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146 | using var api = GetAuthenticatedClient();
// First, let's contrive a document we'll use retrieval with and upload it.
string document = /* language=json */
"""
{
"description": "This document contains the sale history data for Contoso products.",
"sales": [
{
"month": "January",
"by_product": {
"113043": 15,
"113045": 12,
"113049": 2
}
},
{
"month": "February",
"by_product": {
"113045": 22
}
},
{
"month": "March",
"by_product": {
"113045": 16,
"113055": 5
}
}
]
}
""";
OpenAIFile salesFile = await api.Files.CreateFileAsync(
file: Encoding.UTF8.GetBytes(document),
filename: "monthly_sales.json",
purpose: CreateFileRequestPurpose.Assistants);
AssistantObject assistant = await api.Assistants.CreateAssistantAsync(
model: CreateAssistantRequestModel.Gpt4o,
name: "Example: Contoso sales RAG",
instructions: "You are an assistant that looks up sales data and helps visualize the information based"
+ " on user queries. When asked to generate a graph, chart, or other visualization, use"
+ " the code interpreter tool to do so.",
tools:
[
new AssistantToolsFileSearch(),
new AssistantToolsCode(),
],
toolResources: new CreateAssistantRequestToolResources
{
FileSearch = new CreateAssistantRequestToolResourcesFileSearch
{
VectorStores =
[
new CreateAssistantRequestToolResourcesFileSearchVectorStore
{
FileIds = [salesFile.Id],
}
],
}
});
// Now we'll create a thread with a user query about the data already associated with the assistant, then run it
RunObject threadRun = await api.Assistants.CreateThreadAndRunAsync(
assistantId: assistant.Id,
thread: new CreateThreadRequest
{
Messages = new List<CreateMessageRequest>
{
new()
{
Role = CreateMessageRequestRole.User,
Content = "How well did product 113045 sell in February? Graph its trend over time.",
},
},
});
// Check back to see when the run is done
do
{
await Task.Delay(TimeSpan.FromSeconds(1));
threadRun = await api.Assistants.GetRunAsync(
threadId: threadRun.ThreadId,
runId: threadRun.Id);
} while (threadRun.Status is RunObjectStatus.Queued or RunObjectStatus.InProgress);
// Finally, we'll print out the full history for the thread that includes the augmented generation
// TODO: IAsyncEnumerable pagination
ListMessagesResponse messages
= await api.Assistants.ListMessagesAsync(
threadId: threadRun.ThreadId); // ListOrder.OldestFirst
foreach (MessageObject message in messages.Data)
{
Console.Write($"[{message.Role.ToString().ToUpper()}]: ");
foreach (OneOf<
MessageContentImageFileObject,
MessageContentImageUrlObject,
MessageContentTextObject,
MessageContentRefusalObject> contentItem in message.Content)
{
if (contentItem.IsValue3)
{
Console.WriteLine($"{contentItem.Value3.Text.Value}");
if (contentItem.Value3.Text.Annotations.Count > 0)
{
Console.WriteLine();
}
// Include annotations, if any.
foreach (OneOf<
MessageContentTextAnnotationsFileCitationObject,
MessageContentTextAnnotationsFilePathObject> annotation in contentItem.Value3.Text.Annotations)
{
if (annotation.IsValue1 && !string.IsNullOrEmpty(annotation.Value1.FileCitation.FileId))
{
Console.WriteLine($"* File citation, file ID: {annotation.Value1.FileCitation.FileId}");
}
if (annotation.IsValue2 && !string.IsNullOrEmpty(annotation.Value2.FilePath.FileId))
{
Console.WriteLine($"* File output, new file ID: {annotation.Value2.FilePath.FileId}");
}
}
}
if (contentItem.IsValue1)
{
OpenAIFile imageInfo = await api.Files.RetrieveFileAsync(contentItem.Value1.ImageFile.FileId);
byte[] imageBytes = await api.Files.DownloadFileAsync(contentItem.Value1.ImageFile.FileId);
FileInfo fileInfo = new($"{imageInfo.Filename}.png");
await File.WriteAllBytesAsync(fileInfo.FullName, imageBytes);
Console.WriteLine($"<image: {new Uri(fileInfo.FullName).AbsoluteUri}>");
}
}
Console.WriteLine();
}
// Optionally, delete any persistent resources you no longer need.
_ = await api.Assistants.DeleteThreadAsync(threadRun.ThreadId);
_ = await api.Assistants.DeleteAssistantAsync(assistant.Id);
_ = await api.Files.DeleteFileAsync(salesFile.Id);
|