openai/openai-dotnet
Publicmirrored from https://github.com/openai/openai-dotnetAvailable
examples/Assistants/Example01_RetrievalAugmentedGenerationAsync.cs
149lines · modecode
| 1 | using NUnit.Framework; |
| 2 | using OpenAI.Assistants; |
| 3 | using OpenAI.Files; |
| 4 | using System; |
| 5 | using System.ClientModel; |
| 6 | using System.IO; |
| 7 | using System.Threading; |
| 8 | using System.Threading.Tasks; |
| 9 | |
| 10 | namespace OpenAI.Examples; |
| 11 | |
| 12 | public partial class AssistantExamples |
| 13 | { |
| 14 | [Test] |
| 15 | public async Task Example01_RetrievalAugmentedGenerationAsync() |
| 16 | { |
| 17 | // Assistants is a beta API and subject to change; acknowledge its experimental status by suppressing the matching warning. |
| 18 | #pragma warning disable OPENAI001 |
| 19 | OpenAIClient openAIClient = new(Environment.GetEnvironmentVariable("OPENAI_API_KEY")); |
| 20 | OpenAIFileClient fileClient = openAIClient.GetOpenAIFileClient(); |
| 21 | AssistantClient assistantClient = openAIClient.GetAssistantClient(); |
| 22 | |
| 23 | // First, let's contrive a document we'll use retrieval with and upload it. |
| 24 | using Stream document = BinaryData.FromBytes(""" |
| 25 | { |
| 26 | "description": "This document contains the sale history data for Contoso products.", |
| 27 | "sales": [ |
| 28 | { |
| 29 | "month": "January", |
| 30 | "by_product": { |
| 31 | "113043": 15, |
| 32 | "113045": 12, |
| 33 | "113049": 2 |
| 34 | } |
| 35 | }, |
| 36 | { |
| 37 | "month": "February", |
| 38 | "by_product": { |
| 39 | "113045": 22 |
| 40 | } |
| 41 | }, |
| 42 | { |
| 43 | "month": "March", |
| 44 | "by_product": { |
| 45 | "113045": 16, |
| 46 | "113055": 5 |
| 47 | } |
| 48 | } |
| 49 | ] |
| 50 | } |
| 51 | """u8.ToArray()).ToStream(); |
| 52 | |
| 53 | OpenAIFile salesFile = await fileClient.UploadFileAsync( |
| 54 | document, |
| 55 | "monthly_sales.json", |
| 56 | FileUploadPurpose.Assistants); |
| 57 | |
| 58 | // Now, we'll create a client intended to help with that data |
| 59 | AssistantCreationOptions assistantOptions = new() |
| 60 | { |
| 61 | Name = "Example: Contoso sales RAG", |
| 62 | Instructions = |
| 63 | "You are an assistant that looks up sales data and helps visualize the information based" |
| 64 | + " on user queries. When asked to generate a graph, chart, or other visualization, use" |
| 65 | + " the code interpreter tool to do so.", |
| 66 | Tools = |
| 67 | { |
| 68 | new FileSearchToolDefinition(), |
| 69 | new CodeInterpreterToolDefinition(), |
| 70 | }, |
| 71 | ToolResources = new() |
| 72 | { |
| 73 | FileSearch = new() |
| 74 | { |
| 75 | NewVectorStores = |
| 76 | { |
| 77 | new VectorStoreCreationHelper([salesFile.Id]), |
| 78 | } |
| 79 | } |
| 80 | }, |
| 81 | }; |
| 82 | |
| 83 | Assistant assistant = await assistantClient.CreateAssistantAsync("gpt-4o", assistantOptions); |
| 84 | |
| 85 | // Now we'll create a thread with a user query about the data already associated with the assistant, then run it |
| 86 | ThreadCreationOptions threadOptions = new() |
| 87 | { |
| 88 | InitialMessages = { "How well did product 113045 sell in February? Graph its trend over time." } |
| 89 | }; |
| 90 | |
| 91 | ThreadRun threadRun = await assistantClient.CreateThreadAndRunAsync(assistant.Id, threadOptions); |
| 92 | |
| 93 | // Check back to see when the run is done |
| 94 | do |
| 95 | { |
| 96 | Thread.Sleep(TimeSpan.FromSeconds(1)); |
| 97 | threadRun = assistantClient.GetRun(threadRun.ThreadId, threadRun.Id); |
| 98 | } while (!threadRun.Status.IsTerminal); |
| 99 | |
| 100 | // Finally, we'll print out the full history for the thread that includes the augmented generation |
| 101 | AsyncCollectionResult<ThreadMessage> messages |
| 102 | = assistantClient.GetMessagesAsync(threadRun.ThreadId, new MessageCollectionOptions() { Order = MessageCollectionOrder.Ascending }); |
| 103 | |
| 104 | await foreach (ThreadMessage message in messages) |
| 105 | { |
| 106 | Console.Write($"[{message.Role.ToString().ToUpper()}]: "); |
| 107 | foreach (MessageContent contentItem in message.Content) |
| 108 | { |
| 109 | if (!string.IsNullOrEmpty(contentItem.Text)) |
| 110 | { |
| 111 | Console.WriteLine($"{contentItem.Text}"); |
| 112 | |
| 113 | if (contentItem.TextAnnotations.Count > 0) |
| 114 | { |
| 115 | Console.WriteLine(); |
| 116 | } |
| 117 | |
| 118 | // Include annotations, if any. |
| 119 | foreach (TextAnnotation annotation in contentItem.TextAnnotations) |
| 120 | { |
| 121 | if (!string.IsNullOrEmpty(annotation.InputFileId)) |
| 122 | { |
| 123 | Console.WriteLine($"* File citation, file ID: {annotation.InputFileId}"); |
| 124 | } |
| 125 | if (!string.IsNullOrEmpty(annotation.OutputFileId)) |
| 126 | { |
| 127 | Console.WriteLine($"* File output, new file ID: {annotation.OutputFileId}"); |
| 128 | } |
| 129 | } |
| 130 | } |
| 131 | if (!string.IsNullOrEmpty(contentItem.ImageFileId)) |
| 132 | { |
| 133 | OpenAIFile imageInfo = await fileClient.GetFileAsync(contentItem.ImageFileId); |
| 134 | BinaryData imageBytes = await fileClient.DownloadFileAsync(contentItem.ImageFileId); |
| 135 | using FileStream stream = File.OpenWrite($"{imageInfo.Filename}.png"); |
| 136 | imageBytes.ToStream().CopyTo(stream); |
| 137 | |
| 138 | Console.WriteLine($"<image: {imageInfo.Filename}.png>"); |
| 139 | } |
| 140 | } |
| 141 | Console.WriteLine(); |
| 142 | } |
| 143 | |
| 144 | // Optionally, delete any persistent resources you no longer need. |
| 145 | _ = await assistantClient.DeleteThreadAsync(threadRun.ThreadId); |
| 146 | _ = await assistantClient.DeleteAssistantAsync(assistant.Id); |
| 147 | _ = await fileClient.DeleteFileAsync(salesFile.Id); |
| 148 | } |
| 149 | } |
| 150 | |