriteLine($$"""
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File Citation:
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File Id: {{citationAnnotation.OutputFileId}}
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Text to Replace: {{citationAnnotation.TextToReplace}}
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""");
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}
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}
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// Cleanup file resources.
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Console.WriteLine("\n--- Cleanup ---");
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await vectorStoresClient.DeleteVectorStoreAsync(vectorStoreId);
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await filesClient.DeleteFileAsync(uploadedFile.Id);
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File.Delete(searchFilePath);
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Console.WriteLine("Cleanup completed successfully.");
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# File Search with the Responses API
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This sample shows how to use the File Search tool with a `ChatClientAgent` using the Responses API directly.
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## What this sample demonstrates
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- Uploading files and creating vector stores via `AIProjectClient`
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- Using `HostedFileSearchTool` with `ChatClientAgent`
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- Handling file citation annotations in agent responses
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- Cleaning up file resources after use
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## Prerequisites
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- .NET 10 SDK or later
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- Microsoft Foundry service endpoint and deployment configured
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- An authenticated Azure identity (for example, sign in with `az login`)
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Set the following environment variables:
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```powershell
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$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
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$env:FOUNDRY_MODEL="gpt-5.4-mini"
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```
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## Run the sample
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```powershell
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dotnet run
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```
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