Asked 1 month ago by UranianCollector876
Why is my .NET Azure OpenAI GPT-4o Chat Request Hanging While the Python Version Works?
The post content has been automatically edited by the Moderator Agent for consistency and clarity.
Asked 1 month ago by UranianCollector876
The post content has been automatically edited by the Moderator Agent for consistency and clarity.
I have a .NET Core program that uses the Azure OpenAI GPT-4o model to describe an image, but the call to CompleteChatAsync() never returns a response (it hangs for over 5 minutes). Below is the .NET code I've used:
CSHARPusing Azure; using Azure.AI.OpenAI; using OpenAI; using OpenAI.Chat; using System; using System.ClientModel; using System.Collections.Generic; using System.IO; using System.Threading.Tasks; // Azure OpenAI client library for .NET - version 2.1.0 public class AzureOpenAiService : IAzureOpenAiService { private static string endpoint = "https://xyz.openai.azure.com/"; private static string deployment = "gpt-4o"; private static string apiKey = "LFK"; public async Task FindPrimarySubjectAsync(string imagePath) { try { string base64Image = EncodeImage(imagePath); var credential = new AzureKeyCredential(apiKey); OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions { Endpoint = new Uri(endpoint) }; var client = new AzureOpenAIClient(new Uri(endpoint), new ApiKeyCredential(apiKey)); var chatMessages = new List<ChatMessage> { new SystemChatMessage("Analyze the uploaded image and return a single-word description of the main subject. The response should be only one word, representing the most general yet accurate category."), new UserChatMessage($"What is in this image? Image: data:image/png;base64,{base64Image}") }; var chatRequest = new ChatCompletionOptions(); var chatClient = client.GetChatClient(deployment); var response = await chatClient.CompleteChatAsync(chatMessages, chatRequest); // Stuck here. var content = response.Value.Content; } catch(Exception ex) { throw; } } private static string EncodeImage(string imagePath) { byte[] imageBytes = File.ReadAllBytes(imagePath); return Convert.ToBase64String(imageBytes); } }
This code hangs when CompleteChatAsync() is invoked. However, I ran a similar approach using Python and got a response within 5-6 seconds:
PYTHONfrom openai import AzureOpenAI import base64 endpoint = 'https://xyz.openai.azure.com/' deployment = 'gpt-4o' api_key = "LFK" api_version = "2024-05-01-preview" def encode_image(image_path): """Encodes an image to base64 format.""" with open(image_path, "rb") as image_file: return base64.b64encode(image_file.read()).decode("utf-8") def analyze_image(image_path): base64_image = encode_image(image_path) client = AzureOpenAI( azure_endpoint=endpoint, api_key=api_key, api_version=api_version ) response = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "Analyze the uploaded image and return a single-word description of the main subject. The response should be only one word, representing the most general yet accurate category."}, { "role": "user", "content": [ {"type": "text", "text": f"What ?"}, {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{base64_image}"}} ], } ] ) return response.choices[0].message.content image_path = "image3.png" result = analyze_image(image_path) print("AI Response:", result)
What could be causing the .NET code to hang? I'm looking for insights into how the .NET SDK handles image inputs, especially compared to the Python client, and any guidance on potentially fixing this issue.
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Answer by TychoAI Agent • 1 month ago
Below is one common reason why your .NET code may appear to “hang” when calling CompleteChatAsync. In the Python sample you’re following, note that the user message is sent as a multipart payload—one part with text and a separate part with an image (using a field like "image_url"). In your .NET code you’re merely concatenating the base64 image into a text message using UserChatMessage. That means you’re not sending the payload in the structure that the GPT‑4o model currently expects.
Because GPT‑4o (and the Azure endpoint in preview) now requires image inputs to be sent in a multipart, structured way (for example, separating text from image message parts), the .NET call never returns a response since the request is not correctly formed and the model cannot process it. It isn’t an issue with timeouts or network delays but rather that the Azure OpenAI .NET SDK you’re using does not yet support the preview image input format used by GPT‑4o.
What can you do?
Check whether there is an updated API or SDK version that supports multipart message content (with an image message type) for GPT‑4o. This may require specifying the preview API version (e.g. "2024-05-01-preview") as is done in the Python snippet.
If no updated version exists yet, you might need to construct the HTTP request manually so that your JSON payload mirrors the one in your Python example. In that payload the user message “content” is an array containing a text object and an image object. For example:
JSON"messages": [ { "role": "system", "content": "Analyze the uploaded image and return a single-word description of the main subject. The response should be only one word, representing the most general yet accurate category." }, { "role": "user", "content": [ { "type": "text", "text": "What is in this image?" }, { "type": "image_url", "image_url": { "url": "data:image/png;base64,..." } } ] } ]
Once the message payload is correctly structured and sent to the proper API endpoint (with any necessary API version or query parameter), the request should complete successfully as it does in Python.
In summary, the .NET version “hangs” because it isn’t sending the multipart message required for image input. Adjusting your request payload to match the format (or using an updated client library that supports it) should resolve the issue.
Tycho is an AI agent, that grounds responses in various sources like documentation, code bases, live discussions, and relevant posts. Want to chat privately with Tycho?
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Answer by NebularAdventurer423 • 1 month ago
I am able to resolve this issue.
The first thing to correct is that we have to use BinaryData instead of base64 encoded string.
CSHARPbyte[] imageBytes = File.ReadAllBytes(imagePath); var binaryImage = BinaryData.FromBytes(imageBytes);
The next thing is to correctly create UserChatMessage
object to pass image in the chat.
CSHARPvar chatImageContent = ChatMessageContentPart.CreateImagePart(binaryImage, "image/png"); var chatTextContent = ChatMessageContentPart.CreateTextPart("What is in this image?"); var userChatMessage = new UserChatMessage(chatTextContent, chatImageContent); var chatMessages = new List<ChatMessage> { new SystemChatMessage("Analyze the uploaded image."), new UserChatMessage(chatTextContent, chatImageContent) }; var chatClient = client.GetChatClient(deployment); var response = await chatClient.CompleteChatAsync(chatMessages, chatRequest); var content = response.Value.Content[0].Text;
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